The global energy transition increasingly relies on the sustainable use of the subsurface, which commonly involves fluid injection. Such injection can induce earthquakes, posing significant challenges to the safety and operability of geo-energy applications. Addressing these challenges requires a geomechanical understanding of induced seismicity and the coupled subsurface processes that govern it. This Award Lecture introduces recent research on fluid injection-induced earthquakes, spanning the evaluation of causal mechanisms to an in-depth understanding of the fault-slip processes that control earthquake magnitude and frequency.

The first part of the presentation focuses on identifying and evaluating the causal mechanisms for injection-induced earthquakes. The problem is formulated as assessing the susceptibility of fracture and fault slip driven by coupled thermo-hydro-mechanical (THM) processes in fractured porous media. Through several geo-energy case studies, it is demonstrated that induced seismicity commonly results from fracture and fault reactivation through multiple, co-occurring mechanisms. The relative contribution of these mechanisms largely depends on regional geology, fracture and fault properties, ambient stress conditions, and operational parameters. Fluid overpressure typically develops rapidly following injection and may influence a large area, depending on hydraulic connectivity and fault permeability. Poroelastic stressing accompanies fluid pressurisation, with its contributions controlled by the distance to susceptible faults and fault orientation relative to the ambient stress field. Thermal stressing is generally more spatially localised around injection wells but can become dominant over longer timescales. In addition, fault slip-induced stress transfer can explain seismicity beyond the region affected by fluid pressure and poroelastic stress changes. Understanding these mechanisms enables the development of physics-based approaches for induced seismicity hazard assessment that explicitly account for both geological conditions and operational strategies.

The second part of the presentation addresses fault frictional slip processes that ultimately control the earthquake magnitude and frequency. Three key governing processes are identified for injection-induced fault slip: fluid pressurisation, hydraulic diffusion, and frictional nucleation, each characterised by a distinct timescale. Their interactions give rise to a wide range of induced earthquake behaviours. To disentangle their combined effects, a coupled hydro-mechanical-frictional modelling framework was developed that integrates frictional contact models for faults with poroelastic models for surrounding rocks. The results have shown that frictional properties exert first-order control on fault slip regimes and the maximum earthquake magnitude, whilst fluid pressurisation primarily governs earthquake frequency and also influences the maximum magnitude through poroelastic stressing. These effects are further modulated by hydraulic diffusion, highlighting the role of reservoir hydraulic conductivity in controlling how injected fluids interact with distant faults. Building upon this understanding, this contribution illustrates how fluid pressurisation rate influences induced earthquake magnitude and frequency, and discusses the implications for designing injection strategies that minimise seismic risk while maintaining operational efficiency.

Acknowledgement: I gratefully acknowledge the support and nomination by Prof. Sevket Durucan, Dr. Suzanne Hangx, Prof. Chris Spiers, Prof. Paul Glover, and Prof. Keita Yoshioka, and the many collaborators who contributed to the research presented.

How to cite: Cao, W.: Understanding fluid injection-induced earthquakes: From causal mechanisms to fault frictional slip, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13423, https://doi.org/10.5194/egusphere-egu26-13423, 2026.

The increasing global demand for nickel, driven by its critical role in stainless steel production and emerging battery minerals technologies, has intensified exploration efforts in geologically diverse terrains. This study focuses on the Cuddapah Basin, a Proterozoic sedimentary basin in southern India, which presents a complex geological framework with promising yet underexplored potential for nickel mineralization. Through an integrated approach combining lithological mapping, geophysical surveys, and geochemical analysis, this paper present fingerprints of geochemical and geophysical signatures to target Nickel Exploration. The preliminary findings indicate the presence of ultramafic intrusions and favourable host rocks such as picritic sills which are typically associated with nickel sulfide deposits. The western margin of the Proterozoic-aged Cuddapah Basin contains gabbro and plagioclase bearing sills within the Tadapathri formations These sills have 4-28% MgO and 30-1050ppm Ni and they are characterized by elevated Th/Nb which is indicative of contamination by upper crustal material. The low MgO mafic magmas have one to two orders of magnitude viscosity higher than the picritic sill they are emplaced all along the Cuddapah basin margin. No Ni-Sulphide mineralization is known in this belt, but trace interstitial sulphide is present. The following features of the Pulivendla-Vemula sill complex indicate that the rocks are prospective for magmatic sulfide exploration:1. Tholeiitic lavas and sills were emplaced during extensional intra-cratonic rifting at a time of major Ni ore formation at ~1.9 Ga metallogenic epoch i.e late Proterozoic-Archaean in age.2. Un-deformed fresh differentiated ultramafic sills have a range in Ni concentration over a narrow interval of forsterite content with primary olivine 3. These sills and other sills in the footprint of regional magnetic and gravity anomalies possibly contain feeders where immiscible magmatic sulfides may have formed. correlating between Werner depth estimations and seismic data, particularly in pinpointing fault zones. These zones act as critical conduits for fluid migration from the mantle to the surface, playing a vital role in both tectonic interpretation and mineralexploration4. Despite the absence of magmatic sulfide mineralization and magmatic breccias, there is untested potential within the basin stratigraphy for the development of intrusions which have a magnetic and density signal, possibly in association with a structural break as well as a diagnostic electromagnetic signal from highly conductive sulfide mineralization. However, the geological complexity, including structural deformation and metamorphic overprints, poses significant challenges in locating economically viable deposits. The study underscores the importance of advanced exploration techniques and multidisciplinary data integration to improve discovery success rates. Ultimately, this work contributes valuable insights into the Ni-mineral prospectivity of the P-V Picritic Sill in western margin of Cuddapah Basin and highlights its potential as a frontier region to relook for nickel exploration in India.

How to cite: Sunder Raju, P. V.: Fingerprints of Nickel Exploration in the Pulivendla-Vemula (P-V) sill in Cuddapah Basin:Geological Complexity and Discovery Potential, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1384, https://doi.org/10.5194/egusphere-egu26-1384, 2026.

High wind and solar penetrations would make bulk energy storage increasingly important for electricity system reliability. We introduce a deficit stretch framework that relates the temporal structure of generation shortfalls to optimal storage configurations in a decarbonizing grid and links the intensity, duration, and frequency of deficits to storage needs and cost–reliability trade-offs. Using Karnataka (India) as a case study, we simulate wind–solar–demand scenarios to examine (i) drivers of deficit-stretch emergence, (ii) which wind–solar–storage portfolios align with available storage technologies, and (iii) how these choices map onto Pareto frontiers of cost versus reliability. We cluster deficit stretches to identify characteristic storage durations (across hours to seasons) enabling a direct mapping from variability patterns to feasible technology options. Results indicate that solar share largely controls the deficit stretch duration spectrum. The proposed framework offers an empirical approach leading from analysis of renewables variability to consideration of bulk energy storage portfolios amidst cost–reliability tradeoffs and is extendable to other regions as well.

How to cite: Gangopadhyay, A. and K Seshadri, A.: Designing cost-effective storage portfolios in decarbonizing power systems: a deficit stretch approach, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3742, https://doi.org/10.5194/egusphere-egu26-3742, 2026.

Coal is an important major source of energy for sustainable development and growth of economy around the world. Coal fire and mine water issues are two aspects of mining-induced safety and eco-environmental issues which occurred during and after mining. In the present presentation, the author illustrates the understanding of these two issues by employing the theoretic analysis, the experimental simulation, the numerical simulation, and the field investigation, etc. Results from this research show that the rational scientific mining methods and technologies can be used to reduce the occurrence and influence of these two phenomena which leads to the possible sustainable exploitation of coal resource.

How to cite: Zeng, Q.: Coal fire & Mine water: two major post-mining issues, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4291, https://doi.org/10.5194/egusphere-egu26-4291, 2026.

Investment decisions for offshore wind-to-hydrogen (W2H) projects are often framed as “better forecasts reduce uncertainty,” but it is less clear when higher-fidelity scenario modelling meaningfully changes a financing decision versus merely narrowing outcome ranges. We address this question using a decision-coupled evaluation that scores forecast skill on propagated economic distributions and links it directly to financeability metrics.

Using 61 years of ERA5 wind data at 150 m hub height, we generate 1000 synthetic 23-year hourly wind scenarios per method and propagate them through a techno-economic model of a 375 MW offshore W2H project (development in 2024, operation in 2026-2050, base hydrogen price €8/kg, discount rate 7%). We compare three probabilistic scenario generators: historical bootstrapping, parametric Weibull fitting, and a calibrated probabilistic long short-term memory (LSTM) sequence model (used as a benchmark rather than architectural novelty).

We evaluate (a) continuous ranked probability score (CRPS) of levelized cost of hydrogen (LCOH), net present value (NPV), and internal rate of return (IRR), (b) decision bandwidths W(Y) = P₉₅(Y) – P₅(Y), (c) threshold-crossing probabilities P_r(NPV>0) and P_r(IRR>10%), and (d) a local elasticity E(Y) = dW(Y)/dCRPS that maps marginal forecast skill to risk-band compression. Finally, we run a financing price sweep to identify the minimum hydrogen offtake price that achieves a 90% probability target for NPV > 0 and the joint target NPV > 0, IRR > 10%.

Results show that improved scenario modelling can substantially reduce economic distribution error and compress risk bands: the LSTM lowers CRPS by 30% for LCOH and NPV and by 25% for IRR versus the best bootstrap/Weibull configurations. However, under base assumptions the financeability thresholds are nearly invariant across methods: the 90%-target required hydrogen price is €7.76-7.78/kg for P_r(NPV>0) and €9.16-9.18/kg for P_r(NPV>0 and IRR>10%), with cross-method spread below €0.02/kg indicates a threshold-saturated regime where better modelling mainly narrows uncertainty rather than shifting the decision boundary. Sensitivity analysis indicates decision value is highest in moderate-margin regimes (roughly €5.5-8/kg) and diminishes at high profitability where models converge.

This work reframes “better scenarios” into an investment-relevant diagnostic: use elasticity and threshold behaviour to identify when modelling improvements will shift financeability versus only compress risk bands, supporting more defensible screening and policy design.

How to cite: Aditama, P. and Zia, A. W.: When Does Better Scenario Modelling Improve Financeability? A Decision-Coupled Evaluation for Offshore Wind-to-Hydrogen, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5058, https://doi.org/10.5194/egusphere-egu26-5058, 2026.

This study evaluates annual changes in wind power density (WPD) in a domain covering the Iberian Peninsula and adjacent areas using several CMIP6 global climate models and the ensemble mean under historical (1961-1990) and SSP5-8.5 scenarios for two-time horizons—near future (2041–2070) and far future (2071–2100).

Results from the ensemble indicate a robust and generalized decrease in WPD throughout the 21st century. The most pronounced declines occur in windows starting mid-century (2050–2055), with reductions of about -90 W m^-2 century^-1 persisting for up to 40-year periods. Short-lived positive trends (≈ 50 W m^-2 century^-1) appear around 2030 and 2045, suggesting temporary peaks before a marked decline (≈ -100 W m^-2 century^-1) in later decades. Comparisons between future and historical periods reveal strong WPD decreases (-70 W m^-2), mainly offshore, particularly in far-future scenarios.

Inland areas may experience annual mean WPD values falling below the cut-in threshold (3 m/s, ≈ 15.5 W m^-2), rendering some older wind farms economically and technically unviable. Offshore regions, despite current technological priorities, face substantial WPD reductions (up to -60 W m^-2), while inland declines are significant in northeastern Spain, where major wind farms are located. These projected reductions—especially offshore (10–20%)—could challenge the financial viability of future wind energy projects.

How to cite: García-Miguel, A., Calvo Sancho, C., Díaz Fernández, J., González Alemán, J. J., López Reyes, M., Bolgiani, P., Martín Pérez, M. L., and Luna, M. Y.: Assessing future wind energy resources in the Iberian Peninsula under climate change scenarios, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6552, https://doi.org/10.5194/egusphere-egu26-6552, 2026.

How to cite: Touloumenidou, L.: Pumped‑Storage Hydropower in a Post‑Mining Landscapes: A Feasibility Study for Repurposing the Ptolemaida Lignite Basin in Western Macedonia, Greece, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6952, https://doi.org/10.5194/egusphere-egu26-6952, 2026.

Accurate assessment of ecological vulnerability in island systems under natural and anthropogenic pressures is crucial for ecosystem stability and sustainable development. Constructing an adaptive and scientific framework for evaluating ecological vulnerability in island regions remains a key challenge. This study introduces a novel Pressure–Vigor–Organization–Resilience (PVOR) model for assessing ecological vulnerability, applied to the main island of Malta. A combined weighting approach using game theory was used to determine composite indicator weights, while multi-source data (e.g., remote sensing and geospatial data) were integrated to investigate the long-term spatiotemporal evolution of ecological vulnerability from 2000 to 2020 and its driving factors.

The results show that: (1) Over 20 years, the ecological vulnerability index (EVI) of Malta fluctuated but declined from 0.65 to 0.58. From 2000 to 2015, vulnerable areas were mainly located in the eastern built-up zones. By 2020, the area of highly vulnerable zones decreased by 86% due to ecological protection policies and the COVID-19 pandemic, with minor increases in vulnerability (less than 5 km²) along the southwestern coastline. (2) Ecological vulnerability exhibited significant spatial clustering (global Moran’s I > 0.80, p < 0.01), with high-value clusters in the east and low-value clusters in the west and north. (3) Key driving factors include habitat quality, landscape fragmentation, population density, and development intensity, with interaction effects being stronger than individual factors. (4) Based on both static and dynamic vulnerability assessments, ecological zoning was defined, and targeted management strategies were proposed.

This study provides a scientific foundation for ecological restoration and sustainable development in Malta, offering a transferable framework for other island systems.

How to cite: Wang, L., Chi, J., and Xiao, X.: Spatiotemporal Patterns of Ecological Vulnerability in Malta: An Empirical Analysis Using the PVOR Model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7454, https://doi.org/10.5194/egusphere-egu26-7454, 2026.

How to cite: Davis, D. and Saraf, N.: Unfolding the rise in cooling demand from residential buildings sector in India, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8851, https://doi.org/10.5194/egusphere-egu26-8851, 2026.

Artisanal and small-scale mining (ASM) is an important source of livelihood in Mozambique, directly involving over 100,000 people, largely through informal and poorly regulated operations (Delve, 2020). ASM activities are concentrated in provinces with high mineral potential, including Manica, Tete, Zambézia, Niassa, Nampula and Cabo Delgado (Mapurango, 2014), and primarily involve the extraction of gold, precious and semi-precious stones, as well as construction materials. Despite its socio-economic relevance, the sector is characterised by weak technical organisation, limited regulatory integration and widespread informality.

This study examines the main safety and sustainability challenges associated with ASM in Mozambique, with particular emphasis on occupational health and safety and environmental management. The methodological approach is based on a review of secondary literature and documentary analysis of existing legal and policy frameworks. The analysis indicates that high levels of informality contribute to unsafe working conditions, inadequate use of personal protective equipment, frequent occupational accidents and significant environmental degradation, including soil and water contamination.

Recent regulatory interventions, such as the suspension of mining licences in Manica Province in October 2025 due to uncontrolled discharge of mining effluents, highlight the urgency of strengthening environmental governance and enforcement mechanisms. The results suggest that the adoption of sustainable mining principles—focused on risk management, environmental protection, decent working conditions and long-term economic viability—can substantially improve the performance of ASM operations. Practical measures include basic technical training, increased awareness campaigns on occupational health and safety, gradual adoption of appropriate technologies and progressive formalization supported by effective monitoring.

In conclusion, enhancing safety and sustainability in ASM is essential not only to reduce occupational and environmental risks but also to ensure that small-scale mining continues to positively contribute to local communities and the national economy.

How to cite: dos Santos, L. V. S., Guiliche, M. E., and Mugabe, J. A.: Safety and Sustainability in Artisanal and Small-Scale Mining Operations in Mozambique, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9067, https://doi.org/10.5194/egusphere-egu26-9067, 2026.

Contourite sandstones exhibit high lateral continuity, moderate to high porosity (depending on diagenetic overprint), and are typically overlain by fine-grained marls, making them promising candidates for subsurface CO₂ storage. This study investigates contourite channel deposits of late Miocene age that outcrop in the Rifian Corridor (northern Morocco). A fine-grained, bioclastic–siliciclastic sandstone and a medium- to coarse-grained sand representing potential reservoir materials were selected for controlled CO₂–rock interaction experiments.

CO₂ exposure tests were conducted in a batch reactor at 8 MPa and 40 °C for 30 days. Textural and pore-space changes were assessed through comparative SEM imaging, and bulk-rock and brine chemical compositions were analysed before and after exposure. The first reservoir sample experienced only minor dissolution features and limited particle detachment. In contrast, the fine-grained reservoir candidate underwent pronounced physical disintegration during CO₂ exposure. Chemical alteration was modest in both lithologies, expressed mainly as slight increases in dissolved ion concentrations in the brines.

These results highlight contrasting mechanical responses of contourite channel facies to CO₂ exposure and underscore the importance of lithological variability when evaluating contourite systems for CO₂ storage applications.

This research was conducted within the ALGEMAR Project (Ref. PID2021-123825OB-I00), funded by the Plan Nacional of Spanish Ministry of Science and Innovation

How to cite: Berrezueta, E., Kovács, T., Ordóñez-Casado, B., LLave, E., Benjumea, B., Canteli, P., Mediato, J., Hernández-Molina, J., and de Weger, W.: CO2 storage potential of contourite channels – Laboratory studies on geochemical reactions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9664, https://doi.org/10.5194/egusphere-egu26-9664, 2026.

This study investigates mineralogical and geochemical alterations at the matrix scale in carbonate-rich sandstone exposed to supercritical CO₂ (SC-CO₂) and formation brine. Batch experiments were conducted under reservoir conditions (≈8 MPa, 333ºK) to simulate the early stages of CO₂ injection in a deep sedimentary formation of the Guadalquivir Basin (southern Spain).

Rock samples were analysed before and after exposure using scanning electron microscopy (SEM) with microanalysis, X-ray fluorescence (XRF), and X-ray diffraction (XRD). Complementarily, chemical analyses of the brine before and after the experiments were performed. The interaction with CO₂-rich brine caused a marked pH decrease, leading to carbonate dissolution and minor alteration of clay minerals. The Ca concentration in the brine increased by about 300%, confirms active carbonate dissolution driven by CO₂-induced acidification. These reactions, together with particle detachment and micro-scale pore modification, indicate dynamic fluid-rock interactions within the calcarenite matrix.

The results show up that the studied reservoir rocks maintain overall structural integrity under CO₂-rich conditions while undergoing measurable geochemical alteration. This experimental framework provides a reproducible approach to evaluate mineral reactivity and textural evolution in carbonate-rich sandstone reservoirs, offering relevant insights to the design and assessment of CO₂ sequestration projects in comparable geological settings.

This research was conducted within the UNDERGY Project (Ref. MIG-20211018), funded by the Programa Misiones CDTI 2021 of the Spanish Ministry of Science and Innovation and the Next Generation EU Fund.

How to cite: Ordóñez-Casado, B., Ledesma, S., Mediato, J., Kóvacs, T., Chinchilla, D., González-Menéndez, L., and Berrezueta, E.: Carbonate-rich Sandstone Reactivity to Supercritical CO₂ and Brine: A Case Study from the Guadalquivir Basin, Spain, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10232, https://doi.org/10.5194/egusphere-egu26-10232, 2026.

This study presents a comprehensive methodological framework that integrates micro-scale urban geometry with macro-scale climate projections to improve the assessment of rooftop photovoltaic (PV) potential in urban environments. High-precision solar resource estimation is achieved through the use of very high–resolution Digital Surface Models (DSMs; 0.8 m) within the Solar Energy on Building Envelopes (SEBE) model, enabling detailed simulation of shading effects in dense urban fabrics.

Historical and present-day atmospheric inputs—including surface solar radiation, cloud cover, and aerosol optical depth—are obtained from the Copernicus Atmosphere Monitoring Service (CAMS) and combined with meteorological variables from ERA5-Land. Future rooftop PV potential is projected using a multi-model ensemble of CMIP6 climate simulations under the SSP2–4.5 and SSP5–8.5 emission scenarios. Statistical downscaling techniques are applied to translate large-scale climate projections to local urban conditions.

In addition, the study evaluates PV system performance during specific atmospheric episodes, quantifying the effects of dust intrusions and compound events—defined as the co-occurrence of high temperatures and elevated dust concentrations—on energy yield. Finally, cluster analysis is performed on the urban building stock of selected southeastern Mediterranean cities using key performance indicators, including received solar radiation, total energy yield, rooftop area, and building height.

The results demonstrate that integrating micro-scale urban morphology with macro-scale climate projections is critical for accurately estimating rooftop PV potential, particularly in regions characterized by complex urban structures and climate-sensitive atmospheric processes.

How to cite: Agazarian, N., Cartalis, C., Philippopoulos, K., and Agathangelidis, I.: Integrating Micro-Scale Urban Geometry with Macro-Scale Climate Projections to Improve Rooftop Photovoltaic Potential Assessment: An Application to Selected Urban Areas in the Southeastern Mediterranean, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14485, https://doi.org/10.5194/egusphere-egu26-14485, 2026.

Long-term geological CO₂ sequestration relies on quantitative time-lapse geophysical monitoring to assess storage integrity. In this study, we present a multi-physics forward modelling framework for 4D monitoring of CO₂ storage and demonstrate its application through a case study in the Hewett Field, a depleted gas field in the Southern North Sea. The case study focuses on a 30-year CO₂ injection scenario into the Bunter sandstone. Seismic, controlled-source electromagnetic (CSEM) and gravity methods are combined within this multi-physics framework to provide complementary information.

The modelling workflow includes geological modelling, CO₂ injection modelling, rock-physics modelling, and 4D geophysical forward simulations. The modelling starts from a static geological model describing the structural framework of the reservoir. This model is used in the dynamic CO₂ injection simulations, which predict the CO₂ saturation and pressure evolution during CO₂ injection and post-injection migration. The resulting dynamic properties are converted into velocity, resistivity and density changes through rock-physics modelling. Based on these physical properties, 4D geophysical forward modelling is performed for seismic, CSEM and gravity methods to simulate time-lapse geophysical responses associated with CO₂ plume development.

By comparing the simulated time-lapse responses of seismic, CSEM and gravity data, the integrated 4D modelling framework uses the Hewett Field as a case study to develop and test a site-specific monitoring strategy.

How to cite: Yang, J. and Huuse, M.:  4D Multi-Physics Forward Modelling for CO2 Storage Monitoring in the Hewett Field, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16152, https://doi.org/10.5194/egusphere-egu26-16152, 2026.

Groundwater-induced subsurface collapse presents a critical geotechnical hazard in karst terrains, which poses heavy risks to global public safety and infrastructure. Despite the substantial economic impact, predicting these failures remains challenging due to sparse subsurface monitoring and the difficulty of integrating indirect, multi-modal satellite data into traditional models. To address the challenge of low observability, we present a physics-informed neural network (PINN)-based digital twin for simulating coupled hydro-mechanical processes. The framework integrates NASA GPM (IMERG) precipitation data and Sentinel-1 InSAR surface deformation measurements to constrain subsurface dynamics. Implemented in the West-Central Florida Karst Belt, the model represents a three-dimensional domain of unconsolidated overburden overlying a weathered limestone aquifer. Subsurface dynamics are governed by transient Darcy flow and an effective stress relationship, while progressive material weakening is captured through a continuous damage variable, d, which evolves via stress redistribution and pore-pressure diffusion. Through minimizing the residuals of these governing equations, the PINN identifies the start of collapse, defined as the point where localized damage exceeds a critical threshold. Our results indicate that the digital twin produces physically consistent fields with 25–30% lower error in pore pressure and damage predictions compared to simulations that are uncoupled. Predicted collapse initiation times, Tc, remained within 18–23% of benchmark solutions, capturing time-accelerated failure during intense recharge events. Sensitivity analysis reveals that hydraulic conductivity, K, accounts for over 63% of damage variance, highlighting the model's physical interpretability. This framework provides a scalable approach for real-time hazard assessment in data-poor karst regions globally.

How to cite: Korada, S. and Liu, W.: PINN-Based Digital Twins for Modeling Groundwater-Induced Subsurface Collapse under Low-Observability Hydro-Mechanical Conditions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16204, https://doi.org/10.5194/egusphere-egu26-16204, 2026.

Wastewater treatment plants are essential environmental infrastructures that operate continuously and require considerable electrical energy, while simultaneously conveying persistent flows that dissipate low-grade hydraulic energy. Recovering even a fraction of this overlooked resource could support decarbonisation targets and provide autonomous power for environmental monitoring and digital water services, without additional land take or large hydropower installations. Within the Horizon Europe project H-HOPE – Hidden Hydro Oscillating Power for Europe – this study investigates how the selection of structural materials affects the performance of vortex-induced vibration energy harvesters (VIV-EH) deployed in controlled water environments. Rather than optimising device geometry or control strategies, the analysis focuses on how broad material classes influence feasibility, energy potential, and environmental suitability when integrating harvesters into existing wastewater infrastructure. Operational records from a municipal wastewater treatment plant in northern Italy were analysed. A validated one-dimensional modelling framework was used as a comparative tool to estimate annual energy production for harvesters manufactured from widely available metallic and composite materials under realistic operating conditions.

Results show a consistent trend: lighter materials with favourable stiffness-to-mass ratios generate larger oscillation amplitudes and substantially higher harvested energy. Fibre-reinforced composites achieve the highest performance, with an estimated annual production of approximately 800–875 kWh/year for the specific case study. Aluminium alloys produce slightly lower yields (≈800 kWh/year) while retaining advantages in recyclability and manufacturability. In contrast, high-density metals such as structural and stainless steel, typically yield 450–480 kWh/year, highlighting how increased mass suppresses the vortex-induced response. These differences arise solely from material choice, without modifying hydraulic conditions, device geometry, or plant operation.

From a renewable-energy perspective, these results indicate that material-driven design is a practical lever for scaling small, autonomous generators across water networks, providing reliable power for sensors, process control and digital water management. Because devices exploit existing hydraulic infrastructure, they can be replicated modularly and integrated alongside other renewables as part of distributed energy portfolios, supporting resilience and local self-sufficiency. However, performance advantages must be considered alongside environmental trade-offs. Composites show limited recyclability and higher embodied energy compared with metals such as aluminium and stainless steel, which favour circularity but offer lower energy conversion. The study relies on a simplified modelling framework and a single representative site, broader validation under different hydraulic regimes and long-term material ageing will require pilot-scale deployment. Despite this, the comparative trends provide robust guidance for design and prioritisation.

Overall, the study demonstrates that targeted material selection can unlock “hidden hydropower” within wastewater systems, delivering incremental yet scalable renewable generation aligned with European decarbonisation goals while enhancing the sustainability and reliability of essential water services.

How to cite: Siviero, M., Guðlaugsson, B., Nascimben, F., Finger, D. C., Benato, A., and Cavazzini, G.: Material Selection for Vortex-Induced Vibration Energy Harvesting in Water Systems: Environmental and Performance Insights from the Verona Case Study in Italy, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18202, https://doi.org/10.5194/egusphere-egu26-18202, 2026.

The growing demand for Critical and Strategic Raw Materials (CRMs, SRMs) and the limited availability of primary resources in Europe have renewed regulatory and scientific interest in mine waste and tailings as secondary raw material sources (European Critical Raw Materials Act 2023; Hool et al. 2024). Accordingly, efficient and environmentally sustainable extraction technologies are necessary to minimize both environmental impact and processing costs (Whitworth et al. 2022). Among emerging solutions to conventional acidic leaching, glycine has been attracting attention as a non-toxic and biodegradable amino acid capable of forming stable complexes with calcophile elements under alkaline conditions and low temperatures, enabling low-cost, possible industrial applications for recovering precious and critical metals from mine waste and tailings (O’Connor et al. 2018; Barragán-Mantilla et al. 2024; Eksteen et al. 2018). This study investigated the application of glycine leaching as a green chemical approach for the recovery of copper from fine-grained historical tailings samples from the Fenice–Capanne mine, Tuscany, Italy.

Historical tailings samples were preliminarily characterised in terms of granulometry, geochemical and mineralogical composition using multiple methodologies, such as ICP-MS, HH-XRF, SEM-EDS and SEM-MLA for the definition of metal grades and the identification of metal-bearing minerals. Batch leaching tests were conducted using a glycine solution under controlled conditions, including alkaline pH, a constant liquid-to-solid ratio, and progressively increasing leaching times. The performance of glycine as a lixiviant was evaluated in terms of metal extraction efficiency and selectivity using HH-XRF on solid residues and ICP-OES on leaching liquors. Particular focus was addressed on Cu and associated Zn extraction. As a term of comparison, the same samples were leached using sulphuric acid leaching.

Preliminary results indicated that glycine leaching enabled the selective extraction of Cu and minor Zn while limiting the dissolution of Fe, and competitive recovery rates when compared to traditional sulphuric acid leaching. It highlighted its potential as an environmentally friendly leaching agent. The outcomes of this study could contribute to the assessment of sustainable options for the recovery of CRMs and SRMs from mine tailings within a sustainable and circular economy approach.

How to cite: Baldassarre, G., Zasa Courtial, V., Bellopede, R., and Marini, P.: Selective recovery of copper from mine tailings using a green leaching agent, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19216, https://doi.org/10.5194/egusphere-egu26-19216, 2026.

An aquathermal energy system is a sustainable heating and cooling technology for buildings by utilizing low-grade thermal energy from water sources. This contribution presents a full scale pilot at the TU Delft campus that investigates and show-cases the potential of a campus pond to supply thermal energy to the Firma van Buiten (FvB) building, which is a restaurant/meeting location.

The contribution focuses on sensor integration and data acquisition, heat balance modeling, and design considerations for an aquathermal system. Initially, a field campaign was conducted to assess the pond's dimensions, collect bathymetric data, and install temperature sensors at various locations and depths.

The heat balance model uses data from the pond and a nearby weather station to quantify temperature effects on the surface water system. By performing a heat balance of the water body, considering various factors, including solar radiation, wind speed, air temperature, and heat fluxes, the study evaluates the extractable thermal energy from the pond and assesses its suitability for low-temperature heating and cooling applications.

Finally, a design analysis of the pilot aquathermal system is presented, considering technical feasibility, integration with existing building energy systems, and potential scalability across the campus. The contribution also provides recommendations for implementing a more sophisticated data acquisition and monitoring system.

The findings provide practical insights for advancing sustainable energy solutions in dense urban environments and support the broader implementation of aquathermal technologies in the Netherlands.

How to cite: Fremouw, M., Koulidis, A., and Bloemendal, M.: Assessing and Designing a Pilot Aquathermal System on the TU Delft Campus, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19295, https://doi.org/10.5194/egusphere-egu26-19295, 2026.

Underground coal gasification (UCG) offers a viable approach for extracting deep-seated coal deposits with minimal surface disruption. The thermomechanical behavior of adjacent rock formations, particularly shale, which typically acts as a ceiling or floor rock, has a significant impact on the success of UCG operations. This study examines the pore structure evolution of shale samples at increased temperatures from room temperature to 800 °C, approximating the thermal range experienced during UCG procedures. The primary goal is to understand how high-temperature exposure changes the porosity and microstructure of shale, altering gas movement, confinement, and overall system stability.

Shale samples were collected from Jharia Basin, India, and were heated in a muffle furnace at gradually increasing temperatures. The pore properties were assessed by Low-Pressure Gas Adsorption (LPGA), Helium Pycnometry, and Scanning Electron Microscopy (SEM). SEM imaging showed considerable microcrack formation and intergranular pore growth at temperatures above 300 °C. LPGA data showed a shift from microporous to meso- and macroporous materials as temperature increased, implying gradual pore coalescence. The Helium Pycnometer results verified a temperature-dependent increase in apparent porosity, which corresponded well to the observed physical degradation. The findings show a non-linear rise in total porosity and considerable microstructural disintegration of shale at high temperatures, which can improve gas flow paths but may expose the confining layers' stability. These thermal changes are critical to UCG operations because they affect both gas recovery efficiency and subsurface safety. The work sheds light on the thermal behavior of shale under UCG-relevant conditions, emphasizing the importance of complete thermomechanical studies in site selection and operational planning for UCG projects.

Keywords: Underground Coal Gasification, LPGA, Permeability, temperature, Porosity.

How to cite: Sahoo, S. S.: Temperature-Induced Pore Structure Evolution in Shale: Implications for Underground Coal Gasification Applications , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19786, https://doi.org/10.5194/egusphere-egu26-19786, 2026.

How to cite: Singh, J.: Hierarchical Bayesian Modeling of Solar Irradiance under Extreme Weather in the Tucson Electric Power Region, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22088, https://doi.org/10.5194/egusphere-egu26-22088, 2026.

Pyrophyllite is a mineral known for its chemical inertness, thermal stability and low thermal conductivity. Such properties are making it a suitable material for modern and advanced insulation technologies. The study evaluates the potential of pyrophyllite-rich natural resources for industrial usage in heat-resistant, eco-friendly and sustainable geocomposite insulation panels when combined with plant-based fabrics such as cotton, jute and linen.

The samples obtained from the Pütürge district of Malatya, where the majority of pyrophyllite deposits in Türkiye are located, were characterized mineralogically and geochemically in order to evaluate their suitability for industrial purposes and geocomposite production. Pyrophyllite-rich sample powders were micronized to improve bonding between mineral particles and fabric fibers, while plant-based fabrics were mercerized with sodium hydroxide for better surface reactivity. Mercerized fabrics were impregnated with a binder solution which includes the micronized powder and sodium silicate and later subjected to heat treatment to provide stability. Thermogravimetric (TGA) and Differential Scanning Calorimetry (DSC) analyses on both untreated and impregnated fabrics revealed their mass-loss characteristics, thermal decomposition behavior and their flame-retardant potential.

The results indicate that impregnating the plant-based fabrics with pyrophyllite significantly increases the thermal performance. Among these fabrics, the best improvement in thermal mass retention is observed in cotton, followed by jute and linen. Jute fabrics exhibit the highest degree of thermal endurance, maintaining structural stability up to approximately 600 °C. The positive change in heat resistance for cotton and linen is relatively weaker, but all mineral-impregnated fabrics develop a char layer after combustion, with residual masses of 33-43% for jute, 17-20% for cotton, and 15-18% for linen. This mineral-based barrier is essential for sustainable thermal insulation, as it reduces heat transfer and supports the long-term integrity of the resulting geocomposites. In conclusion, the results demonstrate that pyrophyllite-impregnated plant-based fabrics, especially jute, are highly suitable for production of environmentally friendly, sustainable, thermally resistant and flame-retardant geocomposites for insulation purposes.

How to cite: Aykasım, D., Toksoy Köksal, F., and Kılıç, A.: Thermal performance improvement of plant-based fabrics via pyrophyllite impregnation: an environmentally friendly approach to geocomposite insulation materials, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-383, https://doi.org/10.5194/egusphere-egu26-383, 2026.

Electrification of residential heating via heat pumps is a key aspect of the global strategy to reach Net Zero. This is because heat pumps which can convert electricity directly to heat will almost directly reflect the carbon intensity of the electricity they use. The reduction in greenhouse gas emissions is dependent on the raw materials used, the source and quantity of electricity consumed for operation and end of life management of heat pumps. Therefore, it is necessary to evaluate the climate change impact and other sustainability aspects of heat pumps on a life cycle basis. 

However, heat pumps may be installed for individual buildings or as part of a heat network that supplies multiple properties, with significant differences between them in impacts from material usage, installation and operation. This review aims to synthesise and analyse the latest research to compare the environmental impacts of domestic heat pumps at these different scales, for new-build and retrofit cases. Following PRISMA protocols, a systematic search of peer-reviewed literature from 2017–2025 was conducted using the Web of Science and Scopus databases. The keywords used are as follows: 'Heat pump', 'Life Cycle Assessment', 'Environmental impact assessment', 'District heating', 'Domestic heating'. The number of studies found on the Web of Science database was 1256, with 1605 found on Scopus. 1006 studies were removed as duplicates, and the amount studies after removing duplicates were 1857. The review focused on studies quantifying impacts beyond operational energy use, specifically targeting embodied carbon, ozone depletion potential (ODP), resource depletion and the coefficient of performance (COP). 

We found that the life cycle impacts are interlinked with many factors, such as the characteristics of the electricity grid, the temperature lift, and the type of heat pump. We also note that there are differences in the methodological approaches, including choice of functional units and system boundaries, which limit the ability to cross-compare studies by non-experts. Despite this, the conclusions drawn suggest that geothermal heat pumps perform better than air source heat pumps. Moreover, future life cycle assessment studies on heat pumps will benefit by integrating temporal and spatial variations, such as heat pump performance with respect to the ambient temperature, and electricity grid greenhouse gas emission factors. This can help prioritise the deployment at scale of heat pumps on a wider scale based on the sustainability benefits when compared to conventional heating systems. 

The synthesis reveals that while domestic heat pumps generally exhibit lower upfront embodied carbon, they are frequently associated with higher cumulative refrigerant leakage and lower real-world efficiencies due to suboptimal installation. Conversely, district heat pumps consistently show lower environmental impact per kWh of heat delivered in high-density urban zones (>50 dwellings/hectare), primarily driven by the integration of waste heat sources and professionalized maintenance which prevents performance drift.

How to cite: Fadden, L., Radcliffe, J., and Mehta, N.: Decarbonising Residential Heating: A Systematic Review of Life Cycle Impacts for Residential and District Heat Pump Systems, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1219, https://doi.org/10.5194/egusphere-egu26-1219, 2026.

Solar-driven interfacial evaporation (SDIE) offers a sustainable route for treating high-salinity wastewater; however, reconciling ultra-high evaporation rates with long-term salt resistance remains a critical bottleneck. Herein, a structurally robust, sponge-templated composite aerogel (PCPG) is developed by confining a polyvinyl alcohol (PVA)-based semi-interpenetrating network (semi-IPN) within a polyurethane (PU) sponge skeleton. In this architecture, Carbon Black (CB) and PEDOT:PSS are synergistically integrated to ensure broadband solar absorption (>90%) and reinforce the gel matrix.  The abundant hydrophilic groups within the polymer chains regulate the water state, effectively reducing the evaporation enthalpy to 831.5 J g⁻¹. Crucially, the composite features a hierarchical porous structure: the gel's micropores facilitate rapid capillary water supply, while the sponge's macropores enable efficient back-diffusion of salt ions. Leveraging these synergistic effects, PCPG achieves an exceptional pure water evaporation rate of 6.13 kg m⁻² h⁻¹ with 123.08% efficiency under 1 sun irradiation. Remarkably, it sustains a stable rate of 5.21 kg m⁻² h⁻¹ in 20 wt% NaCl brine without salt accumulation.Validated by both experiments and numerical simulations, this work presents a scalable, salt-resistant solution for zero-liquid discharge (ZLD) desalination and industrial brine management.

How to cite: Li, F.: Composite Aerogel with Hierarchical Hydrophilic Networks for Solar Evaporation and Salt-Resistant Brine Concentration, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1909, https://doi.org/10.5194/egusphere-egu26-1909, 2026.

Inspired by sand roses and the geological process of pressure-solution creep, this study presents a geomimetic, low-energy approach for producing sustainable bricks from vernacular geomaterials. By adapting the cold sintering technique, sand - uncalcined gypsum mixtures are densified at room temperature using minimal water and moderate pressure, thereby circumventing the high energy demands, chemical use, and substantial carbon emissions associated with conventional fired-clay or cement-based brick production. The research was conducted in two sequential experimental phases to bridge the gap between fundamental mechanism and practical manufacturability.

The first phase, conducted on small laboratory-scale samples, established the fundamental controls on mechanical performance. It demonstrated that gypsum acts as an effective binder at room temperature via a dissolution–precipitation mechanism. Critical processing parameters were identified, including gypsum content, gypsum particle size, pressure magnitude and loading mode. Notably, cyclic loading significantly enhanced the unconfined compressive strength (UCS) without requiring increases in gypsum content or applied pressure, enabling mixtures to achieve strengths comparable to or exceeding those of equidimensional concrete bricks.

The second phase focused on upscaling the process to brick-relevant dimensions. By optimizing critical parameters such as pressure duration, drying time, and ambient humidity, the study successfully produced 50 mm cubes that meet ASTM standards for load-bearing masonry (13.8 MPa). The optimized process—applying only 50 MPa of uniaxial pressure for 5 minutes, followed by one day of drying (50 °C) at controlled humidity (40 %)—yielded sand–gypsum compacts with a UCS of approximately 18 MPa. This result confirms that reduced processing times are feasible for manufacturing, provided the drying environment is carefully regulated.

Overall, this geomimetic fabrication strategy leverages locally abundant resources, drastically reduces embodied energy and water consumption, and supports circular economy principles through material recyclability. It offers a viable, sustainable alternative for construction in hot, arid climates, directly contributing to global sustainability goals.

How to cite: Radwan, O., Hussein, M., Assaggaf, R., Humphrey, J., Al-Hashem, M., Mahmoud, A., and Abdelaal, A.: A Geologically Inspired Low-Energy Construction Material Based on Vernacular Geomaterials for Hot and Dry Environments, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2354, https://doi.org/10.5194/egusphere-egu26-2354, 2026.

  Global industrialization and population growth have increased the demand for energy and food, leading to a rise in food-processing by-products. Okara (soybean residue) is one of the most abundant by-products, with an annual production exceeding 14 million tons worldwide. Despite its high organic content, okara is often discarded due to its high moisture content and limited processing options. Converting okara into energy or high-value materials has become a significant challenge in light of resource scarcity and circular economy principles. This study proposes an efficient conversion pathway that combines hydrothermal treatment (HT-carbonization/liquefaction) with anaerobic digestion (AD) to transform okara into usable resources without energy-intensive drying.

  The hydrothermal process converts okara into bio-crude oil, hydrochar, and nutrient-rich aqueous phase, while simultaneously breaking down its high cellulose and protein content under high temperature and pressure. This process facilitates the conversion of large molecules into smaller molecules, which enhances methane production during subsequent anaerobic digestion and improves energy recovery efficiency.

  Experiments were conducted in a 500 cm³ high-temperature, high-pressure stainless-steel reactor equipped with a mechanical stirrer. Okara and deionized water were added at solid-to-liquid ratios of 1:10 and 1:5. After nitrogen purging, the reactor was pressurized to 2 MPa. The reaction temperature ranged from 200 to 300°C, with reaction times between 60 and 360 minutes. Results showed that the highest yields of hydrochar (38%) and bio-crude oil (31%) were achieved at 200°C and 120 minutes. Yields decreased when temperatures exceeded 230–250°C or reaction times were prolonged, as more carbon shifted to the aqueous and gaseous phases. At 300°C with short reaction times, moderate yields of hydrochar (20–23%) and bio-crude oil (25–26%) were obtained, indicating that high temperatures with limited exposure promote oil formation without excessive degradation.

  The remaining nutrient-rich liquid phase was subjected to co-digestion with sludge, maintaining a 1:1 liquid-to-sludge ratio based on volatile solids content. Gas was collected daily, and the bottles were opened weekly for gas, solid, and liquid analysis, as well as biodegradability assessments. Anaerobic co-digestion further enhanced methane production, significantly improving energy recovery. The liquid phase provided biodegradable organic matter, which was broken down by anaerobic microorganisms, resulting in increased methane yield and improved overall energy recovery efficiency.

  Additionally, a life cycle assessment (LCA) was conducted to evaluate the environmental impacts of the hydrothermal treatment combined with anaerobic digestion. From number of LCA paper results, it was shown that this integrated process had a lower environmental impact and higher resource efficiency compared to traditional waste management methods, such as landfilling, incineration, or direct AD.

  In conclusion, this integrated system presents a viable waste-to-resource pathway. The hydrochar produced can be used as a soil conditioner, and the bio-crude oil as a fuel. Methane can be utilized for power generation, while the remaining digestate can be applied as liquid fertilizer. The combination of hydrothermal treatment with anaerobic digestion, alongside the incorporation of life cycle assessment, highlights a promising circular economy strategy that reduces carbon emissions, fosters energy production, enhances resource recovery, and supports the sustainable use of agricultural by-products.

How to cite: Lin, C. J., Huang, Y.-Z., and Fan, C.: Valorization of Okara using Hydrothermal Treatment in combination with Anaerobic Digestion for Resource Recovery, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2926, https://doi.org/10.5194/egusphere-egu26-2926, 2026.

In Taiwan, over 400,000 tonnes of fish are consumed annually through commercial fish markets, with approximately 45% converted into low-value fish waste (FW), including viscera, bones, and scales, resulting in more than 200,000 tonnes of fish waste each year. These fish wastes are characterized by high moisture content and high biodegradability, particularly proteins and lipids. They are predominantly managed through low-efficiency practices such as landfilling, composting, or feed conversion, which often attract environmental concerns.

Anaerobic digestion (AD) is a conventional technology for converting organic waste into renewable energy. Previous studies have shown that AD of fish waste is frequently inhibited by long-chain fatty acids and high nitrogen content, leading to limited energy recovery and the generation of large volumes of digestate that require further treatment. Meanwhile, hydrothermal liquefaction (HTL) can effectively convert high-moisture and heterogeneous biomass materials into bio-crude oil without the need for energy-intensive drying, making it particularly suitable for anaerobic digestates.

This study investigates the integration of anaerobic digestion as a pre-treatment step with HTL to explore the resource recovery potential of liquid and solid digestate derived from fish waste. Fish waste was subjected to anaerobic digestion under five different substrate-to-inoculum (S/I) ratios, and HTL subsequently treated the resulting digestate under subcritical water conditions at temperatures ranging from 275 to 325 °C with a residence time of 30-60 min. The distribution and characteristics of the main HTL products, including bio-crude oil, solid residue, and aqueous phase, were analyzed.

The anaerobic digestion results showed variable biomethane production across different S/I ratios (1.84 ± 0.27-93.45 ± 8.84 mL CH₄ g^-1 VS). Notably, the AD process was utilized to partially degrade macromolecules while preserving sufficient organic carbon for subsequent HTL. Under HTL conditions at 325 °C for 60 min, bio-crude oil yields reached over 50 wt%. Gas chromatography–mass spectrometry (GC–MS) analysis indicated that the bio-crude oil was dominated by lipid-derived aliphatic amides, alongside protein-derived nitrogen-containing heterocyclic compounds, including lactams and fatty acid pyrrolidides. This suggests that the organic constituents of fish waste were effectively transformed into the oil phase with promising potential for further upgrading and valorization, while partially incorporating nitrogen into stable oil-phase compounds.

Furthermore, a life cycle assessment (LCA) framework was applied to compare this integrated AD–HTL pathway with traditional fish waste management practices to evaluate its potential environmental benefits in terms of resource recovery and pollution mitigation. Environmental benefits (such as carbon negativity and resource circularity) can be expected compared with conventional treatments for fish waste. Overall, the findings demonstrated that integrating biological and thermochemical processes could contribute to more sustainable approaches for managing biomass wastes, enabling the recovery of high-value secondary energy carriers and material resources.

How to cite: Hsu, T. Y., Huang, Y.-Z., and Fan, C.: Integration of Anaerobic Digestion and Hydrothermal Liquefaction for Resource Recovery from Fish Waste Digestate, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2934, https://doi.org/10.5194/egusphere-egu26-2934, 2026.

Volatile fatty acids (VFAs) are key intermediates produced during anaerobic processing of organic wastes and represent a recyclable carbon stream for resource recovery. Converting mixed VFA streams into microbial lipids offers a potential route to generate lipid feedstocks that can serve as precursors for sustainable aviation fuel (SAF) production. Here, we evaluated stepwise metabolic engineering strategies in the oleaginous yeast Yarrowia lipolytica to improve lipid accumulation from a mixed VFA substrate designed to mimic waste-derived streams (acetic, butyric, and hexanoic acids). While Y. lipolytica efficiently converts acetate into lipids, utilization of mixed-VFA substrates can impose physiological constraints that limit conversion performance. To address this challenge, we first overexpressed DGA1, a key enzyme for triacylglycerol (TAG) synthesis, resulting in lipid production of 0.54 g/L (1.83-fold increase). In contrast, deletion of PEX10 (peroxisomal biogenesis factor 10), a commonly applied strategy to enhance lipid accumulation in Y. lipolytica, led to reduced lipid production due to impaired utilization of butyric and hexanoic acids as substrates, as the ΔPEX10 strain showed significantly lower consumption rates of butyric and hexanoic acids compared to the control, accompanied by reduced lipid accumulation, suggesting that disruption of peroxisomal biogenesis and β-oxidation impairs the utilization of C4–C6 fatty acids as carbon sources under VFA-based cultivation. To further improve lipid biosynthesis, a heterologous acetyl-CoA synthetase from Salmonella enterica(seACS) was overexpressed to enhance acetyl-CoA supply, achieving lipid titer of 0.82 g/L. Overall, these stepwise engineering efforts resulted in a 2.77-fold increase in lipid production from mixed VFAs relative to the parental strain, demonstrating that targeted metabolic engineering can significantly improve the VFA-to-lipid bioconversion. Taken together, our findings highlight the feasibility of upgrading complex, waste-derived VFAs mixtures into microbial lipid feedstocks, providing a foundation for future waste-to-SAF and circular bioresource platforms.

How to cite: Choi, S. and Lee, S.-M.: Waste-to-SAF Precursors from Mixed Volatile Fatty Acids: Stepwise Metabolic Engineering of Yarrowia lipolytica, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6276, https://doi.org/10.5194/egusphere-egu26-6276, 2026.

The efficient development of shale gas in mountainous regions is critical for supporting China's energy security and transition towards carbon neutrality. However, the economic viability of such projects is heavily constrained by complex surface conditions, which introduce significant cost uncertainties that are difficult to quantify using conventional assessment methods. To address this, we develop a quantitative techno-economic model for mountain shale gas that integrates multi-source geospatial data. Framed within a real options analysis, the model expands the standard net present value calculation by incorporating not only traditional costs (e.g., fixed operations, exploration, royalties, surface engineering) but also spatially-variable costs derived from geospatial analysis. These include hazard mitigation, water access, ecological restoration, and community compensation.

Key spatial parameters are derived from open-access data, including high-resolution DEMs, multispectral imagery, land cover maps, infrastructure networks, and geohazard products. These datasets inform a comprehensive surface suitability assessment based on terrain ruggedness, slope, vegetation indices, and proximity to infrastructure, enabling the identification of viable wellpad locations and the estimation of maximum drillable wells. This process quantitatively translates spatial constraints into economic inputs. Monte Carlo simulation is then employed to analyze the sensitivity of project economics to key variables, particularly the number of wells and natural gas price volatility.

An application in the mountainous region of Western Hubei demonstrates the model's effectiveness in differentiating the economic potential of various blocks. The results quantify the substantial negative impact of surface complexity on both net present value and real option value, confirming well count and commodity price as the primary drivers of financial risk. This study presents a novel decision-support tool that systematically embeds geospatial data into the economic evaluation of shale gas resources in complex terrain. The developed "geospatial-data-to-economic-parameter" framework provides a transferable methodology for the techno-economic assessment of natural resource projects subject to strong spatial constraints.

How to cite: Yuan, K., Xu, X., Liu, K., and Qiu, J.: A Quantitative Techno-Economic Assessment Model for Mountain Shale Gas Development Driven by Multi-Source Geospatial Data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8749, https://doi.org/10.5194/egusphere-egu26-8749, 2026.

Driven by the goals of sustainable development, resource development demands drilling technologies with high efficiency and low energy consumption. Scientific drilling, as a key tool for accessing subsurface resources and geoscientific information, relies on energy-efficient drilling systems to achieve sustainable resource exploitation. In response, this study presents a self-balancing drilling rig hoisting system that surpasses conventional rigs in both drilling efficiency and operational stability while significantly reducing energy consumption. To characterize the dynamic performance of this rig’s hoisting system, a mathematical model was developed through theoretical analysis and validated via numerical simulation. The results demonstrate that using the proposed system for tripping operations can increase efficiency by more than 40%, and the rig operates more stably than traditional systems. Moreover, the self-balancing rig hoisting system employs two coordinated traveling-block systems to achieve self-balance against the reaction torque generated by the winch, while effectively recovering and utilizing the gravitational potential energy released during drill stem lowering. These findings provide a novel approach to improving drilling efficiency and reducing energy consumption, with significant engineering implications and theoretical value for the development of high-efficiency, energy-saving drilling operations.

How to cite: Song, W.: Dynamic Modeling and Performance Analysis of a Self-Balancing Drill Hoisting System for Efficient Resource Development, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12110, https://doi.org/10.5194/egusphere-egu26-12110, 2026.

In the context of sustainable development, high-efficiency drilling operations have become a key objective in advancing scientific drilling technology. Given the frequent coring and tripping operations involved in ultra-deep scientific drilling, automating and streamlining the make-up/breakout and handling/transfer of drill pipe wellhead tools is a critical technological pathway for improving overall drilling efficiency. To meet the demand for faster tripping operations, this study designed a high-efficiency transfer system for ultra-long drill pipe and determined its optimal operating strategy by combining experiments with finite element analysis. All experiments were conducted on a dedicated intelligent drilling platform. For three drill pipe sizes (3.5 in, 4.5 in, and 5 in), a series of tests were performed, including four-stand lifting tests, asynchronous up/down transfer tests, and inclined lean-against tests. The results indicate that the maximum bending deformation occurs within 16–21 m above the wellhead, with a peak deflection of 549 mm. Based on these findings, four-stand drill pipe are best transferred using an integrated “lower support + upper clamp” mode, whereas drill collars are better handled using a push-and-support mode. Subsequently, aiming to achieve 25 stands per hour during tripping operations, a corresponding tripping workflow and an offline operational scheme were developed. Finally, an integrated control strategy for the transfer system was proposed, considering the overall rig layout and tubular-handling process requirements. Through systematic design, experimental validation, and process optimization, this study has developed an efficient handling method and integrated control scheme for ultra-long drill pipe during drilling and tripping operations in ultra-deep scientific drilling. The findings provide technical and equipment support for the sustainable development and efficient utilization of resources.

How to cite: Gao, K.: Design and Experimental Study of an Ultra-Long Drill Pipe Transfer System for Efficient Continuous Operations in Resource Development, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12238, https://doi.org/10.5194/egusphere-egu26-12238, 2026.

