The amount of CO₂ taken up by plants (gross primary production) is the largest flux in the terrestrial carbon cycle. However, the uncertainty in how much CO₂ plants absorb is larger than annual anthropogenic CO₂ emissions. This means that small changes in plant uptake could drastically alter the carbon balance, making climate predictions more challenging. A better understanding of the terrestrial carbon cycle is essential for predicting future climate conditions and atmospheric CO₂ mole fractions. Stable isotope measurements of CO₂ (δ¹³C and δ¹⁸O) provide valuable insights into the magnitude of CO₂ fluxes between the atmosphere and biosphere.

Recent advancements in measurement techniques have made it possible to measure ∆^′17O in atmospheric CO₂ with high precision. These high-precision measurements provide valuable constraints on terrestrial carbon fluxes that δ¹³C and δ¹⁸O alone could not achieve. This is because ∆^′17O(CO₂) has a known stratospheric source, its variations are much smaller than those of δ¹⁸O, and conventional biogeochemical processes follow a well-defined three-isotope fractionation slope. Additionally, the triple oxygen isotope fractionation slopes for specific processes are independent of source water isotope composition, insensitive to temperature, and process specific.

In this talk, I will discuss the broader applications of ∆^′17O in atmospheric CO₂ research, the challenges associated with high precision ∆^′17O measurements, the latest advancements in measurement techniques, and future implications for studying the terrestrial carbon cycle.

How to cite: Adnew, G. A.: ∆′17O of Atmospheric CO2 as a tracer for gross fluxes of terrestrial carbon cycle, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3819, https://doi.org/10.5194/egusphere-egu25-3819, 2025.

The ocean carbon cycle is a critical component of the climate system. Each year, the ocean absorbs approximately a quarter of the CO₂ emitted to the atmosphere from human activities, playing a vital role in mitigating climate change. The ocean will ultimately sequester the majority of these emissions over centuries and beyond, thus regulating atmospheric CO₂ concentration and climate stabilisation in the long term. Understanding the mechanisms and drivers of the observed trends and variability in ocean carbon storage is therefore essential for reducing uncertainty in long-term climate projections.

Trends and variability in ocean carbon storage arise from a complex interplay of factors, including atmospheric CO₂ growth, warming, ocean acidification, physical ocean dynamics, and marine ecosystem changes. While the physico-chemical effects of warming and ocean acidification on the ocean carbon cycle are well-known, the impacts of large-scale changes in ocean circulation remain less well understood. Notably, shifts in surface winds over the Southern Ocean and a weakening Atlantic Meridional Ocean Circulation could induce important changes in carbon storage that are poorly quantified. Changes in marine ecosystems under multiple stressors and their effect on the marine carbon cycle remain poorly constrained and were categorized as a “known-unknown” in the last four assessment reports of the Intergovernmental Panel on Climate Change (IPCC).

In this lecture, I will synthesise recent understanding of the drivers of trends and variability in ocean carbon storage, focusing on timescales ranging from years to centuries. I will present new insights into how marine ecosystem shape carbon dynamics and discuss how changes in ecosystems could influence the ocean carbon storage well beyond 2100. These insights underscore the need to develop new and better integrated “Ocean Systems Models” that include more detailed representations of marine ecosystems and their interactions with biogeochemical cycles.

How to cite: Le Quéré, C.: Carbon storage by the ocean in a changing climate, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9776, https://doi.org/10.5194/egusphere-egu25-9776, 2025.

Alpine treeline ecotones are extremely vulnerable to climate change, making them important early warning systems in climate research. Advanced remote sensing tools, such as Light Detection and Ranging (LiDAR), enable detailed mapping and monitoring of these high-altitude zones, offering critical baseline data for future change detection. This study combines ground-based Terrestrial Laser Scanning (TLS) and space borne Global Ecosystem Dynamics Investigation (GEDI)- LiDAR data to analyze the structural attributes and delineate the position of alpine treelines in the Tungnath Himalaya, India, located at elevations between 3252 and 3,590 meters above mean sea level (a.m.s.l).  TLS provided high-resolution three-dimensional data on alpine vegetation, including tree height, diameter at breast height (DBH), and canopy structure. Using an automated algorithm, 84.84% of individual trees were segmented from TLS data. TLS-derived tree height and DBH estimates achieved root mean square errors of 44.74 cm and 78.45 cm, respectively, compared to field-measured values. A semi-automated method using GEDI LiDAR identified trees taller than 3 meters to delineate the treeline, achieving a positional accuracy of ~ ±40 m a.m.s.l when validated against TLS-derived data.  The results show that combining TLS with GEDI provides a non-destructive and effective method for assessing treeline structure and location in the Indian Himalaya. Future research might use multi-temporal LiDAR datasets to track treeline movements and obtain a better understanding of the long-term effects of climate change on alpine ecosystems.