This work utilizes the universal concepts of energy and Carnot Heat Engine to explain the formation of natural capital types as products of evolutionary processes, activated and driven by planetary heat engines. On this foundation, it further argues on the need for a fundamental redesign of the global economic and financial architecture with consistency to thermodynamic principles. The Laws of Thermodynamics dictate that the generation of physical work in a system with well-defined boundaries requires the existence of a heat gradient. Beginning from a typology of planetary natural capital species -ranging from fossil and nuclear fuels to minerals, biomass and genetic information- it is argued that the global stock of natural capital essentially constitutes and accumulated surplus of useful work or exergy, as the fundamental potential of economic growth. The exergy embodied in each natural capital type establishes three major economic functions: (1) for inorganic natural capital (such as fossil fuels, nuclear materials and minerals) it sets a reference state above thermodynamic equilibrium that contains intrinsic economic value and (2) for organic natural capital (such as chemically structured biomass, ecosystem functions and genetic information) it sets an optimal ecological state, sustained by daily planetary exergy flows. These two functions derive the third, (3) on the global economy’s ecological constraints to generate heat and material wastes -from the thermodynamic transformation of natural capital into economic goods- that distort the optimal ecological state. On these grounds, this work develops a quantitative economic framework with consistency to the laws of thermodynamics, introducing innovative key metrics on humanity’s evolutionary course by its energy paradigm, the thermodynamic conditions for a steady-state economy, the Jevons’ Effect as an inevitable evolutionary pressure towards energy paradigm shifts, the re-postulation of the Hartwick’s Rule of intergenerational equity on thermodynamic foundations, as well as the Scarcity Rent as a financial investment instrument for energy technology transitions.

Keywords: energy, Carnot Heat Engine, natural capital, Laws of Thermodynamics, useful work, exergy, economic growth, energy paradigm, Jevons’ Effect, Hartwick’s Rule, intergenerational equity, Scarcity Rent

References

• Kümmel Reiner. The Second Law of Economics. New York: Springer-Verlag; 2011
• Ayres Robert U, Warr Benjamin. The Economic Growth Engine. Cheltenham: Edward Elgar Publishing Ltd; 2009.
• Roegen Nicolas Georgescu. The Entropy Law and the Economic Process. Cambridge MA: Harvard University Press; 1971.

How to cite: Karakatsanis, G.: Energy, natural capital and economic growth, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13588, https://doi.org/10.5194/egusphere-egu26-13588, 2026.

Public trust is widely recognized as a key condition for public cooperation in the energy transition, yet surprisingly little is known about whether and how government communication can actively shape that trust. In particular, value-based framing strategies are often assumed to be a low-risk way to strengthen credibility, but empirical evidence on their effects remains scarce. This study examines how the value content and institutional source of government communication influence trust in practice, using a large-scale national experiment (N ≈ 3,000) embedded in an online Participatory Value Evaluation (PVE) on sustainable heat policy in the Netherlands.

Participants were randomly assigned to one of six experimental conditions or a value-neutral control group. The treatments varied along two dimensions: value-based framing (environmental, financial, or stability-related) and governance level (local versus national government). Trust in government was measured immediately before and after exposure, enabling a Difference-in-Differences design that isolates trust changes attributable to the communication treatments. To examine heterogeneity, the analysis combines DiD estimation with Latent Profile Analysis of baseline trust orientations and Honest Causal Forests to detect non-linear treatment-effect variation.

Across all specifications, value-based framing does not increase institutional trust and, in several cases, reduces it. The most consistent negative effect appears for stability framing delivered by local government. Importantly, these average null effects mask strong heterogeneity: trust responses differ substantially across latent trust profiles but not across socio-demographic groups. Individuals with higher baseline trust tend to react more negatively to value-laden messages, whereas lower-trust respondents show weakly positive or neutral responses. This indicates that communication sensitivity is driven primarily by pre-existing trust dispositions rather than demographic characteristics.

By contrast, participation in the PVE itself generates a modest but robust increase in trust across both treated and control groups, independent of framing. This pattern suggests that being invited to engage with policy trade-offs and provide input may strengthen perceptions of procedural fairness and benevolence more effectively than persuasive messaging. Overall, the findings challenge common assumptions in the nudging and public communication literatures. The findings suggest that participatory decision tools may strengthen trust, whereas value-laden communication risks unintended negative effects.

How to cite: Goes, K., Thépaut, L., Mouter, N., Chappin, E., and Kluiving, S.: Participation Builds Trust, Not Framing: Insights from a National Energy-Transition Experiment , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13892, https://doi.org/10.5194/egusphere-egu26-13892, 2026.

Tetracyclines (TCLs) are prevalent in environmental matrices and can bypass conventional wastewater treatment systems, thereby posing risks to human health and aquatic organisms. A 2D/3D Z-scheme Bi₁₂O₁₅Cl₆/Fe₂O₃@C (BFC) (specifically BFC-II, consisting 10% Fe₂O₃@C) heterojunction photocatalyst was utilized for the degradation of TCL, under visible light. At reaction conditions (initial TCL concentration: 5 mg/L; photocatalyst dosage: 0.5 g/L; solution pH: 7; temperature: 27 ± 2 ^oC), the photocatalyst demonstrated a degradation efficiency of approximately 95% after a reaction time of 90 min, with the pseudo-first order degradation rate constant (k) of 0.0329 min^-1. This could be associated with the reduced recombination rate of photoinduced charge carriers and their improved separation efficiency. Furthermore, hydroxyl radicals were identified as the primary reactive species facilitating the photocatalytic degradation of TCL. Overall, the BFC-II offers novel aspects related to the development of bismuth oxyhalide-based photocatalysts and their modification using Fe-MOF-derived materials.

How to cite: Singh, A. and Gupta, A. K.: Fe-MOF derived Fe2O3@C modified Bi12O15Cl6 for the visible light driven photocatalytic degradation of tetracycline, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16022, https://doi.org/10.5194/egusphere-egu26-16022, 2026.

Slurry-based photocatalyst reactors often suffer from secondary pollution due to catalyst leaching and low reusability, resulting from inefficient catalyst recovery. In this context, a visible light-driven Hematite/Bi₄O₅I₂ (HBI) nanocomposite was decorated on porous polyurethane foam (PU). The HBI nanocomposite was prepared by facile room temperature chemical precipitation, subsequently immobilized on PU via an eloquent chemical deposition technique. The inherent floating property of PU supported the mass transfer within the reactor, which could be attributed to the heat-induced convection across the HBI@PU  bed depth and stirring-induced convection throughout the phenolic solution. Thus, facilitating the transportation of pollutants and reactive species to the catalyst surface. As a result, the adsorption and photocatalysis were enhanced simultaneously. Moreover, the as-synthesized HBI and HBI@PU materials were characterized thoroughly using various techniques, including XRD, SEM, TEM, UV-DRS, and XPS. Furthermore, the photocatalysis of phenolics using HBI@PU was evaluated under optimal conditions: initial concentration of phenolics, 10 ppm; weight of catalyst material used, 0.25 g; pH, 6.2; and photocatalysis time, 80 min. The open-pore structure of the PU foam significantly enhanced the adsorption of phenolics, indicating that the foam provides additional porosity and adsorption sites. Consequently, the overall recorded removal of BPA, m-cresol, and phenol was 92.07 ± 1.53%, 84.25 ± 2.59%, and 59.41 ± 2.14%, respectively. Notably, only a marginal drop in removal efficiency was observed after subsequent recycles of photocatalysis. Hence, the as-synthesised visible light-driven floating HBI@PU photocatalyst holds potential applications in green and sustainable environmental remediation.

How to cite: Rawat, A., Srivastava, S. K., Tiwary, C. S., and Gupta, A. K.: Vis-LED responsive floating Hematite/Bi4O5I2 decorated polyurethane foam for synergistic adsorption-photocatalysis of phenols, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16043, https://doi.org/10.5194/egusphere-egu26-16043, 2026.

The widespread presence of antibiotics such as sulfamethoxazole (SMX) and tetracycline (TC) in aquatic environments poses a significant threat to ecological safety. In this study, aluminum-based multicomponent alloys engineered into two-dimensional quasicrystals (2D QCs) are presented as a robust and reusable photocatalyst for visible-light-driven degradation of SMX and TC. The catalyst achieved degradation efficiencies of approximately 94% for SMX and 89% for TC within 2 hours. The photocatalytic activity was thoroughly examined under various conditions, including pH variations, catalyst dosage, pollutant concentration, and the influence of common inorganic ions. The 2D QCs demonstrated excellent reusability with negligible metal leaching across successive cycles. Notably, substantial degradation was also achieved in real water matrices such as tap water, pond water, and municipal wastewater, highlighting their environmental practicality. Furthermore, in situ liquid-phase transmission electron microscopy captured the real-time degradation of SMX antibiotic molecules on QC surfaces. Phytotoxicity assays with Vigna radiata confirmed that the treated effluents were non-toxic, as seed germination and root growth were comparable to those of the controls. This work identifies 2D QCs as a highly effective photocatalyst for antibiotic removal in complex water systems, addressing an urgent global challenge.

How to cite: Manzoor, Z., Chowdhury, S., and Tiwary, C. S.: Mechanistic insights into antibiotic degradation using multicomponent 2D quasicrystals as robust photocatalysts via in situ TEM, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18267, https://doi.org/10.5194/egusphere-egu26-18267, 2026.

Water distribution networks (WDNs) are a critical component of modern society, responsible for delivering water to local communities and industries while maintaining continuous, stable flow within the system, which carries low-grade hydropower potential. These systems are vulnerable to disruptive events, such as pipeline failures and water contamination. To mitigate the risk of disruption events, recent EU policies have focused on the digitalisation of critical infrastructure, including WDNs and wastewater treatment plants (WWTPs), through the integration of Internet of Things (IoT) technologies. Digitalisation enables system operators to collect real-time data and perform predictive maintenance, thereby improving resilience and operational efficiency. Thus, system electricity requirements will increase to support IoT and digitalisation retrofitting.

This creates an opportunity to deploy energy-harvesting (EH) devices within WDNs and WWTP infrastructure that harness and utilise the resonant and kinetic energy inherent in water flow. Although the benefits of EH devices are often considered minimal and their energy outputs are low, EH devices are considered a viable power source for low-power sensors, such as pressure, contamination, and temperature sensors.

This study proposes and applies a feasibility assessment framework to evaluate EH devices as an alternative, decentralised power source for IoT-enabled monitoring in WDNs. The framework includes technical performance analysis, economic viability, and environmental impact assessments, combined with probability-based resilience modelling. It uses case-specific hydraulic, operational, design, and economic data to quantify EH power outputs, assess the costs of design and deployment, evaluate the environmental footprint of the devices, determine sensor energy requirements, and assess system resilience across different deployment scenarios.

Results demonstrate that the EH device has a mechanical power-generation capacity potential ranging from 0.049 to 36 watts, depending on the study location, flow conditions, and design characteristics. This EH generation capacity is sufficient to power pressure, contamination, and temperature sensors. The resilience modelling indicates that the detection probability of WDNs exhibits the most significant gains from adding sensors at low deployment levels. Thus, most of the improvement in detection levels occurs between deploying the first five to ten sensors; beyond this threshold, adding more sensors exhibits diminishing marginal returns to detection probability and system resilience. In addition, adding more sensors can significantly reduce system resilience by increasing power requirements, thereby placing excessive load on the power supply of the EH devices. Thus, it increases the risk of failure rather than enhancing resilience.

Overall, the results underscore the importance of strategic sensor allocation over high-density deployment and of balancing monitoring coverage with energy availability. Furthermore, the results show that EH devices are suitable power-generation technologies for supporting the digitalisation of WDNs and informing the design of new monitoring systems and sensor placement to enhance system reliability, enable cost-effective monitoring, and maximise mitigation benefits. In addition, the proposed framework provides decision-makers with a structured approach to assessing EH integration applications for digitalised WDNs, focusing on enhancing resilience through monitoring, conducting technical performance and cost-benefit analyses, assessing environmental trade-offs, and designing monitoring strategies aligned with sustainability and resilience objectives.

How to cite: Guðlaugsson, B., Stepanovic, I., Marguerite Bronkema, B., and Christian Finger, D.: Enhancing water system resilience and reliability: Application of Multidimensional Feasibility Assessment framework to assess if the deployment of energy harvesting devices in urban water systems enables a higher degree of system resilience., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19267, https://doi.org/10.5194/egusphere-egu26-19267, 2026.

Agent-based models (ABMs) are increasingly used to study climate action, yet models remain fragmented and highly case-specific, preventing the field from rigorously advancing shared modeling principles, comparing models across cases, and cumulating knowledge over different applications. Our paper proposes a transferable two-tier ABM framework serving as a conceptual and practical guide for researchers tackling climate-action research questions with ABMs, offering an abstract architecture to replace the ad hoc design of case-specific models for climate action. Tier 1 introduces a functional architecture in which social, economic–financial, governance, and biophysical subsystems generate policies, information, physical impacts, and market interactions that feed the agent decision-making mechanism. Agents process these inputs, select and implement climate actions, and thereby generate feedback that updates all subsystems over time. Between Tier 1 and an implementable model, our pathway introduces a classification step that links the generic architecture to specific decision-making. We classify climate actions by action locus (individual, collective, autonomous) and adaptation timing (reactive, concurrent, proactive), indicating how decision-making and information flows from Tier 1 should be represented for each class. In our study, we instantiate one cell of the design space—proactive, individual household action—by extending the Protective Action Decision Model (Lindell & Perry, 2012) to longer decision horizons and embedding economic–financial drivers, social cues, and environmental signals into a multi-stage decision pathway. Our Tier 2 module describes how households process cues, appraise risk, screen feasible actions, and implement measures under evolving conditions. Our framework provides a structured pathway for developing transparent, comparable, and empirically grounded ABMs for climate action and for accumulating evidence across applications.

How to cite: Brahim, W. and Heinz, B.: From Ad Hoc to Transferable: A Two-Tier Architecture for Agent-Based Climate Action Models, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20849, https://doi.org/10.5194/egusphere-egu26-20849, 2026.

The global pursuit of clean and sustainable energy has increased interest in hydrogen as a key energy carrier for achieving carbon neutrality. Consequently, global demand for hydrogen is anticipated to grow significantly in both the near and long term, necessitating the development of hydrogen production methods. While several researches have examined hydrogen generation through inorganic processes such as serpentinization, the potential of organic-rich sedimentary formations remains underexplored. This study investigates hydrogen-rich gas generating potential and fracture evolution of organic-rich rocks, with a particular focus on immature shales under controlled thermal treatment, aiming to enhance the yield of clean hydrogen gas. Pyrolysis experiments were conducted to simulate subsurface geological conditions, supported by comprehensive characterization using X-ray diffraction (XRD), X-ray fluorescence (XRF), thermogravimetric analysis (TGA). Gas Chromatography (GC) was used to analyze the gases generated at various heating temperatures and micro-CT imaging was used to examine the samples subjected to varying temperatures. The results show that hydrogen generation increases with temperature, with yields rising from 0.31% at 100°C to 36.02% at 450°C. High-resolution micro-CT imaging shows that thermally induced fractures developed predominantly parallel to bedding planes, enhancing permeability and facilitating gas migration. The progressive decomposition of organic matter, coupled with fracture development, significantly improved hydrogen release efficiency. These findings highlight the potential of organic-rich rocks, as viable and cost-effective targets for natural hydrogen exploration and in situ hydrogen gas generation and offering a pathway toward sustainable subsurface hydrogen exploitation strategies.

How to cite: Kimayim, A., Tawabini, B., Abu-Mahfouz, I., and Yaseri, A.: Exploring the Potential of Organic-Rich Shales for In Situ Hydrogen Production through Thermal Stimulation and Fracturing., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-708, https://doi.org/10.5194/egusphere-egu26-708, 2026.

The geochemical interactions between shale, supercritical carbon dioxied (SC-CO₂ ), and brine play a significant role in determining both the possibility of carbon storage and the long-term stability of shale gas reservoirs. The shale samples were exposed to CO₂-brine-rich environments for a period of 30 days to simulate the in-situ conditions of the shale reservoirs. The pre- and post-analysis were conducted to identify changes in mineralogy, chemical bonding, pore structure, surface texture and morphology. Several analytical techniques, including X-ray diffraction (XRD), thermogravimetric analysis (TGA), Fourier transform infrared spectrometry (FTIR), scanning electron microscopy (SEM), and low-pressure gas adsorption (LPGA), were used for characterisation. The results show that significant mineralogical changes occurred to clay minerals and carbonate, accompanied by modification in hydrocarbon functional groups and fluctuation in micropore and mesopore parameters. The consistent variations in pore characteristics are attributed to continuous processes of dissolution- precipitation and development of increased surface roughness due to reaction. The formation of microfractures and the etching effect of the samples were studied using high-resolution SEM images. TGA study confirmed the systematic mass loss caused due to prolonged reactions. These findings indicate that the reservoir integrity and the storage capacity can be affected due to pore structure evolution during geological CO₂ sequestration. Additionally, the changes documented in this study can provide the pathway to improve shale gas recovery, signifying the crucial role of shale formation in global decarbonization efforts

How to cite: Ghosh Dastidar, S., Sarkar, K., Chandra, D., Vishal, V., and Hazra, B.: Experimental Investigation of Geochemical Interactions between Supercritical CO₂ and Shale, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-756, https://doi.org/10.5194/egusphere-egu26-756, 2026.

Oil shale self-heating in-situ conversion technology has emerged as a significant development direction due to its environmental friendliness and cost advantages. However, conventional constant injection-production parameters often lead to inefficient compression energy input and formation oxidation losses, limiting further improvement in energy return ratio (ERR) and oil yield. This study establishes a dynamic optimization model for injection-production parameters in oil shale self-heating in-situ extraction and develops a method for dynamically regulating gas injection rate and oxygen content to enhance process economy and feasibility.Results indicate that under the optimal gas injection parameters (adjustment duration: 120 days, decay rate: 1200, final flow rate: 40 m³/day), the steady-state phase in late production reduces compression energy consumption by 90% and CO₂ production by 48%, significantly decreasing cumulative compression energy input and suppressing hydrocarbon oxidation losses. Consequently, the peak ERR reaches 13.87, representing a 132.33% improvement over constant-rate injection, while oil production increases to 47 m³/m, a 66.9% enhancement. Furthermore, synergistic regulation of oxygen content and injection rate reduces compression energy by an additional 16%, elevating the peak ERR to 14.80—a 6.71% further increase—demonstrating technical feasibility for industrial application. These findings and key parameters provide theoretical and technical support for the large-scale implementation of oil shale self-heating in-situ conversion technology.

How to cite: Zhu, C., Li, Q., Deng, S., Bai, F., and Guo, W.: Dynamic Optimization Control of Injection-Production Parameters for Oil Shale Self-Heating In-Situ Conversion, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1481, https://doi.org/10.5194/egusphere-egu26-1481, 2026.

The mobility and producible volume of shale oil are key factors controlling the effectiveness of shale oil exploration and development and are fundamentally governed by the occurrence state of hydrocarbons within shale pore systems. Consequently, accurate identification and quantitative characterization of oil–water occurrence in shales represent a core scientific challenge in shale oil research. Current investigations rely heavily on fresh or pressure-preserved cores. However, during routine coring, handling, and storage, substantial fluid loss is inevitable, rendering most conventionally cored shale samples unsuitable for in situ fluid-occurrence analysis. Although pressure-preserved coring can effectively maintain original fluid states, its high operational cost severely restricts large-scale application. Therefore, restoring the original pore-fluid occurrence in conventionally cored shales has become a critical technical bottleneck.To overcome this limitation, we develop a novel workflow integrating alternating oil–water spontaneous imbibition with nuclear magnetic resonance (NMR) measurements to recover the original fluid-occurrence state in conventionally cored shales. Pressure-preserved shale cores were first exposed to laboratory conditions to simulate fluid loss during conventional coring. Subsequently, a multistage alternating spontaneous imbibition procedure was implemented using n-dodecane and 15 wt% KCl brine as imbibing fluids to progressively restore the original oil and water contents. Throughout the entire fluid-loss and restoration processes, NMR T₁–T₂ maps were continuously acquired to dynamically monitor variations in oil and water contents and their pore-scale migration behaviour.

The results indicate that shale cores experience rapid oil–water loss during the initial 0–80 h, followed by a markedly reduced loss rate between 80 and 500 h, and reach a quasi-steady state after approximately 500 h, with a cumulative fluid loss of ~45%. During the alternating imbibition procedure, the samples undergo four successive stages, namely primary oil imbibition, water imbibition, secondary oil imbibition, and secondary water imbibition, each approaching a new dynamic equilibrium. After restoration, the oil and water saturations of the conventionally cored shales show strong agreement with those of the corresponding pressure-preserved samples.These findings demonstrate that the proposed method can effectively recover the original pore-fluid occurrence state in conventionally cored shales, enabling reliable characterization of shale oil and water distribution. The workflow is expected to significantly improve the accuracy of shale oil sweet-spot evaluation and provide new technical support for shale reservoir exploration and development.

How to cite: Chen, J. and Wang, M.: Restoring Original Pore-Fluid Occurrence in Conventionally Cored Shales: Insights from Alternating Oil–Water Spontaneous Imbibition and Nuclear Magnetic Resonance, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2169, https://doi.org/10.5194/egusphere-egu26-2169, 2026.

Oil and gas reserves are crucial resources for human survival, directly affecting the sustainable development and utilization of future energy. In order to protect the Earth we live on, it is crucial to enhance our understanding and judgment of the trends in oil and gas reserves and to use these resources wisely. To explore new methods for predicting oil and gas reserves, promote sustainable energy development, and provide a theoretical basis for oil and gas exploration and development, this study takes the Neuquén Basin in South America as an example. By combining oil and gas reserve growth data with various geological characteristics and other comprehensive information, a Monte Carlo search + ARIMA algorithm-based method for predicting oil and gas reserves is proposed and applied to the Neuquén Basin for predictive validation. This method analyzes the structural background and divides the basin into structural units to decompose the basin’s reserves into reserves within each structural unit. The reserve growth data from each unit are input into the model, and the parameters required by the model are obtained through Monte Carlo search to produce predictive results. This approach successfully captures the inherent trends of reserve changes and the dynamic features of reserve growth. The method shows significant effectiveness in predicting reserves in the Neuquén Basin, with the predictive model demonstrating high accuracy in fitting.

How to cite: Li, H. and Zhang, L.: oil and gas reserve prediction method based on Monte Carlo Search + ARIMA algorithm: A case study of the Neuquén basin in South America, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2263, https://doi.org/10.5194/egusphere-egu26-2263, 2026.

Lacustrine shale reservoirs exhibit complex pore structures and strong heterogeneity, which exert a critical control on hydrocarbon storage and fluid flow. Although numerous studies have independently investigated organic matter–hosted pores and inorganic mineral pores, the coupled evolution of organic matter and inorganic minerals—and its influence on pore development across different thermal maturity stages—remains insufficiently understood. In this study, shale samples from the Qingshankou Formation in the Gulong Sag, spanning a range of thermal maturities, were analyzed using field-emission scanning electron microscopy (FE-SEM) combined with quantitative pore characterization techniques. The results indicate that pore formation and evolution in lacustrine shale are fundamentally governed by the coupled evolution of organic matter and inorganic minerals. Organic matter–clay composite pores are closely associated with organic matter thermal cracking and clay mineral transformation processes, and their development is primarily controlled by thermal maturity and clay mineral content. Organic matter–hosted pores are mainly influenced by organic matter type, abundance, and maturity, while inorganic minerals—particularly pyrite and clay minerals—can significantly promote organic matter cracking. Interparticle pores are closely related to the abundance of felsic minerals and thermal maturity; however, organic acid dissolution and ion precipitation during clay mineral transformation may partially or completely occlude these pores. In addition, organic acid dissolution capacity (controlled by total organic carbon content, soluble mineral content, and vitrinite reflectance Ro) and clay mineral transformation processes (controlled by clay content and Ro) further regulate intraparticle pore development by influencing dissolution pores and clay intercrystalline pores, respectively. These findings provide important insights into the genesis and evolutionary mechanisms of pores in lacustrine shale reservoirs.

How to cite: Dong, S. and Wang, M.: Pore Genesis and Organic–Inorganic Synergistic Evolution of Lacustrine Organic-Rich Shales, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2286, https://doi.org/10.5194/egusphere-egu26-2286, 2026.

Abstract

The buried depth of Archean metamorphic buried hill in Bozhong L Oilfield of Bohai Bay Basin is more than 4000 meters, and the matrix porosity and permeability are extremely low. As an effective reservoir space and seepage channel, natural fractures are the core controlling factors for oil and gas enrichment and high yield in buried hills of tight metamorphic rocks. Due to the influence of multi-stage tectonic movement and weathering, the development of buried hill fractures is complex. At the same time, due to the lack of core and imaging logging data, the study of fracture regularity is not systematic. In this study, the data of core, thin section, scanning electron microscope, imaging logging, conventional logging and production performance were comprehensively used to carry out conventional logging fracture identification, and the vertical and plane distribution of fractures and their influence on productivity were clarified. The conventional logging is calibrated by core and imaging logging, and four logging curves sensitive to fractures, such as resistivity difference, density, acoustic time difference and natural gamma, are optimized. The correlation degree between each parameter and fracture is calculated and weighted, and the fracture indication parameter curve is constructed. Compared with the results of fracture identification such as core and imaging logging in the study area and the dynamic data such as leakage, the accuracy of fracture identification based on conventional logging is more than 85 %. In the longitudinal direction, the strong weathered zone is dominated by weathering fractures, with high degree of fracture filling and strong reservoir heterogeneity. The sub-weathered zone develops structures and weathering fractures, which are transformed by dissolution and have high porosity and high permeability. The tight zone only develops regional structural fractures with low porosity and low permeability. The inner fracture zone is dominated by fault-related structural fractures, with low porosity and high permeability. The degree of fracture development is sub-weathered zone > strong weathered zone > inner fracture zone > tight zone. On the plane, fracture development is mainly controlled by faults. With the increase of distance from faults, the degree of fracture development decreases exponentially. The degree of fracture development is significantly positively correlated with productivity. The more developed the fracture is, the higher the productivity is. The research results can provide reference for the characterization of natural fractures in deep metamorphic buried hill reservoirs, and provide geological basis for the efficient development of deep metamorphic buried hill reservoirs in this area.

Key words

Metamorphic buried hills; Conventional logging; Fracture identification; Distribution law; Capacity; Bohai Sea

How to cite: Guo, R., Lv, W., Zeng, L., Du, X., Li, H., and Yin, J.: Study on fracture distribution law of buried hill in deep metamorphic rock : A case study of Bozhong L oilfield in Bohai Bay Basin, China, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3007, https://doi.org/10.5194/egusphere-egu26-3007, 2026.

Abstract: Natural fractures in tight sandstone reservoirs play an important role in hydrocarbon migration and accumulation. Fracture identification remains challenging due to the scarcity of labeled data and the complex logging responses of fractures. To address these problems, we propose a novel hybrid deep learning framework (CNN-Attention-BiLSTM). First, labeled fracture classification based on Full waveform sonic logs characteristics is employed to screen unlabeled data, replacing sampling algorithms for data balancing. This approach provides more fracture labels that align with authentic geological information. Subsequently, one-dimensional convolution is applied to construct multi-dimensional fracture logging response patterns that characterize fracture development. A Channel Self-Attention is introduced to assign optimal weights to response patterns across different dimensions, achieving an optimized pattern combination. A double-layer BiLSTM is then utilized to mitigate the impact of sedimentary cycles on logging identification, while capturing both short- and long-term dependencies of fracture responses across different network layers. The identification method is applied to the H1 member of the Lower Shihezi Formation in the Hangjinqi area, China. The test set accuracy is higher than 90%, and blind wells verification demonstrates an improvement of over 8% in accuracy compared to conventional methods. The identification results reveal that fractures are the most developed in H1-2, followed by H1-1 and H1-3, while H1-4 is the least developed layer. The fracture distribution pattern is evidently controlled by sedimentary rhythms, with fracture density decreasing in the order: interbedded sandstone and mudstone layers, thick sandstone and thick mudstone, thick mudstone and poorly developed sandstones. This trend is primarily attributed to the thickness of mechanical stratigraphy. Under equivalent tectonic stress conditions, thin sandstone layers are more prone to fracturing due to stress concentration, resulting in higher fracture density. Additionally, the proposed method deepens the correlation between the log response types of fractures and their development degree. It clarifies that fractures occur in varied patterns across different regions. In sandy conglomerates and gravel coarse sandstone intervals with high porosity and permeability, fractures tend to occur as single or multiple parallel fractures and are relatively less developed. fractures are more prevalent in the overlying and underlying intervals. Conversely, in tight sandstone intervals with poor porosity and permeability, the rock is more brittle, leading to the development of dense, interconnected fracture networks. And gas distribution shows correlate strongly with fracture-developed intervals. Therefore, it can be inferred that in intervals with high-quality sandstone reservoirs in the study area, fractures likely serve as vertical conduits connecting upper and lower gas-bearing zones, acting as preferential migration pathways. In contrast, within tight sandstone intervals, fractures primarily enhance matrix reservoir quality, thereby facilitating gas migration and accumulation. The intelligent fracture identification method proposed in this study can provide guidance for the migration, accumulation and efficient development of tight sandstone gas, Further, it can also offer a basis for the later carbon dioxide storage and the construction of underground gas storage of tight sandstone.

Keywords: Fracture identification; Tight reservoirs; Full waveform sonic logs; Conventional logs; Deep learning 

How to cite: Liang, B., Zeng, L., and Dong, S.: Intelligent fracture identification and its geological significance in tight sandstone reservoirs., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4140, https://doi.org/10.5194/egusphere-egu26-4140, 2026.

Free hydrocarbon content (S1) is a key parameter for source rock evaluation and sweet spot identification in organic-rich shale reservoirs. Accurate determination of S1 is essential for petroleum exploration; however, traditional measurements rely on expensive core acquisition and Rock-Eval pyrolysis, limiting spatial coverage and operational efficiency. Empirical and log-based models often fail to capture complex non-linear relationships between S1, petrophysical logs, and geochemical properties. This study presents an integrated, physics-informed machine learning workflow for predicting S1 from well logs, mineralogical, and geomechanical data in the upper Shahejie Formation. The dataset comprises 357 S1 core measurements matched to high-resolution well logs (gamma ray, acoustic travel time, density, neutron porosity, and resistivity) over a 799 m stratigraphic interval. To address the inherent depth mismatch between irregularly spaced cores and regularly sampled logs, a constrained nearest-neighbor depth-matching strategy was implemented and validated.  Quality control confirmed minimal bias and high precision, ensuring that observed log S1 correlations represent true petrophysical trends rather than alignment-related biases. Physics-informed feature engineering was applied to capture geological ratios, porosity interactions, and depth trends. Interaction terms, including resistivity-TOC combinations, were incorporated to reflect hydrocarbon saturation and organic matter effects. Six ML algorithms were evaluated, including tree-based ensembles, kernel-based methods, and neural networks. The gradient boosting model achieved the best performance, with a correlation coefficient of 0.92 on independent test data and an RMSE of 0.58, representing a 33% improvement over a logs-only baseline. Cross-validation based on unique S1 measurements was used to prevent data leakage and demonstrated stable generalization across the dataset. Feature importance analysis highlights the dominant contribution of physics-informed terms, confirming that physically constrained predictors outperform individual logging or geochemical parameters. The proposed workflow enables continuous S1 profiling with minimal core measurements, supporting reservoir characterization and sweet-spot identification while reducing reliance on expensive geochemical analyses. This study demonstrates how combining rigorous depth alignment, physics-guided feature engineering, and machine learning can deliver reliable continuous S1 prediction for shale energy resources.

How to cite: Bennani, R. and Wang, M.: Physics-Informed Machine Learning Workflow for Free Hydrocarbon Content (S1) Prediction in Organic-Rich Shale Formation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5306, https://doi.org/10.5194/egusphere-egu26-5306, 2026.

With the continuous advancement of oil and gas exploration technologies and associated theoretical frameworks, deep to ultra-deep oil and gas exploration has emerged as a pivotal component of contemporary petroleum geology research and currently seems as a focal area of interest. But, overpressure is prevalent in deep to ultra-deep formations, and there are substantial discrepancies in studies regarding the impact of overpressure on the maturity of hydrocarbon source rocks and hydrocarbon generation. These discrepancies have hindered a comprehensive understanding of hydrocarbon formation and phase states in ultra-deep settings, thereby constraining deep oil and gas exploration endeavors.

The Shawan Sag in the Junggar Basin is characterized by widespread and high-intensity overpressure development, coupled with huge hydrocarbon resources in the lower stratigraphic assemblage. Among these, The Fengcheng Formation, serving as the primary hydrocarbon source rock, is the main source of oil and gas for the reservoirs within the sag. Consequently, this study focuses on the Permian hydrocarbon source rocks in the Shawan Sag of the Junggar Basin as the primary research target. After ascertaining the overpressure development in the Permian strata, typical low-maturity samples were selected to conduct hydrocarbon generation physical simulation experiments under varying pressure conditions. Based on these experiments, maturity evolution and hydrocarbon generation kinetic models that account for pressure were established, and thermal-maturity-hydrocarbon generation evolutionary history simulations were performed for typical wells and a 2D cross-section.

The results reveal the following: (1) There is a negative correlation between vitrinite reflectance and pressure in the vertical direction, with Ro evolution being lower than the normal trend in overpressure zones. (2) Thermal simulation experiments confirm that, under identical temperature conditions, higher pressure leads to a lower equivalent Ro and a greater proportion of medium-to-heavy components in the generated hydrocarbon products, demonstrating the inhibitory effect of pressure on hydrocarbon source rock maturity and hydrocarbon generation products. (3) Based on the results of physical simulation experiments and measured geological data, a 2D thermal-maturity-hydrocarbon generation evolutionary history for the Shawan Sag was simulated. It is concluded that the hydrocarbon source rocks in the Fengcheng Formation of the Shawan Sag are predominantly Type II highly mature hydrocarbon source rocks. The hydrocarbon generation threshold is suppressed until the end of the Triassic, with significant oil generation commencing in the late Jurassic and entering the highly mature stage by the end of the Cretaceous. Regarding hydrocarbon generation products, the cracking of heavy hydrocarbons to generate gas in the Fengcheng Formation is inhibited by overpressure. This study contributes to enhancing the theoretical understanding of overpressure-inhibited hydrocarbon generation and holds practical significance for hydrocarbon exploration in ultra-deep formations within the Shawan Sag.

How to cite: He, B. and Liu, J.: Maturity Evolution History and Hydrocarbon Generation Evolution History of Hydrocarbon Source Rocks in the Fengcheng Formation, Shawan Sag, Under the Influence of Overpressure, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6097, https://doi.org/10.5194/egusphere-egu26-6097, 2026.

Shale reservoirs exhibit complex wettability. Under in-situ formation conditions, oil and water coexist as two phases, and interfacial interactions are pronounced, thereby influencing fluid occurrence state and mobility. Therefore, developing methods to evaluate wettability and mobility under oil–water coexistence conditions, and elucidating the controlling mechanism of wettability on mobility, is crucial for assessing petroleum reserves, production performance, and economic benefits. To this end, this study selected representative terrestrial medium- to high-maturity shale samples from the Lianggaoshan Formation in the Sichuan Basin and conducted alternating oil–water imbibition–NMR–centrifugation experiments. The results indicate strong heterogeneity in pore wettability: water-wet pores are mainly associated with quartz–feldspar minerals, attributable to their intrinsically hydrophilic surfaces; oil-wet pores are related to clay minerals and organic matter rich in polar functional groups, where adherent oil films readily form; mixed-wet pores are associated with carbonate minerals, for which a more balanced interfacial energy state is conducive to oil–water coexistence. Mobility analysis further shows that better reservoir properties, favorable pore–throat configuration, higher proportions of NMR-identified large pores plus microfractures, and higher TOC content all promote shale-oil mobility. Moreover, wettability serves as an even more critical factor influencing mobility: the mobile fraction is positively correlated with the proportion of mixed-wet pores and negatively correlated with the proportion of oil-wet pores. Wettability differences can enhance fluid connectivity by regulating capillary effects and interfacial tension, thereby increasing the mobile fraction. This study highlights the necessity of investigating the controlling mechanism of wettability on mobility, providing an important theoretical basis for understanding pore-scale fluid behavior in shale and for optimizing unconventional oil and gas recovery.

How to cite: Li, T. and Wang, M.: Evaluation of Shale Pore Wettability under Oil–Water Coexistence Conditions and Its Control on Fluid Mobility, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7418, https://doi.org/10.5194/egusphere-egu26-7418, 2026.

The high-temperature conditions of deep mining significantly affect the mechanical stability of tar-rich coal. The mechanical properties and energy evolution characteristics of heat-treated tar-rich coal are discussed in this study through experiments and corresponding analyses. The research object is tar-rich coal from the Shaanxi coalfield in China. Microstructural and static/dynamic mechanical tests were conducted on specimens heat-treated at different temperatures (25℃, 200℃, 400℃, and 600℃) to study their structural changes and mechanical behavior. The study shows that tar-rich coal undergoes rapid pyrolysis after 418℃. Therefore, the surface cracks of the coal sample treated at 600℃ deepen, leading to an eight-fold increase in porosity and a permeability as high as 87.1%. The size distribution range of pores and cracks expands, and multifractal characteristics become more pronounced. The carbon composition of the heat-treated tar-rich coal gradually changes from being predominantly aliphatic carbon to being predominantly aromatic carbon. Its surface structure undergoes an evolution from “dense” to “cellular” and then to “fracture-connected”. After static pressure, the failure mode shifts from brittle failure dominated by tension to ductile failure dominated by shear slip and plastic rheology. The energy evolution under different confining pressures exhibits an inherent consistency, with approximately 29% of the input energy dissipated irreversibly. The energy dissipation mechanism under dynamic compressive loading tends towards volumetric fragmentation and shear slip, while the energy in dynamic splitting tests is more concentrated in the generation of through-tensile cracks. This results in the energy absorbed during dynamic compressive failure being 2-3 times that absorbed during dynamic splitting under the same conditions. Overall, temperature significantly affects parameters directly reflecting mechanical properties, while impact pressure influences strength indicators by increasing energy absorption.

How to cite: Meng, F. and Xie, Q.: Study on the structural evolution and mechanical deterioration characteristics of heat-treated tar-rich coal, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7522, https://doi.org/10.5194/egusphere-egu26-7522, 2026.

Understanding shale oil occurrence differences and their controlling factors is essential for evaluating shale oil resource potential and predicting favorable oil-bearing lithofacies. The Lianggaoshan Formation shales in the Sichuan Basin, China, are characterized by diverse lithologies and strong reservoir heterogeneity, resulting in significant variations in shale oil occurrence modes, distribution, and content. Previous studies have mainly focused on oil-bearing differences among lithofacies, whereas fine-scale characterization of shale oil occurrence and its controlling mechanisms at the lamina-to-layer scale remains limited. In this study, shale oil occurrence characteristics of the Lianggaoshan Formation were systematically investigated using X-ray diffraction (XRD), X-ray fluorescence (XRF), rock pyrolysis, nitrogen adsorption before and after extraction, nuclear magnetic resonance (NMR), laser scanning confocal microscopy, scanning electron microscopy (SEM), and multiple temperature step rock pyrolysis, combined with light hydrocarbon recovery and micro-drilling sampling. Results show that the Lianggaoshan Formation shales exhibit good oil-bearing capacity from the nanometer to centimeter scale. Shale oil mainly occurs as oil films, with no nearly spherical oil droplets observed. Light oil is preferentially enriched in interparticle pores and bedding fractures, whereas heavier components are mainly retained within interparticle pores. Five shale lithofacies are identified: moderately organic laminar siliceous-rich shale (MLSS); moderately organic laminar clay-rich shale (MLCS); highly organic laminar clay-rich shale (HLCS); moderately organic laminar mixed-composition shale (MLMS); and moderately organic beded clay-rich shale (MBCS). Among them, HLCS exhibits the highest contents of both free and adsorbed oil, with oil occurring across the entire pore-size spectrum and the oil-bearing volume peaking at a pore diameter of approximately 100 nm. In contrast, the other lithofacies contain oil mainly within the 3–100 nm pore-size range, with the lower limit for free oil occurrence at 3 nm.At the millimeter scale, different lithofacies are composed of various combinations of pure clay layers, clay–siliceous/calcareous interbeds, pure siliceous layers, and calcareous laminae or Beded structures. Clay-dominated layers and clay–siliceous/calcareous assemblages contain significantly higher free oil contents than pure siliceous or calcareous laminar/Beded structures. HLCS consists of interbedded clay layers and clay–siliceous/calcareous units, in which siliceous and calcareous laminae provide higher-quality reservoir space, accounting for its elevated free oil content. Free oil abundance is mainly controlled by total organic carbon (TOC), porosity, and pore volume, and shows weak correlation with siliceous mineral content. These results provide a scientific basis for screening favorable shale oil lithofacies in the Lianggaoshan Formation.

How to cite: zhang, Y., wang, M., and wang, X.: Mechanisms and Main Controlling Factors of Shale Oil Occurrence Differences: A Case Study of the Lianggaoshan Formation, Sichuan Basin, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10378, https://doi.org/10.5194/egusphere-egu26-10378, 2026.

Reservoir quality in carbonate systems is commonly controlled by secondary porosity associated with fractures and karst. Accurate characterisation of these features is critical for predicting fluid storage and permeability distribution, yet remains challenging using conventional downhole geophysical logging techniques. Interpretation is typically performed manually using resistivity borehole images (BHIs), which resolve rock texture at millimetre scale. However, this approach is time-consuming and yields only a limited and largely qualitative representation of the true porosity distribution, as only a small number of features can be mapped.

To obtain a more comprehensive picture of the macroscopic porosity distribution, we developed a semi-automated workflow for high-resolution pore space mapping and classification in BHIs. We focus on greyscale-converted images rather than raw resistivity data because they are more commonly available for legacy wells. Our workflow applies simple thresholding to generate binary porosity maps from both static (linear conversion of resistivity to brightness) and dynamic images (with histogram equalisation). The dynamic map is grafted onto the static map in areas identified as dark or bright in the blurred static image, resulting in a millimetre-scale porosity map of the borehole wall. Following interpolation between the imager pads and/or flaps, geometric properties are extracted for each connected cluster of mapped pixels, allowing classification of pore types as fractures, vugs, or karst features. The workflow performs well in limestone and dolostone sequences with high resistivity contrast between matrix and pore space, but is less reliable in marly intervals and in sections affected by poor borehole or data quality. We are currently developing an updated, fully automated workflow leveraging machine learning algorithms for pore space segmentation and classification.

As a first application, we analysed BHIs from the North Alpine Foreland Basin in Bavaria, where the Upper Jurassic hosts a hydrothermal reservoir. Of the 16 good-quality BHIs analysed, visual inspection indicates that 13 produced reliable results. By combining the derived macroscopic porosity with available matrix porosity measurements, total porosity can be estimated along the well path. Integration with additional well data enables us to define porosity–permeability trends for active flow zones, elucidate controls on pore space distribution, and derive realistic porosity ranges for reservoir model parameterisation.

How to cite: Bamberg, B., Gajjala, G. R., and Zosseder, K.: Semi-automated porosity mapping in carbonate reservoirs using borehole images, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12538, https://doi.org/10.5194/egusphere-egu26-12538, 2026.

Targeting the extreme downhole environments of oil-rich coal in-situ pyrolysis—characterized by high pressure up to 21MPa, severe corrosion with 3% H₂S content, substantial temperature fluctuations from 120℃ to 650℃, and inherent difficulties in data acquisition—traditional heater control systems suffer from inadequate precision, weak anti-interference capability, poor adaptability, and lack of effective life prediction methodologies for unoperated scenarios. To address these issues, this study conducts in-depth research on an intelligent control system centered on the full-link closed-loop control logic of "perception-decision-execution-feedback".

A novel three-model collaborative decision-making architecture integrating "physical benchmark-condition adaptation-time series supplement" is established. The Weibull model serves as the physical life baseline to ensure compliance with equipment aging laws, reflecting the late-stage accelerated aging characteristic of downhole heaters with a shape parameter greater than 1, a scale parameter representing the characteristic life corresponding to a 63.2% failure probability, and a position parameter defining the minimum safe life threshold. The XGBoost model quantifies the impact of operating conditions such as pressure and corrosion rate through an additive integration mechanism, enabling accurate life correction without relying on the target equipment’s own operating data. The LSTM network captures time-series dynamic anomalies via its gate control unit structure, and its weight is adaptively reduced in unoperated scenarios while the weights of the preceding two models are enhanced through a dynamic weighted fusion approach, addressing the limitation of single-model dependence on operational data.

A hierarchically collaborative control architecture is designed. The perception layer deploys a high-temperature and high-pressure resistant sensor array, achieving 10ms-cycle data transmission through the PROFINET industrial bus and MQTT/OPC UA dual protocols to mitigate environmental interference. The decision layer integrates adaptive fuzzy control with PID regulation, interfaces with a digital twin system for real-time state mapping and fault pre-diagnosis, and embeds a predictive maintenance model based on resistance drift rate and thermal response time. The execution layer takes Siemens PLC as the core, complemented by a thyristor regulator with a response time of less than 10ms and an independent hard-wired safety loop that terminates power supply within 0.5s under extreme conditions. The feedback layer calibrates PID parameters every 10 days and optimizes model weights for full-cycle iterative optimization.

Hardware optimization involves integrating PLC with high-temperature resistant sensors and developing reliable packaging processes including wellhead sealing and cable crossing sealing. Validated by 1200-hour continuous operation on a 205m-deep in-situ test platform, the system achieves life prediction accuracy with a coefficient of determination of no less than 0.9 and a mean absolute percentage error of no more than 10%, controls outlet temperature fluctuation within ±3℃, maintains a control response time of no more than 10ms, an insulation resistance of no less than 100MΩ, and a thermal efficiency of 89.7%. Stable performance is retained even with 30% data loss, providing a systematic theoretical and engineering framework for the safe and efficient operation of oil-rich coal in-situ pyrolysis equipment.

How to cite: Li, Q. and Guo, W.: Multi-field Coupling Precision Control Technology of Downhole Heater for Oil-Rich Coal In-Situ Pyrolysis, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15511, https://doi.org/10.5194/egusphere-egu26-15511, 2026.

The pore structure of tight reservoirs exhibits significant heterogeneity. Understanding the microscopic distribution and occurrence characteristics of tight oil is crucial for optimizing tight oil resource development. This paper focuses on the Copper Bowl Temple Formation gravel reservoir in the Uersun Sag of the Hailar Basin. Through the use of ultra-thin sections and laser scanning confocal microscopy, the distribution and occurrence characteristics of tight oil components in the reservoir were revealed. By integrating thin-section analysis, SEM, and micro-CT, we systematically analyzed how pore networks influence tight oil occurrence. The results show that the gravel reservoir can be classified into two types: grain-supported and matrix-supported frameworks. The occurrence of tight oil in the reservoir is diverse, mainly manifesting as bound-state star-shaped, particle-adsorbed, semi-bound-state fissure-shaped, and free-state cluster-shaped forms. The pore network in the grain-supported framework reservoir is relatively uniform, with good pore connectivity. Intergranular pores are the primary space for oil and gas accumulation, where tight oil primarily occurs in the free-state cluster-shaped and particle-adsorbed forms. In contrast, the matrix-supported framework reservoir has uneven pore distribution, with numerous isolated pores and poor connectivity. In this type of reservoir, tight oil primarily occurs in the bound-state star-shaped and particle-adsorbed forms, with a small amount occurring in the semi-bound-state fissure-shaped form, restricting the development of tight oil.Cluster-shaped oil in intergranular pores exhibits the highest mobility, spanning the broadest pore size distribution (0.33–7.29 μm), followed by the fissure-shaped and particle-adsorbed forms. Star-shaped oil predominantly occurs in isolated pores with the narrowest pore size range (0.28–4.37 μm).

How to cite: Huang, Y.: Research on the Microscopic Occurrence State Characterization and Influencing Factors of Tight Oil: A Case Study of the Sand and Gravel Reservoir in the Hailar Basin, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15592, https://doi.org/10.5194/egusphere-egu26-15592, 2026.

Understanding the mechanisms of hydrocarbon migration, accumulation, and alteration, particularly how evolution controls these processes, is critical for exploring lithologic hydrocarbons in reservoirs. In the complex tectonic settings of the continental margin of the stable North China Craton, there is a significant presence of small yet highly prolific hydrocarbon reservoirs. The processes of hydrocarbon migration and accumulation are complex and thus represent an important research focus in geology. This study, based on core, logging, and seismic data and integrating fluid inclusion analysis, quantitative fluorescence techniques, and geochemical experiments, combines the shale smear factor and paleotectonic reconstructions to clarify the hydrocarbon accumulation episodes, migration pathways, and factors controlling reservoir adjustments in the Yanwu area of the Tianhuan Depression in the Ordos Basin, China. The results reveal three types of NE-trending left-lateral strike-slip faults: linear, left-stepping, and right-stepping. Shale Smear Factor (SSF) analysis confirms that these faults exhibit segmented opening behaviors, with SSF > 1.7 identified as the threshold for fault openness. Multiparameter geochemical tracing based on terpanes and steranes shows that lateral migration along fault zones dominates the preferential migration pathways for hydrocarbons. Fluid inclusion thermometry revealed homogenization temperatures within the 100–110°C and 80–90°C intervals, while the oil inclusions exhibit blue or blue-and-white fluorescence, reflecting early hydrocarbon charging and late-stage secondary migration. Integrated analysis indicates that during the late Early Cretaceous (105–90 Ma), hydrocarbons were charged upward through open segments of linear strike-slip fault zones in the northern study area, experiencing lateral migration and accumulation along high-permeability sand bodies and unconformities in the shallow strata. Since the Late Cretaceous (65 Ma–present), the regional tectonic framework has evolved from a west-high, east-low to a west-low, east-high configuration, inducing secondary hydrocarbon migration and leading to the remigration or even destruction of early-formed oil reservoirs. This study systematically demonstrates that fault activity and tectonic evolution control the accumulation and distribution of hydrocarbons in the region. These findings provide theoretical insights for hydrocarbon exploration in regions with complex tectonic evolution within stable cratonic basins.

How to cite: Yang, Z.: Influencing factors of hydrocarbon migration and adjustment at the edge of a stable cratonic basin: Implications from fluid inclusions, quantitative fluorescence techniques, and geochemical tracing, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15641, https://doi.org/10.5194/egusphere-egu26-15641, 2026.

The reservoir of Qinhuangdao 32-6 oilfield is a complex fluvial sedimentation, with large lateral variations in sand bodies, complex oil-water relationships, and diverse reservoir types. According to its sedimentary characteristics, the sedimentary facies of the oilfield can be further divided into two types: braided river and meandering river. The level of channel sand body configuration interface, configuration units, and their combinations are not yet clear; There is still a lack of understanding on how configuration units and their combinations under different levels of configuration interface control can control reservoir heterogeneity, which makes it difficult to predict the gas content inside individual sand bodies in the study area.

In response to the above issues, under the constraint of the configuration interface level, combined with the lithology and lithofacies of sedimentary microfacies units and their combination types, the configuration interface of the study area is divided. Based on the vertical sequence sedimentary characteristics of the configuration unit combination, the configuration unit combination is further divided, and the control effect of configuration on reservoir heterogeneity under different levels of interface control is clarified. Among them, the 5-level configuration interface controls the reservoir plane heterogeneity, which is controlled by the rise of the reference plane and structural subsidence; The level 4 configuration interface controls the heterogeneity between reservoir layers, which is controlled by terrain slope and erosion; The 3-level configuration interface controls the heterogeneity within the reservoir layer, which is controlled by hydrodynamic conditions, channel curvature, channel migration degree, sedimentary load, flow rate, and diagenesis. Finally, a control mode for reservoir heterogeneity under 3-5 level interface constraints was established.

How to cite: li, S.: Heterogeneous characterization of reservoirs at different levels and types of rivers---Taking the Neogene Reservoir of Qinhuangdao 32-6 Oilfield as an Example, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16087, https://doi.org/10.5194/egusphere-egu26-16087, 2026.

Quantitative evaluation of source rock thermal maturity is a core component of petroleum system analysis. Traditional deterministic modeling methods are affected by geological parameter uncertainties, making it difficult to meet the demands of shale oil and gas sweet spot prediction. Taking the Permian source rocks of the Junggar Basin as the research object, this paper constructs a thermal evolution surrogate model integrating 3D convolution and spatial attention mechanism, and adopts the Unscented Kalman Inversion method to realize key parameter inversion and uncertainty quantification. Thermal history uncertainty propagation is accomplished via Monte Carlo sampling. Simulation results show that this method can efficiently improve the accuracy of source rock thermal maturity evaluation. The Permian source rocks have generally entered the oil generation stage, with the sag centers reaching the high-maturity gas generation stage, which is consistent with drilling measured data. This method provides a new paradigm for uncertainty modeling of petroliferous basins and has important guiding significance for hydrocarbon exploration.

How to cite: Xu, B., Lei, Y., Zhang, L., and Liu, N.: Uncertainty Analysis Method for Petroleum System Modeling Based on SurrogateModel to Improve Thermal Maturity Evaluation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21757, https://doi.org/10.5194/egusphere-egu26-21757, 2026.

Efficient and accurate estimations of submarine gas reservoir porosity and gas saturation are essential for successful reservoir characterization. However, most classical rock-physics inversion methods for gas saturation (e.g., [1-2]) require pre-existing data, such as porosity, the mineral constituent ratio of the rock, or assumed empirical equations. These methods have limited applicability due to incomplete data and the unclear physical significance of the empirical equations, often yielding inversion results that deviate significantly from well log data and cannot be applied to non-well regions. Although an effective multi-parameter inversion method [3] exists that can estimate critical parameters from elastic impedance data, elastic impedance inversion requires high-resolution raw seismic gathers and complex procedures [4], making it more expensive for 2D/3D reservoir characterization.

To address this, a new method (US appl. 19/432,887) based on rock-physics theory for submarine gas reservoirs is proposed now. In this approach, gas saturation, porosity, the mineral composition of the rock matrix, and fluid-mixture properties are treated as independent variables, while density and P-wave velocity are treated as dependent variables. These four parameters are simultaneously inverted from density and P-wave velocity data.

Testing this method at Site 1245E on Hydrate Ridge along the Cascadia Margin [5] produced acceptable root-mean-square errors for gas saturation (0.0598) and porosity (0.0151), and the estimated mineral constituent proportions closely matched smear-slide analyses. Inversion tests at three additional gas-bearing sites [6-8] demonstrated that the proposed method outperforms previous approaches in accurately estimating porosity and gas saturation, with further validation using 2D density and P-wave velocity profiles from post-stack seismic inversion, which yielded porosity and gas-saturation profiles below the bottom-simulating reflector that align well with logging data.

[1] M., Collett, T.: Gas hydrate and free gas saturations estimated from velocity logs on Hydrate Ridge, offshore Oregon, USA. In: Proc Ocean Drill Prog Sci Results 204:1–25, 2006.

[2] Tinivella, U.: A method for estimating gas hydrate and free gas concentration in marine sediments, Boll Geofis Teor Appl, 40, 19–30, 1999.

[3] Yan, Y., Li, H., Hao, G., et al.: Simultaneous inversion of five physical parameters of submarine gas reservoir from synthetic elastic impedance for high-efficiency reserve evaluation, J Petrol Explor Prod Technol, 15, 68, 2025.

[4] Maurya, S. P.: Estimating elastic impedance from seismic inversion method: A case study from Nova Scotia field, Canada, Current Science, 116, 628–635, 2018.

[5] Tréhu, A. M., Bohrmann, G., Rack, F. R., Torres, M. E., et al., Proc ODP Init Repts, 204, 1–75, 2003.

[6] Riedel, M., Collett, T., Malone, M., Expedition 311 scientists: Site U1329, Proc IODP, 311, 107–2006, 2006.

[7] Collett, T., Riedel, M., Cochran, J., Boswell, R., Presley, J., Kumar, P., Sathe, A., Sethi, A., Lall, M., NGHP Expedition Scientists: National Gas Hydrate Program Expedition 01 Initial Report, Directorate General of Hydrocarbons, Ministry of Petroleum and Natural Gas: New Delhi, 2008.

[8] Paull C, Matsumoto R, Wallace P, et al. Proceedings of the Ocean Drilling Program, Initial Reports, 164, 1996.

How to cite: Yan, Y., Zhao, Z., and Hao, G.: Effective estimation of critical parameters in submarine gas reservoirs using P-wave velocity and density data for 2D/3D reservoir characterization, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2255, https://doi.org/10.5194/egusphere-egu26-2255, 2026.

The São Domingos Mine (Mértola, Portugal) is an abandoned sulfide mine. Heavy metal (HMs) contamination of the soil extends for approximately 20 km along a watercourse connected to a reservoir and two international rivers. Assessing the contamination is a slow process involving the collection of soil samples for HMs analysis.

The INCOME (Inputs for a more sustainable region – Instruments for managing metal-contaminated areas) project is an interdisciplinary study that aims to determine faster ways to obtain contamination maps using Artificial Intelligence techniques combining data from Geophysics, Chemistry Analysis, and Remote Sensing.

This approach allows to improve the sustainability of management of contaminants, which will drive optimization and reduce resources spent on sampling and analysis phases. Furthermore, the model aims to provide important real-time information for decision-making related to pollution monitoring and management. It also has high potential for replication in other contaminated environments, such as landfills, industries, or even intensive agriculture.

This work presents the results of electromagnetic induction surveys conducted in several sectors of the São Domingos Mine. The results are analyzed graphically, through shape analysis and compared with patterns observed in visible satellite imagery. Furthermore, the values ​​obtained for these shapes are also analyzed to attempt to establish correspondence with standard values ​​of the physical parameters of the contaminating materials present in the mine.

Acknowledgments: The work is supported by the Promove Program of the “la Caixa” Foundation, in partnership with BPI and the Foundation for Science and Technology (FCT), in the scope of the project INCOME – Inputs para uma região mais sustentável: Instrumentos para a gestão de zonas contaminadas por metais (Inputs for a more sustainable region: Instruments for managing metal-contaminated areas), PD23-00013, and by national funds through FCT, in the framework of the UID/06107/2025 – Centro de Investigação em Ciência e Tecnologia para o Sistema Terra e Energia (CREATE – University of Évora), and in the frame of UID/00073/2025 and UID/PRR/00073/2025 projects of the R&D unit of Geosciences Center (University of Coimbra, Portugal).

How to cite: Oliveira, R. J., Teixeira, P., Rodrigues, G., Potes, M., Custódio, M., Catarino, A., Semedo, N., Borges, J. F., Costa, M. J., Palma, P., and Caldeira, B.: Electromagnetic induction characterization of soil contamination from the São Domingos Mine (Portugal), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4796, https://doi.org/10.5194/egusphere-egu26-4796, 2026.

Contaminants of emerging concern (CECs) have received increasing attention due to their persistence and potential ecological risks in freshwater environments. However, their spatial patterns, source contributions, and transfer from aquatic systems to surrounding soils remain insufficiently understood. Moreover, CECs are often poorly regulated, partly because interactions between individual contaminants and groups of contaminants are complex, making it hard to assess the risks they may cause. Given their adverse effects on ecosystems and human health through direct and indirect exposure, this study presents a first attempt to predict the occurrence of CECs in soil in a highly agricultural area in Serbia using machine learning techniques.

The investigation was conducted along the Veliki Bački Canal in Vojvodina (Serbia), which presents one of the main water supplies for irrigation. Initially, concentrations of CECs in canal water were measured and their spatial distribution mapped for the most frequently detected substances, including 4-acetamidoantipyrine, acesulfame calcium, estradiol, venlafaxine, and carbamazepine. Based on these results, representative locations for soil sampling on agricultural land were selected, and two soil sampling campaigns were carried out, where 96 samples were collected.

The analysis revealed that the dominant soil contaminants were primarily of industrial origin, such as tributyl phosphate, dodecyl sulfate, 2,5-di-tert-butylhydroquinone, and triethylene glycol bis (2-ethylhexanoate). Using soil and terrain characteristics as predictor variables, three machine learning algorithms were trained and evaluated - Multiple Linear Regression, Support Vector Machine, and Random Forest. Random Forest models showed strong predictive capability, particularly for industrial contaminants, such as tributyl phosphate, with a coefficient of determination (R²) of 0.65 and a mean squared error of 38.45 ng/g. Only in one case, for the prediction of 2,5-di-tert-butylhydroquinone, the Multiple Linear Regression model outperformed Random Forest. Feature importance analysis indicated that soil sand content and flow accumulation were the most influential factors controlling contaminant distribution in soil.

Although model performance is constrained by limited soil sampling data, the proposed framework provides a robust foundation for predicting soil contamination patterns and supports improved risk assessment and monitoring strategies in freshwater-influenced agricultural landscapes.

How to cite: Radulović, M., Živaljević, B., Kireeva, M., and Mimić, G.: Predicting CEC concentration in soil using machine learning algorithms, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7015, https://doi.org/10.5194/egusphere-egu26-7015, 2026.

Legacy landfill sites often contain buried trenches that are not well delineated, not documented to modern standards, with subsurface voids that can act as preferential pathways for water, sediment and contaminants. To evaluate whether geophysical methods can help identify these features in a landfill, we conducted integrated electrical resistivity tomography (ERT) and ground-penetrating radar (GPR) survey along three collocated transects; at a closed 1950’s landfill site in Ontario, Canada. The survey used a multi-electrode ERT array and a 250 MHz GPR to image shallow structures associated with historical waste trenches and potential soil-pipe development.

The survey results reveal a consistent pattern: high-resistivity anomalies in ERT between 1-2 m depth align with wide, crossing hyperbolas in the respective GPR profiles. The high-resistivity anomalies are interpreted as waste trenches. Located between the identified trenches, elongated resistive zones corresponding to GPR troughs and dipping reflectors, are tentatively interpreted as sedimentary layers with possible soil-pipe-like connections. These results, overlaid with site monitoring data, will improve the overall clarity and allow a better understanding of these subsurface structures. Three trench-like structures with two connecting anomalies are imaged along each transect, demonstrating a repeating subsurface pattern. Deeper ERT anomalies (4-9 m) lack GPR counterparts due to the limited penetration of the 250 MHz antenna Further surveys will use different antenna types to achieve deeper resolutions.

The study results show that combining ERT resistivity contrasts with GPR hyperbola geometry, provides a reliable means of mapping buried trenches and potential erosion pathways at legacy landfill sites. Next steps include expanding the survey grid, forward modeling, integrating other geophysical methods that complements ERT and GPR, and developing 3D interpretations to support long-term environmental monitoring and risk assessment.

How to cite: Binod, A., Bank, C.-G., Ebie, E., and Ngueleu Kamangou, S.: Mapping the 3D subsurface structure of a legacy landfill using a multi-geophysical approach, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8035, https://doi.org/10.5194/egusphere-egu26-8035, 2026.

The South Caspian Basin, positioned within the dynamic Alpine-Himalayan orogenic belt, is distinguished by its intricate geological architecture, featuring a sedimentary cover exceeding 20 km and substantial lateral fluctuations in Moho depth. Due to the presence of these deep, massive geological bodies, standard potential field maps frequently fail to resolve fine tectonic nuances. However, the gravitational signals from deep structures often mask subtle features, creating ambiguities in interpreting the regional deformation. For the first time, we utilize the Improved Logistic (IL) filter on Bouguer gravity anomalies to clarify these structural uncertainties and accentuate density contrasts that are otherwise obscured in conventional datasets. The results of our analysis uncovered a complex network of lineaments, predominantly trending NE-SW and WNW-ESE, which provide a multi-scale perspective on the basin's tectonic framework. We successfully highlighted critical tectonic boundaries, such as the Turkmenbashi-Makhachkala fault, and corroborated the segmentation of major uplift zones like Godin and Safidrud. We believe that the Improved Logistic filter acts as a powerful mechanism for revealing subsurface architecture in basins blanketed by thick sedimentation, offering a refined structural model for hydrocarbon exploration and seismotectonic assessment in this complex region. Compared to standard gradient methods, this technique effectively equalizes the gravitational response from varying depths to better interpret deformation mechanisms driven by ongoing plate convergence.

How to cite: Gahramanov, M., Safarov, R., Maden, N., and Gadirov (Kadirov), F.: Structural delineation of the South Caspian Basin using edge enhancement techniques: Application of the Improved Logistic filter to gravity data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10532, https://doi.org/10.5194/egusphere-egu26-10532, 2026.

Mining activities generate significant soil contamination, leaving behind a persistent legacy of potentially toxic elements (PTEs) in the environment. At the inactive São Domingos mine in southern Portugal, the legacy of mining is marked by acid mine drainage (AMD), which facilitates the release and dispersion of PTEs, creating ongoing risks to ecosystem integrity and public health. In this context, the present study aims to characterize and evaluate the risks of soil contamination by PTEs in a selected area of São Domingos, where 11 topsoil samples (0-20 cm; A2 to A12) were collected. The PTE analyzed were cadmium (Cd), chromium (Cr), copper (Cu), lead (Pb), nickel (Ni), zinc (Zn), and arsenic (As). Quantification was performed by inductively coupled plasma mass spectrometry (ICP-MS) after microwave-assisted digestion, according to the USEPA (2007) method. PTE concentrations were compared with Portuguese reference values for agricultural and industrial soils, respectively (Cd: 1.0/1.9 mg/kg; Cr: 160 mg/kg; Ni: 130/340 mg/kg; Pb: 45/120 mg/kg; Cu: 180/300 mg/kg; Zn: 340 mg/kg; As: 18 mg/kg; APA, 2019) and Canadian soil quality guidelines for agricultural and industrial soils, respectively (Cd: 1.4/22 mg/kg; Cr: 64/87 mg/kg; Ni: 45/200 mg/kg; Pb: 70/600 mg/kg; Cu: 63/91 mg/kg; Zn: 250/410 mg/kg; As: 12 mg/kg; CCME, 2018). Cadmium (0.29–0.43 mg/kg) and chromium (25.31–67.27 mg/kg) showed low concentrations, remaining below guideline values for agricultural and industrial soils. The Ni concentrations (Ni; 36.34–163.29 mg/kg) exceeded agricultural thresholds but remained below limits established for industrial land use at some sampled locations. In contrast, As (324.72–2612.97 mg/kg), Pb (153.51–5321.22 mg/kg), Cu (197.50–1307.09 mg/kg) and Zn (61.17–2743.12 mg/kg), exhibited the highest concentrations, largely exceeding both national and international guideline values for agricultural and industrial soils. The results revealed high spatial variability in PTE concentrations across the study area, a characteristic feature of mining-impacted environments, with the identification of located hotspots representing critical zones of environmental risk.  The results highlighted distinct contamination patterns, identifying As, Pb, Cu, and Zn, as the primary contaminants. These contaminants are primarily associated with historical mining activities and acid mine drainage processes. These elements are characterized by high toxicity and persistence in soils and therefore constitute the main contributors to the environmental risk identified in the study area. These findings support the INCOME project’s environmental management framework and inform the development of integrated and sustainable strategies for the remediation of abandoned mining areas.

Funding: The work is supported by the Promove Program of the “la Caixa” Foundation, in partnership with BPI and the Foundation for Science and Technology (FCT), in the scope of the project INCOME – Inputs para uma região mais sustentável: Instrumentos para a gestão de zonas contaminadas por metais (Inputs for a more sustainable region: Instruments for managing metal-contaminated areas), PD23-00013, and by national funds through FCT, in the framework of the UID/06107/2025 – Centro de Investigação em Ciência e Tecnologia para o Sistema Terra e Energia (CREATE – University of Évora), and in the frame of UID/00073/2025.

How to cite: Custódio, M., Semedo, N., Catarino, A., Rodrigues, G., Teixeira, P., Potes, M., Caldeira, B., Costa, M. J., Oliveira, R. J., and Palma, P.: Spatial distribution and assessment of potentially toxic elements in an Iberian Pyrite Belt Mine: the case-study of São Domingos (Southern Portugal), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13845, https://doi.org/10.5194/egusphere-egu26-13845, 2026.

The São Domingos Mine (southern Portugal) is an abandoned sulphide mining area where metal contamination extends over approximately 20 km along a watercourse connected to a reservoir and two international rivers. Conventional soil contamination assessment relies on extensive field sampling and laboratory analysis, both of which are time-consuming and spatially limited.

Within the INCOME project (Inputs for a more sustainable region – Instruments for managing metal-contaminated areas), satellite-based remote sensing is explored as a means to parametrise the study area at a spatial resolution of approximately 30 m, helping to overcome the spatial limitations inherent to point-based laboratory measurements.
Multispectral and hyperspectral satellite data, including Sentinel-2 MSI, EnMAP and PRISMA observations, are used to characterise metal-contaminated surfaces. This combines the high spatial and temporal coverage of the MSI with the enhanced spectral resolution of the hyperspectral sensors, which is essential for identifying the absorption features associated with metals. Atmospheric correction based on radiative transfer modelling (6SV) ensures consistent surface reflectance products, and machine learning techniques are employed to correlate satellite-derived information with laboratory measurements of specific metals. Overall, this work presents the potential of integrated remote sensing approaches in supporting the more efficient monitoring and management of metal-contaminated areas.

Acknowledgments: The work is supported by the Promove Program of the “la Caixa” Foundation, in partnership with BPI and the Foundation for Science and Technology (FCT), in the scope of the project INCOME – Inputs para uma região mais sustentável: Instrumentos para a gestão de zonas contaminadas por metais (Inputs for a more sustainable region: Instruments for managing metal-contaminated areas), PD23-00013, and by national funds through FCT, in the framework of the UID/06107/2025 – Centro de Investigação em Ciência e Tecnologia para o Sistema Terra e Energia (CREATE – University of Évora), and in the frame of UID/00073/2025 and UID/PRR/00073/2025 projects of the R&D unit of Geosciences Center (University of Coimbra, Portugal).

How to cite: Rodrigues, G., Teixeira, P., Custódio, M., Oliveira, R., Catarino, A., Semedo, N., Potes, M., João Costa, M., Gonçalves, T., Palma, P., Salgueiro, P., Rato, L., and Caldeira, B.: Integrated multispectral and hyperspectral remote sensing for mapping metal contamination in the São Domingos mining area (southern Portugal), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14968, https://doi.org/10.5194/egusphere-egu26-14968, 2026.

The pore structure, which serves as a conduit for gas and leachate migration during municipal solid waste (MSW) landfilling, undergoes continuous changes in pore size and connectivity with waste degradation. In this study, we established two types of landfill simulation containers filled with either formless or fixed-shaped MSW particles. Computer tomography (CT) scanning technology was used to monitor the pore structures regularly in situ during degradation, and Avizo image processing software was used to extract the characteristic parameters of the pore structure. The results showed that the pore structures all had unimodal distributions. The pore structures of the formless synthetic MSW particles continued to shrink, the sizes of the nodal pores decreased, and the pore channels narrowed and shortened with degradation. In contrast, the pore structures of the fixed-shaped MSW particles continued to grow during degradation, the nodal pores enlarged, and the pore channels expanded. Specifically, the pore channel length increased by nearly 1000 μm. This finding indicated that changes in the pore structures of wastes could be determined by the supporting factors of waste particles and by the biodegradation of microorganisms. The pore structures grew when the supporting factors were predominant and shrank when microorganism biodegradation was predominant.

How to cite: Liu, X.: Changes in the pore structures of municipal solid waste samples with different abilities to provide support to the landfill structure during degradation: Analysis of synthetic waste using X-ray computed microtomography, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15520, https://doi.org/10.5194/egusphere-egu26-15520, 2026.

Mining environments exhibit geochemically dynamic landscapes driven by geogenic and anthropogenic processes, resulting in the deterioration of groundwater and surface water quality. The hydrogeological alterations in such settings further facilitate contaminant mobility, thereby increasing the vulnerability of (sub)-surface water resources to contaminant transport. This study presents an integrated hydrogeological and hydrochemical framework to delineate contaminant pathways and understand (sub)-surface hydrochemical processes in a semi-arid mining region. To operationalize this framework, a series of electrical resistivity tomography (ERT) surveys were conducted to characterize subsurface heterogeneity and identify potential pathways for contaminant movement. The ERT survey was followed by (sub)-surface water quality analysis to understand the hydrochemical process governing water contamination. The resistivity variations in ERT profiling revealed distinct subsurface geological formations. The low resistivity values varying from 2.99 to 10 Ωm reflected aquifers saturated with a possible contaminated plume from either surface runoff or anthropogenic mining activities. The high resistivity values (>100 Ωm) corresponded to weathered formations, which serve as active sites for geogenic rock-water interactions. The entropy water quality index revealed distinct spatial variations in contaminant levels, whereas principal component analysis distinguished between anthropogenic and geogenic factors influencing water quality in the mining-impacted region. The isotopic composition of groundwater (δ²H = 3.67·δ¹⁸O – 17.09) indicated recharge from an evaporatively modified, surface-influenced source, suggesting increased susceptibility to surface-derived contamination, whereas the surface-water samples (δ²H = 5.70·δ¹⁸O – 13.94) primarily reflected evaporative enrichment. Overall, the integrated hydrogeological and hydrochemical framework is found to be effective for understanding the key subsurface processes that drive contaminant mobility and deterioration of water quality in mining regions.

Keywords: Hydrogeological alterations, Contaminant mobility, ERT profiling, Electrical resistivity tomography, Rock-water interactions

How to cite: Singh, B. and Yadav, B. K.: Unraveling (Sub)-surface Water Dynamics in a Mining Environment: Hydrogeological and Hydrochemical Insights, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-472, https://doi.org/10.5194/egusphere-egu26-472, 2026.

Placing reclamation covers is an effective method to reduce NO₃^- release from coal gangue. This study considered the impacts of different reclamation covers on the contributions and release of NO₃^- from explosive and exchangeable NH₄⁺ (NH₄⁺-ex) sources in coal gangue using column experiments. The δ¹⁸O-NO₃^- values were measured to identify the sources of NO₃^- in coal gangue, and the calibrated and validated hydraulic and solute parameters were used to simulate the release of NO₃^- for all treatments (without cover, CK; 30 cm sandy loess, T1; 30 cm Pisha sandstone, T2; 30 cm mixed soil, T3; 15 cm Pisha sandstone overlying 15 cm sandy loess, T4; and 15 cm sandy loess overlying 15 cm Pisha sandstone, T5). The results indicated SEEP/W and CTRAN/W with optimized parameters could accurately simulate water movement and NO₃^- transport. The contribution of the explosive source was 80, 81, 86, 82, 84, and 84% and of the NH₄⁺-ex source was 20, 19, 14, 18, 16, and 16% for CK, T1, T2, T3, T4, and T5, respectively. The five covered treatments respectively decreased the total cumulative water volume by 5.80, 11.11, 7.73, 9.18, and 10.63% and the total NO₃^- cumulative mass released from the coal gangue by 5.59, 20.95, 7.41, 14.61, and 14.36% compared to CK. Our results suggest the reclamation covers significantly reduced the release of NO₃^- from coal gangue primarily by decreasing the release of NO₃^- derived from the NH₄⁺-ex source, with the most significant effect noted for the 30 cm Pisha sandstone cover (T2).

How to cite: Huang, M. and Liu, X.: The impact of different reclamation covers on the release of nitrate from various sources in coal gangue, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2016, https://doi.org/10.5194/egusphere-egu26-2016, 2026.

Mining activities are a major driver of long-term geo-environmental and eco-environmental degradation, particularly during the post-mining stage when residual contamination and ecological risks often persist or intensify. The rapid expansion of lithium mining and processing linked to the battery and energy-transition industries has increased Li accumulation in soils and waters around mine sites, posing emerging risks to terrestrial ecosystems and land reclamation. Owing to its high mobility and weak natural attenuation, lithium presents particular challenges for post-mining soil remediation, highlighting the need for effective, low-cost, and ecologically compatible remediation strategies.

Here we evaluate perennial ryegrass (Lolium perenne L.) for lithium phytoremediation using a 42-day hydroponic experiment with six LiCl treatments (0, 7, 140, 280, 560, and 700 mg L^-1). Plant performance was assessed through seed germination, growth traits, photosynthetic pigment contents, oxidative stress indicators, and antioxidant enzyme activities. Lithium removal and accumulation were evaluated to assess plant tolerance and remediation efficiency. Lithium exposure induced clear dose-dependent inhibitory effects on germination and seedling development, with pronounced suppression occurring at concentrations ≥280 mg L^-1. Under high Li stress (560–700 mg L^-1), ryegrass exhibited significantly reduced growth and photosynthetic pigment contents, accompanied by enhanced oxidative damage, indicating that prolonged and intense Li stress can disrupt physiological homeostasis. Correlation analysis further demonstrated a stress-threshold–dependent physiological shift, whereby Li accumulation was positively associated with oxidative stress indicators (MDA) and antioxidant enzyme activities (SOD, POD, and CAT) under moderate Li stress, but became negatively correlated with growth and photosynthetic parameters at higher Li levels, reflecting a transition from adaptive defense responses to toxicity-dominated inhibition. Despite these adverse effects, ryegrass maintained substantial remediation capacity across a wide concentration range. Lithium removal increased consistently with exposure time, and after 42 days, removal efficiencies exceeded 60% for all moderate-to-high treatments (280–700 mg L^-1). At the highest Li concentration, maximum Li accumulation reached 38.26 mg g^-1, which is significantly higher than Li accumulation levels reported for maize and sunflower under comparable conditions. Tissue partitioning indicated root-dominated Li retention, limiting translocation to shoots.

To elucidate the microscale mechanisms of Li stabilization, time-of-flight secondary ion mass spectrometry (TOF-SIMS) imaging was conducted on root cross-sections, and an ion–ion spatial correlation matrix was constructed. Lithium signals were concentrated in organic-rich microdomains near the cortex and endodermis, showing strong co-localization with oxygen-rich fragments derived from polysaccharides and phenolic structures (indicative of carboxyl and hydroxyl functional groups), as well as phosphate-related fragments. In contrast, negative spatial associations with Si-rich mineralized regions were observed, highlighting the dominance of biochemical domains rather than silicified structures in Li sequestration.

Overall, effective Li removal by perennial ryegrass is supported by root-dominated uptake and coordinated physiological regulation, with Li primarily associated with oxygen-rich organic functional groups and phosphate domains in roots, and a remediation threshold around 280 mg L^-1. These findings provide both quantitative performance metrics and mechanistic evidence supporting the application of ryegrass-based phytoremediation for Li-mining and Li-industrial soil pollution, and they offer practical guidance for developing scalable remediation strategies at post-mining sites.

How to cite: Zhang, Y. and Chen, N.: Lithium Uptake, Physiological Responses, and Root-Scale Stabilization Mechanisms in Perennial Ryegrass, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2495, https://doi.org/10.5194/egusphere-egu26-2495, 2026.

The backfilling method stands as a widely employed extraction technique in contemporary mining practices, with the performance of cemented tailings backfill (CTB) being pivotal in determining the overall quality of backfilling. Nevertheless, traditional CTB exhibits suboptimal mechanical properties, particularly crack resistance, under complex stress environments. Presently, one of the extensively explored backfill types is the fiber-reinforced cemented tailings backfill (FRCTB), with a particular emphasis on those reinforced with polypropylene fibers. In order to scrutinize the mechanical characteristics of FRCTB under intricate stress states, this study, employing a triaxial Hopkinson pressure bar experimental apparatus, investigates the dynamic mechanical behaviors, fracture damage patterns, and energy dissipation features of FRCTB under five different confining pressures (0, 1, 2, 3, 4 MPa) and various strain rates. Key findings include:

(1) Under dynamic loading, FRCTB exhibits a pronounced strain rate strengthening effect along with a notable confining pressure strengthening effect. The presence of confining pressure significantly alters the stress-strain curve of FRCTB. The peak stress and dynamic increase factor (DIF) of FRCTB linearly increase with the augmentation of both confining pressure and strain rate. The peak strain linearly increases with the strain rate, with confining pressure exerting minimal influence on the peak strain. Confining pressure substantially enhances the elastic modulus of FRCTB, while the impact of strain rate is comparatively marginal.

(2) In the absence of confining pressure, FRCTB specimens, with increasing strain rates, exhibit an outward-expanding conical failure shape. The crack volume and surface area increase in a stepwise fashion, and the hollow cylindrical polypropylene fibers undergo flattened failure. At this juncture, the polypropylene fibers endure a limit strain rate ranging from 206.5 s^-1 to 232.3 s^-1. As confining pressure gradually increases, the outward expansion tendency is progressively restrained until no discernible internal damage occurs. At this point, the polypropylene fibers manifest phenomena such as splitting, bending, and extraction. Under low (no) confining pressure conditions, the fractal dimension and porosity of FRCTB increase with the rising strain rate. In high confining pressure conditions, the fractal dimension and porosity of FRCTB are relatively similar across different strain rates.

(3) At lower confining pressures, the strain rate strengthening effect is evident in both fracture morphology and energy dissipation but diminishes as confining pressure increases. Dissipated energy density exhibits an increasing trend with the rise in confining pressure, while the energy dissipation rate shows a quadratic function decrease with increasing strain rate. The stress-strain curves of FRCTB under no confining pressure and with confining pressure can be categorized into four and five segments, respectively: elastic growth, plastic yield, post-peak energy accumulation, and post-peak failure for the former, and elastic growth, plastic damage incubation, plastic damage development, plastic damage accumulation, and post-peak failure for the latter. Under low confining pressure conditions, the fractal dimension linearly increases with the growth of dissipated energy. This trend gradually transforms into a cubic function change as confining pressure increases. There exists a notable similarity between fractal dimension and energy dissipation rate, as well as between strain rate and confining pressure.

How to cite: Zou, S., Gao, Y., and Zhou, Y.: Study on Dynamic Mechanical Behavior and Damage Evolution Mechanism of Fiber Reinforced Cemented Tailings Backfill, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3329, https://doi.org/10.5194/egusphere-egu26-3329, 2026.

Potassium (K) is an essential nutrient for all living organisms. Its high mobility in soils often limits its availability to plants, constraining growth. To meet the increasing demand for food, K-based fertilizers are routinely applied to enhance the yields of agricultural crops. However, the use of conventional KCl fertilizers can lead to soil salinization, their supply is vulnerable to geopolitical and economic fluctuations, and the production of soluble KCl is energy- and environmentally intensive. Therefore, potassium-rich aluminosilicate minerals, such as micas, glauconite, and K-feldspar, have been considered as alternative potassium fertilizers. This study investigates the usability of mining waste composed of glauconitic sandstone as a raw material for potassium fertilizer, with a focus on mechanical activation as a method to enhance potassium leachability. Bulk sandstone and enriched glauconite samples were subjected to mechanical activation to evaluate changes in particle size, morphology, specific surface area, and potassium solubility. Mechanical activation significantly enhanced the release of plant-available K, with up to 80% of total K released into solution in 240 minutes, with 55% of K extracted in  first 30 minutes, indicating high process efficiency. Glauconite sandstone enrichment improved the K content by 14% but also led to a nearly seven-fold increase in bulk Cr concentrations reaching 291 ppm, approaching regulatory limits for fertilizers agricultural use. While mechanical activation offers a scalable, energy-efficient alternative to conventional K-fertilizers, the relatively low bulk K₂O content (<5%) and elevated Cr levels limit the practical application of the Estonian glauconitic sandstone as a K-fertilizer. These findings highlight both the potential and constraints of mechanical activation for sustainable potassium fertilizer production.

How to cite: Pihel, R., Lumiste, K., Kirsimäe, K., and Paaver, P.: Mechanically activated glauconitic sandstone: potential for alternative potassium fertilizer, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4895, https://doi.org/10.5194/egusphere-egu26-4895, 2026.

This research presents an integrated methodology for enhanced slope stability analysis in mining areas by merging remote sensing, artificial intelligence, and temporal deep learning. It advances beyond traditional numerical models by utilizing multi-source satellite data (Sentinel-1, Sentinel-2, DEM) to extract critical stability parameters—including slope angle, deformation, and rainfall intensity, among others within a multimodal geographic information system (GIS) environment. Current research focuses on generating a pixel-level risk-susceptibility map of the stability of mining slopes and classifying them into different risk zones — high, medium, and low by integrating fuzzy logic and multi-criteria decision-making (MCDM) techniques. Subsequently, the identified high-risk zones are processed to analyze temporal patterns and mine expansion/deformation in land from time-series imagery using a ConvoLSTM/U-Net deep learning model, thereby improving predictive capability for evolving slope geometries. The methodology has been validated through field surveys using drone imagery and laboratory tests of physico-mechanical properties on rock and dump samples. These support the interpretation of remote sensing–derived slope deformation and stability patterns. Ultimately, this research offers a cost-effective, scalable solution for predicting and monitoring OB dump slope stability by integrating remote sensing and AI, filling gaps left by traditional methods.

How to cite: Agarwal, S., Kumar, P., Sahoo, M. M., and Reale, G.: Beyond Numerical Modeling: An Integrated Remote Sensing and AI Methodology for Rapid Slope Stability Analysis in Mining Regions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5418, https://doi.org/10.5194/egusphere-egu26-5418, 2026.

San Quintín was a former galena (PbS) mine rich in Ag, and sphalerite (ZnS), whose extractive activity generated a set of mining wastes with high contents of heavy metals and metalloids, mainly present as primary sulfides and secondary sulfates, accompanied by significant amounts of pyrite (FeS₂). These wastes pose an environmental risk due to their dispersion into the surrounding natural environment. The presence of sulfides, such as pyrite, promotes the formation of acid mine drainage (AMD), generating waters with low pH and high electrical conductivity (EC).

The objective of this study was to assess the quality of water in streams and ponds in the San Quintín area through physicochemical parameters (pH and EC) during the restoration stage, comparing them with values obtained prior to the remediation actions. To this end, a network of sampling points was established along the stream system and in rain-formed ponds, prioritizing areas close to former waste rock dumps and tailings. Measurements were carried out both in situ and in the laboratory using calibrated equipment, allowing detailed monitoring of the physicochemical variability of temporary surface waters.

The results indicate that under drought conditions, which represent the critical load of acidity and ion concentration, partial recovery of pH and EC is observed in sectors associated with old ponds and waste rock dumps. During the rainy season, pH increases markedly due to dilution, while EC decreases near the deposits but increases at the confluence points of the stream system, where ions transported by runoff become concentrated.

As a provisional conclusion, considering the factors affecting the variability of physicochemical parameters, a partial recovery of pH and EC is observed in the temporary surface water system of the mining area, largely attributable to the neutralizing action of carbonate materials deposited during restoration. Nevertheless, continued monitoring of these parameters is still necessary to verify that conditions of near neutrality are ultimately achieved in the waters throughout the area.

How to cite: Bakale, F., Jaeger Collantes, J. L., Nsue Eneme, M. T., Obama Ntutumu, D. M., Morales Laurente, J. A., Barquero Peralbo, J. I., and Higueras Higueras, P. L.: Monitoring of surface water quality in the San Quintín mining area during its restoration, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6954, https://doi.org/10.5194/egusphere-egu26-6954, 2026.

Open-pit coal mining exerts long-lasting and cumulative disturbances on terrestrial ecosystems during the post-mining stage, and the associated environmental impacts and recovery processes exhibit pronounced temporal persistence and spatial heterogeneity. Long-term remote sensing monitoring is therefore essential for understanding post-mining ecosystem dynamics and evaluating restoration outcomes. In this study, we constructed a Mining Landscape Disturbance Index (MLDI) and a Mining Landscape Recovery Index (MLRI) based on the Enhanced Vegetation Index (EVI) and Land Surface Temperature (LST). Combined with the LandTrendr algorithm, post-mining disturbance-recovery trajectories of 46 open-pit coal mines in northern China were systematically monitored and analyzed over the period 1984-2025. Using disturbance and recovery trajectory information extracted by LandTrendr, ecosystem resilience was comprehensively assessed from three dimensions: resistance, recovery capacity, and stability. Based on disturbance magnitude and recovery magnitude, the 46 mining areas were classified into four types: high disturbance-high recovery (HH), high disturbance-low recovery (HL), low disturbance-high recovery (LH), and low disturbance-low recovery (LL). The results indicate that the median MLRI values of all four types show an overall increasing trend at the interannual scale, suggesting a general post-mining recovery tendency of ecosystems during the study period, although significant differences exist in recovery levels and recovery rates among different types. Meanwhile, the median MLDI values also exhibit a continuous upward trend, reflecting persistent cumulative degradation pressure on mining ecosystems under long-term mining activities. Distinct multidimensional differentiation patterns were observed among the four disturbance-recovery types in terms of resistance, recovery capacity, and stability. This study provides an effective remote sensing-based framework for monitoring long-term post-mining ecological dynamics and offers scientific support for differentiated environmental management and ecological restoration strategies in post-mining areas.

How to cite: Liu, Y. and Xie, M.: Post-mining Ecological Disturbance-Recovery Trajectories and Resilience Assessment of Open-pit Coal Mines Based on Long-term Remote Sensing Indices, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7127, https://doi.org/10.5194/egusphere-egu26-7127, 2026.

Froth treatment tailings (FTT) are a byproduct of bitumen extraction in Alberta’s oil sands and, while the smallest tailings stream by volume, they present disproportionate challenges for closure and reclamation. Produced during froth treatment, where diluent such as naphtha is added to separate bitumen from water and solids, FTT contain residual hydrocarbons and sulfide minerals like pyrite. These constituents can influence redox conditions, microbial activity, and hydrocarbon degradation processes, ultimately affecting long-term deposit behavior. Despite their importance, FTT remain understudied compared with other tailings types, especially in the context of terrestrial beach deposits targeted for reclamation.

This study investigated the spatial and vertical distribution of hydrocarbons and microbial communities across a 1.4 km transect of a naphtha-based FTT beach deposit at Syncrude’s Mildred Lake Settling Basin. Samples were collected from six locations spanning the pond edge to a reclamation dyke, with depths ranging from 0.15 to 46 m. Chemical analysis revealed that petroleum hydrocarbon (PHC) and residual naphtha concentrations reflected deposition history, with higher concentrations found in deeper, older FTT near the dyke and at shallower depths adjacent to the pond. Naphtha concentrations were most strongly correlated with heavier PHC fractions (F2–F4), while toluene and ethylbenzene emerged as key indicators of microbial variation.

Distinct microbial communities were observed in FTT relative to the underlying coarse tailings, with reduced diversity at depths greater than ~30 m. FTT were enriched in hydrocarbon degraders (e.g., Pseudomonas), sulfur-cycling taxa (Thiobacillus, Desulfovibrio, Desulfotomaculales), and methanogens (Methanosaeta). Community composition varied with depth, distance from the pond, and presence of FTT, with the strongest drivers being PHC concentrations and pyrite content. These findings suggest that residual hydrocarbons act both as substrates and stressors, shaping microbial ecology while interacting with geochemical processes such as sulfur reduction and oxidation as well as methanogenesis.

Together, this work provides one of the first spatially resolved assessments of FTT deposits illustrating how residual diluent, hydrocarbons, and microbial processes interact to influence subsurface conditions. Accurate characterization of FTT is essential for predicting long-term behavior, guiding the design of closure landforms, and informing reclamation monitoring programs.

How to cite: Balaberda, A., Escolástico-Ortiz, D., Martineau, C., Heshka, N., Lindsay, M., and Degenhardt, D.: Characterizing Residual Hydrocarbons and Microbial Dynamics in Froth Treatment Tailings for Reclamation Planning, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7788, https://doi.org/10.5194/egusphere-egu26-7788, 2026.

Quarrying activities have significant impacts on the human and the natural environments. Following a quarry's closure, exposed surfaces remain vulnerable to wind erosion and dust emission until full long-term reclamation is achieved. The objective of this research is to examine the efficacy of using quarry by-product material (Nivrar) to fill such surfaces in inactive quarries to prevent erosion until full rehabilitation takes place. This pilot research is conducted in a calcareous quarry. The fill sample consists of Nivrar supplemented with a local topsoil from the edge of the quarry to enrich it with seeds of native vegetation. Additionally, a biopolymer is used to stabilize the upper layer for immediate-term protection. Samples of the Nivrar and the topsoil were analyzed at various ratios to determine the optimal composition related to erosion and soil fertility, including aggregation, organic matter, dust fraction, electrical conductivity. A controlled experiment was performed to test seed germination and growth within the Nivrar. Experiments in a boundary-layer wind tunnel allowed for testing the samples' resistance to soil erosion and dust emission (PM). The results indicate that the Nivrar material is not a limiting factor for plant development, and its wind erosion coefficients are relatively low compared to the quarry's surfaces despite the relatively high amount of dust fraction. The addition of the topsoil increased the percentage of organic matter and essential elements (potassium). The polymer application significantly reduces dust emissions. The research results to date demonstrate the potential for implementing this method in the field as a sustainable ecological-environmental solution for the rehabilitation of inactive quarries until full reclamation is achieved.

How to cite: Esther, A., Ben-Hur, M., and Itzhak, K.: Preventing dust emission in non-active quarries by filling enriched waste material, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8067, https://doi.org/10.5194/egusphere-egu26-8067, 2026.

Opencast coal mining lastingly alters the landscape and hydrology of impacted regions, such as the Lusatian lignite mining district in Eastern Germany. As mining operations are being phased out, groundwater recharge leads to an increased exfiltration of iron- and sulphate-containing compounds into surface waters where they precipitate as iron hydroxide sludge (IHS). These processes occur either under natural conditions or induced through specific technical water treatment interventions. Thus, approximately 60,000 tons of IHS accumulate in Lusatia annually, which currently must be disposed of at great expense to the local authorities, due the absence of viable recycling solutions. Depending on the specific location and precipitation context, IHS can vary greatly in terms of their chemical and mineralogical composition. Initial applied research suggests that there is great potential for using iron-rich, fine-textured and, in some cases, organic-rich IHS in soil amelioration, aiming to stabilise soil carbon, improve water retention capacity and nutrient storage. Respective positive effects are particularly relevant for the restoration/improvement of sandy post-mining soils, prevalent in Lusatia. However, since some IHS are associated with potentially toxic elements, a detailed characterisation of these mineral residues is necessary to determine their suitability for potential uses. As part of the European Centre of Just Transition Research and Impact-Driven Transfer (Project: CO₂-Sequestration and Soil Recultivation Through Recycling of Mineral Residues), we are presenting a comprehensive geochemical and mineralogical systematisation of Lusatian IHS, relying on data derived from RFA, XRD, XPS, ⁵⁷Fe Mössbauer spectroscopy, wet chemical extractions, and BET surface area measurements. The high geochemical and mineralogical diversity of IHS, even across short geographical distances, is highlighted by the range of exemplary key parameters such as pH (2.1–7.7), total S content (0.1–3.0 %), Dithionite-Citrate-Bicarbonate-extractable iron Fe_d (124.1–388.4 mg/g), Oxalate-extractable iron Fe_o (63.0–322.6 mg/g), and Fe_o/Fe_d ratio describing the degree of crystallinity of the iron phase (0.16–1.0). This data from Lusatia is contextualized with published (inter)national case studies, and perspectives for the use of specific IHS types in soil amelioration are critically discussed.

How to cite: Herrmann, J., Harlow, E., Pohl, L., Mikutta, R., and Stein, M.: Iron hydroxide sludges from the post-mining landscape of Lusatia, Germany: Prospects for their application as soil ameliorant based on geochemical and mineralogical characteristics, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9925, https://doi.org/10.5194/egusphere-egu26-9925, 2026.

In deep hard-rock rotary–percussive drilling, energy efficiency is often constrained because only a fraction of the input energy is converted into effective volumetric fragmentation. The combined action of high-frequency impacts and bottom-hole rotational loading promotes localized crushing, excessive fines generation, and non-directional crack growth, so the crack network fails to evolve into a dominant fracture system capable of effectively detaching rock fragments; instead, substantial energy is dissipated through secondary crushing and high-frequency vibration, yielding only marginal gains in fragmentation while increasing the risk of borehole-wall damage. To address this limitation, the present study relates drilling efficiency to bottom-hole fracture modes by clarifying how crack connectivity and propagation mechanisms govern effective breakage work. A coupled tooth–rock stress-field and fracture-evolution framework is developed to systematically evaluate how tooth geometry, cutter layout, and operational parameters steer crack-network development, and an energy-based metric is formulated to interpret trends in specific energy. The framework is validated against laboratory experiments and dynamic numerical simulations using cuttings size distribution, energy consumption, and borehole-wall damage as verification targets; based on the validated model, practical design and operating windows are identified to increase the fraction of effective breakage work and provide actionable guidance for high-efficiency drilling.

How to cite: Zhang, Y.: Crack Propagation and High Efficiency Rock Fragmentation Mechanisms in Rotary Percussive Drilling, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11908, https://doi.org/10.5194/egusphere-egu26-11908, 2026.

Open-pit mining severely disturbs land by removing vegetation, altering soils, degrading soil structure, and promoting soil erosion and nutrient loss. Waste rock and tailings can release toxic trace elements (TEs), which may be taken up by plants and transferred through the food chain, thereby exposing humans and wildlife to contamination. These long-lasting ecological and health risks highlight the need for soil rehabilitation, vegetation recovery, and ongoing environmental monitoring.

Within this context, reclaimed sites located in a bitumen mining and upgrading area in Alberta, Canada, were selected to: (i) assess the potential bioavailability and transfer of TEs from cover soils to wild berries growing on them; (ii) evaluate the extent to which TEs are enriched in berries from reclaimed lands compared to natural background levels; and (iii) compare TE concentrations in berries with existing thresholds intended for human consumption.

Following metal-free, ultra-clean laboratory procedures, soils and eight species of unwashed berries collected in 2024 were dried and milled, digested in HNO₃, and analyzed using ICP-MS. Phytoavailable TEs in soils were determined following extraction with DTPA. Micronutrients (Cu, Mn, Ni, and Zn), bitumen-enriched elements (Mo, Re, Se, and V), and chalcophile elements (As, Ag, Cd, Pb, Sb, and Tl) were below the remediation guidelines for natural areas in Alberta. Average TE concentrations in these soils were also lower than those reported for soils worldwide and were either lower than or comparable to concentrations in regional parent materials. Based on DTPA soil extracts, it was estimated that 0.1–23% of bitumen-enriched elements, 0.1–75% of chalcophile elements, and 0.1–25% of micronutrients are potentially available for plant uptake.

To distinguish between TE deposition on berry surfaces and root uptake, linear regressions were performed between TE concentrations and conservative lithophile elements (Al, Th, and Y), and Y-normalized TE concentrations in berries were compared with those in soils. These analyses indicate that As, Sb, Pb, Tl, and V are predominantly deposited on berry surfaces (R² > 0.6), whereas Ag, Cd, Cu, Mn, Mo, Ni, and Zn (R² < 0.6) are primarily taken up from the soil. Iron, an essential and abundant element in soils, occurs both internally and on the surface of berries. With the exception of Mn and Mo, TE concentrations in unwashed berries from reclaimed sites were 2-fold (Cd, Cu, Zn) to 38-fold (Y) higher than those measured at remote locations. These differences are attributed to berry species as well as greater dust deposition at reclaimed sites compared to remote areas.

After accounting for the average berry water content (80%), TE concentrations were 7–17 times lower than EU guidelines for safe consumption (30–40 µg/kg for Cd and 100 µg/kg for Pb). However, these results should be interpreted cautiously, as population-related factors such as age, dietary habits, and risk perception must also be considered.

How to cite: Barraza, F., Nelson, E., Ybañez, Q., Thirupurasanthiran, S., Moffett, K., Bujaczek, T., and Shotyk, W.: Trace elements in soils from reclaimed lands and their bioavailability in wild berries , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14587, https://doi.org/10.5194/egusphere-egu26-14587, 2026.

A long history of mining has resulted in hundreds of tailings cells in Canada that are orphaned or abandoned. Often the only feasible restoration strategies for such tailings, due to financial constraints, are facilitation of natural revegetation or surface amendment followed by direct planting into tailings. Small changes in substrate conditions, therefore, can have large impacts on revegetation success. This research focuses on a 2.6 km² gold mine tailings impoundment in northern Ontario, Canada. Over three years, samples were collected from multiple locations and depths across the tailings cell and directly from the processing plant. Elements of interest include S, Cu, and Cr. Metal concentrations were measured using ICP-MS and changes in elemental speciation were measured using synchrotron x-ray absorption spectroscopy. Cr is unchanged along sampling gradients, while S and Cu exhibit great variation in their chemical state along sampling gradients. Results surprisingly show that trace organic carbon from gold processing has a strong effect on Cu speciation, and we further discuss the efficacy of correlating proxy measures of chemical states (e.g. S redox state, pH, conductivity, and carbon content) to Cu and Cr speciation. The results from this research provide insights into how chemical characteristics, including elemental speciation, can vary across time and spatial scales in mine tailings impoundments and what processes may be driving these changes. Future work should consider the described processes when designing sampling methodologies and restoration strategies of similar tailings impoundments.

How to cite: Lundell, L., Peak, D., and Stewart, K.: Investigating processes driving copper, chromium, and sulphur chemistry changes across space and time in a boreal Canadian gold mine tailings impoundment , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15907, https://doi.org/10.5194/egusphere-egu26-15907, 2026.

The diverse geology and geomorphology of Western Canada have facilitated the development of a mature mining industry. A variety of commodities such as metals, bitumen, and coal are mined across mountainous, Arctic, and boreal forest regions. In parallel with industrial development, significant research on mine waste and reclamation has occurred in the Western Canadian provinces and territories. In this presentation, the timeline of mine waste research at a Western Canadian university (the University of Alberta) is used to illustrate how perceptions of the geotechnical challenges of mine waste materials and reclamation priorities have evolved over the past 5 decades.

Academic research on oil sands tailings, a fine-grained waste product produced by bitumen mining, began in the 1970s with early work focused on characterizing geotechnical behaviour. The goal of much of this work, from its early stages until the present day, has been to understand consolidation behaviour, which contributes to the challenges of dewatering oil sands tailings. This included a 30-year long standpipe experiment beginning in 1982, and continued interest in consolidation contributed to the construction of Western Canada’s only geotechnical beam centrifuge in 2012 to simulate the effects of long term vertical stress. Starting in the 1990s, different methods of dewatering tailings to speed reclamation progress have been studied, ranging from physical processes such as freezing and thawing to more recent studies on polymer chemical amendments.

Similar to other jurisdictions, acid rock drainage (ARD) is a significant concern for many hard rock mines in Western Canada. Due to the cold climate of the region, a number of studies have investigated the effect of freezing temperatures on ARD. Computer modelling of temperature and water flow in mine waste to predict ARD has been a research focus since the 2010s. This has led to recent research on soil covers and novel mine waste disposal methods such as filtering and commingling.

​The importance of tailings and reclamation research to the mining industry in Western Canada is exemplified by longstanding collaborations with major mining operations and government regulators. This has enabled the application of continuously-evolving geotechnical best practices to academic research. As more rigorous methods of soil mechanics analysis, such as unsaturated and critical state soil mechanics, have been developed, they have been increasingly applied to mine waste. More recently, developing risk-based design approaches for reclamation strategies has been an area of research focus.

Over the past 5 decades, research on tailings and reclamation in Western Canada and beyond has evolved from early geotechnical characterization of mine waste to the development of novel management strategies. While this represents a remarkable technical achievement, the development of resilient reclamation ecosystems remains a challenge. It is suggested that future geotechnical research on tailings and reclamation should prioritize interdisciplinary collaboration to support the development of safe, sustainable, and resilient post-mining landscapes.

How to cite: Paul, A., Barsi, D., Dos Santos Cardoso Coelho, P., Waseem, O., Whitehead, C., and Zheng, T.: Evolution of tailings and reclamation research in Western Canada: 1970 - 2026, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16014, https://doi.org/10.5194/egusphere-egu26-16014, 2026.

Coal wastes deposited in heaps may undergo self-heating and spontaneous combustion processes. Under oxygen-limited conditions in the dump, besides burning, pyrolysis processes occur. Both processes (pyrolysis and oxidation) result in emissions of volatile pollutants and have been developed in several heaps in the Upper Silesian Coal Basin (USCB), where coal exploitation has lasted for over a century.

         To examine the molecular composition and yields of volatile compounds produced during self-heating, in relation to organic matter (OM) content and its maturity, mineral matter composition, temperature, water presence and oxidation conditions, four coal waste samples were collected from the Polish part of the USCB: two from the Janina Mine (JAN-1, JAN-2) (Rr ca. 0.5%) and two from the Marcel Mine (MAC-1, MAC-2) (Rr ca. 0.9%). JAN-1 and MAC-1 are siltstones containing more quartz and less OM than JAN-2 and MAC-2 claystones. Results of the Rock-Eval analysis evidenced 1.8, 27.3, 1.9, and 21.4 wt. % TOC, respectively and the presence of the Type-III kerogen in all samples. Simulations of the self-heating were conducted in 1-L closed reactors in conditions: dry pyrolysis (DP), hydrous pyrolysis (HP) in 250, 360, and 400^oC for 72 h, and oxidation with air (OXI) in 250 and 400^oC for 72 h.

The molecular composition of generated gases (i.e., HCs (C₁-C₈), CO, CO₂, H₂, H₂S, organic S-compounds) was determined and then re-calculated as yields, taking into account the amount of gas generated (pVT) and the mass and TOC of the rock used for each experiment.

The concentration of HCs in HP and DP runs increases with temperature increase up to 58.4 mol %. The concentrations of other generated gases in these experiments strongly relate to the temperature increase of the process as well: the concentration of CO decreased, and the concentration of CO₂, H₂, H₂S and organic S-compounds increased. The presence of water and elevated TOC amounts boost the generation of S-compounds (dominated by H₂S). During all OXI experiments, only traces of HCs, H₂ and S-compounds were produced; the concentration of CO₂ increased and CO decreased with experiment temperature increase. Gases generated from TOC-rich rocks are richer in HCs, and organic S-compounds, resulting in yields of these gases, up to 4.3 kg/Mg rock and 1.4 g/Mg rock, respectively. The highest CO₂ and CO yields were recorded in OXI experiments, reaching approximately 390 and 20 kg/Mg rock, respectively; in pyrolytic experiments, these yields did not exceed 8.4 and 0.15 kg/Mg rock, respectively. After recalculating the gas yields per TOC mass in waste, it appeared that the highest HCs yields, exceeding 20 kg/Mg TOC, were recorded during HP and DP pyrolysis at 400°C of samples poor in organic carbon. CO₂ and CO yields are highest in OXI experiments of the above-mentioned samples, reaching 850-2000 and 10-50 kg/Mg TOC, respectively. The yields of these gases in pyrolysis experiments for these samples reach 24-310 kg/Mg TOC and 0.0-1.3 kg/Mg TOC, respectively. 

This study was financed from the AGH University of Krakow research subsidy (16.16.140.315) and the National Science Centre, Poland, grant No 2017/27/B/ST10/00680.

How to cite: Więcław, D., Bilkiewicz, E., Jurek, K., Fabiańska, M., Ciesielczuk, J., and Misz-Kennan, M.: Assessment of factors influencing the composition and yield of gases emitted during the self-heating of coal waste based on laboratory simulations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17007, https://doi.org/10.5194/egusphere-egu26-17007, 2026.

Mining activity is essential for providing the raw materials necessary for societal development. The life of an underground mine depends on multiple factors, such as geological characteristics (e.g., mineral quantity and quality), economic drivers (costs, market prices, technology), technical constraints (e.g., extractive efficiency), and environmental/social considerations (e.g. regulations, impact). Following closure, multiple processes can occur, such as subsidence, slope instability, uplift, and the flooding of galleries. Therefore, continuous monitoring of abandoned mines is essential to mitigate risks to human safety and infrastructures. Some abandoned mines are repurposed for uses such as underground tourism, gas storage, fungi cultivation or geothermal resources, among others. The Candín-Fondón underground coal mine is located in the Nalón River valley in Langreo (NW Spain). Coal extraction in the region began in 1840 at the La Nalona mountain mine, later transitioning to the deep-shaft mining complexes of Fondón and Candín. The Fondón shaft reached a depth of 667 m and remained operational until 1995, while the Candín complex reached depths of up to 717 m. During the exploitation of the mines, groundwater levels dropped by more than 600 m in some areas. Today, these sites have been repurposed for industrial heritage and geothermal energy production (up to 3.488 MWh) using mine groundwater. Consequently, the groundwater level in the galleries has gradually recovered. However, the recovery of groundwater levels to the design level for geothermal exploitation has led to an increase in pore pressure within the rock mass joints, causing rock mass expansion and subsequent ground surface uplift. This uplift was detected using European Ground Motion Service (EGMS) Synthetic Aperture Radar Interferometry (InSAR) datasets for the period 2015–2021. Positive uplift rates exceeding 10 mm/year and accumulated uplift of over 4 cm were measured. These displacements are concentrated mainly over the mining works of Candín and Fondón, with maximum displacements located near the Fondón mine shaft. The InSAR time series shows a clear sigmoidal evolution of positive displacements starting in 2016, increasing until 2019, and then stabilizing. EGMS datasets from 2019–2023 show stabilization with residual uplift rates below 2 mm/year. Therefore, this work presents an example of how high-resolution InSAR datasets, such as the EGMS, can be used to accurately characterize the non-linear surface response to groundwater rebound in abandoned mines repurposed for geothermal energy.

How to cite: Tomás Jover, R., Álvarez-Fernández, I., González Nicieza, C., and Alejano, L. R.: Monitoring ground uplift in an abandoned mountainous coal mine converted to geothermal facilities using Synthetic Aperture Radar Interferometry (InSAR), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19082, https://doi.org/10.5194/egusphere-egu26-19082, 2026.

Lignite open-pit mining causes long-term disturbances of natural soils with losses of their environmental functions. Oxidation of sulfide minerals in the dumped overburden of coal mines and subsequent leaching increase iron and sulfate concentrations in groundwater. If these waters reach the surface and become exposed to oxygen or elevated pH conditions, iron precipitates as iron hydroxide sludge (IHS). The large volumes of IHS generated annually pose a significant environmental challenge due to their complex and costly disposal. Soils developing on post-mining dump substrates in Lusatia are often characterized by high sand contents, poor structure, low water-holding capacity, and a limited ability to retain nutrients and, in particular, organic matter. In contrast, iron hydroxides provide highly reactive surfaces that can effectively bind soil organic matter (SOM), thereby improving soil structure as well as water and nutrient retention. The potential use of IHS in post-mining soil reclamation therefore warrants systematic scientific investigation. The proposed approach offers opportunities and challenges. While IHS may enhance carbon storage and other soil functions, there is a risk of releasing associated potentially toxic elements (PTEs) or immobilizing nutrients on iron oxide surfaces. Here we report results from the first year of a three-year lysimeter experiment evaluating IHS application under field conditions. We quantified potential PTE release as well as water balance, nutrient availability, and effects on SOM contents. Overall, our study provides first evidence on whether the use of acid mine drainage-derived IHS can contribute to the improvement of previously unproductive and low SOM post-mining soils.

How to cite: Stein, M., Herrmann, J., Harlow, E., Winkler, P., and Mikutta, R.: New perspectives in post-mining soil restoration: Use of iron hydroxide sludge from acid mine drainage as soil ameliorant, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21213, https://doi.org/10.5194/egusphere-egu26-21213, 2026.

Tailings materials are inherently heterogeneous systems where deposition processes produce layering, segregation, and spatial variability in density and structure. Conventional analyses often neglect this spatial variability and instead rely on a single deterministic representation of in-situ state. This study presents a practical framework to assess tailings storage facility (TSF) stability by integrating random field theory with the NorSand model, which explicitly links strength, dilatancy, and static liquefaction susceptibility to the state parameter (ψ). Unlike prior works that approximate state dependence indirectly by randomizing shear strength, the present work models the initial state parameter (ψ_0) itself as a spatially correlated random field with a depth-dependent mean profile, reflecting depositional variability while keeping the NorSand constitutive parameters fixed. Random-field correlation lengths and anisotropy are adopted from CPTu-based spatial variability studies on tailings deposits while the NorSand parameters are calibrated against published experimental response data using an element-level implementation developed in MATLAB. The ψ_0 field is generated through Karhunen-Loève expansion and propagated through Monte Carlo effective-stress TSF stability analyses in PLAXIS 2D. Results show that ψ_0 heterogeneity creates zones with different degrees of contractive response, which leads to localized pore-pressure build-up and deformation. As a result, excess pore-pressure response and the predicted failure mechanism vary across realizations, rather than remaining confined to a single deterministic prediction. The probabilistic workflow provides a robust, data-driven pathway toward performance-based TSF assessment and strengthens mine-closure decisions for long-term stability under depositional uncertainty.

How to cite: Liu, F. and Agarwal, E.: Probabilistic TSF stability assessment using a NorSand-based random-field framework, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21801, https://doi.org/10.5194/egusphere-egu26-21801, 2026.

Ophiolitic succession of the Eastern Mediterranean region includes one of the most famous natural H₂ leakage spot, globally known as “Chimera Gas Seepage”, noted since ancient times. Geochemical analysis on the seepage revealed that the origin of the gas is abiotic and along CH₄, %10-12 of H₂ is associated with the seepage due to the serpentinisation process which is widely accepted as one of the main mechanisms for the natural H₂ generation.

Radiolysis, considered as another natural H₂ generation process, is defined as the decomposition of H₂O by decay of ²³²Th-²³⁸U-⁴⁰K causing an increase in radioactivity levels. Therefore, increasing radioactivity levels can be detected to identify potential natural H₂ generating zones by calculating the radiogenic heat generation. This study aims to test this hypothesis by implementing the usually neglected or overlooked ²³²Th-²³⁸U-⁴⁰K concentration measurements, also known as SGR logs. A-1 well drilled in the onshore portion of the Antalya Bay, SW Turkey, includes ²³²Th-²³⁸U-⁴⁰K concentration measurements covering an allochthonous ophiolitic section. Penetration into the ophiolites by a well, proximity of well location to the Cirali gas seepage (60 km NE of the seepage) and 2D seismic sections acquired in the region make the study area a perfect spot to test the applicability of integrated methods for natural H₂ exploration.

The most significant finding along the ophiolitic section of the A-1 well is the presence of a peak in radiogenic heat generation that might indicate a potential natural H₂ generation zone. On the other hand, thermal models derived from the interval velocities of 2D seismic survey nearby indicate that vast majority of generated H₂ by serpentinisation process must have migrated from the deepest sections of the ophiolites as temperatures are generally quite low in the area. Apart from that, thermal models also demonstrate the presence of temperature anomalies exhibiting themselves as rapid lateral increases in temperatures that can be associated with the fluids in the sedimentary succession.

As a conclusion, this study provides a unique workflow to reveal potential natural H₂ generating zones that can be applied all along the wells if ²³²Th-²³⁸U-⁴⁰K concentration measurements cover zone of interest not only in the Eastern Mediterranean but for any region. In terms of play fairway, 2 play types have been identified. Naturally generated H₂ can accumulate both in the serpentinites as it is already proven by Chimera gas seepage, or it can migrate into Plio-Miocene aged reservoirs in the area. In terms of expulsion mechanism, heavy deformation and compressional tectonic phase controlled by ongoing convergence of African and Anatolian plates create faults and fracture zones that might allow migration of natural H₂ from the deeper sections into the shallower structures. However, detailed geomechanical analysis should be performed to understand and prevent potential seal breach risks. The methodologies provided by this study might unlock the path to a potential natural H₂ discovery that can turn the Eastern Mediterranean region into a unique natural H₂ exploration theatre.

How to cite: Uyanik, A.: Highlighting Natural H2 Generation Potential of the Eastern Mediterranean Ophiolites by Implementing 232Th-238U-40K Concentration Measurements and Thermal Modeling, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-758, https://doi.org/10.5194/egusphere-egu26-758, 2026.

Helium is a critical raw material for medical, industrial, and scientific applications, yet its global supply is largely dependent on hydrocarbon production, linking helium availability to CO₂ emissions and geopolitical constraints. This dependency has driven growing interest in alternative, low-carbon helium sources, particularly radiogenic helium systems associated with N₂-rich and CO₂-poor geological fluids. However, the geological controls on helium generation, migration, and accumulation in such non-hydrocarbon systems remain poorly constrained.

Radiogenic helium systems require the combination of a U–Th-enriched crystalline basement generating helium through alpha decay, sufficient heat to liberate helium from mineral hosts, and fault- and fracture-controlled pathways enabling upward migration while limiting diffusive loss. Where suitable reservoir and seal configurations exist, migrating helium may locally accumulate. Continental rift and geothermal provinces seem especially favourable for these conditions due to elevated heat flow, crustal thinning, and dense fault networks.

In this study, we first compile helium data from the literature to produce a Europe-wide map linking helium occurrence to rifts, sedimentary basins, and Variscan basement exposures, providing a european framework for helium exploration. New helium concentration data from thermal fluids in the Upper Rhine Graben are used to assess the spatial distribution of helium fluxes and their relationship with fault architecture. While near-surface degassing limits shallow accumulation, major fault systems emerge as first-order controls on helium transport. Their deeper continuations beneath sedimentary basins represent promising exploration targets where appropriate reservoir–seal configurations may allow helium retention. This study provides a preliminary framework to guide exploration of helium in European rift and geothermal settings.

How to cite: Wallentin, A., Murray, J., Truche, L., and Lemarchand, D.: Exploring Helium in European Rifts: New Insights from the Upper Rhine Graben, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2992, https://doi.org/10.5194/egusphere-egu26-2992, 2026.

Natural hydrogen (H₂), often referred to as white hydrogen, is attracting increasing attention as a potential subsurface energy resource. Its occurrence, migration, and preservation are strongly controlled by faults and fracture networks, which regulate fluid flow, fluid–rock interactions, and overall reservoir integrity. This contribution provides a state-of-the-art review of current research on natural hydrogen systems, with particular focus on the role of fault and fracture zones and on recent advances from Italy as an emerging natural laboratory.

At the global scale, natural hydrogen has been reported in a wide range of structurally complex geological settings, including rift zones, ophiolitic complexes, mid-ocean ridges, sedimentary basins, and fractured crystalline basement (e.g., Zgonnik, 2020; Wang et al., 2023; Sequeira et al., 2025; Gorain, 2025). Hydrogen can be generated through multiple processes—such as serpentinization, radiolysis, organic matter pyrolysis, and mantle degassing—that commonly operate in tectonically active and faulted environments. Owing to its small molecular size and high diffusion coefficient, hydrogen migration is particularly sensitive to fracture connectivity, fault permeability, and fault (re-) activation, making structural architecture a primary control on both accumulation and leakage.

Field observations, well data, and monitoring studies indicate that hydrogen frequently migrates along fault and fracture networks, may accumulate transiently within structurally controlled traps, or is released at the surface through focused seepage (Prinzhofer et al., 2019; Baciu and Etiope, 2024). Recent studies emphasize that circulation of hydrogen-rich fluids within fault zones can significantly modify the mechanical and transport properties of host rocks through fluid–rock interactions, potentially leading to either enhanced or reduced permeability and sealing capacity (Sequeira et al., 2025; Gorain, 2025). These coupled processes have important implications for fault stability, leakage risk, and the long-term viability of subsurface energy systems.

In this context, Italy is a particularly favourable setting for research on natural hydrogen. The country hosts a broad spectrum of geological environments conducive to hydrogen generation and migration, including ophiolites, such as those exposed in the Tuscan–Emilian Apennines, active fault systems, geothermal areas, and sedimentary basins sealed by evaporites. Recent structural, geochemical, and geophysical studies suggest that the occurrence of hydrogen in Italy is closely linked to fault architecture, deformation processes, and multiscale fluid circulation (Azor de Freitas et al., 2025).

By integrating global observations with insights from Italian case studies, this review outlines current research trends, identifies key knowledge gaps, and highlights the need for multidisciplinary approaches combining field investigations, monitoring of potential gas emissions from active fault systems, interpretation of subsurface data and conceptual modelling of potential reservoirs and hydrogen emission areas. These insights are directly relevant to low-carbon energy exploration and to the assessment of fault-controlled leakage, reservoir performance, and system stability in subsurface energy applications.

How to cite: Cremonesi, A., Borghini, L., Corradetti, A., Del Ben, A., Franceschi, M., and Bonini, L.: Understanding natural hydrogen systems: From generation to surface emissions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6527, https://doi.org/10.5194/egusphere-egu26-6527, 2026.

Natural hydrogen (H₂) emissions in the northern United Arab Emirates (UAE) occur within the northern continuation of the Semail Ophiolite, where serpentinized peridotites, fault permeability, and groundwater circulation jointly control H₂ generation and migration. Recent soil-gas surveys in Ras Al Khaimah (RAK) and the Masafi structural window report systematic H₂ anomalies above a regional background, including locally elevated concentrations along fault corridors and lithological contacts. In parallel, regional geophysical studies in the UAE–Oman mountain belt provide independent constraints on the ophiolite’s three-dimensional architecture, indicating kilometre-scale thickness variations and structural segmentation, while broadband magnetotelluric (MT) models resolve resistivity contrasts and conductive zones consistent with fluid-focused deformation along major fault systems.

Here we develop an integrated, exploration-oriented workflow that constrains depth-resolved ultramafic/serpentinized source geometry and evaluates its spatial consistency with mapped surface H₂ anomalies. We combine available gravity and magnetic datasets with petrophysical constraints and geological priors to perform petrophysically guided joint inversion, targeting (i) the depth extent and volume of ultramafic bodies, (ii) the distribution of serpentinization-related physical property changes, and (iii) structurally controlled corridors that may promote water ingress and gas migration. Where available, MT-derived constraints on conductive pathways and seismic interpretations of basin/foreland structure are used to reduce non-uniqueness and to test competing structural models.

We then translate the recovered 3D ultramafic geometry into bounded H₂ generation estimates by coupling volume-based metrics with physically realistic limits, including temperature constraints informed by regional geothermal/Curie-depth patterns and process caps imposed by hydrogen solubility and water supply. Spatial comparisons between predicted subsurface H₂-favourable domains and mapped soil-gas anomalies provide a quantitative test of whether surface signals preferentially occur above specific ophiolite blocks and fault systems. The results establish a reproducible template for assessing hydrogen in ophiolite-hosted environments under realistic data availability, supporting evidence-based prioritization of targets in the UAE and across the wider Arabian ophiolite belt.

How to cite: Sobh, M., Ali, M. Y., Saibi, H., Abdelmaksoud, A., and Fadel, I.: Imaging and quantifying ophiolite-hosted natural hydrogen potential in the northern UAE Semail Ophiolite using petrophysically guided joint inversion of geophysical data , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7111, https://doi.org/10.5194/egusphere-egu26-7111, 2026.

Natural hydrogen gas (H₂) generated through the serpentinization of mantle rocks is a promising source of clean energy. For large-scale serpentinization and natural H₂ generation to occur, the mantle rocks need to be brought into a optimal temperature range (the serpentinization window) and into contact with water. Alpine-style rift-inversion orogens, formed during the closure of rift basins, provide excellent environments for serpentinization-related natural H₂ generation, while also harbouring extensive volumes of sediments in which natural H₂ accumulation could form. In such orogens, erosion is known to have an important impact on exhumation processes and sediment distribution, but to what degree erosion efficiency influences natural H₂ resource potential remains poorly understood. We use numerical geodynamic models of rift-inversion to explore and, importantly, quantify the relative roles of erosion and tectonic processes by applying different erosion efficiencies and initial rift phase durations.

Our modelling shows that, regardless of erosion efficiency, initial rift duration is a dominant factor during both the extension and inversion phase. Prolonged rifting causes increased mantle exhumation and thus higher natural H₂ generation potential. Erosion efficiency exerts only a secondary effect, in that more efficient erosion modestly reduces H₂ generation potential by narrowing the serpentinization window. Inversion of advanced rift basins results in asymmetric orogens in which mantle material is incorporated into the overriding wedge, a configuration that is critical for generating high natural H₂ generation potential in these systems. Nevertheless, efficient erosion of otherwise symmetric orogens formed after limited rifting allows for a shift to an asymmetric style, with significant mantle exhumation and natural H₂ generation potential.

However, efficient erosion and associated fast exhumation of relatively hot material in orogens can also decrease the vertical extent of the serpentinization window, reducing natural H₂ generation potential. Moreover, rapid erosion can remove the otherwise abundant potential reservoir rocks and seals needed for exploitable natural H₂ accumulations to form. Still, these negative effects of erosion on “conventional” natural H₂ resources (involving H₂ accumulation in reservoir rocks), may be favourable for “unconventional” natural H₂ resources. Systems with relatively hot mantle material close to the surface may in fact be suitable for stimulated natural H₂ exploitation efforts, involving direct drilling of the mantle source rock itself.

Thus, although erosion efficiency is not the dominant factor, it can still have a considerable impact on natural H₂ potential in rift-inversion orogens. Therefore, a thorough understanding of the evolution of those orogens targeted for exploration, will be of great importance. This challenge can be aided by numerical geodynamic models such as those presented here, with which we perform a first-order analysis of natural examples from the Pyrenees, Alps, and Betics.

How to cite: Zwaan, F., Glerum, A. C., Brune, S., Vasey, D. A., Naliboff, J. B., Manatschal, G., and Gaucher, E. C.: The impact of erosion processes on natural H2 resource potential in Alpine-style orogens, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8255, https://doi.org/10.5194/egusphere-egu26-8255, 2026.

With the growing emphasis on reducing the carbon footprint of transport, there is increasing interest in identifying local sources of hydrogen (H₂) and helium (He) closer to consumers. In this context, we present an integrated approach combining near-surface geophysical imaging, soil gas sampling, and bubbling well gas sampling to investigate fluid and gas pathways near a fault system in the Morvan massif, located in the southeastern Paris Basin. Using electrical resistivity and seismic refraction tomography, we mapped a fault network in the area. Soil gas sampling along these faults revealed a helium hotspot, strongly linked to a specific fault segment, indicating a preferential pathway likely driven by water advection. Additionally, exceptionally high helium concentrations were detected in nitrogen (N₂)-dominated free gas from two nearby bubbling wells, closely associated with the soil helium hotspot. Our geophysical data further suggest the presence of a shallow water reservoir at the basement-sediment interface, containing N₂-He gas bubbles. In contrast, hydrogen (H₂) exhibits a broader spatial distribution, likely due to biological production and consumption processes, as well as soil aeration. A potential geological seep, with diffusion controlled by clay and marls, may also contribute to H₂ dispersion. The distinct spatial patterns observed for He and H₂ reflect their differing transport mechanisms. We propose a simple geochemical model to explain the N₂- and He-rich signature of the bubble gas, attributing it to the exsolution of dissolved atmospheric N₂ during recharge, while radiogenic He originates from the underlying granitic basement.

How to cite: Léger, E., Sarda, P., Bailly, C., Zeyen, H., Pessel, M., Portier, E., Dupuy, G., Lambert, R., Courtin, A., Guinoiseau, D., Calmels, D., Durand, V., Monvoisin, G., Battani, A., Moreira, M., Barbarand, J., and Brigaud, B.: Deciphering Intermittently Bubbling Degassing Mechanisms of He‐Rich N2 ‐Bubbles at theSedimentary Basin‐Basement Interface by Surface Geophysics and Gas Geochemistry, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9629, https://doi.org/10.5194/egusphere-egu26-9629, 2026.

Global copper demand is projected to increase from 22.8 Mt in 2024 to 35 Mt by 2040, driven largely by the transition to green energy technologies. Existing and announced Cu mining projects are forecast to meet only 70% of this demand by 2035, creating a significant supply deficit. Mining of subvolcanic magmatic brines - hypersaline and potentially supercritical fluids enriched in metals – has been proposed as an alternative source (Blundy et al., 2021). Here, we assess the potential mass of Copper Initially in Place (CIIP) in such reservoirs.

Based on published resistivity models from 46 active magmatic-hydrothermal systems, we estimate the typical volume of brine reservoirs to range from 10 to 200 km³ and the average top reservoir depth to be 1.7 km, well within reach of modern drilling technology. Typical reservoir porosity in the shallow sub-critical zone is 8±6% and decreases to 3±3% in the deeper supercritical zone. Copper concentration in the brines is the most uncertain property.  Data from fluid inclusions and Cu solubility modelling suggest that most brine reservoirs will host modest Cu concentration (ca. 10’s to 100’s ppm), but values could exceed 10,000 ppm in the most Cu enriched systems.

We combine these estimates of reservoir volume, porosity and copper concentration using a probabilistic Monte Carlo framework to provide estimates of CIIP. Our analysis indicates a lognormal CIIP distribution with a median (P50) of 8.6 Mt and a P90 of 55 Mt, suggesting that individual magmatic brine resources may be comparable in size to conventional copper porphyry deposits. Moreover, a single high-flow-rate well tapping into a supercritical reservoir could produce approximately 2.4 kt of copper per year. A large-scale operation comprising multiple wells could yield 0.24 Mt/year, equivalent to roughly 1% of current global demand.

A Cu brine mine could extract geothermal energy from the produced fluids. We envisage a self-powered Cu brine mine, with net positive energy per kg of Cu and a minimal environmental footprint. While significant challenges remain regarding exploration for copper-rich brine reservoirs and production of very hot and possibly supercritical brines, brine mining offers a potentially significant source of Cu that could be produced with much lower energy demand and negative environmental impact than conventional mining.

Blundy, J., et al. "The economic potential of metalliferous sub-volcanic brines." Royal Society Open Science 8.6 (2021): 202192.

How to cite: Paulatto, M., Jackson, M., Hu, H., Berry, A., Crisp, L., Beckie, R., and Pacey, A.: Assessing potential ‘copper in place’ in subvolcanic brines, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10130, https://doi.org/10.5194/egusphere-egu26-10130, 2026.

The Engadine valley, located in the Grischun area in SE Switzerland, presents multiple mineralized springs distributed along the Engadine fault. Hydrogen (H₂) concentration measured along the Engadine fault can reach up to 1900 ppm, indicating the presence of both, a deep groundwater flow system and a deep-seated 'kitchen'. These observations suggest that the Engadine fault may control the regional hydrodynamics and likely also the hydrogen production along the Engadine valley. A key factor to identify and understand the location of the H₂ kitchen, fluid pathways and related water in- and H₂ out-flow is the understanding of the nappe stack in the Grischun area and its relation to the Engadine fault. The latter, represents a major SW-NE striking >100km long structure that resulted from post-collisional oblique strike-slip movements during Oligocene-Miocene time. It transects the Late Cretaceous Austroalpine nappe stack, floored by the Pennine, ultramafic rocks bearing ophiolites, inherited from the closure of the Alpine Tethys proto-oceanic domain. Thus, a key question is whether there is a hydrodynamic link between the ultramafic source rocks flooring the rift-inversion nappe stack, the Engadine fault, acting as a possible conduit for deep water circulation, and the occurrence of springs and H₂ anomalies in the soil gas. To answer to this question, we constructed a numerical hydrodynamic model of the Engadine and surrounding area, including the Engadine fault. This model allows us to carry out regional-scale simulations to investigate the interplay between topography and a deep, permeable conduit (e.g. Engadine fault) and its control on hydrothermal circulation. The model couples groundwater flow, heat transport and solute transport, and will be calibrated with surface observations (location of springs and chemical anomalies in water and soil gas). First results suggest that fluid upwelling occurs SW of St.Moritz and NE of Scuol along the Engadine valley, whereas the fault-segment between St.Moritz and Scuol corresponds to a region of meteoric recharge. This SW-NE distribution of deep upwelling correlates well with first geochemical field measurements. Future work will include chemical fluid-rock interaction to fully understand the hydro-chemical conditions of H₂ formation and H₂ pathways to the surface along the Engadine valley. Ultimately, this well-constrained, regional scale model, will serve as an exploration tool, allowing us to quantitatively evaluate the potential for energy-related exploitation (H₂ and/or geothermal).

How to cite: Gasser, Q., Manatschal, G., Alt-Epping, P., Gaucher, E. C., Pierre, S., Dimasi, F., and Ulrich, M.: The link between deep groundwater flow and serpentinization-sourced H2 production in rift inversion orogens: the example of the Engadine valley (SE Switzerland), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10381, https://doi.org/10.5194/egusphere-egu26-10381, 2026.

The dual production of geothermal energy and lithium from fault-controlled reservoirs, such as the Rittershoffen doublet in the Upper Rhine Graben (URG), presents a significant opportunity for the energy transition. However, long-term feasibility depends heavily on the complex interplay of fluid flow and chemical transport. We developed a numerical model using a control volume finite element method with embedded discontinuities, calibrated against comprehensive field data (pressure transients, tracers, and thermal profiles).

Our results reveal a highly heterogeneous flow field: a rapid primary path through the major fault/damage zone creates hydraulic "short-circuits," while slower secondary paths sweep the surrounding fractured reservoir. While thermal energy production remains remarkably stable over a 50-year forecast, lithium concentrations are more sensitive to these flow dynamics.

We show that in the absence of active lithium leaching, concentrations decline as lithium-depleted brine recirculates. However, we demonstrate that even modest leaching rates (0.3 g/m3/yr) can sustain concentrations above 100 ppm. These findings highlight that constraining in-situ leaching rates and hydraulic connectivity is not just a geological challenge, but a critical requirement for de-risking the "lithium-from-brine" industry in the URG.

How to cite: Lamy-Chappuis, B., Pezzulli, E., and Driesner, T.: Numerical Modeling of Geothermal Heat and Lithium Co-Production in Fault-Hosted Reservoirs, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11903, https://doi.org/10.5194/egusphere-egu26-11903, 2026.

Reliable subsurface temperature models are a key prerequisite for geothermal exploration, reservoir assessment, and broader subsurface energy applications. Within the GeoChaNce research project, we present an integrated geological and thermal characterization of the Bavarian part of the North Alpine Foreland Basin (NAFB), combining petrophysical analyses of a large heterogeneous well dataset with advanced geostatistical modelling approaches.

The thermal analysis focuses on developing a fully volumetric 3D temperature model that covers depths ranging from 300 m to 5000 m true vertical depth. The temperature dataset comprises 196 bottom-hole temperature (BHT) values, which were corrected using Monte Carlo methods to account for uncertainty, and 19 high-quality continuous temperature logs, including wireline and fiber-optic measurements. To robustly account for data heterogeneity and measurement uncertainty, particularly in the error-prone BHT correction methods, Empirical Bayesian Kriging (EBK) was applied within a 3D framework. The model was computed on a 100 × 100 × 100 m voxel grid and provides probabilistic temperature distributions for P10, P50, and P90 scenarios. Cross-validation using a leave-one-out approach yields a mean standard error of 5.6 K, with more than 87% of predictions falling within the modelled 90% confidence interval.

The resulting temperature model reproduces well-known regional thermal anomalies of the Molasse Basin, including positive anomalies in the Munich and Landshut areas and a pronounced negative anomaly associated with the Wasserburg Trough. In addition, a 3D Empirical Bayesian Indicator Kriging approach was used to derive probability maps for reaching specific temperature thresholds (e.g., 80 °C and 100 °C), providing a robust probabilistic framework for geothermal assessment.

Ongoing work focuses on coupling the solely statistical EBK temperature model with lithology-specific thermal conductivity data derived from laboratory measurements, mixing-law models, and petrophysical interpretations of logging data. This will allow calibration of the temperature field, derivation of regional heat-flow densities, and calculation of horizon-based temperature gradients. The GeoChaNce results provide an improved, uncertainty-aware thermal framework for the Bavarian Molasse Basin, contributing to more reliable geothermal resource assessments and forming a key component for a future geothermal decision-support system for the reservoir.

How to cite: Schölderle, F. and Zosseder, K.: From Heterogeneous Well Data to Probabilistic 3D Temperature Modelling of the Bavarian Molasse Basin for Geothermal Exploration, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13093, https://doi.org/10.5194/egusphere-egu26-13093, 2026.

Salt tectonics is often simplified with a homogeneous halite rheology, but natural evaporite sequences are heterogeneous, including frictional-plastic anhydrite and low-viscosity K-Mg salts, that can alter the architecture and controlling factors of intra-salt deformations in diapiric structures. We use 2D high-resolution finite-element simulations (FANTOM) to investigate how the vertical position of intra-salt layers controls the formation, geometry, and internal architecture of salt diapirs. The models simulate diapirism driven by sedimentary loading (with varying sedimentation rates and no basal tectonics) and explore different intra-salt stratigraphies. Our results shows that layer position have a first-order control on diapir evolution. When an anhydrite layer is placed at the top of the salt sequence, it acts as a stiff caprock that limits salt flow, resulting in a broad, low-relief salt structure with minimal surface deformation. In contrast, a mid-level anhydrite induces flow partitioning and a bimodal deformation pattern: it decouples movements above and below anhydrite, producing sharp diapir margins and localized folding and disruption of the internal layers. This leads to contrasted intra-diapir complexity. If the strong layer is located near the base of the salt, it initially shows high diapirism from the upper salt but eventually forces the lower salt to flow inside this first diapirs. These tall diapirs are associated with intense rotation of the minibasins and the development of welds where the intra-salt layer breaks and salt flows upward. The presence of low-viscosity K-Mg salt layers further amplifies internal deformation: these weak units flow fast and undergo drastic thinning, creating additional shear zones and irregular internal geometries without significantly impeding diapir growth. Our high-resolution models demonstrate that even thin intra-salt layers significantly influence the localization of deformation, thereby shaping both the external form and internal structure of diapirs. These results are applicable to layered evaporite sequences (LES, e.g. Zechstein Basin) and offer a new way for interpreting complex intra-salt features observed at the seismic scale. These insights have important implications for structural interpretation, resource exploration, and the development of salt formations as effective caprock for CO₂ and for hydrogen storage in salt caverns.

How to cite: Ramos, M., Huismans, R., Pichel, L. M., Theunissen, T., Callot, J.-P., Pichat, A., Célini, N., Delahaye, S., and Gout, C.: Architecture and controlling factors of intra-salt deformation in diapiric structures: A numerical modelling approach, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13177, https://doi.org/10.5194/egusphere-egu26-13177, 2026.

Geological hydrogen and helium exploration have increased substantially in recent years, driven by requirements for the energy transition and high-tech industries. These efforts have highlighted the need for fundamental understanding of the underlying geologic systems influencing the generation, migration, and storage of these gases. Since hydrogen (H₂) and helium (He) are naturally produced in the subsurface via chemical and nuclear reactions involving major igneous rock types that are common in crystalline basements (e.g., mafic/ultramafic for hydrogen and felsic for helium), predicting and mapping basement terranes and lithologies has become a key focus in these new exploration efforts. Further, historical data from oil and gas wells have suggested the presence He and H₂ at depth. While these findings offer promising leads, many of these measurements are outdated and require modern verification to assess their current relevance and potential for commercial accumulation.

Our research aims to generate regional-scale interpretations of the He and H₂ system across the state of Texas. To this end, we explore field and well data to complement and refine existing basement lithology interpretations previously derived from core and geophysical data. The main contribution of our work is the application of Bayesian analysis as the basis for joint inversion of gravity and aeromagnetic data to produce probabilistic estimates of basement lithologies throughout the state. Secondly, the extensive analysis of soil and well gas samples for determining He and H₂ generation and storage. Thirdly, improve well log analysis of basin scale lithological interpretations to increase the accuracy of the hydrogen and helium migration and storage potential across the system. These methods ultimately aim to significantly improve the predictive capability of He and H₂ plays based on a suite of geochemical and geophysical data.

The research is currently focusing on the Permian Basin and Ouachita Thrust Belt region in West Texas (USA) that have traditionally been targeted for oil and gas exploration. The Mesoproterozoic basement of the Permian Basin forms an intractonic sag and consists of a complex assemblage of igneous and metamorphic rocks, which are rock types known to generate He and H₂. Interestingly, the basin comprises a 300-1200 m thick Permian evaporite sequence, which may act as an effective seal for basement-sourced He and H₂. A soil gas survey was conducted to identify potential emission zones and to evaluate the sealing potential of the evaporite sequence. This survey was complemented by well data to investigate gas presence below any overburden. In the most favorable areas, long-term H₂ monitoring was implemented to assess possible cyclicity (e.g., diurnal, seasonal) in gas emissions. Basement rock sampling and well gas analyses provide insights into both past and potentially ongoing reactions beneath the overburden, helping to constrain the He and H₂ system and the geological controls.

How to cite: Thompson, J., Schuba, C. N., Pasquet, G., Salah, S., Rodriguez Calzado, E., Horne, E., Arasada, R., Mow, V., Kasperczyk, D., Markov, J., Bhattacharya, S., Moscardelli, L., and Shuster, M.: Building a Picture of the Geological Hydrogen and Helium System in West Texas, USA, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13651, https://doi.org/10.5194/egusphere-egu26-13651, 2026.

Energy consumption and heating efficiency are key bottlenecks constraining the large-scale application of in-situ conversion technology. Autothermic pyrolysis in-situ conversion technology (ATS) proposes an innovative solution: by injecting oxidants such as ambient-temperature air into preheated shale formations, the exothermic oxidation reaction of residual carbon after the thermal cracking of kerogen is utilized to continuously generate substantial heat. This sustains the self-propagating thermal cracking process within the reservoir, significantly reducing the need for external energy supply. Laboratory experiments and numerical simulations show that, through precise control of process dynamics, the technology can achieve an energy efficiency of up to 14.80. With the auxiliary injection of a small amount of hydrocarbon gas, its applicability in shale formations with oil content below 5.0% can also be greatly enhanced.

To advance the engineering application of this technology, our team has developed a series of supporting key technologies, including efficient heating technology, shale complex fracture network construction technology, cross-scale multi-field coupling numerical simulation technology for thermal, fluid, solid, and chemical processes, underground space sealing technology, in-situ catalytic enhancement technology, and an integrated development system combining in-situ conversion, waste heat recovery, and CO₂ sequestration. This has established a comprehensive technological support system. Based on these technologies, our team has conducted two pilot tests in the Qingshankou Formation and Nenjiang Formation of the Songliao Basin in China, at formation depths of 80 meters and 480 meters, respectively. Both tests successfully extracted crude oil and natural gas, verifying the feasibility of this technological approach.

With the growing global demand for cleaner extraction of fossil energy resources, this technology can be widely applied in areas such as in-situ development of oil shale and low-to-moderate maturity shale oil, in-situ coal-to-oil and gasification, in-situ hydrogen production from crude oil, and high-temperature upgrading of heavy oil, demonstrating broad prospects for engineering applications.

How to cite: Guo, W., Zhu, C., Li, Q., Deng, S., and Bai, F.: Autothermic Pyrolysis in-situ Conversion Technology and Pilot Test Project, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15257, https://doi.org/10.5194/egusphere-egu26-15257, 2026.

Abstract

Against the backdrop of the global energy transition, hydrogen is gaining prominence as a clean energy carrier due to its zero emissions and high energy density. In-situ gasification of crude oil reservoirs for hydrogen production has thus emerged as a promising technology. However, conventional process of H₂ production from crude oil suffer from high operating temperatures and energy consumption. Developing effective catalysts to lower the required reaction temperature is therefore crucial.

In this study, a series of Fe-based catalysts, including Fe-Zn, Fe-Co and Fe-Ni composite catalysts, were developed. Their properties were comprehensively characterized, and their catalytic performance was evaluated through hydrous pyrolysis experiments. The results indicate that all catalysts significantly reduced the initial hydrogen production temperature. The Fe‑Ni catalyst exhibited the best performance, followed by Fe‑Co and Fe‑Zn. The abundant micropores in these catalysts facilitated the cracking of short‑chain hydrocarbon intermediates, thereby enhancing hydrogen yield. Furthermore, the presence of Fe improved the catalysts' resistance to coking. The reaction mechanism during in‑situ catalytic gasification of crude oil was also explored. This work provides theoretical insights and technical guidance for the future engineering application of in‑situ hydrogen production from crude oil gasification.

Keywords: Hydrogen production; Crude oil; In-situ gasification; Fe-based catalyst

How to cite: Deng, S., Liu, H., and Guo, W.: In-situ catalytic hydrogen production from crude oil gasification using Fe-based composite catalyst: An experimental investigation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16296, https://doi.org/10.5194/egusphere-egu26-16296, 2026.

The evidence base for geological hydrogen sources is expanding rapidly, moving from anecdotal reports to systematic surveys, exploration, and focused research that address fundamental knowledge gaps. These efforts will determine whether geological hydrogen remains a small-scale, local energy source or can evolve into a large-scale resource capable of contributing meaningfully to the global energy transition. In this interactive presentation, we aim to present and discuss effective ways of applying thermo-hydro-mechano-chemical (THMC) modelling approaches to geological hydrogen research. The objective is to reduce interdisciplinary barriers and to enable effective discussion that optimizes the use of THMC modelling for constraining fundamental research questions. These questions primarily relate to assessments of geological hydrogen resource potential and to informing exploration strategies and detection methods.

Much of the scientific and technical progress in deep-seated applications in recent decades has benefited from the development of THMC numerical and theoretical models. Such applications range from fossil fuel exploration and recovery to geothermal energy utilization, ore-forming systems, and the assessment and mitigation of induced seismicity. These advances were facilitated by improvements in computational capability and algorithmic development, enabling effective integration of experimental results and field observations into models. This has often enabled the development of a mechanistic understanding of nonlinear and tightly coupled THMC processes operating at depth across wide spatial and temporal scales.

Geological hydrogen systems are similarly governed by crustal processes, which can be described as interconnected components encompassing the generation, migration, accumulation, and preservation of hydrogen. Leveraging established multiphysics modelling approaches to investigate these components can provide valuable insights. Key examples include constraining migration mechanisms of dissolved or free-phase hydrogen from deep source regions toward potentially exploitable reservoirs, and assessing fluxes into and out of hydrogen reservoirs. Assessing the relative timescales  can enable first-order evaluation of losses due to biotic and abiotic reactions, as well as accumulation potential.

How to cite: Aharonov, E., Roded, R., and Toussaint, R.: A cross-disciplinary exchange between modelling, field studies, and industry: How can multiphysics modeling advance geological hydrogen resource development?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16404, https://doi.org/10.5194/egusphere-egu26-16404, 2026.

Unlike traditional hydrocarbon and mineral exploration, where decades of empirical data informed threshold values, natural hydrogen exploration requires establishing new baselines for what constitutes an economically significant anomaly. To use soil gas measurements as an effective tool in the geological hydrogen research and exploration we must understand the limitations of the existing instruments, what are background hydrogen values in soil and what other data are required for the reliable interpretation of the soil gas measurements and monitoring data sets.
 Current technology constraints remain a significant challenge in natural hydrogen soil gas sensing. Field-appropriate commercially available sensors exhibit combinations of limited operating ranges, cross-sensitivity to humidity and other gases, baseline drift over time and exposure, and hysteretic dynamics. CSIRO has developed Seeptracker multi-gas (hydrogen, methane, carbon monoxide and carbon dioxide) monitoring device. In this presentation we want to share findings regarding the commercially available hydrogen sensing components comprising Seeptracker and results of deploying this instrument around the world to collect soil gas data in various geological settings. Seeptracker utilises multiple commercially available sensors to measure hydrogen and other gases and the output is enhanced by an extensive calibration routine to improve gas measurement accuracy. Developing Seeptracker revealed the challenge of balancing sensing quality, deployment compatibility, and cost/effort scaling. To achieve suitable long-term large-scale autonomous field deployment requires a clearly and concisely defined study scope, together with a well-characterised sensor package and robust calibration routine to address the multi-variate challenge. 
 Interpreting multi-gas measurements introduces both opportunities and risks for false positives. Effective interpretation of soil gas data for geological hydrogen research requires integration with multiple complementary datasets. Geological mapping identifying serpentinisation fronts, radiolytic source rocks, or fault systems provides essential structural context. Geophysical surveys, particularly magnetotellurics and gravity, can delineate subsurface fluid pathways and potential trap geometries. Geochemical analysis of associated gases, including methane, helium, nitrogen, carbon and noble gas isotopes, potentially enables source discrimination and migration pathway delineation. 
Our work with Seeptracker deployments across diverse geological settings around the world suggests that sustained hydrogen concentrations in soil gas can be used as an effective tool for natural hydrogen exploration, but it cannot be used in isolation. The detailed follow-up investigation is required, particularly when accompanied by spatial coherence and temporal stability and crucially ensuring that measured natural hydrogen is geological. Our studies demonstrate that continuous monitoring data capturing temporal variability, rather than single-point measurements, enhances interpretation confidence. In this presentation we show the performance of the current hydrogen sensors within the CSIRO multi-gas monitoring system Seeptracker, including limitations, and present soil gas monitoring results from various sites around the world. We also show in greater detail soil gas studies from Australia, and the interpretation of the soil gas monitoring results is constrained by geochemical, geophysical and isotope data sets.

How to cite: Markov, J., Mow, V., Kasperczyk, D., Breedon, M., Moran, M., Down, D., Camilleri, M., Strand, J., and Liang, J.: Establishing meaningful soil gas measurements for geological hydrogen research and exploration, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18056, https://doi.org/10.5194/egusphere-egu26-18056, 2026.

The Upper Jurassic to Lower Cretaceous (Purbeck) sedimentary succession of the South German Molasse Basin, here referred as the Malm Reservoir, hosts one of the largest hydrothermal resources in continental Europe. It exhibits strong heterogeneity driven by depositional facies variability within a sequence stratigraphic framework, diagenetic overprint including karst horizon development, and structural elements typical for foreland sedimentary basins. The GIGA-M project aims to study the deep geothermal reservoir of the greater Munich area through integrated well data and large-scale 3D seismic interpretation, providing the geological basis for a reservoir management model enabling synergetic geothermal utilisation. Hydraulically active zones in the most productive geothermal wells are commonly observed within karstified intervals (Hörbrand et al., 2025, Schölderle et al., 2023) and are therefore commonly described as one of the main reasons for the exceptional productivity of the reservoir. Facies architecture and Mesozoic to Cenozoic faults further influence reservoir heterogeneity and fluid flow. Karst horizons are unevenly distributed throughout the reservoir, indicating a complex interplay of syn-depositional and diagenetic controls that is common in many karstified carbonate reservoirs worldwide.

This study evaluates how sequence stratigraphy, facies architecture, and karst development control flow zones and matrix porosity in the Malm Reservoir. The analysis focuses on stratigraphic and facies organisation and karst characterisation. Available well data and recent studies indicate that fault systems and fractures play only a minor role in the hydraulic behaviour of the Malm Reservoir; consequently, they are not a primary focus of this study. Our workflow integrates geophysical well logs, mud-log descriptions, and borehole image logs to identify and classify karst features in wells and, where flow data are available, to correlate karst categories with observed flow zones. This approach enables the recognition of karst horizons associated with enhanced porosity and permeability, directly relevant to reservoir quality and well-interference assessment.

A regional sequence stratigraphic framework (Wolpert et al, 2022; Wolpert, 2020) is used to link relative sea-level changes to facies distribution within the carbonate ramp system. Facies associations primarily control matrix porosity and storage properties, whereas sequence boundaries mark exposure surfaces and sedimentary gaps where karst can develop. While early diagenetic karst may initiate at sequence boundaries, the most extensive karst development is interpreted to result from prolonged subaerial exposure of the reservoir during the Cretaceous, highlighting the critical importance of identifying and differentiating sequence boundaries according to their timing and duration of exposure. This Cretaceous karst generation is considered the main candidate for the laterally extensive karst systems that cross-cut facies boundaries and form the main geothermal flow zones, as confirmed by flow observations in wells. These karst horizons exert a first-order control on transmissivity and hydraulic connectivity. Within the GIGA-M project, this stratigraphic and karst framework provides the geological basis for developing facies- and karst-probability maps calibrated with existing and future GIGA-M 3D seismic data, enabling the assessment of flow connectivity and well interference and supporting geothermal reservoir management at the greater Munich area scale.

How to cite: Crinière, A., Ernst, V., Beichel, K., Bendias, D., Bamberg, B., Schölderle, F., Nasralla, M., Pfrang, D., Banerjee, I., and Zosseder, K.: Sequence-stratigraphic control on facies and karst in Europe’s largest geothermal carbonate reservoir: The Malm Reservoir of the South German Molasse Basin (greater Munich area), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18135, https://doi.org/10.5194/egusphere-egu26-18135, 2026.

Young igneous geothermal systems recharge by magmatic activity. Due to Iceland’s location on the mid-ocean ridge, repeated dyking compensates here for the spreading. This study examines the impact of intrusive and eruptive events on the thermal evolution of the Krafla geothermal system. The so-called “Krafla fires” in 1975-84 were a volcanic episode comprising 20 intrusive and eruptive events, during which seven of them intersected the geothermal system.

The effects of repeated dyking on temperature, pressure, and enthalpy, as well as steam content, are modelled in simple 2D profiles with HYDROTHERM (USGS). Calculating a heat budget can help to exploit geothermal energy sustainably: How much energy is inputted by the dykes into the geothermal system? How much of this heat is lost to the atmosphere by advection and conduction? How fast is heat transferred in the subsurface?

The total heat input of the dyke into the geothermal system is 0.5-1 x 10¹⁸ J. During, and shortly after the eruptive episode, the dyke nearly cools down to the ambient temperatures of the system. Models and previous analyses of steam clouds in air photos indicate that around 10 % of the heat is lost from the surface to the atmosphere, mostly in the first weeks/months after the dyking event, while 90 % of the dyke’s energy is dissipated into the geothermal reservoir. As the system is already close to the boiling point, the additional heat input by the dyke, leads to steam generation, which rises in the high-permeable lava-hyaloclastite layer. It collects below the clay cap and rises through fissures and fractures. In the lower permeable layer of basement intrusions, the steam is less mobile and stays in the vicinity of the dyke. The main changes in temperature and pressure can be observed in the two-phase and superheated steam regions, where enthalpy increases strongly compared to the initial setting. Long-term simulations indicate that the heat input by the dykes formed in the Krafla fires remains in the reservoir for at least several decades and plays a critical role in maintaining the geothermal system.

How to cite: Fehrentz, P., Gudmundsson, M. T., and Reynolds, H. I.: Thermal effects of intrusive events on geothermal systems: Heat transfer modelling during (and after) the Krafla volcano-tectonic episode 1975-84, NE-Iceland, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18250, https://doi.org/10.5194/egusphere-egu26-18250, 2026.

Natural hydrogen (H2) is emerging as a promising carbon-free energy source, aligning with France’s ambition for carbon neutrality and energy sovereignty by 2050. Yet, its occurrence, distribution and long-term sustainability remain largely unexplored. In this context, the H2 and helium exploration company 45-8 Energy was granted the “Grand Rieu” exploration license in the northwestern Pyrenees (SW France), to further investigate its natural H2 system prospectivity, with the objective of drilling an exploration well in the near future.

The license covers part of the Mauleon Basin (North-Pyrenean Zone), a Cretaceous hyperextended rift basin inverted during the Tertiary Pyrenean orogeny (e.g. Saspiturry et al., 2020). This region and the adjacent Pyrenean foreland (Arzacq basin) to the north benefit from extensive historical datasets acquired since the 1950s by major academic research programs (e.g. Orogen project) and the Oil & Gas industry (e.g. historical Lacq and Meillon gas fields), including deep exploration wells, 2D/3D seismic reflection surveys and gravimetric and magnetic data.

Our current work aims to integrate and interpret these datasets to characterize each element of the H2 system and perform volumetric and risking evaluations of H2 prospectivity within the Grand Rieu license. Geophysical studies (e.g. Wang et al., 2016; Wehr et al., 2018; Lehujeur et al., 2021; Saspiturry et al., 2024) highlighted gravimetric, magnetic and velocity anomalies suggesting the existence of a large mantle body at depth (8-10 km) under ideal P-T conditions for serpentinization and H2 generation. Numerous active H2 seepages measured at the surface along the North Pyrenean Frontal Thrust system (Lefeuvre et al., 2022) suggest active serpentinization at depth and preferential migration pathways along regional faults. Proven Upper Jurassic and Lower Cretaceous carbonate reservoirs with overlying effective seals are well-known northward in the Pyrenean foreland (Lacq and Meillon gas plays). However, their presence and properties in the Mauleon Basin remain historically poorly studied and therefore needed to be further characterized to improve their predictability. Ongoing seismic interpretation, aiming to identify potential traps and H2 migration pathways at regional scale, reveals a complex structural framework directly linked to Cretaceous hyperextension and following Cenozoic Pyrenean compression. Preliminary results suggest the existence of deep-seated structures suitable for H2 accumulation.

Overall, the Mauleon Basin appears to offer a unique geological setting favorable for natural H2 generation, migration and accumulation. Further characterization of these processes through dynamic numerical modelling is necessary to better constrain the natural H2 system. In addition, volumetric and risking evaluations will guide the selection of a drilling target within the Grand Rieu license, marking a critical step toward assessing the viability of natural hydrogen as a sustainable energy resource in France’s energy transition.

How to cite: Laurent, A., Boka-Mene, M., De Boisgrollier, T., Fontanelli, L., Potel, S., and Hauville, B.: Exploring natural hydrogen in the NW Pyrenees (France), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18410, https://doi.org/10.5194/egusphere-egu26-18410, 2026.

Solid bitumen is an important organic matter (OM) component in shale systems, and its chemical and resulting nanopore structure exert a strong control on unconventional reservoir properties. Solid bitumen is commonly regarded as a product of thermal evolution of primary kerogen or secondary transformation products such as retained oil. The nanoporous structure of post-oil solid bitumen is strongly influenced by the molecular composition of its organic precursors.

In this study, pyrolysis experiments on heterogeneous precursor oil samples were conducted to systematically investigate the coupled chemical and nanostructural evolution of solid bitumen under proceeding thermal maturation. A combination of Fourier-transform infrared spectroscopy (FTIR), X-ray photoelectron spectroscopy (XPS), Raman spectroscopy, optical reflectance measurements, pore structural characterization, and scanning electron microscopy (SEM) was applied.

The results show that the size and arrangement of aromatic structural units and the abundance of functional groups vary for solid bitumen derived from different oil types at comparable thermal maturity level. These nanostructural variations control nanopore development, leading to systematic differences in pore types and pore size distributions among samples. Micropores and small mesopores are closely linked to the growth, stacking, and structural reorganization of aromatic clusters, whereas stress-related processes mainly control larger mesopores and therefore exhibit a weaker coupling with molecular-scale aromatic evolution.

This study suggests that nanopore development in post-oil solid bitumen is not solely governed by thermal maturity but is also strongly influenced by the composition of precursor oils. These findings are important for assessing the fluid storage and transport behavior of fine-grained OM-rich sedimentary rocks. 

How to cite: Fan, Q., Cheng, P., Xiao, X., and Misch, D.: Coupled chemical and nanostructural evolution of solid bitumen derived from oils with heterogeneous composition, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19864, https://doi.org/10.5194/egusphere-egu26-19864, 2026.

The Upper Jurassic-Lower Cretaceous (Malm-Purbeck) reservoir of the North Alpine Foreland Basin (NAFB) in Bavaria represents one of Europe’s most important deep hydrothermal reservoirs for sustainable heat supply. Reservoir transmissibility shows strong spatial variability and remains insufficiently characterized. In particular, the linkage between basin-scale transmissibility, vertically resolved hydraulically active zones, and their sequence stratigraphic context has not yet been systematically investigated. This gap is addressed by integrating transmissibility, hydraulically active zones, and a sequence-stratigraphic framework to provide a comprehensive characterisation of the reservoir.

Transmissibility values were derived from pressure transient analyses of geothermal and research well tests, resulting in a harmonised dataset of 57 high-quality measurements across the NAFB. These data were used to generate a basin-wide probabilistic transmissibility map using Empirical Bayesian Indicator Kriging (EBIK), a geostatistical approach that explicitly accounts for spatial uncertainty and is well-suited for sparse datasets. The resulting map confirms a general decrease in transmissibility with increasing burial depth from north to south, while also revealing regional deviations from this trend.

To resolve reservoir heterogeneity at the vertical scale, flowmeter measurements from 14 wells were analysed to identify hydraulically active zones and quantify their relative contribution to total flow. By distributing total well transmissibility according to flow contribution and zone thickness, transmissibility values were converted into permeability for individual hydraulically active zones. This approach reveals a systematic decrease in permeability with depth, characterized by distinct regional reservoir types previously identified by multivariate statistical analyses.

Hydraulically active zones were further positioned within a sequence-stratigraphic framework, enabling basin-scale correlation. The results demonstrate that hydraulically active zones occur predominantly within specific sequence-stratigraphic intervals, while deeper units contribute progressively less to flow. Although sequence-stratigraphy does not directly control permeability magnitude, it provides a consistent framework for understanding the vertical distribution of flow zones. Overall, this study provides the first integrated basin-scale assessment linking transmissibility, hydraulically active zones, and sequence stratigraphy in the NAFB. The results significantly improve reservoir characterisation, form a robust basis for static and dynamic modelling, and will be a key component of a decision support model for deep geothermal energy in the future.

How to cite: Ernst, V., Felix, S., Crinière, A., and Zosseder, K.: Characterising the Heterogeneity of Transmissibility and Hydraulically Active Zones in the Deep Geothermal Reservoir in Bavaria , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20209, https://doi.org/10.5194/egusphere-egu26-20209, 2026.

Legacy fly ash, stored in ash ponds and landfills, poses a significant environmental concern due to the dust nuisance caused by its fine particle size, non-cohesive nature, and high susceptibility to atmospheric dispersion. Apart from being ineffective, conventional dust suppression methods, such as water spraying, airborne particle capture, and chemical binders, provide short-lived solutions that are resource- and energy-intensive, lacking long-term sustainability. Enzyme-Induced Calcite Precipitation (EICP) is emerging as a green, durable, and long-term sustainable alternative, which relies on the enzymatic hydrolysis of urea to precipitate calcite minerals. These minerals bind loose, non-cohesive particles together, thereby increasing surface strength while significantly reducing airborne dust particles. However, limited studies have examined the effect of centrifugal purification on plant- derived urease, which influences calcite precipitation and the resulting cementation strength. Urease extracted from plants contains fibers, fatty acids, and other organic impurities that compromise the bonding between the particles of a treated sample. Experimental results indicate that although the cementation solution with unpurified urease yields more calcite precipitation, the associated organic impurities significantly reduce surface strength. In the case of centrifuged-treated urease, the treated samples achieved nearly double the penetration resistance, attributed to enhanced purity. The microstructural attributes confirmed the presence of fibers in samples treated with unpurified urease and illustrated enhanced particle bonding in purified treatments. The pore size distribution characteristics highlight the distinct qualities in terms of pore structure and particle agglomeration between the samples treated with purified and unpurified urease. Overall, the purification process of plant-derived urease was found to be crucial for enhancing EICP performance, thereby improving both the strength and long-term stability of treated fly ash surfaces, thereby mitigating their dust nuisance ability.

How to cite: Nikitha, T. R. and Arnepalli, D. N.: Removal of Organic Impurity in Enzyme for Enhanced Efficacy of Enzyme-Induced Calcite Precipitation in Dust Mitigation Practices, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-622, https://doi.org/10.5194/egusphere-egu26-622, 2026.

Community mini-grids are small, decentralised power systems that supply electricity to groups of households, local businesses, and community facilities within a village or neighbourhood. They serve as a promising solution to achieve SDG 7 goals in the regions where central grid extension remains uncertain or faces reliability challenges. The real performance of the mini-grids, however, cannot be understood through the physical systems (hardware) alone. These systems evolve within the communities (people), depend on the local institutions (structure), and are shaped by the environmental conditions. This study presents an integrated modelling approach that brings these layers together to understand how the community Solar PV mini-grids, as a 'socio-technical system', behave over time and what supports their long-term operational sustainability.

The approach brings together system dynamics with a probabilistic modelling of uncertainty. System dynamics helps make sense of how everyday elements such as the condition of the physical system, the routine maintenance, the growing demand, the revenue flow, the community satisfaction, and the local institutional practices gradually influence one another. Many of these relationships may be overlooked when seen separately, but they become clearer once the feedbacks over time are mapped together. The probabilistic component adds a way to deal with the uncertainty that surrounds the community engagement, the payment behaviour, the institutional reliability, and the chances of key operational events. This allows the model to explore a range of possible scenarios instead of relying on a single prediction.

The modelling efforts begin with the development of the causal loop diagrams (CLDs) based on the existing literature on mini-grid operations and insights obtained through interactions with the stakeholders. CLDs reflect the ground realities that influence the operations, such as informal load expansion, changes in expectations of service quality, and delays in billing recovery or maintenance. The CLDs are then translated into a stock-flow model that simulates how the system evolves. This holistic approach helps identify which interactions strengthen the system's performance and which ones push it toward unsustainable operations.

Real-world case studies from the mini-grids across India and a few international ones are used to test the approach. This allows the model to explore how different local contexts shape the operational behaviour. The findings show that sustainable operations emerge by balancing many interconnected elements. The scenarios also identify safe operating spaces where operational sustainability can be maintained even under uncertainty. The work offers a structured way to integrate the social and the technical dimensions into one modelling framework. It provides a practical tool for planning, decision-making, and long-term management of the community mini-grids. It also supports a deeper understanding of why some systems sustain the operations while others face dysfunctionality.

The work can be extended in future through a multi-level perspective (MLP) in order to connect the daily operational dynamics with the wider patterns of the socio-technical transition. This will explore how niche-level practices within the community mini-grids interact with the broader regime forces and the landscape pressures, e.g. main grid arrival, and how these interactions shape the long-term energy transitions.

How to cite: Buwa, O., Rao, A. B., and Venkateswaran, J.: Integrated System Dynamics Modelling of the Community Solar PV Mini-grid Operations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1149, https://doi.org/10.5194/egusphere-egu26-1149, 2026.

 Offshore energy islands, serving as integrated marine carbon neutrality platforms that consolidate diverse ocean-based energy sources, are emerging as strategic pivots for safeguarding national energy security and propelling the green, low-carbon transition. Their development follows an evolutionary pathway from "platform-based" to "hub-type" to "network-type", providing a blueprint for the systematic exploitation and deep decarbonization of marine energy resources. This paper employs a case study methodology, conducting in-depth analyses of internationally representative projects such as Norway's Hywind Tampen and Denmark's Bornholm Island, to reveal the inherent logic of offshore energy islands as an effective carbon reduction pathway. We find that their core driver lies in addressing specific energy pain points such as high carbon emissions, while the key to success hinges on the synergy between technological feasibility and business model innovation, jointly constructing an economically sustainable carbon reduction closed-loop. Based on this, the study proposes that energy enterprises should systematically advance from four dimensions: strategic planning, differentiated layout, core technology breakthroughs, and industrial ecosystem development. This aims to accelerate the large-scale development of offshore energy islands in China and contribute a practical and forward-looking Chinese solution to global carbon neutrality efforts.

How to cite: Yukihara, T. and Sun, Q.: Promoting Marine Carbon Neutrality through Offshore Energy Islands               , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2448, https://doi.org/10.5194/egusphere-egu26-2448, 2026.

The Chulai area is situated within the tectonically active longitudinal valley zone, located between the Central Mountain Range and the Coastal Mountain Range in eastern Taiwan. The terrain is steep and undulating, with frequent geological structures and seismic activity. Influenced by multiple active faults and long-term orogenic processes, the subsurface geologic structure is dominated by metamorphic rocks, with widespread development of schist, slate, and related metamorphic rocks, indicating intense tectonic compression and metamorphism. To better constrain the geometry and characteristics of the geothermal reservoir system in this structurally complex setting, this study integrates comprehensive well-logging datasets acquired by Schlumberger from a geothermal exploration well drilled to a depth of 1850 m. The logging program includes gamma ray, spontaneous potential, multi-array resistivity, caliper, deviation, FMI resistivity imaging, dipole sonic, temperature, pressure, and fast-shear azimuth measurements. The well-logging results are synthesized with existing geological, stratigraphic, and active-fault surveys conducted by the Geological Survey and Mining Management Agency (GSMMA) to delineate lithologic boundaries, fracture zones, and potential fluid-flow pathways. This information, integrated with geophysical logging data, is then incorporated into a three-dimensional geothermal reservoir model developed using PetraSim, allowing for the simulation of subsurface temperature distribution under geological conditions characteristic of the Chulai region. Model outputs accurately reproduce the observed downhole temperature gradient, demonstrating the reliability of well–logging–constrained reservoir geometry and supporting the inference that the region exhibits a high geothermal gradient and favorable reservoir properties. These findings confirm that integrated well-logging data provide essential information for accurately characterizing subsurface structures, evaluating geothermal reservoir potential, and guiding future development strategies in one of Taiwan’s most promising geothermal prospects.

How to cite: Chuang, P. Y., Wu, H. Y., Lin, H. H., Chen, T. C., Su, T. C., and Lee, C. A.: Constraining Geothermal Reservoir Geometry and Development Potential Using Integrated Well-Logging Data: A Case Study from the Chulai Area, Taitung, Taiwan, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3708, https://doi.org/10.5194/egusphere-egu26-3708, 2026.

India’s iron and steel industry (IISI) contributes nearly 10% of national GHG emissions, making it one of the most carbon-intensive sector. India being an agrarian economy, makes decarbonization using biochar (charcoal derived from biomass) is a viable option. However, its adoption by steel plants is quite limited due to lack of available studies on the optimal number, placement and capacity of biochar facilities in the near-by regions. Moreover, techno-economic viability of biochar utilization has also not been studied so far. This study bridges these gaps by first developing an integrated GIS-MINLP model that optimizes the location, capacity and logistics of biochar production facilities for a case study of steel plant located in Southern India, IISI-A. Further, it assesses the techno-economic and environmental viability of the proposed supply chain and identifies whether adoption of biochar would be economically beneficial for the plant or not.

Results demonstrate that 48 optimal biochar production plants with a combined capacity of 19.62 MTPA can meet ISI-A’s annual biochar requirement of 5.29 MT. Lifecycle CO₂ emissions revealed that when used as a reductant and fuel substitute in steelmaking, biochar achieves up to 53% overall emission reduction, lowering specific emission intensity from 2.55 to 1.19 tCO₂/tcs. The levelized cost of biochar is estimated at USD 298 per tonne, while the marginal abatement cost varies from -39 to 33 USD/tCO₂ depending on market and policy conditions. Policy interventions such as carbon-linked pricing, PLI incentives for decentralized pyrolysis units, concessional loans, and carbon revenue contracts can promote large-scale biochar adoption and strengthen India’s low-carbon steel competitiveness.

How to cite: Swami, D. and Tikadar, B.: Decarbonizing Indian Iron and Steel Industry: An optimization based framework for India, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4092, https://doi.org/10.5194/egusphere-egu26-4092, 2026.

Observation-based constraints on methane mitigation pathways are essential to meet the global 1.5 °C target, especially in large fossil-fuel-dependent economies undergoing rapid structural transition. China is a particularly informative case given its scale, sectoral heterogeneity, and recent emission inflection. While fossil-fuel-related methane emissions in China have declined in recent years, a systematic long-term analysis of national emission trajectories, spatial heterogeneity, and targeted mitigation strategies remains lacking. Here, we develop a transferable Emission–Economy–Ecology–Well-being (E3W) coupled system framework to characterize heterogeneous methane emission trajectories across fossil-fuel and urban systems. China serves as a large-scale testbed to demonstrate the framework under complex, multi-sectoral conditions. Integrating top-down and bottom-up approaches, the framework combines 38 years of methane inventories (1986–2023), satellite-derived ecological indicators, and socio-economic datasets, providing a systematic basis for regionally tailored and phased mitigation strategies. Results show that total methane emissions exhibit a downward inflection after 2022, whereas extreme events declined around 2010, revealing asynchronous turning points between mean and extreme emissions. Urban emissions follow a logistic (S-shaped) trajectory, while mining emissions display a skewed near-normal distribution with rapid peaks and prolonged gradual declines. Nighttime light intensity accounts for ~45.7% of urban methane fluxes, while ecological factors, temperature, and precipitation exert spatially heterogeneous regulation. Some gas-rich mining areas reduce emissions below pre-extraction levels within 3–5 years. These findings highlight that regionally tailored mitigation strategies, prioritizing urban systems and accelerating ecological restoration in mining areas, are essential to avoid climate tipping points and support the 1.5 °C target. These findings offer transferable insights for designing real-zero methane pathways in other fossil-fuel-dependent economies, supporting both climate mitigation and sustainable land-use planning.

How to cite: Yan, X., Fu, J., Lin, G., and Jiang, D.: Regionally Differentiated Methane Mitigation Pathways toward the 1.5 °C Target using Large-Scale Socio-Ecological Observations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4323, https://doi.org/10.5194/egusphere-egu26-4323, 2026.

As the introduction of Locational Marginal Pricing (LMP) gains momentum to address regional imbalances in power supply, the role of Small Modular Reactors (SMRs) as decentralized energy sources is increasingly emphasized. This study evaluates the social acceptance of SMRs in comparison with traditional distributed energy resources, such as solar and wind power, to identify the relative standing of SMRs in the evolving energy landscape. Utilizing a Discrete Choice Experiment (DCE), we quantify the preference gap between different energy sources and analyze how providing information on electricity bill benefits under the LMP system serves as a nudge to shift public perception. Furthermore, the study employs the Contingent Valuation Method (CVM) to estimate the willingness to accept (WTA) for SMR hosting and identifies the specific policy attributes—such as safety enhancement, economic incentives, and regional development—that are most effective in improving acceptance. The findings provide critical insights into the strategic policy interventions required to enhance the viability of SMRs. By identifying which attributes most significantly influence public choice, this research offers a practical framework for policymakers to design effective communication and incentive strategies, ultimately facilitating the integration of SMRs into the future distributed energy grid.

Keywords: Locational Marginal Pricing (LMP), Small Modular Reactor (SMR), Distributed Energy Resources, Social Acceptance, Discrete Choice Experiment, Policy Attributes

How to cite: Son, W. and Woo, J.: Analysis of Social Acceptance of SMRs as Distributed Energy Resources under the Prospective Locational Marginal Pricing in Korea, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4620, https://doi.org/10.5194/egusphere-egu26-4620, 2026.

As countries pursue net-zero emissions targets, data centers present a paradox: they are essential for digital transformation yet pose significant challenges to decarbonization due to their intensive energy consumption and carbon footprint. In South Korea, where aggressive climate commitments coincide with rapid digitalization, understanding public acceptance of data center infrastructure is critical for sustainable energy transitions.
This study examines social acceptance of data center construction through a nationwide survey (n≈1,000), employing contingent valuation methods (CVM) with discrete choice experiments to estimate residents' willingness-to-accept (WTA) compensation. We focus on risk perception related to environmental and health impacts, particularly invisible risks such as electromagnetic fields, thermal emissions, and their implications for local climate and wellbeing.
Critically, we investigate how waste heat recovery and community benefit-sharing—including district heating systems, public libraries, and recreational facilities—can transform data centers from energy burdens into integrated components of circular energy systems. This aligns with net-zero strategies that emphasize energy efficiency, waste heat utilization, and co-location with urban heating infrastructure.
By analyzing trade-offs between perceived environmental risks and tangible decarbonization benefits, this research provides empirical evidence for designing socially acceptable pathways to integrate digital infrastructure within net-zero energy systems, contributing to both climate mitigation goals and just energy transitions.

How to cite: Yang, Y. and Woo, J.: Public acceptance of data centers in South Korea: Balancing digital Infrastructure expansion with Net-Zero transitions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4629, https://doi.org/10.5194/egusphere-egu26-4629, 2026.

Rapid growth in energy demand driven by population increase, urbanisation, and economic development, combined with continued dependence on fossil fuels, poses a major challenge for Egypt’s long-term sustainable energy transition. Addressing this challenge requires integrated modelling approaches that jointly assess renewable energy deployment, demand-side transformation, and system-wide decarbonisation strategies. This study develops a national, bottom-up, integrated energy system model for Egypt using the LEAP (Long-range Energy Alternatives Planning) framework, soft-linked with the NEMO optimisation module, to analyse long-term transition pathways over the period 2017–2070. The model is calibrated to a detailed 2017 base year using national energy balances, sectoral activity drivers, and technology-specific techno-economic parameters. A structured scenario framework is implemented to assess the roles of alternative transition strategies in a transparent and comparable manner. Six scenarios are examined: (1) a Business-as-Usual reference (BAU/REF), (2) a Policy-Aligned Transition reflecting Egypt Vision 2030, Egypt's Integrated Sustainable Energy Strategy (ISES) 2035, Egypt's National Climate Change Strategy 2050 (NCCS 2050) and updated NDC commitments (PET), (3) a Renewable Power Transition focusing on large-scale integration of renewable electricity (RPT), (4) an Efficiency-Driven Transition emphasising demand-ide efficiency and demand moderation (EDT), (5) a Combined Carbon-Neutrality Strategy integrating high renewable penetration with demand-side measures under a long-term emissions constraint (CNS), and (6) a least-cost Net-Zero benchmark derived using NEMO (NZ-OPT). The integrated assessment indicates that neither renewable electricity expansion nor efficiency improvements alone are sufficient to deliver carbon neutrality. Deep system-wide decarbonisation requires their coordinated deployment, supported by accelerated electrification of end-use sectors, enhanced system flexibility, and appropriate investment sequencing. The study provides a consistent modelling framework for assessing sustainable energy transitions in Egypt and offers transferable insights for other rapidly growing emerging economies such as developing countries.

How to cite: Elhaddad, A. and Park, C.: Long-term Energy Demand and Carbon-Neutrality Pathways for Egypt: A LEAP-Based Scenario Analysis (2017–2070), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6927, https://doi.org/10.5194/egusphere-egu26-6927, 2026.

The Just Transition of coal-dependent regions represents one of the most demanding challenges within Europe’s ongoing energy transformation. The progressive phase-out of coal-fired power plants is associated with socio-economic implications, particularly in regions historically reliant on fossil-based energy production. At the same time, the transition must ensure energy security, industrial continuity, and the reduction of greenhouse gas emissions in a rapidly changing energy landscape. Within this context, carbon mitigation strategies that go beyond simple emission reduction are gaining increasing attention. Carbon Capture and Utilization (CCU) technologies offer a promising pathway by transforming carbon dioxide emissions into valuable products. The LIFE CO2toCH4 project (https://co2toch4.eu/) addresses these challenges by developing and demonstrating an integrated CCU and hybrid energy storage system based on biological methanation, converting captured carbon dioxide and renewable hydrogen into biomethane on-site through a mobile, autonomous unit. This approach contributes to emissions mitigation while enhancing energy system resilience and supporting a more circular use of carbon.

Beyond pilot-scale demonstration, the long-term impact of such technologies critically depends on their replicability and transferability across diverse geographical and industrial contexts. This work presents a structured replication and transferability framework supporting the large-scale deployment of CCU technologies across Europe. Replicability is addressed through the development of a replication roadmap, focusing on the identification of suitable power plant sites across Europe for the deployment of the CO2toCH4 technology. This assessment is based on a structured set of criteria, including the intensity of carbon dioxide emissions, geographical representativeness, and the commitment of installations to future sustainability pathways. The analysis is supported by comprehensive databases and corresponding maps of European non-renewable power plants, as well as a refined spatial representation of the selected priority sites identified as the most suitable candidates for replication. The transferability assessment highlights that the biogas sector emerges as particularly well-suited, as the carbon dioxide fraction of biogas can be further upgraded to methane, increasing biomethane yields and improving overall plant efficiency. Given the widespread deployment of biogas installations across the European Union, this application highlights the significant replication potential of the technology. Techno-economic assessments indicate that, despite relatively high upfront investment costs and uncertainties linked to early-stage deployment, the technology shows economic viability at large scales. Successful implementation, however, depends on supportive policy frameworks, access to targeted funding mechanisms, and regulatory recognition of CCU-derived fuels. Overall, LIFE CO2toCH4 illustrates the potential role of innovative CCU solutions in supporting the Just Transition, by exploring pathways for the utilization of carbon dioxide within emerging circular energy systems.

Acknowledgements

The project “LIFECO2toCH4 - Demonstration of a mobile unit for hybrid energy storage based on carbon dioxide capture and renewable energy sources” (LIFE20 CCM/GR/001642) is co-funded by LIFE, the EU’s financial instrument supporting environmental, nature conservation and climate action projects throughout the EU.

How to cite: Antoniadis, A., Partheniou, E., Konstantinidi, S., Servou, A., and Roumpos, C.: Innovative Carbon Utilization Pathways for Supporting Europe’s Just Transition: Insights from the LIFE CO2toCH4 Project, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7243, https://doi.org/10.5194/egusphere-egu26-7243, 2026.

Automotive manufacturing is a multi-trillion-dollar industry that demands significant energy, materials, innovation, and safety, making it challenging to reach “real zero” in this sector. Remanufacturing can cut energy and material needs, but little is known about its potential greenhouse gas (GHG) reductions. Here, we compare GHG emissions from aluminum automotive control arms produced via conventional manufacturing and cold spray additive remanufacturing (CSARM). We quantify per-part GHG emissions (kgCO_2e/part) in collaboration with lab-scale and industrial CSARM and automotive manufacturers. Canada is a top global producer of aluminum, using Quebec’s predominantly hydro-powered grid. We focus on Ontario, Canada’s auto manufacturing hub. We test key system parameters, like grid intensity, deposition efficiency, powder production processes, facility energy use, and transportation.

Results indicate that choice of manufacturing pathway (conventional vs. CSARM) substantially impacts per-part GHG emissions. CSARM reduces GHG emissions by up to 95% relative to conventional manufacturing. However, the magnitude of this difference depends heavily on process parameters such as grid intensity, deposition efficiency, and aluminum powder production route. Emissions from remanufacturing one control arm range from 0.18-2.3 kg CO_2e, as opposed to 3.1-7.9 kg CO_2e for conventional manufacturing. We find that component-level remanufacturing can support meaningful real zero oriented industrial decarbonization; however, this relies on low-carbon energy, energy efficient facilities, and improvements in upstream material production.

In this presentation, we present these part-level findings and sensitivity analysis. We further apply it to assess the potential for CSARM of aluminum automotive parts to decarbonize automotive manufacturing in Ontario, using optimized reverse logistics to identify used parts and site remanufacturing facilities.

How to cite: Bindas, S., Saari, R. K., Jahed Motlagh, H., Alumur Alev, S., Afros, S., Marzbanrad, B., and Woo, A.: Re-made in Ontario: Greenhouse gas (GHG) emissions impact from cold-spray additive remanufacturing in the auto industry in Ontario, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8246, https://doi.org/10.5194/egusphere-egu26-8246, 2026.

The EU HydroMine project investigates waste valorisation, carbon capture, and the reuse of legacy mine infrastructure to produce hydrogen (targeting 90–99.99% purity) from refuse-derived fuel (RDF). RDF is non-recyclable municipal waste in the sense of circular economy, but currently applied in, i.e., thermal recycling in cement plants or deposited on landfills. Hence, reduction of overall RDF volumes is central to address the main challenges of urban waste management and decarbonisation of energy systems. In this course, HydroMine supports circular economy developments in mining regions in transition and advances sustainable hydrogen production strategies by repurposing existing mining infrastructure for RDF beneficiation. Techno-economic modelling was carried out in the project to quantify the economics of this technology by means of a dedicated, dynamic and modular simulation framework. It employs surrogate models using response functions and tables as well as empirical data correlations developed within the project, and was validated for regional operational scenarios at a Polish study area. For that purpose, the complete process chain from RDF pre-processing through gasification for synthesis gas production and cleaning, hydrogen as well as carbon monoxide and dioxide separation by membrane systems [1] and pressure-swing adsorption (PSA) is taken into account. Further unit stages comprise treatment of tail gases by plasma technologies and final product gas compression. All simulations integrate mass and energy balances with cost calculations at unit scale. Sensitivity analyses were embedded into the workflow to establish a comprehensive assessment of influential parameters. The established models are supporting the project in developing commercially viable waste-to-hydrogen strategies for stakeholders, investors, policymakers, and operators to accelerate the adoption of sustainable hydrogen production in the decarbonising energy transition landscape.

[1] Avruscio, E., Marsico, L., Brunetti, A., Theodorakopoulos, G. V., Karousos, D. S., Kempka, T., ... & Barbieri, G. (2026). Syngas hydrogen upgrading using green-based ultra-microporous carbon hollow fibre membranes. International Journal of Hydrogen Energy, 198, 152598. https://doi.org/10.1016/j.ijhydene.2025.152598.

The present study has received funding from the EU RFCS - 2022, under grant agreement No. 101112629 (HydroMine).

How to cite: Ernst, P., Kempka, T., Kapusta, K., Lejwoda, P., Barbieri, G., Brunetti, A., Tekeli, Ł., Gogol, B., Maseri, F., Godfroid, T., Boutsen, P., and De Weireld, G. and the HydroMine Partners: Techno-economic assessment of hydrogen production from refuse-derived fuel using legacy mining infrastructure, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9388, https://doi.org/10.5194/egusphere-egu26-9388, 2026.

India faces a formidable challenge in balancing its development goals and climate targets. Addressing this requires a holistic understanding of the system, including the interconnections and trade-offs involved in achieving these objectives. While Integrated assessment models (IAMs) aid in such analysis, they under-represent the Global South, lack transparency in model structures and input parameters, over-rely in futuristic technologies such as carbon dioxide removal (CDR) technologies and miss the non-linear feedbacks yielding least-cost optimal pathways which can be misaligned with the regional reality. In this context we developed Sustainable Alternative Futures for India (SAFARI), a transparent integrated system dynamics simulation model encompassing all economic sectors, the only global south model tailored specifically for these challenges in the Indian context.  SAFARI prioritizes Desired Quality of Life (DQoL) goals such as food and water security, housing, healthcare, and universal access to education while explicitly modelling resource feedbacks such availability of land, water and materials. This framework enables the development of sector-by-sector mitigation or “real-zero” scenarios without compromising energy requirements or carbon space necessary for development. Unlike some global IAM scenarios, SAFARI ensures no DQoL goals like food security are compromised in low-carbon futures. SAFARI’s unique approach yields results that complement global integrated assessment models, which are least-cost and GDP-driven and primarily inform IPCC scenarios. This study details SAFARI’s sectoral modeling approach and presents indicative scenarios towards India’s Net zero 2070 target. In Business-as-usual (BAU) scenario emissions continue to rise and peak in 2070. The Long-Term Strategy (LTS) scenario simulates moderate interventions across multiple demand-side sectors and the supply sector including behavioural shifts, increased efficiency and fuel changes. The emissions in LTS scenario peak in 2041 with a post-peak decline. Land use sector offset residuals for the net zero by 2070. Demand-side interventions have the potential to reduce primary energy demand to a large extent alleviating pressure from the power sector to decarbonize, enhancing the feasibility of achieving net zero emissions without heavy reliance on CDR technology. These scenarios highlight SAFARI as a decision-support tool for creating multiple what-if scenarios that aid in better understanding of overall system and the trade-offs and synergies among various sectors.

How to cite: Sundaresan, A., Natarajan, R., Ashok, K., Gangopadhyay, A., Davis, D., Ravishankar, K., and Murthy, I.: SAFARI: Modelling Sustainable Alternative Futures for India's Net-Zero Transition, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9547, https://doi.org/10.5194/egusphere-egu26-9547, 2026.

The HydroMine project investigates the development of a hydrogen-oriented municipal waste refinery that repurposes legacy mining infrastructure through an integrated gasification and gas separation concept. This contribution presents the results of a 3D thermo-hydraulic-chemical numerical model developed to simulate the gasification of Refuse-Derived Fuel (RDF) - produced from municipal solid waste - into a hydrogen-rich synthesis gas under laboratory-scale conditions, and thereby supporting the transition toward scalable reactor designs.

The fully coupled numerical model was developed to simulate fluid flow, heat transfer and chemical reactions within a packed RDF bed. Model calibration and validation were performed using experimental datasets from 3-m and 7-m laboratory reactor tests, covering the temporally dynamic oxidant and steam injection.

The simulations successfully reproduce the key synthesis gas components (CO₂, CO, and H₂), showing a good calibration results for the 3-m reactor data used for model calibration as well as the validation based on the 7-m reactor data across all injection regimes applied. This confirms that the applied reaction kinetics and thermo-hydraulic-chemical model formulation effectively represent the governing processes of RDF gasification in a packed bed.

The validated numerical model provides a physics-based foundation for further process optimisation and scale-up analyses to guide investigations in the HydroMine project, including commercial-scale reactor configurations, alternative operational strategies and varying compositions of the RDF feedstock. The findings support techno-economic and environmental feasibility as well as life-cycle assessments within the HydroMine project.

The present study has received funding from the EU RFCS-2022 programme under grant agreement No. 101112629 (HydroMine).

How to cite: Otto, C., Kapusta, K., Wiatowski, M., Lejwoda, P., Szyja, M., Korol, J., Wodołażski, A., Basa, W., Pankiewicz-Sperka, M., Koteras, A., Stańczyk, K., Stańczyk, K., and Kempka, T.: Validation of refuse-derived fuel gasification for hydrogen-optimised synthesis gas production by numerical modelling, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9680, https://doi.org/10.5194/egusphere-egu26-9680, 2026.

Agrivoltaic systems have been implemented internationally and have demonstrated significant potential to balance agricultural production and renewable energy development under appropriate regulatory and design. In Taiwan, however, agrivoltaic applications are currently limited to aquaculture–photovoltaic (PV) systems, and ground-mounted agrivoltaics have not yet been permitted, partly due to potential unknown consequences of agrivoltaic systems. In this study, we aimed to assess the influence of agrivoltaics on crop yields, considering the variability in crops’ light requirements and the seasonal crop rotations in Changhua County, Taiwan. Shading factors (SFs), representing the ratio of shaded area to total area, were monthly simulated for an agrivoltaic system designed for planting fruit vegetables, leafy vegetables, and C3 cereals outside the vertical projection area of PV modules to reduce the impact of shading. On the other hand, logistic and hormesis response models were employed to construct the relationships between crop yield and SF, enabling predictions of crop yield variation under a specific PV array configuration. Results of effect analysis indicated that the thresholds of SFs enabling 80% of attainable yields were 61.28% for fruit vegetables, 17.59% for leafy vegetables, and 32.60% for C3 cereals. When the PV array spacing was set to 5 m, SFs ranged from 0.39% to 11.50% over one year, with an average value of 4.27%. Results indicated that, under the crop rotation scenario involving fruit vegetables, leafy vegetables, and C3 cereals, crop yields could still reach 80% of attainable yields. These findings could provide practical insights for the design and planning of agrivoltaic systems in Taiwan and offer a quantitative framework for future policy development and implementation.

How to cite: Lu, T.-H. and Huang, W.-Y.: Integrating the Simulations of Shading Factors and Effect Analysis to Assess the Suitability of Agrivoltaics under a Crop Rotation Scenario in Changhua, Taiwan, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10196, https://doi.org/10.5194/egusphere-egu26-10196, 2026.

Green hydrogen is pivotal for the global energy transition; however, its environmental footprint extends beyond carbon emissions, particularly concerning water consumption in water-scarce regions. This study presents a cradle-to-gate Life Cycle Assessment (LCA) of green hydrogen production via Polymer Electrolyte Membrane (PEM) electrolysis, focusing on the trade-offs between Global Warming Potential (GWP) and Water Scarcity Footprint (WSF).

We modeled three scenarios based on different renewable energy sources (solar PV, wind, and hybrid systems) and water supply methods (freshwater vs. seawater desalination) in Taiwan. The inventory data were analyzed using SimaPro method.

Our results indicate that while solar-driven electrolysis achieves the lowest GWP, it significantly exacerbates regional water stress due to high cooling requirements and panel cleaning, unless coupled with desalination.  The study highlights that ignoring the water footprint in hydrogen roadmaps may lead to burden shifting—solving the carbon problem while creating a water crisis. We conclude by proposing site-specific environmental management strategies to optimize the location of hydrogen hubs.

How to cite: Wang, Y.-S., Kuo, N.-W., and Yeh, H. J.: Beyond Decarbonization: A Comparative Life Cycle Assessment of the Water-Energy Nexus in Green Hydrogen Production, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10526, https://doi.org/10.5194/egusphere-egu26-10526, 2026.

The need to phase out fossil energy has promoted a rapid development of wind power, yet this development may negatively affect biodiversity and encounter resistance among local citizens. To study whether optimal locations for wind power differ when considering biodiversity impacts or social acceptance (in terms of distance to settlements), we used spatial suitability analysis for allocating wind power in Pirkanmaa region in southern Finland. First, we identified areas completely restricted from wind power using constraints based on legislative and authority guidelines. Second, we implemented two suitability analyses based on criteria weighted using analytic hierarchy process (AHP). For biodiversity-based suitability, we used multiple spatial datasets such as bird migration routes, biodiversity value of forests and distance to conservation areas, while acceptance-based suitability was based on distances to residential buildings and second homes. We clustered high-suitability areas using Anselin Local Moran’s I cluster analysis to find spatially contiguous areas for wind power. We compared the results of biodiversity-based and acceptance-based allocation in three scenarios for electricity production for the year 2035: scenario 1 corresponded the current production-consumption ratio in the region, scenario 2 electricity self-sufficiency, and scenario 3 the maximum production capacity. The most suitable areas for wind power were forested areas in the sparsely populated parts of the region. Optimal areas for biodiversity-based and acceptance-based suitability showed only partial overlap, suggesting trade-offs in wind power allocation. The overlap area increased from 0% in scenario 1 to 41% in scenario 3. Highly suitable areas based on both biodiversity and acceptance were not sufficient to cover the production capacity in scenario 2, indicating that reaching electricity self-sufficiency may not be possible without compromising biodiversity or citizen acceptance. The results highlight the importance of consideration of both biodiversity values and citizen acceptance in wind power development, as potential for land use conflicts is likely to increase with growing electricity demand in the future. The proposed method offers a framework to identify areas for wind power development where conflicts between biodiversity values and social acceptance can be minimized.

How to cite: Luukkonen, S., Räsänen, A., Koivula, M., and Tolvanen, A.: Synergies and trade-offs between biodiversity and social acceptance in the spatial allocation of wind power, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11032, https://doi.org/10.5194/egusphere-egu26-11032, 2026.

The 2023 UAE Consensus (COP28) marked a watershed in global climate governance, committing parties for the first time to “transition away from fossil fuels in energy systems.” Yet the text’s constructive ambiguity leaves the operational content of this commitment uncertain. Four categories of ambiguity emerge: whether transitioning away applies uniformly globally or presupposes differentiated regional responsibilities; whether “net zero energy systems” encompasses industrial processes or only energy supply and demand; whether “mid-century” net zero must be achieved exactly by 2050 or permits some delay; and whether net zero refers to CO2 alone or all GHG. Here we assess whether any plausible interpretation permits policy retrenchment. We benchmark COP28 commitments against IPCC AR6 1.5°C-consistent pathways and develop bespoke scenarios using the MESSAGEix-GLOBIOM integrated assessment model to stress-test each ambiguity dimension. We find that targets for tripling renewable capacity and doubling energy efficiency exceed the median of cost-optimal pathways assessed by the IPCC. Across all tested configurations, reduced fossil fuel output dominates emission reductions (>90%), with carbon capture and storage serving a strictly secondary role (<10%). System boundary definitions prove analytically inconsequential; pollutant and temporal scope affect transition pace but not mechanism. Imposing phaseout constraints on Annex I regions alone dramatically expands feasibility compared with globally uniform mandates, quantifying the enabling effect of differentiated leadership consistent with common but differentiated responsibilities. Even the most lenient interpretations of Article 28 permit no room for backsliding.

How to cite: Al Khourdajie, A., Ju, Y., Meng, M., Ganti, G., Mori, S., Fricko, O., Fujimori, S., Gidden, M., Joshi, S., Krey, V., Riahi, K., Rogelj, J., and Schleussner, C.: No room for backsliding: Assessing the ambition floor of the COP28 agreement, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11113, https://doi.org/10.5194/egusphere-egu26-11113, 2026.

The marine environment is and will continue to be subject to major changes as an area of interest in the transition to renewable sources of energy. Offshore wind farms are springing up throughout Europe and the world, with EU targets projecting 60 GW by 2030 and 300 GW by 2050. Further commercial and regulatory interests target the addition of additional marine renewables strategies to existing offshore wind energy construction goals, further increasing the variety of structures and technologies introduced to the oceans. Not only structures or industrial activities themselves lead to emissions, but also forms of protection (particularly galvanic anodes, meant to protect large steel structures from corrosion). Lacking is exact knowledge of how emissions from offshore renewable structures interact with and accumulate in their environment. Furthermore, existing uses and historical pollution of coastal areas in combination with a naturally variable, dynamic environment.

This investigation makes use of nearly a decade of data from offshore wind farms and nearby sites in the North Sea, primarily conducting an analysis of metal mass fractions in the fine fraction (< 20 µm) of sampled sediments. Related analyses on seawater and biota are or will become available for reference. Established ICP-MS/MS methods have been used, with focus on technologically critical elements and elements considered by previous publications to have potential as tracers for offshore emissions. These include the galvanic anode components Zn, Ga, In, and Pb. Additionally, the method allows for analysis of over 50 elements. Statistical analyses of the data are complicated by environmental considerations: high natural variability of many elements, historical sources of pollution such as the element Pb, and active simultaneous inputs of contaminants such as Zn from other sources mask signals from the offshore structures under investigation.

These new data and their analysis are of value to understand effects on the marine environment in the context of planned acceleration of renewable energy generation strategies. As installations of offshore wind farms and other offshore renewables infrastructure intensify across Europe and the world, the potential to cause unintended environmental impacts grows along with them. Supported by national and internationally funded projects, the investigation presented here aims to explore the magnitude and ecological consequences of chemical emissions from offshore structures with the goal of informing policy and industry decision-making.

How to cite: Zonderman, A., Ebeling, A., Wippermann, D., Zimmermann, T., and Pröfrock, D.: Chemical Emissions from Offshore Wind in the North Sea, or, Needles in a Needlestack, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11789, https://doi.org/10.5194/egusphere-egu26-11789, 2026.

This study addresses the potential role of Pumped Hydro Energy Storage (PHES) within the Kenyan electricity system pathways by combining high-resolution geospatial analysis for the site suitability and spatially explicit energy system optimisation model (ESOM) to evaluate optimal power system expansions to 2050. The modelling framework further incorporates a Gaussian copula-based Bayesian network to represent uncertainties related to demand and market pricing for net-zero target scenarios.
The study brings together three elements of PHES technologies by quantifying site-specific capital costs based on topology, implementing and optimising their scale and spatial patterns in future power systems, and addressing known uncertainties. Initially, techno-economically viable PHES sites are explored in Kenya by applying geospatial operations and redeveloping existing water bodies. Considering the country’s distinctive geography, climate, land use, and water supply, the potential sites have been assessed within the nexus framework. The results indicate that Kenya offers considerable potential for PHES, with unit capital expenditures ranging from $750/kW to $6000/kW, with many options being comparable to the lower end of global cost ranges. This spatial heterogeneity of PHES potential motivates a spatially explicit dispatch and expansion analysis to identify which sites are cost-effective, where, and at what scale in future electrification pathways.
For this purpose, the study introduces a spatially explicit ESOM, termed PyPSA-KE, based on the open-source PyPSA-Earth framework. The model is calibrated using Kenya-specific data and applied to investigate optimal power system expansion pathways to 2050 under carbon tax-based net-zero scenarios. Closed-loop PHES sites identified in the Global Atlas of PHES (Stocks et al., 2021) are represented explicitly, with site-specific capital costs and grid-connection distances derived from local topography. Results indicate a substantial potential for PHES deployment across Kenya for both daily and multi-day storage, complemented by battery storage to ensure peak demand is met. The absolute amounts of storage required in 2050 are highly sensitive to uncertain exogenous socio-techno-economic factors, most notably future electricity demand, battery cost trajectories, and the stringency of carbon taxation. Although the ESOM is deterministic, explicitly accounting for such uncertainty is essential, in line with a growing shift towards global sensitivity analysis in the literature (Yue et al., 2018). To this end, the study proposes a Bayesian framework enabling probabilistic characterisation and rapid exploration of long-term scenarios. A Gaussian-copula-based Bayesian network is constructed using Monte Carlo samples of PyPSA-KE outputs, generated by imposing probability distributions on key uncertain inputs. Despite limitations associated with network structure and the use of bivariate Gaussian copulas, the approach demonstrates strong potential to extract robust insights and inform policy discussions on long-term power system planning under deep epistemic uncertainty.

Stocks, M., Stocks, R., Lu, B., Cheng, C., & Blakers, A. (2021). Global Atlas of Closed-Loop Pumped Hydro Energy Storage. Joule, 5(1), 270–284. https://doi.org/10.1016/j.joule.2020.11.015
Yue, X., Pye, S., DeCarolis, J., Li, F. G. N., Rogan, F., & Gallachóir, B. Ó. (2018). A review of approaches to uncertainty assessment in energy system optimization models. Energy Strategy Reviews, 21, 204–217. https://doi.org/10.1016/j.esr.2018.06.003

How to cite: Sadak, D., Karamountzos, P., Mares-Nasarre, P., van de Giesen, N., and Abraham, E.: A Spatially Explicit Planning of Pumped Hydro Energy Storage in Kenya’s Long-Term Decarbonisation Pathways, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12682, https://doi.org/10.5194/egusphere-egu26-12682, 2026.

Repurposing post-mining shafts for adiabatic compressed air energy storage (ACAES) requires gas-tight lining of shaft collar. Even where macroscopic cracking is absent, the connected pore network of concrete can sustain pressure driven gas transport, leading to standby losses and reduced round-trip efficiency during long idle periods. This contribution presents an experimental investigation and measurements of candidate lining systems for shaft sealing for the A- CAES concept.

Two representative concrete samples were tested (C20/25 and C40/45), reflecting older and modern shaft linings. Two film forming surface protection systems were evaluated: (i) a thin-layer, waterborne epoxy coating WallCoat T; typical dry film thickness ~0.25 mm), and (ii) a thicker Xolutec membrane (Sikagard M 790; typical dry film thickness ~0.7–0.8 mm) that provides crack bridging capability and broader application tolerance. Specimens (Ø25 mm × 30 mm) were prepared and cured per EN 206 and EN 12390-2, with coating application and quality control aligned to EN 1504-10.

Gas permeability was determined using a steady-state flow method with helium as the measurement medium and Klinkenberg-corrected extrapolation to intrinsic permeability. Uncoated concretes exhibited mean permeabilities of ~4.6×10⁻⁴ mD (C20/25) and ~1.4×10⁻⁴ mD (C40/45). Coatings reduced permeability by 3–4 orders of magnitude: WallCoat T achieved ~3.7×10⁻⁸ mD, while Sikagard M 790 yielded ~5.0×10⁻⁷ mD with higher variability attributable to local coating heterogeneities.

How to cite: Lutyński, M. and Kołodziej, K.: Experimental Investigation of Gas Permeability of Concrete Lining and Membrane for CAES in Repurposed Mine Shafts, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14000, https://doi.org/10.5194/egusphere-egu26-14000, 2026.

Flooding of underground mines after closure often leads to groundwater rebound, land uplift, and sinkhole formation. Such land surface changes create direct risks for infrastructure and for people living in affected areas. In recent years, the number of underground mines being closed has increased, particularly in Europe, which raises the need for efficient techniques that can monitor land surface deformation, improve process understanding in post-mining areas, and support the planning of mitigation and land-management measures.
This study focuses on the Olkusz-Pomorzany zinc-lead underground mining district (southern Poland), closed in 2020, where groundwater pumping stopped in 2021, and since then numerous sinkholes have been reported, together with uplift and local subsidence zones affecting forests, fields, and infrastructure. The area is a challenging case because mining has been conducted since the 13th century using different methods, including shallow and partly undocumented workings, and because the geological setting includes fractured and locally karstified carbonate rocks covered by Quaternary unconsolidated deposits of highly variable thickness.
We present land surface deformation results based on satellite radar interferometry and time-series analysis. We use Sentinel-1 Persistent Scatterer InSAR (PS InSAR) for 2021-2024 to map long-term motion patterns, and short-period SBAS results from Sentinel-1 and SAOCOM (2023) to better capture faster, non-linear changes associated with sinkhole formation in areas where C-band coherence is limited. The displacement time series are analysed in two ways. First, Independent Component Analysis (ICA) is applied to separate the main signals present in the whole dataset, including long- and short-term deformation patterns and acquisition-geometry effects; ICA is then used to map spatial differences in component amplitudes and to highlight zones with changing deformation dynamics. Second, each time series is classified into stable, linear, non-linear (quadratic), bilinear, and discontinuous behaviours, including sensitivity tests of the classification thresholds to provide reliable separation between stable and moving points.
Results are compared with a sinkhole inventory (2021-2024) and with mining layers, including the extent of historical workings, areas of shallow mining, and local geological conditions such as overburden type and thickness. Sinkholes are most often located within zones of strong uplift, associated with groundwater rebound, but they do not occur across all uplifting land surface. Instead, they cluster where the time series show the largest change in deformation rate (acceleration/deceleration or breaks) and where shallow, old mining is reported. These patterns suggest that rebound-driven uplift sets the regional background signal, while local weakening and structural complexity related to legacy workings control where sinkholes occur. The combined ICA and trend-classification approach helps to separate regional-scale rebound from local instabilities and supports targeted hazard management in post-mining landscapes.

How to cite: Guzy, A., Łucka, M., Walczak, S., Zhang, X., and Witkowski, W. T.: Drivers and spatio-temporal characteristics of land movements associated with sinkhole formation in flooded, abandoned mines, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14118, https://doi.org/10.5194/egusphere-egu26-14118, 2026.

Limiting global warming to 1.5 °C above pre-industrial levels requires a rapid and sustained transition to renewable energy systems, with photovoltaic (PV) solar energy playing a central role due to its scalability and declining costs. However, PV power generation is inherently sensitive to atmospheric conditions such as aerosols, cloud cover, and temperature, which vary spatially and are expected to evolve under climate change. While global PV capacity has expanded rapidly, climate-related impacts on PV energy generation, particularly at the facility level, remain insufficiently quantified. Many existing assessments rely on generalized assumptions, overlooking the heterogeneity of PV deployment and local environmental conditions, which limits their relevance for integrated energy system modelling and planning.

This study combines machine learning and satellite-based observations to improve the representation of PV systems and climate-related performance losses in global-scale assessments. A machine learning model is trained on diverse geospatial datasets to identify PV installations across a range of geographic and land-use contexts, including complex terrains. Facility-level PV data are then integrated with satellite and reanalysis products to quantify the influence of aerosols, cloud variability, and temperature on solar energy generation over the past decade.

Results reveal pronounced regional variability in PV energy losses, driven by differences in atmospheric composition, cloud dynamics, and thermal stress. Elevated aerosol loads are associated with significant reductions in surface solar irradiance, while cloud variability affects both average generation and short-term reliability. Extreme temperatures further reduce PV efficiency in certain regions. These findings highlight the importance of incorporating site-specific climate sensitivities into energy system models to better assess performance, resilience, and trade-offs in renewable energy deployment.

By shifting the focus from installed capacity to climate-related energy losses, this work contributes to integrated assessments of sustainable energy transitions. The approach provides actionable insights for system planning, model improvement, and policy development, supporting more robust and environmentally informed strategies for scaling solar energy within diversified and resilient energy systems.

How to cite: Song, R., Yin, F., Muller, J.-P., Povey, A. C., Swain, B., Huang, C., and Grainger, R. G.: Climate Impacts on Photovoltaic Performance and Implications for the Global Solar Energy Transition, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14977, https://doi.org/10.5194/egusphere-egu26-14977, 2026.

Managing Overshoot Through Collective Carbon Debt Drawdown

Setu Pelz, Oliver Fricko, Keywan Riahi, Shonali Pachauri, Elina Brutschin, Joeri Rogelj, Volker Krey, Injy Johnstone, Adriano Vinca, Carl F. Schleussner, Jarmo Kikstra, Matthew J. Gidden

The impending breach of the 1.5C limit requires urgent collective action to minimize overshoot magnitude. To date, most Integrated Assessment Model (IAM) experiments treat the principles and norms informing collective action as distinct and typically ex-post considerations, separating, for example, assessments of fairness from the scenario modelling process. Here, we propose and demonstrate a modular framework that endogenizes fairness considerations directly into standard IAM scenario generation processes. We use ‘carbon debt’ to track and minimise regional responsibilities for overshoot corresponding to varied considerations of fairness, and thereby identify a broader solution space for collective high-ambition than previously recognized. We demonstrate that high-responsibility regions can manage this carbon debt through varying combinations of interregional financial transfers and intensified near-term domestic gross emissions reductions. Pathways prioritizing domestic gross reductions lower interregional financial transfer obligations and reduce the reliance on novel carbon dioxide removal in lower-responsibility regions. Conversely, delaying the onset of cooperation increases global energy system investment costs. Ultimately, our results indicate that considerations of fairness are wholly consistent with collective global 1.5°C pathways and can provide a wider solution space informing multilateral deliberations.

How to cite: Pelz, S., Fricko, O., Riahi, K., Pachauri, S., Brutschin, E., Rogelj, J., Krey, V., Johnstone, I., Vinca, A., Schleussner, C., Kikstra, J., and Gidden, M.: Managing Overshoot Through Collective Carbon Debt Drawdown, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16344, https://doi.org/10.5194/egusphere-egu26-16344, 2026.

Post underground mining activities can trigger sinkholes that pose long-term risks to infrastructure, public safety, and the sustainable redevelopment of former coal and mining regions. Robust, scalable tools for estimating sinkhole geometry are therefore essential for post-mining risk management, land-use planning, and evidence-based remediation strategies. This study investigates the use of supervised machine learning methods to predict key sinkhole size parameters associated with abandoned underground workings. A multi-country European database was compiled, integrating sinkhole inventories with geological and mining attributes, including characteristics of underground excavations and overburden conditions. Several regression algorithms were trained and compared to estimate sinkhole geometry from available predictors, and model performance was evaluated using standard statistical metrics. To support interpretability and practical adoption, feature-importance analyses were performed to identify the most influential factors controlling predicted sinkhole dimensions. The results demonstrate the potential of data-driven modelling to enhance post-mining hazard assessment and to inform prioritization of monitoring, remediation, and safe land reuse, contributing to risk-aware, sustainable transition pathways in regions affected by underground mining.

How to cite: Szmigiel, A.: Machine Learning for post-mining ground stability: predicting sinkhole geometry to support risk management and land reuse, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17362, https://doi.org/10.5194/egusphere-egu26-17362, 2026.

Decommissioning lignite mines aligns with the EU’s climate goals of reducing greenhouse gas emissions by 55% by 2030 and achieving climate neutrality by 2050. A key strategy involves expanding renewable energy, which demands flexible and scalable storage to manage intermittency. Repurposing decommissioned open-pit lignite mines into Pumped Hydropower Storage (PHS) facilities offers a promising solution, enhancing energy security while supporting regional economic transformation. Over the next two decades, numerous EU lignite mines are scheduled for closure between 2038 and 2045, presenting a unique opportunity for sustainable redevelopment.

While prior research has largely focused on conventional reservoirs, the potential of repurposing abandoned mines for PHS remains underexplored. This study fills that gap by evaluating over 140 closed or soon-to-be-closed open-pit lignite mines across the EU. It identifies 50 sites as technically feasible for PHS development, based on topography, hydrology, and grid connectivity. Two operational scenarios were analyzed: short-term load balancing and long-term seasonal storage.

In the load-balancing scenario - optimised for grid stability and peak demand response - the 50 sites could deliver up to 9.6 GW of power capacity and 117 GWh of energy storage. This represents 21% of the EU’s current PHS capacity and would increase total capacity by 45%, significantly boosting grid flexibility. In contrast, the seasonal storage scenario prioritizes long-duration energy storage, yielding 5.4 GW of power (12% of current EU PHS capacity) but a substantial 13 TWh of storage - 4,860% more than existing levels. This vast storage potential could help overcome seasonal mismatches between renewable supply and demand, particularly in solar- and wind-rich regions.

These findings underscore the transformative potential of repurposing lignite mines into PHS facilities. By leveraging existing geological features and infrastructure, such projects can reduce development costs and environmental impact compared to greenfield constructions. Moreover, they support just transition initiatives by revitalizing post-mining regions through clean energy investment, job creation, and industrial diversification. The integration of PHS into the energy system enhances renewable energy utilization, reduces reliance on fossil fuels, and strengthens energy independence - key pillars of the EU Green Deal. As the bloc accelerates its clean energy transition, closed lignite mines emerge as strategic assets for utility-scale storage. With careful planning and policy support, these sites can play a pivotal role in building a resilient, low-carbon energy future, directly contributing to climate targets and long-term energy security across Europe.

References
Ernst, P., Kempka, T. Pumped hydropower storage in closed open-pit lignite mines can provide substantial contributions to the European energy transition. Journal of Sustainable Energy and Assessments, in review.

How to cite: Kempka, T. and Ernst, P.: Repurposing decommissioned lignite mines for pumped hydropower storage: a key enabler of EU renewable integration and climate goals, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17423, https://doi.org/10.5194/egusphere-egu26-17423, 2026.

The transition from fossil fuels to renewable energy sources has created an urgent demand for large-scale energy storage. Repurposing unused mining infrastructure for Adiabatic Compressed Air Energy Storage (A-CAES) presents a promising solution. However, a critical research gap remains in optimizing the Thermal Energy Storage (TES) component: specifically, the lack of experimental data comparing the thermal efficiency of low-cost, circular economy materials against traditional natural rocks used specifically to store heat.

The primary aim of this study was to design a physical TES model to experimentally evaluate and compare the heat transfer dynamics of two distinct storage media: irregular  rocks of pure basalt and regular spherical beds made of a cement-waste mixture.

The research methodology involved the construction of a small scale physical model featuring dual vertical chambers powered by active fan heating systems. One chamber contained the randomly packed basalt, while the other contained arranged in an ordered manner, cement-waste spheres. This setup allowed for a precise, comparative analysis of heat distribution, airflow resistance, and thermal saturation speeds. Data was acquired in real-time using a custom Arduino-based sensor array.

To rigorously analyze the thermal charging cycles, a novel analytical methodology was developed using Matlab. Unlike standard linear approximations, this study implemented an algorithm based on the sigmoid function to model the temperature increment. This approach provided a superior fit to the non-linear thermal saturation data, allowing for more accurate characterization of the bed's performance.

The results provide critical insights into the viability of using mining waste for thermal energy storage by demonstrating the aerodynamic and thermal advantages of ordered bed geometries.

Keywords: A-CAES, Thermal Energy Storage, mining waste, heat transfer sigmoid function

How to cite: Korpak, W., Snarski, O., Lutyński, M., and Kołodziej, K.: Experimental comparative analysis of thermal energy storage beds using sigmoid function approximation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18372, https://doi.org/10.5194/egusphere-egu26-18372, 2026.

How to cite: Snarski, O., Korpak, W., Kołodziej, K., and Lutyński, M.: Innovative, wireless system for autonomous monitoring of concentration of gases emitted from decommissioned mine shafts, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18509, https://doi.org/10.5194/egusphere-egu26-18509, 2026.

Pumped Hydropower Storages (PHS) in former open-pit lignite mines offer significant potential for large-scale energy storage, supporting Europe’s energy transition. The reuse concept draws on proven, efficient technology that synergises economically with the subsequent use of former mines and transport infrastructure, local energy storage needs, and favourable ecological site conditions. While such projects must demonstrate economic and technical feasibility, their environmental compatibility is equally critical. This study presents conclusions of the first comprehensive modelling assessment of the hydrochemical implications associated with PHS operations in these settings. By combining a newly developed generic reaction path modelling framework with geochemical and hydrochemical data from two European lignite mines, we derive general insights into the evolution of pH, sulfate, and iron concentrations over a potential PHS operational period. Heterogeneities in internal mine dump sediments are analysed via reactive transport simulations since these emerge as important source for potential water contamination.

Results show that the direct hydrochemical impact of PHS operation is generally negligible compared to the influence of local geochemical and hydrological conditions. As in conventional mine flooding, the key drivers of hydrochemistry are the extent of pyrite oxidation in mine dump sediments and the availability of acid-neutralising minerals, such as calcite. The degree of acidification and sulfate release depends primarily on oxygen availability in the sediments and the amount of oxidised pyrite. The importance of site-specific analysis is underlined by field data since the water balance of surface run-off and groundwater dominated systems fundamentally differ, affecting the responsiveness of the hydrochemical system. If the flooded open-pit mine includes an internal mine dump, the dump’s internal structure is important for quantifying the timing and quantity of solute outflux as the sediments are the main source of pyrite oxidation products in the system.

In conclusion, a detailed, site-specific analysis of geochemical and hydrochemical conditions is essential for planning PHS projects in former open-pit lignite mines. While the PHS infrastructure itself is unlikely to substantially alter water chemistry in most scenarios, pre-existing site conditions may lead to environmental or economic challenges during operation.

Literature

Schnepper, T., Kühn, M. and Kempka, T. (2025a): Reaction Path Modeling of Water Pollution Implications of Pumped Hydropower Storage in Closed Open-pit Lignite Mines. Mine Water and the Environment, 44, 107-121. DOI: 10.1007/s10230-025-01039-y

Schnepper, T., Kapusta, K., Strugała-Wilczek, A., Roumpos, C., Louloudis, G., Mertiri, E., Pyrgaki, K., Darmosz, J., Orkisz, D., Najgebauer, D., Kowalczyk, D. and Kempka, T. (2025b): Potential hydrochemical impacts of pumped hydropower storage operation in two European coal regions in transition: the Szczerców-Bełchatów mining complex, Poland, and the Kardia Mine, Greece. Environmental Earth Sciences, 84, 9, 247. DOI: 10.1007/s12665-025-12198-0

Schnepper, T., Kühn, M. and Kempka, T. (2025c): Effects of Permeability and Pyrite Distribution Heterogeneity on Pyrite Oxidation in Flooded Lignite Mine Dumps. Water, 17, 21, 3157. DOI: 10.3390/w17213157

How to cite: Schnepper, T., Kühn, M., and Kempka, T.: Hydrogeochemical implications of pumped hydropower storage in former open-pit lignite mines: conclusions of comprehensive modelling studies, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18832, https://doi.org/10.5194/egusphere-egu26-18832, 2026.

Former lignite mining regions across Europe present not only significant environmental challenges but also unique opportunities for climate-positive land use. These areas are often degraded due to soil compaction, contamination, altered hydrology, and landscape disruption. However, they also offer lands suitable for agricultural reclamation in terms of carbon farming and biomass production. The COFA project (From Coal to Farm) aims to promote evidence-based land management decisions, contributing to the just transition of former lignite-dependent regions. It promotes climate mitigation, renewable energy generation (biomass), and sustainable development.

Our study develops a multi-criteria framework to assess the suitability of reclaimed lignite mining sites for energy crops and carbon farming, integrating multiple environmental factors. Key factors considered include terrain morphology, area, soil quality and degradation type, hydrological conditions, neighbouring land-uses, proximity to biomass power plants and the potential for alternative land uses such as food production, PV installations, or natural succession. The framework aims to identify sites where energy crops and carbon farming can be environmentally viable and socio-economically beneficial. Our research demonstrates how multi-criteria assessments can support the transformation of post mining regions into productive, climate-positive areas. It aligns with the objectives of the European Green Deal and broader sustainable redevelopment goals.

How to cite: Maksymowicz, M., Musałek, M., Merenda, B., Pierzchała, Ł., and Tichá, L.: Energy Crops and Carbon Farming on Reclaimed Lignite Mining Sites: A Multi-Criteria Suitability Assessment for Climate-Positive Land Use as part of COFA Project, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19212, https://doi.org/10.5194/egusphere-egu26-19212, 2026.

Achieving net zero greenhouse gas emissions has become a dominant framework for climate action, with regions, countries and corporations all pledging to reach net zero by around mid-century. However, some net zero pledges rely heavily on carbon capture and storage (CCS) and carbon dioxide removal (CDR) to compensate for continued fossil fuel combustion, rather than eliminating fossil fuels entirely. This approach presents significant risks, as CCS faces fundamental technological and geophysical limitations, while available CDR capacity must be prioritized for temperature reduction rather than enabling continued fossil fuel emissions.

This study introduces the concept of "real zero"—the complete elimination of fossil fuels through replacement with zero-carbon alternatives—and assesses its technical feasibility across five critical sectors: road freight, steel production, international shipping, power generation, and light-duty vehicles. We analyse two complementary lines of evidence: (1) deep decarbonization pathways from global integrated assessment models, and (2) sector-specific bottom-up modelling and industry roadmaps.

Our analysis demonstrates that real zero is achievable in leading regions during the 2040s in many key sectors. The power sector shows the earliest dates of real zero, with multiple IAM frameworks achieving real zero by the late 2030s to early 2040s through solar and wind deployment. For trucking, real zero could be reached as early as 2040 in Europe, driven primarily by battery electric vehicles which offer superior economics and efficiency compared to alternatives. Light-duty vehicles follow a similar trajectory, with electrification enabling real zero by the early 2040s.

Steel production presents greater divergence between our lines of evidence, with the earliest IAM scenarios reaching real zero by 2040 in some regions, though broader literature suggests the 2050s as a more conservative target. A real-zero pathway here relies on expanding secondary steel production via electric arc furnaces and deploying hydrogen-based direct reduction for primary production. International shipping can achieve real zero by 2050, with ammonia emerging as the most viable zero-carbon fuel, complemented by direct electrification for shorter routes.

Beyond these findings, we will outline key parameters for an expanded research agenda on real zero, to help facilitate a community discussion on the analysis required to further interrogate the assumptions behind net zero targets.

How to cite: Grant, N., Khan, Z., Tsekeris, D., Cerny, C., Petroni, M., Getachew, H., and Bhaskar, A.: Real Zero: Assessing the feasibility of a fossil free energy system by mid-century, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19644, https://doi.org/10.5194/egusphere-egu26-19644, 2026.

In many countries the support for “Net Zero” as a political goal is waning. Yet net zero emission targets remain essential in a geophysical sense to slow and ultimately halt future temperature increases.  Future emission pathways that are aligned with the Paris Agreement objectives typically reach net-zero carbon dioxide emissions by the middle of this century. They often go further and reach net-zero or net-negative greenhouse gas emissions later this century. Such scenarios comprise global gross emission reductions and carbon dioxide removals, via nature-based and or technological options. 

This work examines the changing political context around net zero and the need for a refreshed framing.  From a literature review, we have developed a set of principals for generating and evaluating future emission pathways based on their ability to limit the risks from future global warming  and limiting the risks of delivering successful emission mitigation. We discuss the necessity to preserve natural carbon sinks, and the need to consider intergenerational, regional and in-country equity and the perception of fairness.

Rapid phaseout of fossil fuel production and use emerges as a robust characteristic of the least risky Paris-Agreement aligned scenarios. We term these Real Zero scenarios and show that in such scenarios global progress can be accelerated with a greater focus on policy, technology and efficiency innovation to drive near term action.

How to cite: Forster, P. M., Pelz, S., and Barley, S.: Exploring Real Zero definitions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20394, https://doi.org/10.5194/egusphere-egu26-20394, 2026.

Repurposing decommissioned mine shafts into energy storage systems (e.g., Compressed Air Energy Storage or pumped-storage hydroelectric plants) requires verifying their integrity under reversed stress state conditions. Given the lack of analytical solutions in the literature dedicated to assessing rigid linings subjected to high internal pressure, this study addresses this research gap .

The objective was to construct a mathematical model based on the Kirsch solution for elastic media and the modified Coulomb-Mohr criterion, incorporating thermal loads. The model was implemented in the proprietary computational tool PRESS-SHAFT.

Verification of the model on a real-case scenario led to conclusions that are counter-intuitive in light of classical mining geomechanics. It was demonstrated that the critical weak link of the structure subjected to pressures up to 8 MPa (the maximum expected value for such facilities) is not the deepest section, but the near-surface zone (0–80 m) . In this area, due to low lithostatic stresses, there is a risk of stability loss via hydraulic fracturing .

Regarding the deep sections of the shaft, the model confirmed general stability at maximum pressure but identified a potential risk of shear failure under unfavorable conditions during the storage discharge cycle (internal pressure drop). Ultimately, it was shown that with the application of reinforcements in the shallow zone, the shaft adaptation is technically safe.

How to cite: Kołodziej, K., Lutyński, M., and Smolnik, G.: Development of an Analytical Model and Computational Tool for Geomechanical Stability Assessment of Mine Shafts Adapted as Energy Storage Reservoirs, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20643, https://doi.org/10.5194/egusphere-egu26-20643, 2026.

Integrated Assessment Models (IAMs) are critical for mapping mitigation strategies. However, their energy demand projections are often constrained by reliance on deterministic, exogenous methods that often overlook the complexity of demand-side responses to fluctuations in the economy, climate, or the energy system itself.  While some process-based IAMs have replaced GDP-linked projections with endogenous cost-optimization or discrete-choice frameworks, they fail to fully couple these demand-side variables with wider system feedbacks, such as human behaviour related dynamics.

This study uses the FRIDA model, an IAM that introduces a comprehensive internal framework for behavioural change, replacing exogenous parameters or assumptions with a structure that simulates decision-making dynamics in the demand for resources and/or end services, leveraging the existing structure for livestock products demand in FRIDA.

The primary contribution of this work is the shift to a fully closed integration of behaviour-driven sectoral energy demand, specifically for transportation demand, reducing reliance on locked-in demand projections, and significantly improving the interconnectedness between economic, climate and energy sections of the model itself.

This implementation expands the existing behavioural change modelling framework in FRIDA, and internalizes energy demand by linking behavioural responses to sector-specific dynamics and systemic feedbacks. The model internalises climate-driven factors, such as the health risks posed by particulate emissions, the composition of the energy mix in production, and the energy carriers in demand, which dynamically drive or constrain energy demand. This structure, demonstrated with the transport sector, can then be replicated across other energy sectors in FRIDA to capture the fundamental dynamics that drive the behaviour determinants of demand.

This work is supported by FCT, I.P./MCTES through national funds (PIDDAC): LA/P/0068/2020 - https://doi.org/10.54499/LA/P/0068/2020 , UID/50019/2025, https://doi.org/10.54499/UID/PRR/50019/2025, UID/PRR2/50019/2025. This work has also received funding from the European Union’s Horizon 2.5 – Climate Energy and Mobility programme under grant agreement No. 101081661 through the 'WorldTrans – TRANSPARENT ASSESSMENTS FOR REAL PEOPLE' project.

How to cite: Mahú, F., Schoenberg, W., K. Rajah, J., Blanz, B., Wells, C., and C. Köberle, A.: An Endogenous Behaviour-Driven Approach for Sectorized Energy Demand in an Integrated Assessment Model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21045, https://doi.org/10.5194/egusphere-egu26-21045, 2026.

Extreme weather events are growing more severe due to climate change. These events impact energy supplies from both renewable and fossil fuel sources. They also affect pathways to carbon neutrality by altering carbon emissions. This study examines how extreme weather shapes China’s energy system and carbon emissions. Using daily carbon emission data from China spanning 1990–2025, combined with multiple future climate scenarios (SSP pathways). A data-driven machine learning approach quantifies the role of extreme temperatures in raising the carbon intensity of the energy system and increasing its dependence on fossil fuels. Our results show that extreme high- and low-temperature events disrupt the energy system. They increase the carbon intensity of energy production, heighten reliance on fossil fuels, and reduce the actual efficiency of renewable energy generation. Simultaneously, we also find that provinces with a larger share of renewable energy tend to have energy systems that are more sensitive to extreme temperatures. Climate simulations indicate that under the SSP1-2.6 pathway, China is projected to achieve carbon neutrality around 2062 with a regional average warming of approximately 2°C, most pronounced in the northwest. Compared to higher-emission scenarios (SSP2-4.5 and SSP5-8.5), achieving carbon neutrality helps mitigate climate change and slows the intensification of extreme warming across most of China. The study concludes that while China's “dual carbon” goals are essential for long-term climate risk reduction, the ongoing energy transition must seriously address the immediate impacts of extreme weather on renewable energy systems. These findings offer a scientific basis for planning a reliable energy system that supports China’s carbon neutrality objectives.

How to cite: Yu, Y.: Assessment of China's Energy-Carbon Emission System Under Extreme Climate Conditions in the Context of Carbon Neutrality, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21324, https://doi.org/10.5194/egusphere-egu26-21324, 2026.

Balancing climate mitigation with development priorities poses a significant challenge for developing economies where climate action must be pursued alongside economic growth, energy access and tackling poverty. In Pakistan, the challenge gets compounded when national climate commitments rely on an optimistic growth trajectory for projecting baseline assumptions. This in result, risks the accurate assessment of mitigation ambition and policy needs. NDC baseline emissions are anchored to GDP growth of ~9%, while realized growth has averaged closer to ~4% over the last decade. Using MESSAGEix-Pakistan, a national integrated assessment model, we estimate business as usual assumptions to be about 50% lesser.  This gap results in inflated projected baseline emissions, making reported mitigation appear larger even when it reflects slower economic activity rather than policy-driven structural change.

To more structurally evaluate different dimensions of economy, we developed three scenario narratives in line with current NDC assumptions and Shared Socio-economic Pathways (SSPs 1,2 & 5). For each, we first develop a current-measures scenario reflecting existing policies and then assess three mitigation benchmarks using fair share principles (ability-to-pay and equal-cumulative-per-capita) and a low-emissions pathway (LE). The range between ability-to-pay (AP) and equal-cumulative-per-capita (ECPC) defines defensible unconditional commitments; the gap between this range and the low-emissions pathway quantifies the case for conditional support.

Across scenarios, the model identifies consistent transition patterns including rapid electrification of buildings sector and phase out of traditional biomass for cooking under all pathways. While transport and industry remain challenging to decarbonize. In industry, coal phases out by 2060 under all emission-reduction scenarios (ECPC, AP, LE) and is replaced by gas and hydrogen. In the power sector, solar becomes the dominant technology by 2060 under AP and LE pathways, with wind as a complementary pillar. More ambitious mitigation pathways require substantially higher investment levels, particularly in the power sector, where achieving a low-emissions pathway entails nearly double the investment compared to equity-based pathways, highlighting the scale of international support needed to enable deeper emissions reductions.

Overall, the analysis demonstrates how integrated assessment modelling can be used to identify credible emissions baselines, quantify the space between feasible, fair, and conditional mitigation pathways, and link climate ambition with development constraints. These insights support the design of climate strategies that balance mitigation goals with development priorities, while anchoring long-term transitions in feasibility, equity, and transparent investment needs.

How to cite: Yaseen, A., Awais, M., and Manzoor, T.: Balancing Climate Mitigation Goals with Development: Insights from Pakistan, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21598, https://doi.org/10.5194/egusphere-egu26-21598, 2026.

The European Green Deal requires coal-dependent regions to undergo a rapid yet socially balanced transition toward climate neutrality. In countries such as Greece, Poland, and Germany, the phase-out of lignite has created pressing challenges related to energy security, economic restructuring, and social cohesion. At the same time, these regions host extensive legacy energy infrastructures and strong institutional experience, offering unique opportunities for sustainable redevelopment through decentralised and digitally enabled energy systems.

This paper explores how digitally supported energy communities can act as a key mechanism for supporting the just transition of former coal regions, bridging policy frameworks with advanced digital solutions. Based on the FlexBIT project, this study combines a comparative regulatory analysis of selected EU Member States with a focus on interoperability, data governance, and cybersecurity requirements for energy communities, alongside the design of digital platforms that enable flexibility services, energy sharing, and local energy market participation.

The analysis highlights that while EU legislation, particularly RED II/III, the Electricity Market Directive, the Data Act, and NIS2, provides a strong enabling framework, national implementation gaps and fragmented digital infrastructures remain critical barriers. In Greece, regulatory complexity, uneven digital readiness, and limited access to interoperable platforms constrain the ability of communities to fully exploit local renewable generation, storage, and flexibility potential.

The paper demonstrates how interoperable digital platforms, combining real-time data exchange, AI-based flexibility optimisation, and secure governance models, can repurpose existing energy infrastructures and empower local actors, including municipalities, SMEs, and citizens. By aligning regulatory compliance with digital innovation, energy communities can contribute to grid resilience, energy affordability, and social inclusion, transforming former lignite regions into hubs of clean energy innovation.

Overall, the study positions digitally enabled energy communities as a scalable and replicable pathway for integrating policy objectives, technological solutions, and social equity within the just transition of coal regions in Greece and across Europe.

How to cite: Karatrantou, C., Koukouzas, N., Tyrologou, P., Zizzo, G., Lombardi, P. A., Papadaskalopoulos, D., Sikorski, T., Janik, P., Micallef, A., and Kott, M.: Re-imagining Post-Coal Regions through Digital Energy Communities: Bridging Policy, Interoperability and Just Transition Goals, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22020, https://doi.org/10.5194/egusphere-egu26-22020, 2026.

Europe has mainly focused on large-scale wind and solar projects. However, an abundant renewable energy resource remains untapped within the existing water infrastructure. The continuously flowing energy through the drinking-water pipelines, irrigation canals, and wastewater systems has not been noticed. Yet, tapping into this hidden hydropower is crucial for building a decentralized, carbon-neutral future.

This research assessed Europe’s potential for hidden hydropower through comprehensive technical analyses. For open-channel and natural systems, GIS-based modelling combined with custom Python algorithms mapped and measured the available resource. Within pressurized pipelines, we focused on Pump as Turbine (PaT) technology, demonstrating how to retrofit existing infrastructure for energy recovery.

To complement these large-scale recovery approaches, dedicated hydropower models were developed to estimate the potential of piezoelectric energy harvesting. These models investigate how micro- and nano-hydropower can exploit flow-induced vibrations to supply power for distributed sensor networks. The results show that there is a wealth of untapped power across Europe, underscoring the viability of low-impact and cost-effective micro-hydropower (MHP) technologies. By integrating these energy solutions with smart sensors and real-time monitoring, this research contributes to the development of a more efficient, resilient, and interconnected "energy-water networks" in Europe.

Keywords: Hidden Micro-Hydropower (MHP); Energy Harvesting; GIS-Based Modelling; Water Infrastructure; Piezoelectric Energy Harvesting (PEH), Pump as Turbine (PaT).

How to cite: Emamian Verdi, M., Gezer, D., Karaagac, U.,  Guðlaugsson, B., and Christian Finger, D.: Assessment of Pan-European Potential for Hidden Micro-Hydropower (MHP) and Energy Harvesting in Water Infrastructure , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22943, https://doi.org/10.5194/egusphere-egu26-22943, 2026.

Methane (CH₄) emissions from livestock production remain one of the largest and most uncertain components of national greenhouse gas inventories, largely because direct measurements at operational facilities are limited. This measurement gap constrains the accuracy of agricultural CH₄ estimates and the development of effective mitigation strategies. Strengthening the empirical basis for these inventories is therefore essential. Emerging close-range tools, such as uncrewed aerial vehicle (UAV) plume-sampling systems, can enhance monitoring, reporting, and verification (MRV) by providing high-resolution, facility-level observations.

To evaluate this approach, this study conducted a five-day field campaign at a commercial cattle feedlot in southern Alberta, Canada, housing approximately 28,000 cattle. UAV plume sampling was deployed alongside continuous CH₄ measurements from an open-path laser (OPL) to estimate CH₄ emission rate downwind of the facility. For both techniques, emission rates were derived using inverse dispersion modeling, for a direct comparison of performance and assessing the extent to which UAV-based sampling can complement established ground-based flux measurements.

Uncrewed aerial vehicle-derived CH₄ emission rates varied from 149 to 392 g head^-1 day^-1 (mean ± SE: 280 ± 22), in near-perfect agreement with OPL-derived emissions of 152-438 g head^-1 day^-1 (280 ± 22). Daily mean emissions differed by only 0.08% during overlapping sampling periods, and statistical distributions were highly consistent across methods. Hour-to-hour variability reflected transient atmospheric dynamics and associated changes in plume dispersion, rather than methodological bias. UAV flights also revealed spatial plume gradients not captured by the fixed OPL geometry, and consistent hourly emission estimates were found when UAV flights collected at least four usable plume samples per hour. Performance declined under very low-wind or highly turbulent conditions, clarifying key operational constraints for future deployments.

Overall, these findings demonstrate that UAV-based plume sampling can provide CH₄ emission estimates consistent with established ground-based systems, providing a validated pathway for quantifying emissions from commercial feedlots. The approach aligns with the Integrated Global Greenhouse Gas Information System (IG3IS) good-practice principles and provides empirical information that can improve IPCC Tier 2 emission factors for open-lot beef operations.

How to cite: Dash, S. S., Coates, T. W., and Madramootoo, C. A.: High-resolution measurement-based methane quantification from beef cattle feedlots to improve agricultural GHG inventories, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-671, https://doi.org/10.5194/egusphere-egu26-671, 2026.

Hydrofluorocarbons (HFCs) are used as refrigerants, propellants or insulating foams. They don’t deplete the ozone layer like their predecessors, (hydro)chlorofluorocarbons ((H)CFCs). However, HFCs are still potent greenhouse gases and are regulated under the Kyoto Protocol (1997) and, more recently, the Kigali Amendment to the Montreal Protocol. The Kigali amendment targets reductions in HFC production and consumption over the coming decades.^{1, 2} Observing halogenated substances in the atmosphere provides an independent means to verify compliance with these international treaties. From these observations, regional and global emission estimates can be obtained by combining them with atmospheric modelling or using a reference tracer with known emissions.^{3, 4} Due to rapid industrialization and high demand for refrigeration and air conditioning, the eastern Asian region contributes significantly to global HFC emissions. Therefore, it is crucial to understand the emission patterns in this region to assess global compliance.

We have conducted a large-scale controlled-release tracer experiment to estimate regional halocarbon emissions of the greater Seoul metropolitan area (South Korea). Ethyl fluoride (HFC-161)⁵ and hexafluorobutane (HFO-1336mzzE), which are virtually absent in the background atmosphere, were released at one location in the City of Seoul. Release times were selected to align with favorable meteorological conditions that allowed air masses to reach the AGAGE station Gosan (Jeju Island, 490 km south of Seoul). The site is equipped with an instrument for in-situ halocarbon measurements. Intermediately located along the path of air mass transport, sites at the Global Atmosphere Watch (GAW) Observatory Anmyeondo and Mokpo National University (138 km and 320 km from Seoul, respectively) were used for additional flask sampling. The atmospheric transport model FLEXPART⁶ was used to forecast the tracer plume's trajectory and dispersion, and the release and sampling times were adjusted accordingly.

During two releases in November 2024 and April 2025, both tracers were detected at the flask sampling sites Anmyeondo GAW Observatory and Mokpo National University, as well as at Gosan station. The measurements show a strong correlation of our tracer substances with various HFCs. Preliminary emission estimates for the greater Seoul metropolitan area are derived using the tracer ratio method, and its limitations are discussed. Finally, a comparison to a full regional inversion, based on the continuous observations at Gosan, is conducted.

References

[1] Kyoto Protocol to the United Nations Framework Convention on Climate Change. adopted on December 11th, 1997; Kyoto, 1998, 1-22.

[2] Kigali Amendment to the Montreal Protocol on Substances that Deplete the Ozone Layer. adopted on October 15th, 2016; United Nations, Kigali.

[3] Matt Rigby, Sunyoung Park, Takuya Saito, Luke M. Western, Alison L. Redington, et al., Nature, 2019, 569 (7757), 546-550.

[4] Peter G. Simmonds, Matthew Rigby, Alistair J. Manning, Sunyoung Park, Kieran M. Stanley, et al., Atmospheric Chemistry and Physics 2020, 20 (12), 7271-7290.

[5] Dominique Rust, Martin K. Vollmer, Stephan Henne, Arnoud Frumau, Pim van den Bulk, et al., Nature, 2024, 633, 96-100.

[6] Ignacio Pisso, Espen Sollum, Henrik Grythe, Nina I. Kristiansen, Massimo Cassiani, et al., Geoscientific Model Development, 2019, 12 (12), 4955-4997.

How to cite: Müller, M. J., Vollmer, M. K., Henne, S., Yun, J., Choi, H., Park, S., Emmenegger, L., and Reimann, S.: Investigating Regional Halocarbon Emissions: The Seoul Tracer Release Experiment, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2527, https://doi.org/10.5194/egusphere-egu26-2527, 2026.

Bamboo, a perennial grass species, exhibits rapid growth rates surpassing many native trees, offering substantial potential for atmospheric carbon capture and subsequent sequestration into durable products. Despite this promise, the carbon sequestration capacity of bamboo forests and its variability under different land management practices and environmental conditions remain underexplored. This study examines carbon sequestration in a representative bamboo forest in Anji, eastern China, employing a novel observation-based approach utilizing multiple atmospheric tracers (CO₂, CO, and ¹⁴C-CO₂) measurements to attribute fluxes accurately. The study also includes regular biomass inventory to be able to compare CO₂ fluxes between two approaches. Departing from conventional inventory-based estimates of carbon emissions and uptakes, observations-based method yields detailed insights into individual carbon-cycle processes within bamboo ecosystems and identifies the most effective tracers for quantifying regional CO₂ fluxes. Leveraging high-resolution atmospheric CO₂ observations, coupled with advanced modeling systems and analytical tools—including machine learning techniques to reconstruct and correct prior Net Ecosystem Exchange (NEE) fluxes for the bamboo forest—we derive carbon fluxes while accounting for variations in management strategies and environmental factors. These findings enhance our understanding of bamboo's role in global carbon mitigation, informing sustainable forestry practices and climate policy. This work highlights the transformative potential of tracer-based methodologies for precise, scalable carbon flux assessments in managed ecosystems.

The study is supported by the Quadrature Climate Foundation (Grant No. 01-21-000133).

How to cite: Fang, S., Tarasova, O., Li, Y., Turnbull, J., Lin, Y., Brailsford, G., and Mikaloff-Fletcher, S.: Unveiling Carbon Sequestration Dynamics in Bamboo Forests, China: An Observation-Based Approach Using Atmospheric Tracers, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2643, https://doi.org/10.5194/egusphere-egu26-2643, 2026.

Zurich aims for net-zero direct greenhouse gas emissions by 2040, a target supported by 75 % of voters. Progress is tracked through a detailed CO₂ inventory covering energy, transport, industry, and waste. Under the European ICOS Cities project, a monitoring program was launched using two approaches: (i) a network of mid- and low-cost CO₂ sensors combined with atmospheric inverse modeling, and (ii) CO₂ flux measurements from an eddy-covariance system on a city-center high-rise building, paired with footprint modeling.

Here, we focus on the mid-cost (ZiCOS-M) and low-cost (ZiCOS-L) NDIR (nondispersive infrared) CO₂ networks, which were both operational for at least 3 years since 2022.

ZiCOS-M consists of 26 monitoring sites, 21 in the city and 5 outside the urban area. Daily calibrations using two reference gas cylinders, and corrections of the sensors’ spectroscopic response to water vapour were performed. The hourly mean root mean squared error (RMSE) was 0.98 ppm (0.46 - 1.5 ppm) and the mean bias ranged between 0.72 and 0.66 ppm compared to parallel measurements with a high-precision reference gas analyser for a period of 2 weeks or more. CO₂ concentrations in the city were highly variable with site means ranging from 434 to 460 ppm, and Zurich’s mean urban CO₂ increment was 15.4 ppm above the regional background.

ZiCOS-L consists of 56 sites with paired sensors. The sensors require in-field training for model calibration before deployment and further post-processing steps to account for drift and outliers. After data processing, the hourly RMSE was 13.6±1.4 ppm, and the mean bias 0.75±1.67 ppm when validated against parallel reference measurements from ZiCOS-M. CO₂ concentrations were highly variable with site means in Zurich ranging from 438 to 465 ppm, reflecting mainly the influence of sources in the nearby surroundings. Vegetation (mainly grassland) amplified the morning concentration on average in summer by up to 20 ppm due to ecosystem respiration, while heavy traffic increased the morning rush hour concentration by 15 ppm. Despite its lower measurement accuracy, the ZiCOS-L network enables the study of concentration dynamics at a spatial and temporal scale that is not accessible by any other means.

The ZiCOS-M data was extensively used to derive top-down CO₂ emissions. Similar modelling activities are currently ongoing with the ZiCOS-L data, and both are compared to emissions derived from the eddy covariance system and to the city's emission inventory.

Grange SK, … Emmenegger L, The ZiCOS-M CO₂ sensor network: measurement performance and CO₂ variability across Zurich. https://doi.org/10.5194/acp-25-2781-2025.

Creman L, … Bernet L, The Zurich Low-cost CO₂ sensor network (ZiCOS-L): data processing, performance assessment and analysis of spatial and temporal CO₂ dynamics. https://doi.org/10.5194/egusphere-2025-3425

Brunner D, … Emmenegger L, Building-resolving simulations of anthropogenic and biospheric CO₂ in the city of Zurich with GRAMM/GRAL. https://doi.org/10.5194/acp-25-14279-2025.

Hilland R, … Christen A, Sectoral attribution of greenhouse gas and pollutant emissions using multi-species eddy covariance on a tall tower in Zurich, Switzerland. https://doi.org/10.5194/acp-25-14279-2025.

Ponomarev N, … Brunner D, Estimation of CO₂ fluxes in the cities of Zurich and Paris using the ICON-ART CTDAS inverse modelling framework. https://doi.org/10.5194/egusphere-2025-3668.

How to cite: Emmenegger, L., Creman, L., Fischer, A., Grange, S. K., Hüglin, C., Rubli, P., and Brunner, D.: Design, operation, and insights from Zurich’s mid- and low-cost ICOS Cities CO2 sensor network, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2748, https://doi.org/10.5194/egusphere-egu26-2748, 2026.

We use atmospheric inverse modelling to provide observation-based estimates of methane emissions at the national scale in Europe. We apply the numerical weather prediction model ICON-ART to obtain an ensemble of methane concentrations by varying the meteorology, the lateral boundary conditions and emission fields. By comparing to ground based observations of the ICOS network, we employ a 4D LETKF to assimilate both the concentrations and emissions concurrently. We create an ensemble of emissions in two ways: We can perturb the underlying emission field with a gaussian random field, or we can separate it into regions and economic sectors and scale these. We compare the two approaches and the resulting emission estimates to national greenhouse gas inventories and synthesis inversion results with a focus on Germany. The first results are presented for 2021 and we identify a considerable mismatch with the reported emissions in central Europe.

How to cite: Becker, N., Keil, N. H., Bruch, V., and Kaiser-Weiss, A.: Concurrent data assimilation of methane concentrations and fluxes , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2817, https://doi.org/10.5194/egusphere-egu26-2817, 2026.

Achieving effective greenhouse gases (GHGs) mitigation policy requires accurate quantification of contribution from each emission source based on in-situ measurements. In this study, we investigated the spatial distribution of CO₂ and CH₄ emitted from different emission sources by conducting mobile measurements using a GLA331-GGA analyzer (ABB–LGR Inc.) mounted on a vehicle. We conducted seven mobile measurements in spring (N = 3), summer (N = 2), and fall (N = 2) over Seoul Metropolitan Area (SMA) in 2025. By comparing the correlation between two GHGs from various emission sources, we selected representative sites including livestock facilities (cattle and swine barns), industrial complexes, urban, wastewater treatment plants, LNG power plants, rural areas. Background GHGs concentrations were defined as the daily 5th percentile for each measurement day, and correlations between enhancements (ΔCO₂ and ΔCH₄) were assessed. Along with real time measurements, stable carbon isotopes samplings were also conducted to provide complementary constraints on concentration variability and the contributions of end-member of each emission source. For stable isotope measurements, two ambient air samples were collected per site using canisters (Entech, Simi Valley, CA, USA) and analyzed with Picarro G2131-i for δ¹³C–CO₂ (δ¹³C) and Picarro G2132-i for δ¹³C–CH₄ (δ¹³CH₄). Strong co-variability between the two GHGs was observed at several emission sources and seasons, including springtime cattle barns (R = 0.75), LNG power plants (R = 0.83), industrial complexes (R = 0.74), and swine barns (R = 0.64); summertime cattle barns (R = 0.66) and LNG power plants (R = 0.67); and fall industrial complexes (R = 0.70) and cattle barns (R = 0.97). These correlations suggested that CO₂ and CH₄ were likely emitted concurrently from shared sources or similar emission activities in SMA region. The observed δ¹³C values ranged from −8.2‰ to −12.5‰, while δ¹³CH₄ ranged from −47.2‰ to −48.6‰. Seasonal mean δ¹³C values were −11.2‰ in spring, −9.2‰ in summer, and −10.1‰ in fall, consistent with a summertime influence from enhanced biospheric respiration, with the most depleted values occurring in spring. In contrast, δ¹³CH₄ exhibited relatively small seasonal variability, as indicated by the coefficient of variation (sd/mean; 0.004 in spring, 0.013 in summer, and 0.012 in fall), but still provided useful constraints on source attribution. In addition, a Bayesian isotope mixing model (the ‘simmr’ package in R) was applied to quantify relative source contributions indicating that coal combustion contributed most strongly to δ¹³C, whereas wastewater treatment and natural gas were the dominant contributors to δ¹³CH₄.

How to cite: Choi, H., Jun, J., Lee, S., Kim, S., and Choi, Y.: Characteristics of CO2 and CH4 from different emission sources using mobile measurements and stable carbon isotope analysis, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3366, https://doi.org/10.5194/egusphere-egu26-3366, 2026.

Observation based quantification of surface CO2 fluxes relies on the consistent integration of atmospheric observations with numerical transport models. We present the development and demonstration of an ensemble-based data assimilation system that couples atmospheric CO2 observations to the ICON-ART modeling framework using a Local Ensemble Transform Kalman Filter (LETKF).

Starting with a flux estimate provided by CarbonTracker Europe High-Resolution we start with a dynamic model with hourly resolution with a focus on fluxes in Europe for 2021. We then create an ensemble of perturbed prior fluxes within assumed uncertainties using prescribed spatial and temporal correlation structures. We simulate the transport of these ensemble members in ICON-ART in limited area mode, while varying the meteorological conditions to represent meteorological uncertainties. Subsequently, we use the LETKF to update the state vector of concentrations and CO2 fluxes daily, resulting in an posterior estimate of surface CO2 fluxes over Europe. 

This work provides the foundation for an ICON-ART-based CO2 flux assimilation system and establishes a technical basis for future extensions toward longer assimilation periods, refined error modeling, and the assimilation of anthropogenic emission signals.

How to cite: Böttcher, J., Becker, N., Kaiser-Weiss, A., and Harms, M.: Development of an Ensemble-Based Data-Assimilation System for CO2 Fluxes Using ICON-ART, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3437, https://doi.org/10.5194/egusphere-egu26-3437, 2026.

In this research, we propose a simple and effective method for gas analysis of semiconductor and display industries. To achieve this, residual gas analyzer (RGA) was adopted and two high-global warming potential (GWP) gases such as CF₄ and NF₃ commonly used in industrial application were focused. The experiment was conducted in four key steps: identifying gas species using optical emission spectroscopy (OES), calibrating RGA with a quadrupole mass spectrometer (QMS), constructing a five-point calibration graph to correlate RGA and Fourier-transform infrared spectroscopy (FT-IR) data, and estimating the concentration of unknown samples using the calibration graph. The results under plasma-on conditions demonstrated correlation and accuracy, confirming the reliability of our approach. In other words, the method effectively captured the relationship between RGA intensity and gas concentration, providing valuable insights into concentration trends. Thus, our approach serves as a useful tool for estimating gas concentrations and understanding the correlation between RGA intensity and gas composition.

Reference

[1] B. G. Jeong, S. H. Park, D. H. Goh, and B. J. Lee, Metrology 5 (2025) 60

How to cite: Jeong, B. G.: Real-Time Monitoring and Quantification of Fluorinated Greenhouse Gases in Semiconductor/Display Manufacturing, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4566, https://doi.org/10.5194/egusphere-egu26-4566, 2026.

The semiconductor and display industries are significant sources of fluorinated greenhouse gas (F-GHG) emissions in the electronics, making accurate emission estimation essential for addressing climate change. The Republic of Korea, a leading country in the semiconductor and display industries, requires precise evaluation of the environmental impact of these industries due to its global competitiveness. Currently, The Republic of Korea relies on default emission factors provided by the 2006 IPCC guidelines for estimating F-GHG emissions. However, this approach does not account for the latest mitigation technologies implemented in Republic of Korea, resulting in a conservative overestimation of actual F-GHG emissions. To address this issue, this study conducted direct measurements of F-GHG emissions from semiconductor manufacturing processes in facilities equipped with advanced mitigation technologies. By employing state-of-the-art measurement methods, the study evaluated the use rate of gas (U_i) and generation rate of by-product gas (B_byproduct, B_i) and compared the results with the default emission factors provided by IPCC G/L (2006 and 2019). Moreover, based on derived country-specific emission factors (Tier 3b), GHG emissions were estimated and compared with tier-based methodologies using 2006 and 2019 IPCC G/L default factors (Tier 2a, 2b, 2c and 3a). The finding highlights the need for developing country-specific emission factors and contribute to the establishment of precise, data-driven policies for reducing GHG emissions in Republic of Korea’s electronics industry. Furthermore, this research serves as valuable reference for other countries aiming to refine their emission estimates with country-specific data and technological advancements, ultimately contributing to global efforts towards carbon neutrality.

How to cite: Inkwon, J. and Bong-Jae, L.: Comparative Analysis of F-GHGs Emission Estimates between IPCC Default Factors and Measurement-based Korea-specific Emission Factors in Semiconductor Manufacturing, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4570, https://doi.org/10.5194/egusphere-egu26-4570, 2026.

Quantifying urban CO₂ emissions from space can be approached using different methodologies, including direct plume-based analyses, but combining satellite observations with atmospheric transport models requires the ability to realistically reproduce fine-scale spatial gradients over cities. Using the Grand Paris area as a testbed, we investigate the sensitivity of simulated near-surface CO₂ concentrations to urban physics parameterization and horizontal resolution within the WRF-Chem modeling framework coupled to a high-resolution fossil fuel emission inventory. At mesoscale resolution (900 m), a hierarchy of urban representations ranging from simulations without urban physics to multi-layer urban canopy models is evaluated, showing that the Building Energy Model (BEM) provides the most physically consistent simulation of surface energy fluxes, boundary-layer development, and near-surface CO₂ variability. Building on this configuration, we compare mesoscale simulations with Large-Eddy Simulation (LES) runs at 300 m and 100 m resolution. Model results are evaluated against dense urban CO₂ observations from the high-precision Picarro network, a complementary mid-cost sensor network from ICOS-Cities, and surface sensible and latent heat flux observations from the ICOS ETC Level-2 fluxes data product. An extensive urban observation network including wind lidars and ceilometers from Urbisphere project provides an exceptional constraint for the evaluation of boundary-layer structure and vertical mixing at fine scales. The LES simulations substantially enhance the representation of spatial heterogeneity and localized CO₂ enhancements associated with major emission sources, which are smoothed or underestimated at mesoscale resolution. However, increased resolution also amplifies sensitivity to local wind fields and emission inventory uncertainties. These results highlight that both urban physics and model resolution critically shape the ability of transport models to reproduce observed urban CO₂ gradients.

How to cite: Rafalimanana, A., Lauvaux, T., Abdallah, C., Chariot, M., Ramonet, M., Doc, J., Laurent, O., Lopez, M., Raznjevic, A., Krol, M., Järvi, L., David, L., Sanchez, O., Christen, A., Looschelders, D., Bignotti, L., Loubet, B., Grimmond, S., and Morrison, W.: Monitoring urban atmospheric CO2 plumes from space: sensitivity to urban physics and scale effects over Paris, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5198, https://doi.org/10.5194/egusphere-egu26-5198, 2026.

Methane (CH₄) is the second most important greenhouse gas after CO₂, and its emissions from the agricultural sector, particularly rice paddies and dairy farms, remain highly uncertain and challenging to quantify. While recent advancements in satellite technology, such as high spatial resolution instruments, have enabled the detection of methane sources from global to facility scales, agricultural emissions still pose challenges. These emissions are typically diffuse and area-like, making them less detectable by targeted satellites like GHGSat and EMIT, which are better suited for isolated point sources such as oil/gas facilities or landfills. Additionally, agricultural emissions exhibit significant spatiotemporal variability driven by climate conditions, water management practices in rice paddies, and differences in farm types.

In the AGATE project of ESA, we apply an improved divergence method to estimate monthly methane emissions using TROPOspheric Monitoring Instrument (TROPOMI) satellite observations at a 0.1° grid resolution. We focus on major agricultural regions, including the Po Valley in Italy, as well as India and Bangladesh, over the period 2019-2022. To better isolate agricultural emissions, we separate area-like sources (e.g., rice paddies) from isolated point sources. The locations of identified big emitters are cross-validated using bottom-up emission inventories and targeted satellite observations (e.g., EMIT, Carbon Mapper) to minimize the influence of non-agricultural sources. Furthermore, to better understand the seasonality of methane emissions, we analyze the correlations between methane emission variations and auxiliary datasets, such as rice paddy maps and ammonia emissions derived from satellites.

How to cite: Liu, M., van der A, R., van Weele, M., Ioannidis, E., Liu, R., Chen, Z., and Ding, J.: Quantifying Agricultural Methane Emissions Using Satellite Observations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5426, https://doi.org/10.5194/egusphere-egu26-5426, 2026.

In efforts to mitigate the effects of global climate change several prominent policies and guidelines which emphasize the importance of sustainable growth have been introduced in recent years. Examples include the 2019 European Green Deal, and the subsequent Clean Industrial Deal in 2025. A key aspect of these goals is the reduction of air pollutant emissions, particularly from fossil fuel combustion, without sacrificing economic growth. The Green Deal commits to an EU wide emission reduction of at least 55% by 2030, as compared to 1990 levels. Remote sensing offers many advantages for tracking progress towards reduction of pollutant emissions. In particular, the global coverage allows for analysis of regions which do not have sufficient ground-based measurement networks. This study presents a method of using spectral analysis with tropospheric NO₂ column density and the gross domestic product (GDP) to track and compare progress of the German federal states towards decoupling emissions from economic growth. Most studies evaluating economic decoupling focus on CO₂, or CO₂ equivalences. There is a current lack of studies which investigate other key combustion products. This study focuses on NO₂ as a proxy for emissions related to economic activity. NO₂ originates primarily from anthropogenic combustion sources, andhas a short tropospheric lifetime, making it suitable to represent localized fossil fuel emissions.  Measurements of NO₂ used in this study are obtained from the Ozone Monitoring Instrument (OMI) launched aboard the NASA Aura satellite in 2004. The application of spectral analysis techniques, such as the wavelet analysis, gives additional insight into temporal variability of NO₂, to better observe the path of decoupling for each region. Decoupling between GDP and NO₂ variability is observed for all regions of Germany in the period between the two most recent global economic recessions (the 2008 financial crisis, and the Covid-19 pandemic). Similar decreasing trends are observed for both the yearly average tropospheric column density and the calculated yearly variability. The variability obtained from the wavelet analysis shows greater sensitivity to changes in NO₂ emissions than the absolute tropospheric column density. Further regional differences such as the main economic sectors and types of emission regulations in place are discussed to contextualize the differences present in decoupling processes between the federal states. Overall, NO₂ variability is found to be a sensitive and effective indicator for tracking and comparing decoupling progress across different administrative regions.

How to cite: Remy, E., Engert, R., Werner, L., and Bittner, M.: Investigating Germany’s progress in decoupling air pollution emissions from economic activity using satellite-based measurements of NO₂., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5912, https://doi.org/10.5194/egusphere-egu26-5912, 2026.

Reliable and timely information on greenhouse gas (GHG) emissions is essential for evaluating mitigation policies and supporting data assimilation and verification modelling frameworks. In this contribution, we present the sPanisH EmissioN mOnitoring systeM for grEeNhouse gAses (PHENOMENA), a low-latency GHG modelling framework developed within the RESPIRE-CLIMATE Spanish national project, which received formal endorsement from the WMO-IG3IS initiative.

PHENOMENA provides harmonised daily and high spatial resolution (up to 1 km × 1 km) CO₂ and CH₄ emissions for the main combustion-related sectors, including electricity generation, manufacturing industry (cement and iron and steel), residential and commercial combustion, road transport, shipping and aviation. The system estimates CO₂ and CH₄ emissions by combining low latency activity data and fuel- and process-dependent emission factors through bottom-up and downscaling approaches. The data collected and pre-processed includes hourly near-real-time traffic counts from the national road network, hourly electricity production data reported by individual power plants, daily Copernicus ERA5-Land surface temperature, monthly industrial production statistics and AIS (Automatic Identification System) data, among others.

PHENOMENA produces multiple GHG emission products, including high resolution maps of daily emissions per sector, as well as daily summaries of emissions aggregated at different regional levels and for the main Spanish metropolitan regions. The emissions computed with PHENOMENA allows representing the intra-weekly and seasonal variability of GHG emissions as well as changes in their spatial patterns, which can be linked to specific policy, socioeconomic, and weather impacts.

The results produced with PHENOMENA are compared to official GHG emission inventories as well as to other state-of-the-art low latency GHG emission datasets, such as the ones produced by the CAMS Carbon Monitor initiative. Overall, these developments demonstrate the capability of PHENOMENA to deliver consistent, multisector and near-real-time GHG emission estimates, supporting national monitoring, policy evaluation and future verification and data-assimilation efforts.

How to cite: Legarreta, O., Castesana, P., Lombardich, I., Tena, C., Piñero-Megías, C., Viñas, A., Gehlen, J., Rizza, L., Pérez García-Pando, C., and Guevara Vilardel, M.: Low latency and high resolution GHG emission estimates to support monitoring and modelling activities in Spain, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7798, https://doi.org/10.5194/egusphere-egu26-7798, 2026.

As national and sub-national governments, companies, and communities plan methane mitigation action, there is a need for robust emissions tracking systems, especially for major sectors like waste where countries have made commitments to reduce emissions. Landfills are a major source of methane emissions in many jurisdictions spread across the world, so there is a need in the waste sector for monitoring frameworks that are applicable at scale but also provide facility-level insights to guide decision making. 

Given the complexity of landfill emissions both in terms of variability and underlying causes, models are a common tool used for planning and tracking landfill methane mitigation, but past studies show potential biases in models and inventories compared to observations. In this work, we bring together both process-level insights as provided in bottom-up models and our top-down observations from the Tanager-1 satellite by (1) improving the accuracy and consistency of satellite-derived annual average emission rates and (2) developing methodologies for reconciling the two unique datasets. The goal of this work is to use satellite methane observations to identify improved bottom-up model parameters, focusing on the modeling frameworks used by national and sub-national jurisdictions.

As a point source imaging satellite, Tanager-1 is well suited for tracking emissions at landfills as it provides facility-scale methane emissions data, but existing algorithms and workflows for creating the emissions data have been primarily validated based on controlled release experiments which mimic environments more similar to the oil and gas sector than landfills. We identify methods that are robust and best suited to landfills by performing sensitivity tests for our quantification methods, testing algorithms and parameters, and identifying causes of bias unique to landfill environments (e.g., albedo, topography). The next step is translating our Tanager-1 observations to annual averages. We present a new methodology for temporally averaging satellite observations that accounts for null detects through scene-specific probability of detection limits. Finally, we compare our annual average satellite-based emission estimates to bottom-up models typically used by jurisdictions for official reporting (e.g., IPCC, LandGEM, US GHGRP), focusing on select countries where there is sufficient spatiotemporal coverage with Tanager-1. We use statistical methods to adjust parameters in the bottom-up models to reconcile the model estimates with observed emissions, allowing region-specific model parameter adjustments to account for potential climatic and meteorological factors. Finally, we discuss the implications of our initial results in terms of improvements to official national reporting and compare to inverse modeling results.

How to cite: Scarpelli, T., Cusworth, D., Kim, J., O'Neill, K., Duren, R., and Howell, K.: Using point source imaging satellite observations to guide landfill methane model improvements at the national and sub-national scale, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7927, https://doi.org/10.5194/egusphere-egu26-7927, 2026.

ESG (Environmental, Social, Governance) reporting is essential for industry as it helps secure investment for companies’ development. While Scope 1 are direct emissions and Scope 2 are indirect emissions, most of the industrial players report Scope 2 emissions from the use of energy (electricity and gas): these are carbon emissions that are emitted in the power station that uses fossil fuels (oil, coal, gas, biomass, etc.), see [1].

Conventional way to report company’s carbon emissions of Scope 2 is to obtain electrical meter readings and multiply them by the average carbon intensity of the electric grid that supplies electricity. In the UK, such carbon factors were previously published (annually) by the Department for Environment, Food, and Rural Affairs (Defra), then more recently by the Department for Energy Security and Net Zero (DESNZ). These average annual factors are approximate, and actual fuel mix of the electrical grid varies within a few minutes, depending on the operating power generators.

In some cases, the annual carbon intensity may underestimate the actual intensity of the grid. This usually happens in Europe in winter, when a large number of gas-fuelled generators are active to provide sufficient heating, and at the same time wind conditions are placid, providing little of renewable energy. In other cases, when there is lots of wind-generated energy and less gas-generated energy (for example, on a windy summer day), the average carbon factor may overestimate actual carbon intensity of the grid.

In several case studies, we demonstrate that such discrepancies may reach 10-15% of the total carbon emissions, as they are presented in quarterly or annual ESG reports. The results suggest that the current way of reporting carbon emissions should be revised, so that actual state of the dynamical energy grid would be taken into account for improvement of ESG reporting. Subsequently, this will impact their ESG standing and potential investment, which is crucial for European business as well as for the correct accounting of the impact of European carbon emissions [2].

References

[1] Livina et al, International Journal of Metrology and Quality Engineering, in revision.

[2] Livina et al, in preparation.

How to cite: Stokes, L., Przydrozna, A., and Livina, V.: Validating environmental reporting of carbon emissions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8459, https://doi.org/10.5194/egusphere-egu26-8459, 2026.

Reducing methane (CH₄​) emissions through environmentally friendly agriculture, such as Alternate Wetting and Drying (AWD), is a critical strategy for climate change mitigation in rice production. To effectively implement and evaluate these mitigation measures, it is essential to monitor agricultural practices and environmental variables at a high spatial resolution. This study develops a standardized data-processing protocol, which leverages Google Earth Engine (GEE) to generate high-resolution remote sensing features necessary for quantifying CH_4​ emissions.

The protocol integrates multi-sensor satellite data to capture the spatio-temporal dynamics of sustainable rice farming. Central to this protocol is the use of Sentinel-1 Synthetic Aperture Radar (SAR) data to classify water management regimes, specifically distinguishing between continuous flooding (CF) and AWD at the pixel level. Additionally, Sentinel-2 optical imagery is processed to extract key vegetation indices (e.g., NDVI, GRVI) to monitor crop growth. To address environmental factors, coarse-resolution soil moisture data from SMAP is downscaled to resolution by incorporating Sentinel-2 and Digital Elevation Model (DEM) data.

By synthesizing these multi-sensor inputs, the protocol provides the necessary foundation for mapping methane emission hotspots and assessing the impact of environmentally friendly management practices. This high-resolution approach supports the design of region-specific mitigation strategies and the advancement of climate-smart agriculture.

As for future research plans, we will apply the constructed model with the field-measured validation data to the extensive rice paddies in southern Ibaraki Prefecture in Japan to estimate methane emissions on a pixel-by-pixel basis and create hotspot maps. This enables the upscaling of a single-point observation model to a broader area while reflecting regional characteristics. This methodology is expected to serve as a powerful tool for examining highly effective methane reduction measures (such as utilization under the J-Credit system) based on each region's agricultural practices and environmental conditions.

How to cite: Shoyama, K., Hirai, C., and Den, H.: Monitoring Environmentally Friendly Agriculture for Methane Emission Reduction: A High-Resolution Multi-Sensor Remote Sensing Protocol on Google Earth Engine, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8591, https://doi.org/10.5194/egusphere-egu26-8591, 2026.

Inverse modelling of CO₂ and CH₄ using atmospheric in-situ data relies on simulations of atmospheric transport that arederived from models used in numerical weather prediction. The relevant time scales for inversions range from hours to decades, which is far beyond the time scales of a few weeks for which NWP models are designed. The strong diurnal and seasonal variations in surface to atmosphere fluxes of CO₂ covary with atmospheric mixing in the boundary layer, as both are solar radiation driven. This way slight seasonal or diurnal biases in the representation of mixing can be amplified. In addition, different atmospheric models show differences in vertical mixing through turbulent mixing and through moist convection, and thus in the representation of vertical gradients in tracers, which results strong differences in flux estimates from inverse modelling. These facts have been known since several decades by now, but progress in addressing these issues has been slow. Within the atmospheric network of ICOS (Integrated Carbon Observation System) additional meteorological observations are available that provide information on atmospheric mixing heights. Also, IAGOS (In-service Aircraft for a Global Observing System) provides information on vertical gradients which can be related to mixing through turbulence and convection.

ITMS, the Integrated Greenhouse gas Monitoring system for Germany, is implemented in multiple development phases: a first phase with the development of a demonstrator system, followed by the second phase, the development of a first-generation system, and a third and last phase, the transfer to operations. With each phase lasting about four years, the project provides a medium-term framework that allows also addressing some of the longer lasting problems such as transport uncertainty. Within ITMS the CarboScope Regional inversion system (CSR) is used as a reference system for CO₂ and CH₄ inversions, but also as a testbed for model developments. The presentation will provide an overview of recent results obtained within ITMS. This includes evaluating vertical mixing by using additional meteorological profile data or mixing height information, using additional tracers in inversions such as Radon, and confronting vertical profiles from airborne observations with model equivalents. 

How to cite: Gerbig, C., Galkowski, M., Koch, F.-T., Danyeli, L., Maier, F., Munassar, S., Xu, Y., and Rödenbeck, C.: Transport model error in inverse modelling: Developments within the ITMS project, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9177, https://doi.org/10.5194/egusphere-egu26-9177, 2026.

Methane (CH₄) is a key short-lived climate forcer, yet robust monitoring of its anthropogenic sources remains limited by inconsistent national reporting and incomplete inventories, especially from coal mining. Global anthropogenic CH₄ emissions are about 369 million tonnes per year, of which coal mine methane (CMM) contributes roughly 40 million tonnes per year, which is comparable to emissions from the gas sector. In 2023 only 15% of coal production reported annual CMM emissions in national greenhouse gas inventories and this limits the scientific basis for monitoring and verification of progress towards the Global Methane Pledge and the Paris Climate Agreement.

We present Ember’s Coal Mine Methane Data Tracker as a new open, global, evidence based dataset for understanding CMM emissions, reporting quality and methane targets. The Data Tracker compiles and harmonises national greenhouse gas inventory submissions to the United Nations Framework Convention on Climate Change (UNFCCC). It integrates these data with historic coal production statistics from the US Energy Information Administration (EIA), International Energy Agency (IEA) coal production forecasts and independent emission estimates (IEA Methane Tracker, Global Energy Monitor (GEM) Global Coal Mine Tracker).

To reconstruct national emissions from 1990 onwards, we calculate country and year specific CH₄ emission intensities wherever both reported emissions and coal production exist. Emission intensity is defined as CH₄ emissions (in kilotonnes) per million tonnes of coal produced. This approach also enables consistent comparison of reported emissions across countries and over time.

We fill gaps in the intensity time series using values from neighbouring years so that each country has a continuous record. We then multiply these completed intensity series by observed production to estimate unreported emissions. Ember’s gap filled series indicates that global active CMM emissions exceeded 34 million tonnes in 2023, whereas official UNFCCC inventories reported only 4.62 million tonnes, less than 14% of the inferred total. For 2024, the latest compilation of submissions implies 34.5 million tonnes of reported CMM, with underreporting of up to 21.2 million tonnes when compared with independent datasets.

We introduce a quantitative confidence score from 0 to 6 for each country’s reported CMM emissions, combining recency of UNFCCC reporting, consistency with independent estimates from both top down and bottom up approaches, and methodological robustness. Applied to major producers, this score shows that most large coal producing countries fall in the low-to-moderate confidence range, with only a small number, such as Poland (score 5), achieving higher confidence in their reported CMM inventories. 

By providing a transparent, harmonised framework for CMM monitoring, we demonstrate that systematic underreporting pervades national inventories. This gap is driven by widespread reliance on low tier IPCC methods, with 86% of reported CMM emissions relying on emission factors rather than direct measurement. Our quantitative confidence score (ranging from 0 to 6) highlights this reliance, showing that low scoring countries correlate directly with significant underestimation. This evidence necessitates the need for transparent, measurement based Monitoring, Reporting and Verification (MRV) frameworks to establish the rigorous CH₄ accounting required by global climate commitments.

How to cite: Horner, R., Assan, S., and Liepa, A.: A global coal mine methane tracker to highlight inventory gaps and target mitigation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9574, https://doi.org/10.5194/egusphere-egu26-9574, 2026.

An urban greenhouse gas (GHG) monitoring network has been established in the Barcelona Metropolitan Area to support the evaluation of GHG mitigation strategies. The network currently consists of five measurement sites equipped with high-precision Picarro analysers providing continuous observations of carbon dioxide (CO₂) and methane (CH₄). These measurements, in combination with atmospheric modelling will be used to investigate spatial and temporal variability in urban GHG concentrations.

The five sites (Fabra, ICM, ICTA, IDAEA, and UPC-Agropolis) were strategically selected to represent a range of urban and peri-urban environments, including a natural forest, an urban coastal site, a traffic-influenced highway location on the outskirts of the city, an urban park embedded within a densely built area, and a peri-urban agricultural region. This configuration enables the assessment of how different landuse types and emission sources influence observed GHG mole fractions across the metropolitan area.

Hourly averaged CO₂ mole fractions show pronounced differences between sites. Lower values are observed at the forested Fabra site, while the ICTA site, located near a major highway, exhibits the highest mole fractions and the largest variability. These spatial contrasts are consistent with results from previous multi-site measurement campaigns in Barcelona, which indicated that densely urbanized, impermeable landscapes are associated with enhanced CO₂ concentrations compared to greener areas, particularly during morning hours dominated by traffic emissions.

Maintaining a continuous urban monitoring network is essential for capturing both spatial and temporal variability in GHG concentrations and for improving our understanding of urban atmospheric processes. Such observations are also critical for constraining and validating atmospheric models and for quantifying changes in emissions over time. Here, we present recent observations from the Barcelona Metropolitan Area GHG network and illustrate their application to the study of greenhouse gas variability in complex urban environments.

How to cite: Monteiro, V., Villalba Mendez, G., Luo, Q., and Curcoll Masanes, R.: Urban greenhouse gas monitoring across the Barcelona Metropolitan Area, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10112, https://doi.org/10.5194/egusphere-egu26-10112, 2026.

Sulfur hexafluoride (SF₆) is a highly potent greenhouse gas (GHG). Despite its high global warming potential (GWP), it continues to be produced and used in Germany. The reported emission estimates can be used to calculate expected concentrations at measurements sites. Within the PARIS (Process Attribution of Regional Emissions) project we used the operational numerical weather prediction model ICON (ICOsahedral Nonhydrostatic) and its extension module for aerosol and trace gases (ART) as an Eulerian forward model to calculate the expected mixing concentrations response of Germany's largest point source of SF₆. We compared the modelled concentration peaks that occur when the modelled plume crosses the measurement site of the Taunus observatory (TOB) with the respective observed signals (requiring background subtraction). The 4-year period of 2020-2023 was covered, and the uncertainty of the meteorological transport was estimated using a 20-member ensemble in our limited area model for Europe, which was run with a horizontal grid resolution of 6.5 km and 74 vertical levels.The model predicts well when peaks are measured but weWe found that most observed peaks at TOB are considerably higher than in the model, suggesting that prior emissions estimates were too low. 
This indicates that the independent, observation-based emission estimate of our ICON-ART based system is in the range of double-digit tons, which is considerably higher than the self-reported SF₆ emission estimate for this point source, also if the model uncertainties are taken into account. 

How to cite: Harms, M., Meixner, K., Schuck, T., Wagenhäuser, T., Alber, S., Stanley, K., Engel, A., Bruch, V., Rösch, T., Steil, M., and Kaiser-Weiss, A.: Forward modelling of SF6 with ICON-ART, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10768, https://doi.org/10.5194/egusphere-egu26-10768, 2026.

Estuaries are nitrous oxide (N₂O) emission hotspots and play an important role in the global N₂O budget. However, the large spatiotemporal variability of emission in complex estuary environments is challenging for large-scale monitoring and budget quantification. This study retrieved water environmental variables associated with N₂O cycling based on satellite imagery and developed a machine learning model for N₂O concentration estimations. The model was adopted in China’s Pearl River Estuary to assess spatiotemporal N₂O dynamics as well as annual total diffusive emissions between 2003 and 2022. Results showed significant variability in spatiotemporal N₂O concentrations and emissions. The annual total diffusive emission ranged from 0.76 to 1.09 Gg (0.95 Gg average) over the past two decades. Additionally, results showed significant seasonal variability with the highest contribution during spring (31 ± 3%) and lowest contribution during autumn (21 ± 1%). Meanwhile, emissions peaked at river outlets and decreased in an outward direction. Spatial hotspots contributed 43% of the total emission while covering 20% of the total area. Finally, SHapley Additive exPlanations (SHAP) was adopted, which showed that temperature and salinity, followed by dissolved inorganic nitrogen, were key input features influencing estuarine N₂O estimations. This study demonstrates the potential of remote sensing for the estimation of estuarine emission estimations.

How to cite: Fan, W. and Xu, Z.: Satellite-Based Estimation of Nitrous Oxide Concentration and Emission in a Large Estuary, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11447, https://doi.org/10.5194/egusphere-egu26-11447, 2026.

Measurement-based emission estimates derived from atmospheric observations provide an independent and important approach for identifying emission sources, quantifying emissions and verifying reported inventories. This is particularly relevant for halogenated gases, which due to their role as ozone depleting substances and potent greenhouse gases are regulated under various international and national frameworks. Here, we present two studies highlighting the urgency and the challenges of the measurement-based emission estimates of sulfur hexafluoride (SF₆) and fluoroform (HFC-23) with a particular focus on the influence of point sources.

SF₆ and HFC-23 are two of the most potent greenhouse gases with a GWP₁₀₀ of approximately 24,000 and 14,700, respectively. Previous studies consistently showed a dominant emission source in southern Germany contributing to a large share of European SF₆ emissions. Meixner et al., 2025 analysed emission estimates based on 22 European measurement sites revealing an underestimated SF₆ emission point source in southern Germany in contrast to the national inventory reports.

Recent studies highlighted major challenges in quantifying HFC-23 emissions (Adam et al., 2024; Rust et al., 2024). We investigate the effects of intermittency in emissions and explore different possibilities based on a priori assumptions about specific emission sources. Forward calculations from these potential emission sources are used to derive expected time series at observational sites. These are compared to observations from different European stations situated in the regions influenced by the potential point sources. We present different approaches based on European atmospheric measurements combined with multiple model approaches, including ICON-ART, FLEXPART and NAME.

Adam, B., Western, L.M., Mühle, J., Choi, H., Krummel, P.B., O’Doherty, S., Young, D., Stanley, K.M., Fraser, P.J., Harth, C.M., Salameh, P.K., Weiss, R.F., Prinn, R.G., Kim, J., Park, H., Park, S., Rigby, M., 2024. Emissions of HFC-23 do not reflect commitments made under the Kigali Amendment. Commun. Earth Environ. 5, 783. https://doi.org/10.1038/s43247-024-01946-y

Meixner, K., Wagenhäuser, T., Schuck, T.J., Alber, S., Manning, A.J., Redington, A.L., Stanley, K.M., O’Doherty, S., Young, D., Pitt, J., Wenger, A., Frumau, A., Stavert, A.R., Rennick, C., Vollmer, M.K., Maione, M., Arduini, J., Lunder, C.R., Couret, C., Jordan, A., Gutiérrez, X.G., Kubistin, D., Müller-Williams, J., Lindauer, M., Vojta, M., Stohl, A., Engel, A., 2025. Characterization of German SF6 Emissions. ACS EST Air 2, 2889–2899. https://doi.org/10.1021/acsestair.5c00234

Rust, D., Vollmer, M.K., Henne, S., Frumau, A., van den Bulk, P., Hensen, A., Stanley, K.M., Zenobi, R., Emmenegger, L., Reimann, S., 2024. Effective realization of abatement measures can reduce HFC-23 emissions. Nature 633, 96–100. https://doi.org/10.1038/s41586-024-07833-y

How to cite: Meixner, K., Rust, D., Schuck, T. J., Wagenhäuser, T., Gad, F., Couret, C., Jordan, A., Vojta, M., Stohl, A., and Engel, A. and the PARIS project: Using atmospheric observations to identify point sources of halogenated trace gases, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11719, https://doi.org/10.5194/egusphere-egu26-11719, 2026.

Strengthening the link between scientific research and official greenhouse gas (GHG) reporting is an important step under the Paris Agreement’s Enhanced Transparency Framework. The PARIS Project, funded by Horizon Europe, is working with eight European countries to develop practical tools for this purpose.

A central innovation of PARIS is the development of draft annexes to National Inventory Documents (NIDs). These annexes provide a structured and transparent interface between official bottom-up inventories and top-down atmospheric estimates. They do not alter formal reporting rules; instead, they document how independent scientific assessments compare with inventory estimates, identify consistencies and discrepancies, and highlight where further investigation or methodological development is warranted. In this way, the annexes enable inventory compilers, policymakers, and scientists to interpret atmospheric results within the legal and institutional framework of national reporting.

The annexes are underpinned by major advances in PARIS observation and modelling capacity. Expanded and harmonised networks for CH₄, N₂O, F-gases, and aerosols, together with multi-model inverse systems and common data standards publicly available on the ICOS Carbon Portal, provide robust, traceable estimates of regional emissions and their sectoral drivers. These scientific outputs are synthesised in the annexes in a form that is directly usable by inventory agencies.

Through close engagement with national inventory teams in the UK, Switzerland, Germany, Ireland and other focus countries, PARIS has co-developed annex templates and begun populating them with results from multiple inversion systems. This process reduces barriers between the research and inventory communities and supports routine, transparent comparison of bottom-up and top-down estimates.

The poster will present the main outcomes of the PARIS project, demonstrating how the outcomes advance and embed atmospheric science in national GHG reporting to strengthen confidence in emission estimates, improve process attribution of regional emissions, and ultimately support more effective climate policy under the Paris Agreement.

How to cite: Walter, S., Manning, A., Röckmann, T., and Ganesan, A. and the PARIS Team:  Bridging Science and National GHG Inventories: Insights from the PARIS Project – Process Attribution of Regional Emissions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11963, https://doi.org/10.5194/egusphere-egu26-11963, 2026.

The Land Use, Land-Use Change, and Forestry (LULUCF) and agriculture sectors are increasingly central to global climate policy. They play a crucial role in climate mitigation strategies, as land acts as a carbon sink that needs to be enhanced and as a source of greenhouse gas (GHG) emissions that must be reduced. In the European context, the LULUCF Regulation (EU 2018/841), revised in 2023, aims for 310 Mt CO2eq net removals by 2030 and requires spatially explicit land-use representations to monitor land dynamics and assess policy impacts.

Within the Horizon project AVENGERS (Attributing and Verifying European and National Greenhouse Gas and Aerosol Emissions and Reconciliation with Statistical Bottom-up Estimates), a methodology was developed to generate an IPCC-compliant land-use map by integrating multiple Copernicus Land Monitoring Service (CLMS) products. In national GHG inventories, the operational use of spatial explicit data is often limited due to restricted temporal coverage, inconsistencies with national statistics, and challenges in interpreting mixed classes and land-use/land cover definitions. This methodology provides a transparent approach to reconcile inventory data with high-resolution spatial datasets.

The approach combines the CLC Plus Backbone geometry with CORINE Land Cover (CLC) and ancillary CLMS datasets, including the High-Resolution Layer Crop Types and Priority Areas monitoring products (e.g., Coastal Zones, Riparian Zones, and Protected areas). Multiple layers were integrated using overlay techniques and priority rules, resulting in an harmonized map at 10-m spatial resolution. CLC attributes were aggregated to IPCC land use categories, allowing direct comparison between mapped areas and inventory surfaces.

Preliminary validation involved cross-checks with national land-use activity data to ensure reliability of mapped areas across LULUCF categories. The resulting maps enable the spatialization of inventory-based LULUCF and agriculture emissions, producing gridded emission datasets based on improved spatially explicit land-use information. These datasets are suitable for use as input (priors) in atmospheric inversion modelling, a top-down emissions estimation method supporting policy evaluation.

The methodology is designed to be replicable across all European countries covered by CLMS data and to be updated approximately every 2–3 years, in line with the regular update cycle of CLMS products. The methodological framework is modular and flexible, based on a spatial data storage and management scheme developed by ISPRA, which allows the integration of additional datasets and adaptation to different territorial contexts. The approach was applied and tested in three national case studies for the year 2018—Italy, Sweden, and the Netherlands—with specific adaptations introduced to account for distinct territorial characteristics. This first implementation represents a promising step and provides a solid foundation for further refinements and future developments, supporting the production of high-resolution land-use maps helpful for national inventory agencies and inversion modelling experts.

How to cite: Cecili, G., De Fioravante, P., Pellis, G., Vitullo, M., and Fiore, A.: The use of CLMS products for improving the spatialization of greenhouse gases emissions from LULUCF and agriculture sectors , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12319, https://doi.org/10.5194/egusphere-egu26-12319, 2026.

Accurate estimates of greenhouse gas emissions are critical for determining the effectiveness of mitigation strategies under the Paris Agreement. These estimates are commonly derived by atmospheric inversion frameworks, which combine atmospheric transport models with in situ observations to obtain greenhouse gas fluxes. However, regional inversions are often challenged by local-scale signals in atmospheric measurements, that are insufficiently represented by the models. If not properly accounted for, these can introduce biases in inverse flux estimates undermining the reliability of emission estimates.

To address this limitation, observational data has typically been filtered for local influences before being used in inversion simulations, based on assumptions such as stable boundary conditions or wind speed. To make full use of the available dataset, we implemented an observation-dependent model-data uncertainty in the inversion optimisation process, allowing local signals to be explicitly considered. This approach has been applied to CH₄ inversions over Europe using the mesoscale Jena CarboScope-Regional (CSR) system at 0.25° × 0.25° resolution.

To determine the time varying model-data uncertainty based on the local influence signal, a leave-one-out cross validation was performed for ground based in situ data of 47 atmospheric stations, excluding one station per inversion simulation. By determining the difference between modelled and observed concentrations, a model-data mismatch was estimated across station categories defined by surrounding land type. These estimates were then combined with local signal features, resulting from low wind speeds, atmospheric stability, and concentration spikes using a multivariate regression. The derived model-data mismatch function was applied to adjust the data weighting in the inversion enabling the inclusion of the observational dataset without discarding any measurements.

In this presentation, we demonstrate the potential of this novel approach to improve the robustness of regional CH₄ inversions and to reduce the bias from local-scale signals.

How to cite: Zwerschke, E., Koch, F.-T., Gerbig, C., Mueller-Williams, J., Lindauer, M., Keppler, F., and Kubistin, D.: Impact of Local-Scale Effects in Methane (CH₄) Inversions on Model-Observation Discrepancies, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12745, https://doi.org/10.5194/egusphere-egu26-12745, 2026.

Sulfur hexafluoride (SF₆) is an extremely potent (GWP₁₀₀ = 24,300) and long-lived greenhouse gas whose atmospheric concentrations continue to rise due to anthropogenic emissions. Europe represents a particularly relevant test case for investigating SF₆ emissions, as successive EU F-gas regulations over the past two decades have aimed to substantially reduce emissions. A key question is whether these regulatory measures are reflected in observed emission trends and whether reported national inventories are consistent with observation-based estimates.

 In this study, we quantify European SF₆ emissions for the period 2005–2021 using a large ensemble of atmospheric inversions with a strong focus on uncertainty characterization. Uncertainties are assessed using an extensive set of sensitivity tests in which key inversion parameters are systematically varied, while final uncertainties are quantified via a Monte Carlo ensemble that randomly samples combinations of these parameters. This allows us to identify the main sources of uncertainty and to evaluate the robustness of inferred emission trends.

Our analysis focuses on countries with relatively dense observational coverage - the United Kingdom, Germany, France, and Italy - while also examining aggregated emissions for the EU-27.  The inversion results reveal declining SF₆ emissions in all studied regions except Italy, broadly consistent with the timing of EU F-gas regulations (842/2006, 517/2014). In several countries, inferred emissions exceed reported national inventories, although the agreement generally improves in more recent years. At the EU-27 scale, emissions exhibit a pronounced decline between 2017 and 2018, coinciding with a marked reduction in emissions from southwestern Germany, suggesting regional actions were taken as the 2014 regulation took effect.

Our sensitivity tests highlight the crucial role of dense and sustained atmospheric monitoring networks for robust inversion-based emission estimates. In particular, expansions of the UK observing system in 2012 and 2014 lead to significant reductions in emission uncertainties, demonstrating the importance of comprehensive observational networks in refining emission estimates.

How to cite: Vojta, M., Plach, A., Thompson, R. L., Purohit, P., Stanley, K., O'Doherty, S., Young, D., Pitt, J., Arduini, J., Lan, X., and Stohl, A.: Quantifying European SF6 emissions (2005-2021) using a large ensemble of atmospheric inversions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12776, https://doi.org/10.5194/egusphere-egu26-12776, 2026.

Accurate quantification of the sources and sinks of long-lived air pollutants is fundamental for effective emissions management, particularly in urban areas where emissions are generally more intense. Stakeholders commonly use so-called bottom-up methods to estimate emissions for urban areas. This type of emission accounting is typically carried out for annual totals, often with a latency of one or more years. Alternative methods that provide estimates with higher temporal resolution and lower latency could be helpful for stakeholders seeking targeted strategies to reduce emissions. A top-down urban emissions estimation system for the Washington, DC, and Baltimore, MD, metropolitan area, called the Urban Atmospheric Monitoring and Modeling System (Urban-AMMS), is being developed to provide accurate, up-to-date urban emissions data. Urban-AMMS has several components, including tower-based, aircraft, and mobile van measurements platforms, whose data are assimilated by the CarbonTracker-Lagrange analytical inverse model; an ensemble of HYSPLIT backward dispersion simulations driven by in-house high-resolution WRF simulations (spatial resolution of 1 km) enhanced with urban meteorological observations; biospheric models; and bottom-up inventories used for a prior estimate of emissions in the domain. The inversion system is tailored to account for the underlying variability in urban fluxes of an inert tracer (CO₂) by solving for hourly fluxes and incorporating explicit spatiotemporal covariance of prior errors, as well as high-resolution source-receptor sensitivities estimated by WRF-HYSPLIT. Here, we present an overview of Urban-AMMS, including initial results and sensitivity analyses to investigate the effects of prior spatial aggregation, background handling, and the temporal covariance of prior errors. Numerical experiments show improvements in estimates of urban surface fluxes at both the city and grid cell scales. Still, the reliability of inverse fluxes depends on prior uncertainty, as observed in previous studies. These findings provide critical insights for the inverse estimation of long-lived air pollutants in complex urban environments.

How to cite: Cahuich-Lopez, M., Loughner, C., Ngan, F., Karion, A., Hu, L., Lopez-Coto, I., Mueller, K., Marrs, J., Miller, J., McDonald, B., Harkins, C., Lyu, C., Li, M., Gurney, K., Zinn, S., Ren, X., Cohen, M., Diamond, H., Stein, A., and Whetstone, J.: Urban Atmospheric Monitoring and Modeling System (Urban-AMMS): A Top-Down Approach to Investigate Sources and Variability of an Inert Tracer in the Washington, DC, and Baltimore, MD, Metropolitan Area, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14303, https://doi.org/10.5194/egusphere-egu26-14303, 2026.

Nitrous oxide (N₂O) is the third most important long-lived greenhouse gas after CO₂ and CH₄, yet large uncertainties remain in its regional emission estimates. In this study, we apply the regional inverse modeling system CIF-CHIMERE to quantify N₂O surface fluxes over the EU27+3 region (European Union, United Kingdom, Norway, and Switzerland) for the period 2005–2023, providing a long-term and high spatiotemporal resolution assessment of N₂O fluxes. The inversion is primarily constrained by in situ atmospheric N₂O measurements from the ICOS (Integrated Carbon Observation System) ground-based station network across Europe, and uses the CIF-CHIMERE transport model coupled with a four-dimensional variational (4D-Var) data assimilation framework to estimate posterior N₂O fluxes. For 2005–2023, inversions are conducted at a spatial resolution of 0.5° × 0.5°, while for 2018–2023 the resolution is refined to 0.2° × 0.2°. In both configurations, hourly surface fluxes are estimated, enabling analysis of diurnal, seasonal, and interannual variability. The inversions significantly improve the representation of localized emission patterns and short-term flux dynamics. Overall, the results provide a top-down dataset for evaluating bottom-up inventories and for improving the understanding of regional and temporal variability in N₂O emissions across EU27+3.

How to cite: Shi, T., Berchet, A., and Ciais, P.: Quantifying N₂O Flux over the EU27+3 Region Using CIF-CHIMERE Model for 2005–2023, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14957, https://doi.org/10.5194/egusphere-egu26-14957, 2026.

Rice cultivation is the largest source of methane (CH₄) emissions in Vietnam’s agricultural sector, making accurate quantification of these emissions critical for national GHG inventories and the design of mitigation policies. Currently, for UNFCCC GHG reporting, Vietnam primarily employs IPCC Tier 2 approaches using national emission factors combined with Tier 1 scaling factors. With the implementation of large-scale mitigation projects and Vietnam’s ambition to achieve Net Zero by 2050, Methane Global Pledge commitment by 2030, and joining international carbon markets, there is an urgent need to transition towards higher-tier methodologies. However, also process-based model (Tier 3) outputs are associated with uncertainty, which needs to be benchmarked first with established Tier 1 and 2 emission estimates.

In this study, CH₄ emission data from 13 Vietnamese field experiments are split into two groups—one with comprehensive management information (sufficient data) and one with sparse information (limited data)—to test IPCC Tier methods under different activity data conditions. Furthermore, for Tier 3, an inter-comparison is conducted between two biogeochemical models, DNDC and LandscapeDNDC. The evaluation focuses on the performance in estimating rice yields, seasonal CH₄ emissions, and daily flux dynamics, while also analyzing the impact of different model parameterization and simulation setups.

Our evaluation shows that Tier 1 significantly underestimates CH₄ emissions, whereas Tier 2 provides a substantial improvement and remains robust across varying soil and management conditions. In contrast, Tier 3 outperforms Tier 2 only when comprehensive management data is available, reflecting its distinctive capacity to represent daily emission dynamics and management-driven peaks.  Consequently, while Tier 2 remains a practical choice for national inventories, Tier 3 is essential for high-resolution mitigation assessments, particularly for large-scale emission reduction evaluations where detailed management data are comprehensively collected and systematically organized. The process-based model comparison reveals that while DNDC and LandscapeDNDC show similar performance under continuous flooding, they diverge significantly under Alternate Wetting and Drying (AWD) regimes. These discrepancies are primarily attributed to the models' different concepts of representing water table fluctuations.

Building on these results, the Tier 3 approach of LandscapeDNDC was integrated into the web‑based LUI‑RICE platform (https://ldndc.online/rice/). This makes GHG quantification for Vietnamese rice cultivation directly accessible to local stakeholders and policymakers, translating the scientific findings of this study into a practical decision-support application.

How to cite: Nguyen, C., Kraus, D., Nguyen, T., Wassmann, R., Butterbach-Bahl, K., Vo, T. B. T., Mai, V. T., Bui, T. P. L., and Kiese, R.: CH4 emissions in Vietnamese Rice Agriculture: Benchmarking process-based model approaches (Tier 3) against Tier 1/2 Estimates, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15692, https://doi.org/10.5194/egusphere-egu26-15692, 2026.

Long-term coal spontaneous combustion (CSC) represents a severe and persistent threat, resulting in substantial waste of energy resources, significant environmental degradation, and serious risks to human health and safety. To better understand the emission characteristics of CSC, we conducted ground-based measurements of XCO₂, XCH₄, XCO and aerosol optical depth (AOD) using a Fourier-transform infrared spectrometer (EM27/SUN) within the COCCON network, in the Wugonggou coal-fire region near Fukang, Xinjiang.

Our results indicate that TROPOMI satellite data systematically underestimated XCO, with a mean bias of 4.53 ± 5.53 ppb (4.54%). For distinct enhancement events observed by COCCON, ΔXCO₂ and ΔXCO exhibit a strong correlation (R² = 0.6082), with a slope of 9.782 ppb/ppm (9.782 × 10⁻³ ppm/ppm). This value is lower than the CAMS inventory ratio of 13.52 × 10⁻³. This discrepancy arises primarily from their distinct spatial representativeness. The COCCON instrument, located within the coal fire region, captures intense local combustion emission. In contrast, the CAMS product represents a daily average over a much larger model grid cell, which dilutes strong local point sources like coal fires within a broader regional background. Additionally, correlation analysis shows that ΔXCO is more closely linked to AOD (R² = 0.2283) than either ΔXCO₂ or ΔXCH₄, underscoring the distinct behavior of CO in coal-fire plumes.

How to cite: Tu, Q., Fang, J., Hase, F., Butz, A., Barreto, Á., García, O., and Qin, K.: ΔXCO/ΔXCO2 characteristics over coal-fire areas in Xinjiang, China using a portable EM27/SUN FTIR spectrometer, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15734, https://doi.org/10.5194/egusphere-egu26-15734, 2026.

Accurate estimation of methane (CH₄) emissions is essential for assessing mitigation progress, 
yet substantial uncertainties persist at the national scale. In South Korea, CH₄ emissions are 
predominantly anthropogenic, with the waste and agricultural sectors contributing 
approximately 82% of total national emissions. This study analyzes national-scale CH₄ 
emission estimates for South Korea during 2010–2021 using multiple atmospheric inversion 
systems participating in the Methane Inversion Inter-Comparison for Asia (MICA) project. 
Results from inversions using only in situ observations indicate that prior emissions over South 
Korea were likely overestimated. Prior estimates range from 1.5 to 1.7 Tg yr⁻¹ for most years, 
whereas posterior emissions are, on average, about 15% lower than the prior estimates. A 
notable exception is the LMDZ inversion model, which yields posterior estimates that are 40
67% lower than prior values. This substantial reduction is primarily associated with the waste 
sector. Sectoral attribution reveals substantial inter-model differences. LMDZ shows a 
decreasing waste-sector emission trend in Exp. 1 but an increasing trend when only satellite 
observations are assimilated (Exp. 2), whereas the STILT-based inversion consistently 
indicates increasing waste-sector emissions. Given that the waste sector dominates national 
CH₄ emissions, these discrepancies strongly influence total emission estimates. The prior 
waste-sector emissions, derived from EDGAR v7, exceed those reported in South Korea’s 
national greenhouse gas inventory (GIR), contributing to the observed overestimation. 
Additionally, the inversion-derived posterior estimates consistently indicate an overestimation 
of prior agricultural emissions during the summer months. Model performance evaluation over 
the region of interest indicates varying levels of agreement between simulated and observed 
CH₄ mole fractions, with correlation coefficients ranging from 0.24 to 0.85 and posterior biases 
ranging from −65.6 to 0.34 ppb, highlighting the choice of transport model is important. Overall, 
this study highlights the value of multi-model inversion inter-comparisons for constraining 
national-scale CH₄ emissions, diagnosing sector-specific uncertainties, and identifying 
structural differences among inversion frameworks that can guide future improvements. 

How to cite: Takele Kenea, S., Shin, D., Seo, W., Lee, S., Wang, F., Maksyutov, S., Janardanan, R., Lee, S., Belikov, D. A., Patra, P. K., Montenegro, N., Berchet, A., Saunois, M., Martinez, A., Liang, R., Zhang, Y., Ren, G., Lin, H., Hyvärinen, S., and Tsuruta, A. and the Sangwon Joo, Sumin Kim: National-scale methane emissions in South Korea (2010–2021): insights from multiple inversion systems , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16089, https://doi.org/10.5194/egusphere-egu26-16089, 2026.

The international community has continuously monitored carbon emissions by publishing National Inventory Reports (NIRs) under the Paris Agreement adopted in 2015 to address the climate crisis. However, current emission estimation methods predominantly rely on bottom-up approaches based on statistical information, which are subject to limitations, including the potential omission of emission sources and the long time required for emission compilation. To overcome these limitations, top-down approaches that estimate emissions using meteorological models and observed atmospheric greenhouse gas concentrations have recently gained increasing attention. This approach has been adopted as a scientific methodology of the Integrated Global Greenhouse Gas Information System (IG³IS), developed under the auspices of the World Meteorological Organization (WMO), and is regarded as a complementary alternative to conventional emission inventories. In this study, carbon dioxide (CO₂) emissions over South Korea were estimated using a top-down approach based on the Stochastic Time-Inverted Lagrangian Transport Model (STILT) and observations from WMO/Global Atmosphere Watch (GAW) stations, and their accuracy was evaluated. The STILT-based inversion results indicate that anthropogenic CO₂ emissions in South Korea for 2019 amount to 589.7 Mt yr⁻¹, which is 83.6 Mt yr⁻¹ lower than the estimate reported in the existing NIR. The downward correction is primarily concentrated in Seoul and the surrounding metropolitan region. Furthermore, to account for the spatial characteristics of CO₂ emission distributions, high-resolution and realistic emission estimates were derived for regions with dense point-source emissions using the Weather Research and Forecasting (WRF) model. The application of top-down approaches for greenhouse gas emission estimation in East Asian countries, together with continuous technological advancement, is expected to provide a scientific foundation for improving the reliability of emission estimates and supporting future climate crisis response strategies.

How to cite: Shin, H. Y., Shin, D., Kenea, S. T., Lee, S., Kim, S., and Lee, Y. G.: Improving the Accuracy of CO₂ Emission Estimates over South Korea Using a Top-down Inversion Framework, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16769, https://doi.org/10.5194/egusphere-egu26-16769, 2026.

East Asia represents a major source region of greenhouse gas emissions associated with rapid industrialization and increasing energy demand. Among these emissions, halogenated synthetic greenhouse gases such as HFCs and PFCs, which have been widely used as substitutes following international regulations for ozone layer protection, are characterized by high global warming potentials (GWPs).

In South Korea, halogenated greenhouse gases have been monitored at the Gosan station on Jeju Island using the MEDUSA system of the AGAGE network.  However, the expansion of observational coverage and the establishment of measurement capabilities remain essential to better characterize regional emission signals.  In this study, a cryogenic preconcentration and analysis capability for halogenated greenhouse gases (NIMS-preconcentrator) was developed and and evaluate its capability for monitoring halogenated greenhouse gases.

The analytical setup includes a cryogenic thermal desorption (TD) unit and a pre-concentration trap capable of reaching temperatures down to −170 °C, integrated with an automated valve control module and gas chromatography–mass spectrometry (GC–MS). Measurements were conducted using an offline canister-based sampling approach. Analysis of ambient air samples collected at Anmyeondo (GAW station) resolved about ten halogenated greenhouse gas species, including HFC-134a, HFC-125, and legacy chlorofluorocarbons such as CFC-11 and CFC-12. Concentrations were evaluated using calibration standards, and ongoing performance assessment is conducted using laboratory working standards employed at the Gosan AGAGE station.

This study aims to establish a new measurement capability for halogenated greenhouse gases and to assess its consistency with international observation. Continued operation of this system will support the accumulation of long-term observational datasets and facilitate regional-scale analysis and inter-comparison of high-GWP halogenated greenhouse gases in Northeast Asia.

How to cite: Kim, J.-A., Kang, S., Kwon, D., Park, S., Lee, S., and Kim, S.: Development and Application of a Cryogenic Preconcentration System for Halogenated Greenhouse Gas Measurements in Korea, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17209, https://doi.org/10.5194/egusphere-egu26-17209, 2026.

Residential space heating remains a major source of greenhouse gas emissions in the building sector. In Germany, space heating accounts for the largest share of residential energy consumption, and accurate quantification of associated emissions is essential to meet national climate mitigation targets.

Most research on residential heating emissions focuses on the regional or national levels, while estimates at finer spatial scales remain limited. Data availability further constrains the transferability and usability of current models. Consequently, approaches that deliver spatially and temporally detailed emission estimates and interactive tools to support analysis and decision-making by stakeholders are urgently needed.

We introduce the Climate Action Navigator (CAN), a dashboard for the analysis and visualization of climate mitigation and adaptation spatial data, based entirely on open science principles. One of the tools available in the CAN estimates carbon dioxide emissions from residential heating at fine spatial at temporal scales. The tool applies a bottom-up accounting methodology at 100 m spatial resolution based on publicly available census and building characteristics data in Germany, including building age and dominant energy carriers. The resulting emission estimates are consistent with official city- and national-level inventories, confirming methodological reliability. Germany-wide analyses reveal strong spatial heterogeneity in energy consumption and emissions that correlate with urban morphological characteristics.

Temporal dynamics are captured through an hourly simulation using the Demand Ninja model based on local weather data. The resulting temporal emission patterns can support inverse emission modelling applications as well as aid energy management by, for example, revealing peak heating demand times and locations.

Results are delivered via the CAN interface as intuitive, interactive maps and charts that allow users to compare across neighborhoods, explore temporal emission dynamics, and assess potential mitigation actions. By integrating open-source data with high-resolution modeling and visualization, the Climate Action Navigator bridges the gap between scientific emission quantification and practical decision making. The approach supports transparent attribution and tracking of residential space-heating emissions, thereby advancing evidence-based climate mitigation planning.

How to cite: v. Elverfeldt, K., Kong, G., Urlich, V., Martin, M., Schott, M., and Block, S.: High-resolution direct GHG emission estimation and simulation from residential space heating using open data , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17591, https://doi.org/10.5194/egusphere-egu26-17591, 2026.

Understanding the temporal dynamics and controls on greenhouse gas exchange between terrestrial ecosystems and the atmosphere is critical for advancing process-level understanding and informing national greenhouse gas budgets and inventories. A large portion of soils in the Netherlands are either drained or restored peatlands, where the high carbon/organic matter content is accompanied by large risk of carbon loss to the atmosphere through enhanced soil respiration (drained sites) and/or enhanced methane emissions (rewetted sites). For this reason, increasing attention is being paid to understanding and quantifying the greenhouse gas budgets of both drained and restored peatland sites across the Netherlands. 
 
To both inform national GHG inventories and improve our understanding of site scale process, we present a multi-site analysis of a network of more than thirty eddy-covariance sites in the Netherlands. We discuss the daily, seasonal, and annual variability of carbon dioxide (CO₂) and methane (CH₄) fluxes measured at these sites. These sites include intensively managed grasslands, arable fields, semi-natural pastures, forested peatlands, wetlands and marshes. These sites encompass a wide range of vegetation types, soil characteristics, and water-management practices, with continuous or semi-continuous high-frequency flux datasets extending across multiple years within the last decade.
 
We quantify daily, seasonal, and annual CO₂ and CH₄ fluxes and discuss key biophysical drivers, including soil composition and moisture, vegetation dynamics, groundwater levels, and the impacts of climate anomalies such as temperature and precipitation extremes across varying timescales. We discuss differences between sites and potential impacts of soil characteristics, vegetation, land management, and recent climate anomalies.
 
Our analysis indicates substantial variability in both CO₂ and CH₄ fluxes across sites and seasons. These results highlight the invaluable contributions of both high-resolution flux observations and rigorous data processing methods when disentangling ecosystem controls on gas exchange. These flux observations provide much needed empirical constraints for model evaluation and can facilitate improved representation of peatland and wetland systems in greenhouse gas inventories and process-based models.

How to cite: Andueza Kovacevic, I., Bataille, L., Cabezas, I., Engel, F., Franssen, W., van Huissteden, C., Hutjes, R., Ingle, R., Jans, W., Lippmann, T. J., Zerrudo, J., Zhao, H., Nouta, R., and Kruijt, B.: Carbon dioxide and methane emissions from a network of thirty eddy-covariance sites in the Netherlands, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19274, https://doi.org/10.5194/egusphere-egu26-19274, 2026.

Methane emissions from waste and agriculture account for 46.6 % of Aotearoa New Zealand’s (ANZ) gross greenhouse gas emissions in 2023. Despite the significance of methane emissions, the only way to estimate their magnitude is based on emission factor methods, which include large uncertainties.  We present newly developed tools to directly measure methane emissions from wastewater treatment facilities, animal effluent storage systems and herds of dairy cows. We deploy in situ analysers on mobile observation platforms (vehicle and drone) and quantify methane emission fluxes using the tracer gas technique.  The accuracy of this method is estimated in multiple ways: i) a controlled release experiment, ii) through comparison to a mass-balance modelling approach, iii) through comparison to co-located chamber measurements for methane emissions from effluent ponds, iv) through comparison to co-located measurements of animal emissions using the “GreenFeed” technique. The comparisons show excellent agreement, providing much needed assurance of analytical performance to our mobile techniques. Our tools support ANZ’s farmers and waste managers to better understand current emissions, as well as to assess the efficacy of investments into emission mitigation. Additional tests explore new isotope techniques with the goal to quantify methane fluxes from different components within a plant, for example methane derived from digestors versus methane derived from biosolids in wastewater treatment systems, or methane from the open face of a landfill versus emissions from an area that is covered.

How to cite: Sperlich, P., Stiegler, C., Geddes, A., Sutton, H., Smith, B., Leitch, M., Gray, S., Brailsford, G., Moss, R., Bukosa, B., Mikaloff-Fletcher, S., Pirooz, A., Turner, R., Turnbull, J., Laubach, J., Rowe, S., McNaughton, L., Spaans, O., Brian, K., and Wymei, E.: Towards accurate quantification of New Zealand’s methane emissions from waste and agriculture, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19514, https://doi.org/10.5194/egusphere-egu26-19514, 2026.

Uncertainty in atmospheric transport models, especially boundary-layer mixing and turbulence, still limits confidence in top-down GHG emission estimates. In inversion workflows, observation selection is commonly supported by empirically tuned filters based on modelled meteorological variables (e.g., boundary-layer height, wind speed). The selection prioritises periods when transport is expected to be well represented. This motivates continued work to characterise atmospheric mixing and its associated uncertainties using observations.

In the UK GEMMA programme, we investigate whether observation-based atmospheric mixing state can provide complementary information to support uncertainty characterisation in UK CH₄ inversions. We demonstrate the framework at UK sites with radon measurements and at a newly instrumented site in Scotland where only meteorological measurements are available. Where radon is measured, we use it as an independent tracer of near-surface mixing and compare observed radon with radon simulated using the Met Office NAME dispersion model and a radon flux map. This comparison is used to define transport-performance classes (periods of relatively better vs poorer agreement) and associated atmospheric mixing state. At the Scotland site, we derive atmospheric mixing regimes from in situ meteorological measurements alone, using a vertical profile sampled every 10 m to characterise stratification and mixing.

We show how the resulting atmospheric mixing state and transport-performance classes can be used in two operational ways: (i) as additional information to support observation selection alongside existing practice, and (ii) to define regime-dependent uncertainty characterisation within inversion frameworks rather than assuming a single fixed error model. We illustrate the approach using two UK CH₄ inverse methods (InTEM and RHIME) and discuss how observation-based mixing information can improve transparency and reproducibility in hybrid (inventory + atmospheric) emissions estimation for IG3IS-aligned information services.

How to cite: Kikaj, D., Andrews, P., Danjou, A., Manning, A., Rigby, M., Chung, E., Forster, G., Wenger, A., Rennick, C., Safi, E., O’Doherty, S., Stanley, K., Pitt, J., and Gardiner, T.: Can observation-based atmospheric mixing state reduce filtering sensitivity in GHG inversions? Lessons from the UK GEMMA programme, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19832, https://doi.org/10.5194/egusphere-egu26-19832, 2026.

Effective climate mitigation requires obtaining greenhouse gas (GHG) information and accounting that is scientifically robust and actionable for decision-making. The CARBONICA project has developed and implemented a robust climate-positive action plan for carbon farming implementation across the widening countries of Greece, Cyprus and North Macedonia, generating climate information services that operate at regional, national, and international scales. An extended management practices inventory has been developed and implemented in pilot sites across 15 crops between the 3 countries, fully aligned with the IPCC, the Natural Climate Solutions World Atlas, the GHG Protocol, and climate related EU laws and initiatives. GHG accounting is supported by a robust MRV system combining soil sampling, field inputs following IPCC Scope guidance, and management practices, covering direct, indirect, and upstream emissions across the farm system, with all procedures are fully compliant with ISO 14064-2. Farm-level data are also collected using the validated Field Diagnostic Toolbox, which includes soil CO₂ flux monitoring using spectroscopy to support accurate assessment of emissions and carbon removals.

This enables explicit attribution of emissions and carbon removals to farms, regions, and in general, the agrifood sector, supporting monitoring, reporting and validating of mitigation measures for positive climate action. LCA modelling on a pilot site (1ha peach orchard) has shown significant results in emissions reductions and carbon removals. The model was used once on the baseline (business-as-usual scenario) in 2024, and once after the management practices no- till and residues incorporation were implemented in the orchard, for the year 2025. The total greenhouse gas emissions from the pilot peach orchard decreased from 2,660 kg CO₂e in 2024 to 1,280 kg CO₂e in 2025, with emissions per ton of produced fruit dropping from 147.63 kg CO₂e to 71.04 kg CO₂e. Beyond the reduction of the emission sources, the demonstrated change in the soil carbon stock was also significant. While the 2024 cultivation season showed a net-zero change compared to the baseline scenario, the implementation of no-till and crop residue incorporation during the 2025 season created an active carbon sink, resulting in a net removal of 597.76 kg of CO₂e from the atmosphere into the soil. Thus, the project successfully demonstrated a twofold climate benefit: a major reduction in operation emissions and a significant sequestration of atmospheric carbon into the soil.

The results presented above are part of a third-party validated carbon farming project, facilitated through CARBONICA. This work also contributes to IG3IS-aligned applications demonstrating the operational use of multi-source GHG observations for real-world solutions in carbon farming.

How to cite: Kitsou, D., Chantzi, P., Gkoutzikostas, D., Rousonikolos, V., Galanis, G., Papastergiou, A., and Zalidis, G.: From GHG Observations to Actionable Climate Information Services, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20089, https://doi.org/10.5194/egusphere-egu26-20089, 2026.

In the context of the Paris Agreement on climate change and of a global effort to reduce greenhouse gas emissions, the monitoring of anthropogenic carbon dioxide (CO₂) emissions is needed to assist policy makers but represents a major challenge. While current inventories provide rather robust annual emission totals at country scale, they lag behind real time by many months and they lack spatial and sub-annual details. Here we map the daily surface fossil fuel CO₂ emissions at a 1/16 degree resolution over Europe, with the year 2021 as an example, based on spaceborne atmospheric composition observations.

As the high-resolution satellite monitoring of atmospheric CO₂ remains challenging, especially at a local spatial scale and a daily time scale, we take advantage of the co-emission of CO₂ and nitrogen oxides (NO_X) during fossil fuel combustion: we exploit images of nitrogen dioxide (NO₂) concentrations retrieved from the measurements of the Tropospheric Monitoring Instrument (TROPOMI) onboard the Sentinel-5P satellite.

From the TROPOMI NO₂ concentrations, we retrieve daily maps of NO_X emissions based on the divergence of the mass fluxes within the NO₂ images. We combine the changes of these maps from one year to the next with low latency national CO₂ emissions from Carbon Monitor (https://carbonmonitor.org/), and with a baseline of monthly spatially-distributed CO₂ emissions for a previous year (here 2020) from GridFED (https://mattwjones.co.uk/co2-emissions-gridded/) from which we removed aviation and shipping emissions beforehand.

The resulting maps of emission increments from 2020 to 2021 capture changes in highly emitting areas: major urban or industrial areas, and main transport corridors. The emissions for the year 2021 show good consistency with existing inventories. The dataset also produces realistic seasonal variability at a local scale and captures daily variability, although temporally smoothed due to a 5-day rolling average of Carbon Monitor data.

This method is both temporally and spatially scalable and can therefore be extended to the entire world and to additional years, which provides encouraging prospects for the continuation of this work.

How to cite: Héraud, A., Chevallier, F., Broquet, G., Ciais, P., Martinez, A., and Rey-Pommier, A.: Daily and 1/16 degree maps of CO2 fossil fuel emissions based on satellite retrievals of pollutant atmospheric data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20826, https://doi.org/10.5194/egusphere-egu26-20826, 2026.

Quantitative evidence is increasingly required to assess the mitigation potential of cities in achieving global carbon neutrality. However, although urban green spaces contribute simultaneously through biophysical carbon sequestration and reductions in energy demand driven by urban heat island mitigation, few studies have systematically compared and evaluated these two effects within a unified framework at the global scale.This study quantifies the total contribution of urban green spaces to carbon neutrality across global cities and decomposes this contribution into carbon sequestration and cooling driven energy savings, assessing their relative importance and spatial patterns.The urban heat island effect is estimated using remote sensing derived land surface temperature differences between urban and non urban areas, while carbon sequestration by urban green spaces is simultaneously quantified based on satellite based observations.These two contributions are then integrated and compared. Furthermore, this study examines how the relative importance of the two effects varies across major climate zones and how heterogeneity manifests in distinct spatial patterns. Finally, this study investigates how vegetation related indicators, socio economic variables, and urban structural characteristics influence the two effects across climate zones with AI based approaches and identify contextual conditions under which the mitigation benefits of urban green spaces are amplified or attenuated even under similar urban green space availability.This study provides a global assessment of the contribution of urban green spaces to carbon neutrality and offers empirical evidence to support the design of climate and context specific nature based mitigation strategies in cities.

How to cite: Kim, S. and Choi, Y.: The dual role of urban green spaces in carbon neutrality: carbon sequestration and cooling driven energy savings at the global scale, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20959, https://doi.org/10.5194/egusphere-egu26-20959, 2026.

Accurate estimation of greenhouse gas (GHG) emissions at the infrastructure scale remains essential to climate science and policy applications. Powerplant and vehicle emissions often form the majority of fossil fuel CO2 (FFCO₂) emissions in much of the world at multiple scales. Climate Trace, co-founded by former U.S. Vice President Al Gore, is a new AI-based effort to estimate pointwise and roadway-scale GHG emissions, among other sectors. However, limited independent peer-reviewed assessment has been made of this dataset. Here, we update a previous analysis of Climate Trace powerplant FFCO₂ emissions in the U.S. and present a new analysis of Climate Trace urban on-road CO₂ emissions in U.S. urban areas. This is done through comparison to an atmospherically calibrated, multi-constraint estimates of powerplant and on-road CO₂ emissions from the Vulcan Project (version 4.0).

Across 260 urban areas in 2021, we find a mean relative difference (MRD) of 69.9% in urban inroad FFCO₂ emissions. Furthermore, differing versions of the Climate Trace on-road emissions releases shift from over to under-estimation in almost equal magnitudes. These large differences are driven by biases in Climate Trace’s machine learning model, fuel economy values, and fleet distribution values. An update to the powerplant FFCO₂ emissions analysis (from a 2024 paper) show both improved and degraded convergence of emissions. We continue to recommend that sub-national policy guidance or climate science applications using the GHG emissions estimates in these sectors made by Climate Trace should be done so with caution.

How to cite: Gurney, K., Aslam, B., Dass, P., Gawuc, L., Hocking, T., Barber, J., and Kato, A.: Assessing the accuracy of the Climate Trace global vehicular and power plant CO2 emissions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22515, https://doi.org/10.5194/egusphere-egu26-22515, 2026.

  The conventional hydrocarbon accumulation model in the Xihu Depression is predominantly characterized by “late-stage accumulation.” However, with advancing exploration, the potential occurrence of commercially significant early hydrocarbon charging events in the Paleogene Pinghu Formation has become a subject of considerable debate. This study examines the accumulation mechanisms of natural gas in the Pinghu Formation through an integrated approach incorporating scanning electron microscopy (SEM), systematic fluid inclusion analysis, and natural gas carbon isotope geochemistry, with a particular focus on the evolutionary patterns of authigenic illite within the reservoir.

  SEM observations reveal three distinct morphological types of authigenic illite in the Pinghu Formation reservoirs: honeycomb, bridge-like, and fibrous. The crystallization of these illite types is primarily governed by diagenetic temperature and pore fluid pH: honeycomb illite forms at low temperatures (60 to 110°C) via smectite transformation; bridge-like illite develops at 120 to 140°C in association with acidic dissolution of K-feldspar; and fibrous illite requires temperatures above 140°C and alkaline conditions for the illitization of kaolinite. A key anomaly contradicting conventional diagenetic sequences was identified: in the shallower and cooler Huagang Formation reservoirs, fibrous illite constitutes up to 76% of the illite assemblage, whereas in the deeper and presumably hotter Pinghu Formation reservoirs, honeycomb and bridge-like types dominate (collectively 65%), with markedly reduced overall abundance. This inverse distribution with depth is interpreted as evidence of early hydrocarbon charging during deep burial of the Pinghu Formation. The introduction of acidic hydrocarbons inhibited the transformation of kaolinite to fibrous illite, thereby preserving the earlier illite morphologies and providing direct mineralogical evidence for an early accumulation event during the Huagang Movement.

  Geological analysis further supports the coupling of key elements conducive to early accumulation: during the Huagang Movement, source rocks had reached burial depths sufficient for hydrocarbon generation (Ro ≥ 0.5%), providing a material basis for large-scale expulsion. Concurrently, the superposition of the Yuquan and Huagang movements facilitated the development of structural–lithologic traps. At this stage, the average porosity of the Pinghu Formation reservoirs was approximately 21%, not yet entering the tightening phase, providing high-quality reservoir space for early hydrocarbon filling and accumulation.

  Fluid geochemical data provide additional robust evidence: hydrocarbon inclusions exhibiting yellow fluorescence with homogenization temperatures peaking between 105 and 135°C record an early hydrocarbon charging event. Furthermore, the methane δ¹³C values of Pinghu Formation natural gas (–38‰ to -34‰) are significantly lighter than those of the overlying Huagang Formation (–34‰ to 29‰), consistent with an early-generated, low-maturity gas source, effectively distinguishing fluid origins between early and late accumulation phases.

  Based on the above research, an early accumulation model governed by the combined effects of “paleo-highs and high-quality reservoirs” is established for the Pinghu Formation. This provides a key predictive model for early-stage reservoir exploration in basins with similar geological conditions worldwide, thereby further expanding new exploration frontiers.

How to cite: Li, L. and chen, Z.: Evidence from Illite Crystal Evolution: Exposing the Early Phases and Patterns of Hydrocarbon Accumulation in the Pinghu Formation of the Xihu Depression in the East China Sea., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-58, https://doi.org/10.5194/egusphere-egu26-58, 2026.

Rare-earth elements (REE) form indispensable components of daily life, as they are essential constituents of the modern high-technology applications, including clean energy, high-tech electronics, and ultimately to achieve the sustainable development goals of the United Nations. With a growth rate of approximately 10–15% per year, the demand for REE has been increased significantly. However, production and supply chains of REEs are very limited, especially due to the rare occurrences and/or discoveries of REE-enriched deposits. It also invokes an alarming situation, since the REE industry is largely controlled by a small number of countries across the globe, with one holding the dominant position in both mining and processing. Consequently, there is an increasing interest in the REE exploration studies across the globe for finding out new potential sources.

Granitic pegmatites are considered as important sources of rare metals, such as REEs, and other high-field strength elements (HSFE) such as U, Th, Y, Zr, Hf, Nb, Ta and large-ion lithophile element (LILE) such as Li, Rb, and Cs. Here, we report the occurrence of rare-metal granitic pegmatites associated with alkaline granite complex of Munnar in the southern Indian shield. The mineralized pegmatites are intruded along and across the shear planes of granites. The pegmatites are composed of quartz, K-feldspar, plagioclase, biotite and muscovite. Several veins also contain magnetite, pyrite and pyrrhotite. They are characterized by high ΣREEs contents ranging from 1318 ppm to 7682 (avge. 3992 ppm). The chondrite-normalized REE patterns of the pegmatites are characterized by a strong enrichment of LREE over HREE, with a (La/Yb)N ratio between 42 and 1000, with characteristic negative Eu anomalies. The ΣREE of host granites ranges between118 and 6502 ppm. The REE patterns of the pegmatites suggest that the pegmatites are formed from LREE enriched melt, generated possibly during the shearing of host granitic rock. During this process the incompatible REEs are concentrated in the melt causing LREE enrichment, which eventually intruded into the lower curst as granitic pegmatites. This indicates enhanced mobility of REE during alteration of host granites. Thus, the study imposes important insights into the sources and enrichment mechanisms of REEs in the parent rocks as well as their remobilization during alteration processes forming ion-adsorption REE deposits in their weathered crusts.

How to cite: Chettootty, S., Sivankutty, R., and Vasundharan, K.: Rare earth element (REE) enriched granitic pegmatites associated with alkaline granite complex of southern India: Source characteristics, enrichment mechanisms, and insights into potential ion-adsorption REE deposits, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-790, https://doi.org/10.5194/egusphere-egu26-790, 2026.

A key challenge in the 21st century is the successful implementation of the energy transition, which hinges on the development of sustainable (energy) resources. In this context, hydrogen gas (H₂) generated by natural processes is a promising source of clean energy. However, we urgently need to develop the concepts and exploration strategies for this promise of natural H₂ energy to become a reality.

The most likely mechanism of large-scale natural H₂ generation in nature is the serpentinization of ultramafic mantle rocks during their chemical reaction with water. In order to predict the bulk serpentinization and natural H₂ generation that may lead to the development of exploitable H₂ deposits, we consider the following “recipe” for efficient serpentinization, which involves three main ingredients: (1) (fresh) mantle rocks that need to be at (2) optimal temperatures between ca. 200-350˚C (the serpentinization window), and (3) in contact with ample water for the reaction to take place. The serpentinization window can be expected at 8-12 kilometers below the Earth’s surface. However, mantle rocks are normally found at much greater depth; thus these rocks must be brought closer to the surface (exhumed) through geodynamic processes. Moreover, water needs to reach such depths along large faults or other structures that cut into the exhumed mantle. The challenge we are faced with is to understand where (and when) these ingredients may come together in nature, and how much natural H₂ may be generated.

Numerical geodynamic modelling is an ideal means to tackle this issue since it allows us not only to test how mantle rocks can be exhumed, but also to trace the temperature conditions and potential water availabilitiy (Zwaan et al. 2025). By combining this information, we assess favorable settings and timing of bulk natural H₂ generation in different geodynamic systems. Subsequently, we consider where the natural H₂ could be exploited. The serpentinizing mantle source rocks at 8-12 km depth cannot be directly targeted. Ideally, the natural H₂ would instead migrate and accumulate in sedimentary reservoir rocks at depths of only a couple of kilometers that are connected with the mantle source rocks via migration pathways (e.g., faults). Importantly, all key elements need to be in place for the system to work.

Our first-order modelling work and the development of natural H₂ system concepts greatly helps to direct natural H₂ resource exploration efforts, for example in the Alps and Pyrenees. Moreover, substantial opportunity lies in refining both the geodynamic modelling and natural H₂ system analysis, in field- and laboratory testing of our H₂ system concepts, and in extending such a “mineral system” modelling approach to other types of natural resources that are crucial to the energy transition. 

Reference:

Zwaan, F., Brune, S., Glerum, A.C., Vasey, D.A., Naliboff, J.B., Manatschal, G., & Gaucher, E.C. 2025: Rift-inversion orogens are potential hot spots for natural H₂ generation, Science Advances, 11, eadr3418. https://doi.org/10.1126/sciadv.adr3418

How to cite: Zwaan, F., Glerum, A. C., Brune, S., Vasey, D. A., Naliboff, J. B., Manatschal, G., and Gaucher, E. C.: Numerical geodynamic modelling for natural H2 resource exploration, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3352, https://doi.org/10.5194/egusphere-egu26-3352, 2026.

Magma migration is a complex natural process that controls volcanism, the formation of many types of ore deposits, the development of geothermal reservoirs and the thermal structure, and long-term evolution of the lithosphere [1-3]. Because the dynamics of magma migration are difficult to observe directly, numerical simulations provide a powerful tool to investigate magmatic systems, the coupled physiochemical processes involved, and the range of spatial and temporal scales over which these processes operate.

In this study, we present a new multi-phase numerical framework to study magma migration within the Earth, with a particular emphasis on the mechanical interactions between melt and solid. The framework is based on multiphase flow in porous media and it incorporates realistic rheological descriptions of lithospheric rocks, including visco-elasto-viscoplastic behavior, damage, strain weakening and the generation of porosity due to plastic deformation. Interaction between the fluid (magma) and solid (host rock) phases are described via a set of equations derived from a formal phase-averaging framework. An arbitrary Eulerian-Lagrangian solver is used to discretize the equations and solve the fully-coupled system. The validity of the model, and its potential to study multi-scale magmatic systems, are demonstrated using well-known benchmark tests and targeted numerical experiments.

Keywords: Dynamics of lithosphere and mantle, Mechanics, Numerical modeling, Physics of magma, Plasticity

REFERENCES

• [1] Keller, D. A. May, and B. J. Kaus, “Numerical modelling of magma dynamics coupled to tectonic deformation of lithosphere and crust,” Geophys. J. Int., Vol. 195, pp. 1406-1442, (2013).
• [2] Li, A. E. Pusok, T. Davis, D. A. May, and R. F. Katz, “Continuum approximation of dyking with a theory for poro-viscoelastic-viscoplastic deformation,” Geophys. J. Int., Vol. 234, pp. 2007-2031, (2023).
• [3] Oliveira, J. C. Afonso, S. Zlotnik, and P. Diez, “Numerical modelling of multiphase multicomponent reactive transport in the Earth’s interior,” Geophys. J. Int., Vol. 212, pp. 345-388, (2018).

Acknowledgment

EarthSafe Doctoral Network has received funding from the European Union’s Horizon Europe research and innovation programme under the Marie Skłodowska-Curie grant agreement No. 101120556.

How to cite: Hosseinian, N., Afonso, J. C., García-González, A., and Zlotnik, S.: Numerical modeling of magma migration in lithospheric rocks, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5509, https://doi.org/10.5194/egusphere-egu26-5509, 2026.

Eduardo Monsalve^a, Claudia Pavez-Orrego^b, Ángela Flores^a, Nicolás Barbosa^b, Eckner Chaljub^a, Rodrigo Palma-Behnke^a, Nikolai H. Gaukås^d, Didrik R. Småbråten^d, Diana Comte^c*.

• a) Department of Electrical Engineering / Energy Center, Faculty of Mathematical and Physical Sciences, University of Chile, Santiago, Chile
• b) Department of Applied Geosciences, Geophysics, SINTEF Industry, Trondheim, Norway
• c) Advanced Mining Technology Center, Faculty of Mathematical and Physical Sciences, University of Chile, Santiago, Chile
• d) Department of Sustainable Energy Technology, SINTEF Industry, Oslo, Norway

In a global context marked by increasing energy demand and growing constraints on the large-scale deployment of conventional renewable sources, the exploration of alternative energy pathways has become increasingly relevant. Within this framework, vibrational energy harvesting (VEH) has garnered attention due to its potential to exploit ambient energy sources that are typically overlooked, such as mechanical vibrations. In particular, seismic vibrations, both natural and anthropogenic, represent a persistent and spatially distributed energy resource in regions characterized by intense industrial activity and significant seismicity.

This study presents a systematic and replicable methodology for assessing the energy harvesting potential from real seismic vibrations, with a specific focus on high-vibration environments, such as mining areas and urban settings. The proposed framework aims to quantify both the theoretical potential of the vibrational resource, understood as the maximum energy available in the environment, and the technical potential, defined by the current capability of electromagnetic energy harvesters (EMEHs) to capture and convert this energy into usable electrical power.

The developed methodology consists of six main stages: (i) seismic data acquisition, (ii) signal preprocessing, (iii) event identification, (iv) event characterization and classification, (v) device selection, and (vi) dynamic simulation for harvested power estimation. Continuous seismic records are analyzed to detect and isolate energetically relevant events of both natural and anthropogenic origin, including earthquakes, microseisms, blasting activities, and vehicular traffic. These events are characterized in terms of amplitude, frequency content, and duration, providing objective criteria to evaluate their relevance for energy harvesting applications. Representative seismic excitations are subsequently used as non-stationary inputs to a dynamic model of an EMH, enabling the estimation of the harvested power associated with each event type without parameter optimization. This approach allows for a direct comparison between different vibrational sources under realistic operating conditions and highlights the influence of site-specific factors such as local geology, proximity to vibration sources, and spectral characteristics of ground motion.

The application of the proposed framework to a mining environment in northern Chile reveals distinct, yet partially overlapping, ranges of harvestable power across different classes of seismic events. The results demonstrate a strong spatial dependence on the vibrational energy resource and emphasize the necessity of localized assessments when evaluating the feasibility and robustness of vibrational energy harvesting systems. This work contributes a methodological foundation for resource-oriented evaluation, providing quantitative insight into whether seismic vibrations can realistically support low-power applications such as autonomous sensors and monitoring systems.

How to cite: Monsalve, E.: Evaluating Seismic Vibrations as an Energy Resource in Mining and Urban Environments, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5931, https://doi.org/10.5194/egusphere-egu26-5931, 2026.

The prevalence of viscous-dominated regimes within the Earth’s interior gives rise to Stokes-like flow systems in numerous geodynamical applications. A prominent example is sublithospheric mantle convection, which constitutes the primary driving mechanism behind the evolution of dynamic topography. In this context, numerical simulations provide more physically consistent estimates of the Lithosphere–Asthenosphere Boundary (LAB) depth than those derived from first-order isostatic approximations [1].

However, the associated computational overburden is exceptionally high, particularly when accounting for material nonlinearities. The challenge is further complicated when attempting to incorporate them within a Markov Chain Monte Carlo (MCMC) framework that requires an exceptionally large number of evaluations [2], limiting their applicability to large-scale studies and underscores the need for novel and computationally efficient Reduced-Order Modeling (ROM) methodologies [3].

Results from linear Model Order Reduction (MOR) techniques indicate that the complexity of the problem surpasses the capabilities of projection-based ROMs designed to produce globally accurate solutions. This work introduces a localized, goal-oriented criterion to enhance linear reducibility and employs Neural Network (NN) surrogates to replace high-fidelity solver evaluations. These methodological advances jointly underpin the development of a hybrid offline–online reduction framework that efficiently reduces computational complexity while preserving the required levels of accuracy, enabling seamless model updates during parameter-space exploration.

REFERENCES

[1] Afonso, J. C., Rawlinson, N., Yang, Y., Schutt, D. L., Jones, A. G., Fullea, J., & Griffin, W. L. (2016). 3-D multiobservable probabilistic inversion for the compositional and thermal structure of the lithosphere and upper mantle: III. Thermochemical tomography in the Western-Central U.S. Journal of Geophysical Research: Solid Earth, 121(10), 7337–7370. https://doi.org/10. 1002/2016jb013049

[2] Ortega-Gelabert, O., Zlotnik, S., Afonso, J. C., & Diez, P. (2020). Fast Stokes Flow Simulations for Geophysical-Geodynamic Inverse Problems and Sensitivity Analyses Based on Reduced Order Modeling. Journal of Geophysical Research: Solid Earth, 125(3). https://doi.org/10.1029/ 2019jb018314

[3] Hesthaven, J.S., Rozza, G., Stamm, B. (2015). Certified Reduced Basis Methods for Parametrized Partial Differential Equations. SpringerBriefs in Mathematics. Springer International Publishing AG, Cham. https://doi.org/10.1007/978-3-319-22470-1

How to cite: Ramadan, M., Pichi, F., and Rozza, G.: Toward Efficient Stokes Flow Simulations in Multi-Observable Thermo-Chemical Tomography Using Model Order Reduction, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6024, https://doi.org/10.5194/egusphere-egu26-6024, 2026.

Geophysical inverse problems are inherently ill-posed due to sparse, noisy, and indirect observations, making Uncertainty Quantification (UQ) a fundamental requirement for reliable subsurface characterization. Bayesian inversion provides a comprehensive probabilistic framework for inferring subsurface parameters by coherently combining prior knowledge with observational data through the likelihood function. However, the practical deployment of Bayesian methods in large-scale geophysical settings is often hampered by the prohibitive computational cost of repeated forward model evaluations. In this context, uncertainty is often not solely driven by observational noise; a substantial and sometimes dominant contribution arises from model error, resulting from simplified physical descriptions, numerical discretization, and uncertain boundary conditions. When these sources of uncertainty are neglected or inadequately represented, Bayesian inversions may yield biased posterior estimates and unrealistically narrow uncertainty bounds. These limitations are particularly acute in deep Earth applications, where complex rheologies, poorly constrained geometries, and computationally intensive forward models coexist.

A key challenge is the accurate delineation of the Lithosphere–Asthenosphere Boundary (LAB), which plays a central role in controlling mantle dynamics, lithospheric deformation, and deep geothermal processes. Despite the necessity of relying on Bayesian approaches to estimate the LAB and its associated uncertainties, the high computational cost of repeated evaluations of the forward solver makes this unfeasible within realistic time frames [1]. To address these limitations, this work investigates Reduced-Order Modeling (ROM) techniques to enable efficient Bayesian inversion of LAB geometry in geodynamical Stokes flow models. ROMs construct low-dimensional surrogates of high-fidelity solvers, allowing rapid forward simulations while preserving the dominant physical behavior of mantle flow. By integrating ROMs with Bayesian inference, the proposed framework enables effective and reliable UQ for LAB characterization.
Keywords: Geophysical inverse problems; Bayesian inversion; Uncertainty Quantification; Reduced-Order Modeling; Lithosphere–Asthenosphere Boundary

Acknowledgement This research was conducted within the EarthSafe Doctoral Network and has received funding from the European Union’s Horizon Europe research and innovation programme under the Marie Sklodowska-Curie grant agreement No. 101120556.

References [1] Olga Ortega-Gelabert, Sergio Zlotnik, Juan Carlos Afonso, and Pedro D´ıez. Fast stokes flow simulations for geophysical-geodynamic inverse problems and sensitivity analyses based on reduced order modeling. Journal of Geophysical Research: Solid Earth, 125(3):e2019JB018314, 2020.

How to cite: Shahzaib, M., Díez, P., Zlotnik, S., Muixí, A., and Amaya, M.: Coupling Bayesian Inversion and Reduced-Order Modeling: Application to Lithosphere–Asthenosphere Boundary Estimation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8341, https://doi.org/10.5194/egusphere-egu26-8341, 2026.

How to cite: Chakraborty, A., van Hunen, J., Valentine, A., Zlotnik, S., and García González, A.: Toward integrated geodynamic-petrological modelling: coupling ASPECT with thermodynamic calculations , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9853, https://doi.org/10.5194/egusphere-egu26-9853, 2026.

Three-dimensional (3D) Magnetotelluric (MT) probabilistic inversion remains rare in real-world applications because it requires solving the forward problem thousands to millions of times, often making the computational cost prohibitive. Since the total duration of an inversion is directly controlled by the performance of the forward solver, the high computational overhead of 3D MT modeling remains a significant challenge, particularly for large-scale problems requiring high mesh resolutions. To address the poor scaling of existing strategies, we introduce DD–POD, a hybrid framework that integrates Domain Decomposition (DD) with Proper Orthogonal Decomposition (POD). The DD formulation partitions the global problem into subdomains, bypassing the memory limitations of traditional direct solvers and enabling simulations with substantially finer discretizations. Implementing this distributed architecture alone yields simulations that are at least 50% faster than global full-order approaches. Building on this foundation, the integration of POD eliminates the need for repeated large-scale linear system solves within the iterative DD process, delivering total forward-solver speed-ups exceeding 90%. Benchmark experiments and a real-world case study demonstrate that DD–POD consistently outperforms standard global POD strategies in computational efficiency with an acceptable trade-off in numerical accuracy.

(This work was supported by the Marie Sklodowska-Curie Actions (Doctoral Network with Grant agreement No. 101120556))

How to cite: Tao, L., Zlotnik, S., Muixí, A., Zyserman, F. I., Afonso, J. C., and Diez, P.: Reducing Computational Costs in 3D Magnetotelluric Simulations via Domain Decomposition and Reduced-Order Modeling, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10570, https://doi.org/10.5194/egusphere-egu26-10570, 2026.

Geothermal energy is a crucial component of the global transition to sustainable and green energy systems due to its renewable and long-term availability. In order to study potential resources, we need to describe the subsurface by solving inverse problems. The complexity and uncertainty of these problems require the use of probabilistic inversion approaches that repeatedly solve partial differential equations over a grid of parameters describing the subsurface domain. Frequently, the high dimensionality of the parameter space to be inferred implies prohibitive computational times and reduces the sensitivity of each parameter as the grid is refined. In this work, we implement and discuss adaptive parametrization strategies in Bayesian inversions. We model the thermal conductivity structure of 2D sections of the Earth's upper mantle and perform Markov chain Monte Carlo (MCMC) inversions to recover the thermal conductivity as a probability distribution based on the likelihood of the temperature measurements. To verify the solution, we first parametrize the physical properties of the subsurface domain equal to the high-dimensional finite element grid. In order to determine the optimal metaparameters on the run we rely on adaptive MCMC techniques that accelerate the convergence and reduce the risk of getting trapped in local minima. We then use a new parametrization based on the physical structure of the geological faults of the mantle that reduces the dimensionality of the problem. By relying on transdimensional sampling through reversible-jump MCMC, we consider the number of parameters as an unknown of the inversion. In these methods, the algorithm is allowed to increase the number of parameters to invert when the solutions found are not accurate enough and to decrease it when the accuracy of the solution is not significantly affected. Our results show that we recover the thermal conductivity structure both with and without adaptive parametrization, and the performance is improved when using transdimensionality. Moreover, the proposed transdimensional inversion decreases or increases the number of parameters locally, thereby providing an efficient and robust method for addressing the often challenging lack of information on subsurface heterogeneity.

Keywords: geothermal energy; Markov chain Monte Carlo; reversible jump MCMC; transdimensional inversion; adaptive parametrization; finite elements; Poisson equation.

How to cite: Dols, A., Amaya, M., Zlotnik, S., and Díez, P.: Adaptive parameterization in Bayesian inversions using transdimensional methods, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12436, https://doi.org/10.5194/egusphere-egu26-12436, 2026.

Mantle convection plays a fundamental role in governing the thermal and dynamical
evolution of terrestrial planets, yet its numerical simulation remains computationally ex-
pensive due to strong nonlinearities, high Rayleigh numbers, and the presence of thin
thermal boundary layers. In this work, we present a non-intrusive reduced-order modeling
(ROM) framework for two-dimensional mantle convection based on Proper Orthogonal
Decomposition combined with Radial Basis Function interpolation (POD–RBF).
High-fidelity full-order model (FOM) simulations are first performed using a finite-
volume discretization of the incompressible Boussinesq equations under the infinite-Prandtl-
number approximation. The FOM is carefully validated across a wide range of Rayleigh
numbers. Particular attention is devoted to high-Rayleigh-number regimes, where mesh
refinement studies are conducted to improve accuracy and ensure reliable reference solu-
tions.
The ROM is constructed from snapshot data of velocity and temperature fields. POD
analysis reveals a rapid decay of singular values, indicating a low-dimensional structure
of the solution manifold. The parametric dependence of the reduced coefficients is recon-
structed using RBF interpolation, yielding a fully data-driven and non-intrusive ROM.
To rigorously assess predictive capability, the ROM is validated using test points ex-
cluded from the training dataset. Leave-One-Out cross-validation demonstrates that the
ROM accurately predicts unseen solutions across the parameter space, with low relative
L2 errors for both velocity and temperature fields. Field-level comparisons confirm that
the dominant flow structures and thermal patterns are faithfully reproduced.
The framework is further extended to transient simulations, where both time and
Rayleigh number are treated as parameters. This two-dimensional parametric unsteady
ROM successfully captures time-dependent dynamics while providing significant compu-
tational speed-up. The proposed approach offers a robust and efficient tool for parametric
mantle convection modeling and provides a solid basis for future extensions toward three-
dimensional configurations and uncertainty quantification.

How to cite: Haider, Q., Tonicello, N., Girfoglio, M., and Rozza, G.: Non-Intrusive POD–RBF Reduced OrderModeling for Parametric and Transient MantleConvection, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13256, https://doi.org/10.5194/egusphere-egu26-13256, 2026.

Multi-Observable Thermochemical Tomography (MTT) is a simulation-driven, joint probabilistic inversion framework designed to estimate the thermochemical state of the Earth’s lithosphere by integrating geophysical datasets with complementary sensitivities. By jointly inverting observables such as gravity and geoid anomalies, surface heat flow, seismic dispersion, body-wave data, and magnetotelluric responses, MTT directly estimates primary thermodynamic variables, including temperature, pressure, and bulk composition, from which all secondary physical properties are derived through internally consistent thermodynamic models. This bottom-up approach provides physically-consistent constraints on lithospheric structure across regional to prospect scales.

Within this framework, MTT offers a powerful basis for characterizing lithospheric architecture and compositional domains that are commonly examined in mineral systems studies. In particular, MTT can help delineate major crustal- and lithospheric-scale structures, identify metasomatized/altered domains, and map thermochemical contrasts that serve as lithospheric-scale proxies commonly associated with specific classes of magmatic and hydrothermal mineral systems.

Despite recent advances incorporating ray-based seismic tomography solvers (Fomin, I., Afonso, J. C., Gorbatov, A., Salajegheh, F., Dave, R., Darbyshire, F. A., et al. (2026). Multi-observable thermochemical tomography: New advances and applications to the superior and North Australian cratons. Journal of Geophysical Research: Solid Earth, 131, e2025JB031939. https://doi.org/10.1029/2025JB031939 ), the integration of full-waveform seismic solvers within the MTT framework has not yet been achieved. Full-waveform inversion (FWI) offers enhanced sensitivity to both seismic velocity and density and the potential for improved spatial resolution relative to traditional tomography approaches. However, the computational cost of FWI remains prohibitive, particularly in probabilistic or ensemble-based inversion settings required for uncertainty quantification.

This contribution presents a computational strategy aimed at reducing the cost of full wavefield simulations to enable probabilistic seismic FWI within the MTT framework. We extend reduced-order modeling (ROM) techniques to the spectral element method (SEM), which is widely used for accurate time-domain seismic wave propagation in complex geological settings. Specifically, we consider projection (Galerkin)–based ROMs in which the SEM wavefield is approximated in a low-dimensional reduced basis constructed from representative high-fidelity solutions. While ROM approaches are well established for simpler formulations, their application to SEM-based elastic wave simulations remains challenging due to the method’s high dimensionality and complex operator structure. Beyond MTT, such reductions are also relevant to SEM-based workflows that require large numbers of forward simulations, including ground motion studies and FWI with many sources at regional-to-global scales.

We develop and test a reduced-order SEM formulation using synthetic benchmark models relevant to lithospheric-scale imaging. Results demonstrate computational speed-ups of up to two orders of magnitude relative to full SEM simulations, while retaining sufficient accuracy in simulated wavefields for inversion purposes. These results represent a first proof of concept toward incorporating probabilistic FWI into multi-observable thermochemical tomography and reducing a key computational barrier to uncertainty-aware, physics-based lithospheric imaging.

How to cite: Jamasb, A., Afonso, J.-C., Garcia Gonzalez, A., Rozza, G., Pichi, F., Zlotnik, S., Meijde, M. V. D., and Fadel, I.: Enabling Probabilistic Full Waveform Inversion in Multi-Observable Thermochemical Tomography through Reduced-Order Spectral Element Modeling, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13298, https://doi.org/10.5194/egusphere-egu26-13298, 2026.

The identification of hydro-mechanical parameters governing earthfill dam behaviour under transient loading conditions is essential for reliable interpretation of monitoring data and predictive analysis. Although coupled flow–deformation models can represent these processes in detail, their direct use in inverse analyses is often prohibitive due to the large number of forward simulations required. This work addresses the efficient estimation of material parameters in earthfill dams by integrating a reduced-order formulation of the problem into an inverse strategy.

A transient, nonlinear hydro-mechanical model for unsaturated soils is considered in the context of a sensor-driven inverse problem, where piezometric measurements are used to constrain model parameters. Reduced-order models based on proper orthogonal decomposition (POD) are introduced to enable repeated model evaluations within the inversion procedure while retaining the key features of the hydro-mechanical response. The framework targets the estimation of relevant soil properties, such as hydraulic conductivity, water retention characteristics, and mechanical stiffness, and is illustrated using both synthetic observations and field piezometer data from the Glen Shira dam during rapid drawdown events.

REFERENCES

[1]  Pinyol, N. M., Alonso, E. E., Olivella, S. (2008). Rapid drawdown in slopes and embankments. Water Resources Resarch, 44(5). doi: 10.1029/2007WR006525

[2]   Nasika, C., Díez, P., Gerard, P., Massart, T.J., Zlotnik, S. (2022). Towards real time assessment of earthfill dams via Model Order Reduction. Finite Elements in Analysis & Design, 199: 103666. doi: 10.1016/j.finel.2021.103666

How to cite: Zlotnik, S., Schrader, J., Beatrice, J., García González, A., and Muixí, A.:  Hydro-mechanical parameter estimation in earthfill dams using reduced-order models, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13600, https://doi.org/10.5194/egusphere-egu26-13600, 2026.

The reliable assessment of tailings dam response under transient hydro-mechanical loading is a key challenge for mining infrastructure safety and risk management. High-fidelity numerical models capable of representing coupled groundwater flow and deformation in partially saturated soils provide valuable insight into internal states of the dam, but their computational demands often limit their use in operational settings, such as scenario analysis or near–real-time monitoring.

We consider a transient, nonlinear hydro-mechanical finite element model describing groundwater flow in unsaturated soils and apply a proper orthogonal decomposition (POD)–based reduced-basis formulation to accelerate simulations. While POD effectively reduces the number of unknowns, the computational cost of assembling nonlinear operators remains tied to the full-order mesh dimension, limiting efficiency gains. To address this bottleneck, hyper-reduction techniques are investigated that construct reduced approximation spaces for the nonlinear terms themselves, with the goal of alleviating computational cost relative to standard full-order finite element simulations.

How to cite: Muixí, A., Monforte, L., García-González, A., and Zlotnik, S.: Hyper-reduced POD formulation for the hydro-mechanical assessment of tailings dams, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13610, https://doi.org/10.5194/egusphere-egu26-13610, 2026.

Earth imaging is central to our ability to understand our planet and is important for exploration of critical minerals, geothermal energy resources detection, and mitigation of natural hazards such as earthquakes and the study of plate tectonics. As a result, there is a need for more precise images of the earth’s interior. However, as this imaging process is ill-posed and lossy, the images obtained are inevitably a blurry version of the truth. This makes it challenging to robustly interpret results and draw inferences about geophysical systems.  

The full waveform inversion (FWI) has been the state-of -the-art for high-fidelity and physically consistent subsurface imaging, however, its computational expense has driven exploration into machine learning (ML) techniques. These data-driven ML techniques can perform seismic inversion, directly mapping seismic data to subsurface properties without executing the iterative physics modelling loop of FWI. While their success is highly dependent on the availability of comprehensive, high-quality training data, they have proven capable of delivering subsurface predictions orders of magnitude faster than traditional methods.

In our attempt to obtain physically consistent subsurface images while ensuring cheap inferences, we will explore opportunities for ‘seismic super-resolution’: generation of higher-resolution images by combining observed data with prior knowledge about likely structures and the physics of wave propagation. Our approach involves the combination of machine learning techniques for numerical upscaling and physics – informed neural networks ensuring that the underlying laws of physics are embedded within results.  

In this presentation, we will highlight some of the challenges and opportunities in this approach  

and present some early results from numerical experiments.

How to cite: Mahmud, M. O., Valentine, A. P., Reinarz, A. K., and Hunen, J. V.: Seismic Super-resolution Leveraging Machine Learning Techniques , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15494, https://doi.org/10.5194/egusphere-egu26-15494, 2026.

In mineral exploration, on-site analytical techniques provide tools for real-time data acquisition, supporting informed decision-making. Portable instruments such as handheld X-ray fluorescence (pXRF) and short-wave infrared (SWIR) hyperspectral spectrometers enable rapid, non-destructive collection of geochemical and mineralogical information directly from drill cores. When effectively integrated and interpreted, these datasets offer powerful tools for advancing geological understanding and refining 3D models, ultimately improving vectoring toward mineralization and supporting more efficient, sustainable exploration

Where traditional interpretation methods are often subjective and time-consuming, data-driven approaches, particularly machine learning, can identify patterns and correlations within large datasets, accelerating analysis. In this study, we propose a machine learning framework for fusing drill-core hyperspectral and geochemical point data to enhance geological modeling.

Methodologies were applied and tested in two gold target sites hosted by an Archean Ilomantsi Greenstone Belt in eastern Finland. The geology at the selected sites is dominated by visually homogeneous schistose metasediments exhibiting intense sericite–chlorite alteration. Hence, these target areas provide an ideal natural environment for evaluating machine-learning approaches aimed at refining lithological and lithogeochemical discrimination and alteration mineralogy interpretations. The data-fusion and predictive modeling approach has the potential to significantly extend the data-driven geological models in 3D to enhance geological understanding and controls of the Au mineralization.

Lithogeochemical data were first partitioned into distinct compositional groups using the K-means clustering algorithm. The resulting cluster assignments served as training labels for a supervised learning framework aimed at linking geochemical classes to hyperspectral signatures. Selected SWIR spectral parameters corresponding to geochemical sampling points, together with their assigned labels, were used to train a Random Forest (RT) classifier. The trained model was applied to unclassified spectral data to infer lithogeochemical classes to produce a predictive model.

Despite the generally noisy nature of both pXRF and spectral point data and overall, rather poor probability measures of the RT model (< 50% for most classes), in 3D, a clear and spatially reasonable model is produced. Along-strike continuation of lithogeochemical stratigraphy provides a validation argument supporting the success of the predictive model beyond areas with both lithogeochemical and hyperspectral data.

This approach leverages existing drill holes in a fast and cost-efficient manner by utilizing portable data-acquisition technologies. Machine-learning-based integration of multi-sourced datasets is demonstrated to improve lithological/lithogeochemical discrimination and predict subsurface geological features. This aids in the delineation of drilling targets more accurately, supporting dynamic, data-driven decision-making in mineral exploration.

How to cite: Luolavirta, K. and Ojala, J.: Machine learning framework for the integration of drill-core hyperspectral and geochemical point data to enhance geological modeling, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19052, https://doi.org/10.5194/egusphere-egu26-19052, 2026.

How to cite: Latallerie, F., Hjörleifsdóttir, V., Isken, M., Biondi, E., Obermann, A., and Peidong, S.: Characterising vp/vs ratios beneath geothermal systems of the Hengill volcano in Iceland using a global-local approach, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1163, https://doi.org/10.5194/egusphere-egu26-1163, 2026.

In the summer of 2025, the Passive Array for Critical Minerals on the Island of Newfoundland (PACMIN) project was launched. The deployed array comprises 22 broadband seismograph stations, which will record local, regional and global earthquakes as well as ambient ground vibrations for a period of two years. This experiment will yield the first ever detailed 3D lithospheric structure models of the entire island of Newfoundland from multiple types of seismic analysis. From these models, we will be able to investigate how the region was shaped by Appalachian mountain-building processes, while also exploring tectonic controls on the distribution of key mineral deposits such as gold and critical minerals. The onshore seismicity of Newfoundland, while low, will also be investigated to better understand and mitigate mining exploration/exploitation hazards. Improved detection and locating of small local earthquakes will also allow fault networks in the shallow crust to be mapped and assessed in terms of their potential as fluid pathways that may carry critical minerals. 

How to cite: Welford, J. K., Darbyshire, F., and Long, M.: Passive Array for Critical Minerals on the Island of Newfoundland (PACMIN), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5405, https://doi.org/10.5194/egusphere-egu26-5405, 2026.

Seismic ambient noise analysis has become an important tool for subsurface characterization, offering a cost-effective alternative to active sources and enabling continuous monitoring. Array-based techniques such as beamforming are central to ambient noise analysis, allowing the estimation of wavefield properties such as propagation direction and phase velocity. Traditionally, beamforming has been applied either to vertical-component array data, particularly for surface-wave analysis, or to three-component (3C) seismic arrays, which allow for polarization and wave-type discrimination.

More recently, distributed acoustic sensing (DAS) has emerged as a powerful tool for ambient noise studies, providing dense spatial sampling and large apertures at relatively low per-channel cost. However, DAS measurements are primarily sensitive to axial strain and can therefore be interpreted as effectively single-component observations. As a result, DAS arrays deployed along a single line cannot leverage the benefits of 3C beamforming, such as polarization analysis and wave-type identification. Conversely, sparse 3C arrays provide polarization information but are often limited in wavenumber resolution due to restricted aperture and station spacing.

In this study, we develop and test a joint beamforming approach that combines DAS and 3C seismic observations in a unified framework. The joint beamformer is constructed by combining normalized beam power estimates from DAS-only and 3C-only beamforming, enhancing coherent signals that are consistent across both datasets while suppressing incoherent or aliased energy. The performance of the joint approach is evaluated using numerical simulations in layered elastic media. Systematic tests are carried out for different array geometries and station spacings to investigate their effects on aliasing, resolution, and information gain. The results show that the joint beamformer improves the stability of the results, particularly in cases where DAS-only or 3C-only beamforming suffers from aliasing or limited resolution. Finally, the method is applied to a real test dataset to demonstrate its applicability under realistic noise conditions.

Our study suggests that joint DAS–3C beamforming provides a robust framework for ambient noise analysis, offering improved wavefield characterization compared to single-sensor approaches and highlighting the potential of hybrid array designs for future seismic monitoring applications

How to cite: Kaur, S., Finger, C., and Saenger, E. H.: Ambient Noise Beamforming with Joint DAS and Three-Component (3C) Seismic Arrays, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5919, https://doi.org/10.5194/egusphere-egu26-5919, 2026.

Geothermal systems provide a low-carbon, renewable source of heat, whose performance depends on the presence of permeable, fluid-filled rock at depth. Tomographic images of compressional and shear-wave velocities, Vp and Vs, and their ratio, Vp/Vs, are typically used to constrain the lithology, porosity, fluid content and extent of fracturing in such systems: contrasts in seismic velocity delineate lithological boundaries, identify zones of fracture damage or fluid saturation, and thereby indicate areas of elevated permeability.

Passive seismic acquisition is attractive for geothermal exploration, because it is minimally invasive and can exploit microseismicity recorded by dense nodal seismological arrays. Combining data recorded from microseismic events with Bayesian joint inversion of seismic velocity and source location – here implemented with stochastic Stein Variational Gradient Descent (sSVGD) and double difference tomography – yields relocated earthquake events and three-dimensional estimates of Vp, Vs, and Vp/Vs together with their respective uncertainty. sSVGD approximates the statistical description of all possible models that fit the data, referred to as the posterior distribution, using an ensemble of particles or samples. These are initialized from a prior distribution, which encodes the prior information about the domain, and driven toward the posterior by iterative transforms that minimise the Kullback-Leibler divergence between the particle density and the posterior.

We apply this workflow to the Eden Project geothermal site (Cornwall, UK), using microseismic events recorded by an array of 450 STRYDE nodes deployed around the injection site. The objective is to recover mean models of Vp and Vs, and Vp/Vs with their corresponding uncertainty from passive sources alone, enabling probabilistic assessment of the subsurface structure and potential future well-placement targets.

Owing to the nodal geometry and the spatial distribution of microseismic sources, ray-path coverage is highly heterogeneous across the survey volume. Consequently, the posterior uncertainty is large over much of the domain and decreases substantially where ray coverage is dense – mostly around the geothermal well. Within this region, we observe velocity anomalies consistent with fractured and fluid-saturated rock, while regions distant from the well remain poorly constrained. By providing a clearer understanding of uncertainties inherent to tomographic inversions, the probabilistic imaging framework enables more robust and reliable analysis of the results, which is crucial in geothermal exploration.

How to cite: Dromigny, S., Yang, H., Koelemeijer, P., Curtis, A., Hudson, T., Kendall, M., and Zhang, X.: Probabilistic body wave tomography in a geothermal setting in Cornwall, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6450, https://doi.org/10.5194/egusphere-egu26-6450, 2026.

Deep-derived carbon dioxide (CO₂) degassing is a globally important process linking crust–mantle fluid transport with atmospheric carbon budgets. Matched Field Processing-Bartlett Beamformer (MFP-BB) method offers a seismic approach for detecting tremor signals generated by these degassing centers (mofette). Its principle relies on comparing recorded wavefields with modeled replicas to identify the most likely source locations.

This study applies the MFP–BB technique to dense-array seismic noise data from three key mofette areas in the Cheb Basin, western Eger Rift—Bublák, Hartoušov, and Soos. We combine field observations with numerical simulations to evaluate the method’s performance. Synthetic tests with interfering noise-embedded sources (SNR = 5 dB) demonstrate that accurate localization is achievable with appropriate frequency selection, and that even 20% perturbations in the velocity model introduce only minor degradation.

Field data were processed through segmentation, noise filtering, and spectral analysis to determine persistent frequency bands used in the algorithm. Across all sites, MFP-BB energy concentrates near the surface, coinciding with known mofette fields and CO₂ discharge zones. These shallow anomalies reflect microtremors generated as ascending CO₂ interacts with groundwater and unconsolidated sediments; additional, weaker anomalies at depths < 200 m may also represent active gas migration.

How to cite: Karimi, K., Fischer, T., Vlček, J., Mazanec, M., Vilhelm, J., and Masihi, A.: Matched-Field Processing for Detecting Mofette Activity in the Western Eger Rift, Czechia, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10793, https://doi.org/10.5194/egusphere-egu26-10793, 2026.

How to cite: Maatouk, N., Cazenave, F., Gerbaud, L., Noble, M., and Velmurugan, N.: Seismic While Drilling as a Passive Source for Imaging Deep Geothermal Systems , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11305, https://doi.org/10.5194/egusphere-egu26-11305, 2026.

Imaging the Earth’s subsurface is fundamental to a wide range of geophysical applications, including natural hazard assessment and mitigation, geothermal and mineral exploration, and crustal characterization. However, achieving reliable seismic images in strongly heterogeneous media remains a significant challenge. In such environments, conventional seismic imaging approaches, including tomography and migration, often perform poorly due to the prevalence of multiple scattering and high attenuation, which obscures primary reflections and degrades image quality.

While multiple scattering has traditionally been regarded as a major impediment to seismic imaging, recent advances have demonstrated that this scattered energy can instead be exploited to extract valuable information. One such approach is Reflection Matrix Imaging (RMI). RMI involves using seismic interferometry to construct a reflection matrix that contains the full wavefield response between virtual source–receiver pairs, allowing for the analysis of reflected energy generated by subsurface heterogeneities. From this, the distortions undergone by the incident and reflected waves  can be isolated and compensated for even with a rough estimate of the background seismic velocity. RMI has been shown to enhance imaging in complex geological settings, including volcanic environments, and has also been seen to be effective in 3D imaging applications in fields such as optical microscopy and medical ultrasound.

In this study, RMI is adapted to data from a dense seismic array deployed in the Hengill Geothermal Field, Iceland. The subset of the array considered here comprises 267 stations distributed over a rectangular approximately 5X10km² , with continuous recordings spanning 2.5 months. Reflection matrices are constructed, and the applicability and performance of RMI in this highly heterogeneous geothermal setting are systematically evaluated.

How to cite: Berry-Walshe, L., Korta Martiartu, N., and Obermann, A.: Reflection Matrix Imaging of the Hengill Geothermal Field, Iceland, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13211, https://doi.org/10.5194/egusphere-egu26-13211, 2026.

Mapping of fracture networks is critical to the exploration and responsible exploitation of geothermal resources. Fractures provide the permeable pathways required for efficient heat extraction and knowledge of their subsurface distribution is necessary for optimal well placement and reservoir modelling. Additionally, fractures play a significant role in induced seismic hazards both by decreasing rock strength and by providing hydraulic connections between fluid injection/extraction sites and surrounding fault networks that may slip in response to pore pressure perturbations. However, constraining fracture distributions in 3D can be challenging. Geologic mapping provides limited information regarding how these systems evolve with depth and exploratory drilling is expensive and only provides point-wise constraints that may not reflect larger-scale trends. Seismic imaging utilising local earthquakes provides a cost-effective means to overcome these issues and map fractures at the reservoir scale. In this contribution, we constrain the anisotropic P-wave velocity structure of the Hengill Geothermal Field (Iceland) using arrival times from natural and induced seismicity. A Bayesian Monte Carlo sampling approach is used to construct likely velocity models and posterior parameter distributions from which we evaluate hypotheses for fracture properties. The imaged slow P-wave propagation directions constrain the average 3D fracture plane orientations while the degree of alignment and extent of fracturing is inferred from the strength of velocity anisotropy. Our models reveal significant spatial heterogeneity in these fracture properties throughout the Hengill geothermal system. We explore possible mechanisms behind this heterogeneity (e.g. deformation related to topographic loading, tectonic and magmatic stresses, and geothermal energy production) and its relationship to local seismicity patterns.

How to cite: VanderBeek, B., Nowacki, A., and de Ridder, S.: Exploring fracture networks beneath the Hengill Geothermal Field (Iceland) through probabilistic anisotropic P-wave tomography, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13292, https://doi.org/10.5194/egusphere-egu26-13292, 2026.

A sustainable supply of critical and strategic raw materials, like copper, cobalt, lithium, or fluorite, amongst others, is a critical prerequisite for the decarbonisation of the economy and the successful implementation of the green transition. However, Europe currently lacks sufficient knowledge, exploration activity, and domestic supply of these commodities. To overcome these limitations, the DEXPLORE project aims at developing surface to subsurface sustainable cost-effective geological and geophysical techniques for mineral exploration using three pilot zones in Spain and Estonia. Within the framework of this project, we present an innovative non-invasive passive seismic exploration approach and a field test conducted to optimize acquisition and processing parameters. The main objective was to achieve sufficient resolution at prospect depths of 500-1000 m, enabling the identification of ore-associated geological structures in one of the pilot zones, corresponding to the Villabona Fluorite deposit in Asturias (northern Iberian Peninsula, Spain).   

The passive seismic methodology relies on the recording and processing of ambient seismic noise acquired by seismic nodes. We designed a preliminary configuration and workflow based on an extensive review of the passive seismic method to run a five-day small-scale field test in the Minersa Pilot Zone, located in the central part of Asturias (N Spain). In this area, the currently active Villabona Mine produces fluorite hosted by Mesozoic sediments affected by extensional faults on an epigenetic Mississippi-Valley-type ore deposit. The fieldwork encompassed the deployment of 38 seismic nodes along a profile with a total length of 3300 meters, with a sensor spacing of 90 meters. Five days of continuous passive data were acquired. Processing methods included the Extended Spatial Autocorrelation (ESPAC) methodology and the Ambient Noise Interferometry (ANI) procedure. The inversion of 31 dispersion curves enabled the construction of a 2-D S-wave velocity model extending to a maximum depth of 700 m. The model shows two velocity sectors separated by a low velocity corridor and identifies velocity anomalies that correspond with structural variations and major fault systems. These results validate the proposed ambient seismic noise workflow for imaging geological and structural features to depths of approximately 700 meters. Additionally, this study demonstrates that the ESPAC processing method enhances survey efficiency and flexibility, particularly when using irregular array configurations. The ESPAC method provided the most reliable results for developing an S-wave velocity model, with lateral resolution dependent on the number and spacing of seismic nodes. Future works include the development of additional passive seismic profiles in the Villabona Pilot Zone, together with planned tests in two additional pilot areas in Spain and Estonia. The main aim is to further validate and apply the passive seismic methodology across diverse geological settings characterized by variable ore deposit distribution and structural configurations.  

How to cite: Cadenas, P., Olona, J., Acevedo, J., Fernández Martín, E., Mazaira, A., Gallardo, P., Villa, L., Cueto, M., Marín, J. A., Agüera, M., Rodríguez, R., and Olivar-Castaño, A.: Optimization of a land-based non-invasive passive seismic approach for the exploration of deep-seated critical raw materials in the North of Spain, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14029, https://doi.org/10.5194/egusphere-egu26-14029, 2026.

In the pursuit of deep geothermal energy (depths exceeding 3 km), the limitations of traditional surface exploration often render the subsurface "invisible." This study presents an integrated seismic exploration framework: the GEOthermal SEISmic AI Platform (GEOSEIS-AI). This platform leverages high-density microseismic monitoring networks and advanced deep-learning (DL) techniques to resolve the "four pillars" essential for geothermal development: heat sources (temperature), stress states (pressure), fracture distributions (pathways), and fluid properties. Building upon the architecture of the Real-Time Microearthquake Monitoring System (RT-MEMS) (Sun et al., 2025), GEOSEIS-AI utilizes DL phase picking and earthquake localization to accelerate the processing of massive datasets. Key seismic observables—including seismicity, focal mechanism, shear-wave splitting, and seismic tomography—are employed to directly characterize these four parameters. We demonstrate the platform's capabilities through two distinct case studies: a metamorphic region in Taiwan focusing on deep geothermal potential (Huang et al., 2023) and a volcanic region in Japan targeting supercritical energy (Tsuji et al., 2025). By mapping the spatial distribution of microearthquakes, we identify the Brittle-Ductile Transition (BDT) interface. Since seismic activity ceases as rocks transition from brittle to plastic states at high temperatures (350-400°C), the "seismic-quiet zone" serves as a proxy for the top of the heat source. Identifying these thermal upwellings is essential for targeting high-enthalpy drilling sites. By analyzing P-wave first motions with DL techniques, we resolve the local stress field and faulting styles. This provides vital data for assessing wellbore stability and distinguishing between dilated, fluid-conductive faults and compressed, sealing structures. Utilizing shear-wave splitting technique, we quantify the density and orientation of subsurface fracture networks. This provides a "pre-drilling ultrasound" that identifies high-permeability zones and informs hydraulic fracturing strategies for Enhanced Geothermal Systems (EGS). Through V_p/V_s ratio analysis derived from seismic tomography, we can differentiate between solid lithology and fluid-filled pores, and more critically, the identification of fluid phases (liquid water, steam, or melt), where low and high V_p/V_s ratios act as indicators of geothermal steam and fluids, respectively. The results show that GEOSEIS-AI significantly enhances the resolution of reservoir imaging and also provides critical insights into induced seismicity monitoring for future geothermal hydrofracturing and CO₂ injection of CCS operation.

Keywords: GEOSEIS-AI; Deep Geothermal Energy; Supercritical Energy; CCS; Deep Learning; Microseismic Monitoring; Seismicity; Focal Mechanism; Shear-Wave Splitting; V_p/V_s; Seismic Tomography.

References:

Sun, W.-F., S.-Y. Pan, Y.-H. Liu, H. Kuo-Chen, C.-S. Ku, C.-M. Lin, and C.-C.Fu  (2025). A Deep-Learning-Based Real-Time Microearthquake Monitoring System (RT-MEMS) for Taiwan. Sensors, 25(11), 3353. https://doi.org/10.3390/s25113353.

Tsuji ,T., R. Andajani, M. Kato, A. Hara, N. Aoki, S. Abe, H. Kuo-Chen, Z.-K. Guan, W.-F. Sun, S.-Y. Pan, Y.-H. Liu, K. Kitamura, J. Nishijima, and H. Inagaki  (2025) Supercritical fluid flow through permeable window and phase transitions at volcanic brittle–ductile transition zone, Commun. Earth Environ. https://doi.org/10.1038/s43247-025-02774-4.

Huang S.-Y., W.-S. Chen, L.-H. Lin, H. Kuo-Chen, C.-W. Lin, W.-H. Hsu, Y.-H. Liou (2023). Geothermal characteristics of the Paolai Hot Spring area, Taiwan. 45th New Zealand Geothermal Workshop, Auckland, New Zealand.

How to cite: Kuo-Chen, H., Sun, W.-F., Guan, Z.-K., Pan, S.-Y., Chang, C.-J., Liu, Y.-H., and Tsuji, T.: GEOthermal SEISmic AI Platform (GEOSEIS-AI) for Deep and Supercritical Geothermal Exploration, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15245, https://doi.org/10.5194/egusphere-egu26-15245, 2026.

Shear-wave splitting analysis module is part of the GEOSEIS-AI platform, primarily utilized to characterize stress states and subsurface fracture distributions in geothermal sites. However, microseismic data in geothermal sites often face on inherent limitations, including low signal-to-noise ratios (SNR), cycle skipping, fast/slow wave misidentification, and null measurements, all of which compromise the accuracy of automated processing.

To solve these limitations, this study optimizes the pre-processing stage by utilizing adaptive time-window selection to maximize SNR. Furthermore, an automated quality-controlling workflow was developed, based on three diagnostic metrics: (1) peak-picking determination of fast and slow waves; (2) cross-correlation (CC) coefficients; and (3) the energy variation rate between the principal S-wave component and perpendicular component. These tests facilitate the robust identification and remove low-quality seismic events.

This methodology was validated using microseismic monitoring data from the geothermal site in Miaoli, Taiwan. The results reveal two predominant fracture sets oriented NW-SE and N-S. The NW-SE orientations align with the regional focal mechanism solutions, reflecting stress states, while the N-S trends correspond to surface-mapped fault orientations. This workflow was integrated into the GEOSEIS-AI Platform—alongside AI catalogs, focal mechanisms, and seismic tomography—to establish a reliable microseismic monitoring system for geothermal exploration.

Keywords: GEOSEIS-AI; Geothermal Energy; Microseismic Monitoring; Shear-Wave Splitting; fracture distribution.

How to cite: Chang, C.-J., Sun, W.-F., Liu, Y.-H., Pan, S.-Y., and Kuo-Chen, H.: GEOthermal SEISmic AI Platform (GEOSEIS-AI): Shear-wave Splitting Analysis Module and A Case Study of Geothermal Site in Miaoli, Taiwan, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15833, https://doi.org/10.5194/egusphere-egu26-15833, 2026.

Establishing a real-time and high-resolution earthquake catalog is crucial for understanding the development process of earthquake sequences and conducting disaster risk assessment. This study developed a real-time microearthquake monitoring system (RT-MEMS) that integrates deep learning technology (Sun et al., 2025). After testing and verification, it was confirmed that the system can quickly and reliably provide earthquake activity information through a fully automated process. The main data processing process of the system includes: (1) using SeedLink to receive continuous waveform data from four broadband seismic networks, maintained by the Institute of Earth Sciences of Academia Sinica, the National Center for Research on Earthquake Engineering, National Chung Cheng University, and National Taiwan University, and store and build a continuous waveform database; (2) using a deep learning model trained with Taiwan earthquake arrival data to identify and select P- and S-wave arrival times and store them in an arrival database; (3) selecting appropriate seismic station combinations according to the monitoring area, extracting corresponding P- and S-wave arrival times to associate and locate earthquake events, and generating a preliminary deep learning earthquake catalog; (4) preparing daily earthquake reports and sending them to relevant personnel via email, LINE, Discord etc. Compared with the existing seismic observation network, this system has shown advantages in microseismic detection and analysis capabilities and processing efficiency. It is particularly suitable for specific areas or fields that require intensive monitoring. Currently, three real-time microseismic monitoring systems have been established: 1. Chihshang real-time microearthquake monitoring system (2022CSN-RT-MEMS), which observes the background microseismic activity of the creeping segment of the Chihshang fault, including the 2022 M6.9 Chihshang earthquake sequence (Sun et al., 2024); 2. Hualien earthquake real-time microseismic monitoring system (2024HL-RT-MEMS), which continuously observes the changes in the aftershock sequence of the 2024 M7.2 Hualien earthquake; 3. the Chia-Nan real-time microseismic monitoring system (2025CN-RT-MEMS), that this system was established in early 2025 to observe the main aftershock sequence of medium and large earthquakes in the area including the 2025 M6.4 Dapu earthquake sequence (Kuo-Chen et al., 2025). RE-MEMS can quickly provide changes in seismic activity and establish a long-term earthquake catalog. After further data processing (such as absolute or relative relocation), the earthquake catalog will help the subsequent interpretation of earthquake tectonic structures and other earthquake parameter studies, such as focal mechanism, earthquake magnitude, and three-dimensional velocity model inversion. In summary, RT-MEMS serves as an effective reinforcement for the current earthquake observation network, significantly improving the timeliness and resolution of earthquake observation.

Keywords: real-time microearthquake monitoring system; deep learning; SeedLink; automated workflow; earthquake catalog

References

Kuo-Chen H., et al. (2025). Real-time earthquake monitoring with deep learning: A case study of the 2025 M6.4 Dapu earthquake and its fault system in southwestern Taiwan. The Seismic Record, 5(3), 320-329, https://doi.org/10.1785/0320250023.

Sun, W. F., et al. (2024). Deep learning-based earthquake catalog reveals the seismogenic structures of the 2022 M_W 6.9 Chihshang earthquake sequence. Terr. Atmos. Ocean. Sci., 35, 5, https://doi.org/10.1007/s44195-024-00063-9.

Sun, W. F., et al. (2025). A Deep-Learning-Based Real-Time Microearthquake Monitoring System (RT-MEMS) for Taiwan. Sensors, 25(11), 3353. https://doi.org/10.3390/s25113353.

How to cite: Sun, W.-F., Pan, S.-Y., Liu, Y.-H., Kuo-Chen, H., Ku, C.-S., Lin, C.-M., Fu, C.-C., Wen, S., and Kuo, Y.-T.: GEOthermal SEISmic AI Platform (GEOSEIS-AI): A Deep-Learning-Based Real-Time Microearthquake Monitoring System (RT-MEMS) for Taiwan, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16026, https://doi.org/10.5194/egusphere-egu26-16026, 2026.

Deep mineral exploration in high-altitude permafrost regions, such as the Qinghai-Tibet Plateau, faces severe challenges due to complex topography, fragile ecosystems, and intense industrial noise. While passive seismic reflection imaging offers an eco-friendly alternative to active sources, its reliability is often compromised in active mining areas where the ambient noise field is strongly directional and non-stationary, violating the stationary phase assumption required for interferometry.

In this study, we present a successful application of passive seismic reflection imaging at the Huoshaoyun super-large lead-zinc deposit (>5,000 m elevation) in Xinjiang, China. To overcome the artifacts induced by strong directional noise (e.g., heavy mining trucks and machinery), we propose a novel wavefield reconstruction method based on Directional Energy Balancing in the frequency-wavenumber (f−k) domain. Unlike traditional linear stacking, our approach introduces a Directionality Index (DI) to quantify the energy asymmetry of noise slices. We implement a "bucket balancing" weighting strategy that actively screens and balances the noise energy flux, constructing a virtual isotropic illumination environment. This process effectively suppresses spurious artifacts and significantly enhances the signal-to-noise ratio of body-wave reflections.

Utilizing 31 days of continuous waveform data from a dense linear array of 500 short-period seismometers, we retrieved high-resolution reflection profiles reaching 2 km depth. The imaging results clearly reveal the spatial geometry of ore-controlling syncline structures and interlayer fracture zones. These geophysical interpretations were validated by subsequent drilling, demonstrating a high consistency with geological facts. Our findings indicate that the proposed directional balancing strategy can turn "noise into signal" even in strongly heterogeneous noise environments, providing a robust, low-cost, and non-invasive solution for deep resource exploration in extreme environments.

How to cite: Jin, Z. and Wang, Z.: Passive Seismic Reflection Imaging in Active Mining Environments: A Directional Energy Balancing Strategy Applied to the Huoshaoyun Deposit, Tibet Plateau, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16335, https://doi.org/10.5194/egusphere-egu26-16335, 2026.

Geothermal exploration in tectonically active regions requires reliable imaging of subsurface structures, fracture systems, and potential heat sources. Seismic methods play a critical role in providing key constraints on buried fault geometry and geothermal-related structures.

This study applies an AI-assisted seismic workflow to seismic tomography for evaluating geothermal potential in the Western Foothills of Taiwan.Earthquake catalogs generated using AI-based detection and phase-picking algorithms were used as inputs for finite-difference travel-time tomography to construct three-dimensional P- and S-wave velocity models from the surface to 8 km depth, with an approximate spatial resolution of 1 km in the upper 6 km.

Two geothermal areas were investigated: the Tai’an area in central Taiwan and the Baolai area in southwestern Taiwan, both characterized by prominent hot spring outcroppings. A total of 63 and 49 seismic stations, respectively, recorded one month of continuous data in each area. The tomography results reveal shallow seismicity mainly distributed between 3 and 7 km depth, closely associated with mapped active faults from geological investigations. High-velocity anomalies (Vp > 5.2 km/s) observed at depths of 2–5 km are interpreted as uplifted crystalline basement or competent metamorphic rocks related to orogenic processes.

These shallow high-velocity bodies likely act as geothermal heat sources and structural controls for fluid circulation, explaining the development of surface hot springs. Our results demonstrate that AI-assisted seismic tomography provides an efficient and practical framework for geothermal exploration in complex tectonic environments.

How to cite: Guan, Z.-K., Kuo-Chen, H., Sun, W.-F., and Pan, S.-Y.: GEOthermal SEISmic AI Platform (GEOSEIS-AI):AI-assisted Seismic Tomography for Geothermal Exploration in the Western Foothills of Taiwan, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17354, https://doi.org/10.5194/egusphere-egu26-17354, 2026.

Accurate subsurface characterization is fundamental to the successful development of geothermal systems. Such comprehensive knowledge allows determining geological structures that govern local fluid circulation and heat transport. As drilling represents one of the largest cost factors in geothermal development, ensuring that wells target zones of high hydraulic conductivity and permeability can substantially reduce exploration risk and overall project costs. Passive seismic techniques, being both inexpensive and non-invasive, have proven to be effective tools for both geothermal exploration and monitoring. Among them, Horizontal-to-Vertical spectral ratios (H/V) are often used to map subsurface topography. Their interpretation and inversion, however, often rely on prior knowledge of local shear-wave velocity or subsurface layering.