How to cite: Mathew, J., Singh, C. P., Solanki, H., and Sedha, D.: Mapping Alpine Treeline Ecotones in the Tungnath Himalaya Using Terrestrial Laser Scanning and GEDI LiDAR, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-208, https://doi.org/10.5194/egusphere-egu25-208, 2025.

The accelerated pace of urbanization, population growth, and extensive land-use changes has significantly disrupted the ecological balance and functionality of riverine wetland ecosystems, leading to substantial degradation of wetland health. This study evaluates the health and resilience of the Upper Ganga Riverine Wetland (UGRW) in India, which has experienced significant land-use transformations over the past two decades. The analysis highlights the wetland's resilience to various natural and anthropogenic stresses and its ability to sustain critical ecosystem services, including provisioning, regulating, cultural, and supporting services. The findings reveal drastic land-use and land-cover (LULC) changes, with built-up areas increasing by 245%, while forest and wetland areas decreased by 41% and 8%, respectively, between 2000 and 2020. These transformations have led to a marked decline in ecosystem resilience (23%) and a substantial reduction in ecosystem service values (ESVs), which decreased from 2138.28 million USD in 2000 to 1769.16 million USD in 2020—an overall loss of 18%. Urban expansion, deforestation, and wetland fragmentation have further exacerbated the decline in wetland health, diminishing its ecological balance and capacity to deliver vital services. This study underscores the urgent need for integrated environmental management strategies to mitigate the impact of LULC changes, conserve wetland ecosystems, and enhance their resilience. By assessing ecosystem services and their dependence on sustainable land use, this research provides critical insights for policymakers and stakeholders. It emphasizes the necessity of balancing developmental priorities with ecological preservation, offering a strategic framework to foster sustainability and resilience in one of India’s most vital riverine landscapes.

How to cite: Yadav, A., Kansal, M. L., and Singh, A.: Wetland Health in Transition: Resilience and Ecosystem Services Amid Urbanization and Land-Use Change, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-885, https://doi.org/10.5194/egusphere-egu25-885, 2025.

Nitrous oxide (N₂O) is the most important stratospheric ozone-depleting gas of the 21^st century. Most N₂O emissions occur in soils and are associated with agricultural activities. Ammonia (NH₃) is not a greenhouse gas, but it can indirectly contribute to greenhouse gas emissions. NH₃ volatilization is an important indirect N₂O emission pathway in agricultural systems. In addition, NH₃ can have significant effects on both human health and the natural environment, and its emissions negatively affect biodiversity. A meta-analysis was conducted to evaluate NH₃ and N₂O losses and the effectiveness of adding urease and nitrification inhibitors on direct N₂O emissions and NH₃ volatilization. Data were used from 14 separate studies that simultaneously investigated direct N₂O emissions and NH₃ volatilization from irrigated wheat. All studies were conducted on irrigated wheat in semi-arid climates and on calcareous soils with urea application. The average direct N₂O emission factor for irrigated wheat was 0.4%. Our results showed that, on average, nitrification inhibitors reduced direct N₂O emissions by 35% and increased NH₃ volatilization by 29%. The average NH₃ emission factor was 32% and urease inhibitors reduced NH₃ volatilization by 41%. The results showed that indirect N₂O emissions from NH₃ volatilization should be considered in these conditions.

How to cite: Mirkhani, R., Jabbari Malayeri, M., Naserian Khiabani, B., Mousavi, S. M., Ghafariyan, M. H., Ghavami, M. S., Dercon, G., Shorafa, M., and Kheng Heng, L.: Meta-analysis of direct nitrous oxide emissions and ammonia volatilization from irrigated wheat in calcareous soils under semi-arid conditions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1026, https://doi.org/10.5194/egusphere-egu25-1026, 2025.

Seasonally different precipitation infiltration under monsoon humid areas may drive changes of groundwater flow systems and possible nitrate transformation processes in groundwater. In this study, dissolved greenhouse gases, noble gases concentrations (N₂ and Ar) and isotopes of N₂O were used to quantitively identify nitrification and denitrification to reveal spatial and temporal characterization of nitrate transformation in typical groundwater flow profiles in the Qingyi River basin, east China. In dry and wet seasons, the recharge altitudes of groundwater were distinctive and dominant nitrate transformation processes differed spatially and temporally. According to the N₂-Ar estimation, the recharge altitudes of groundwater in dry season were higher than those in wet season, indicating obviously less proportion of precipitation from lower altitudes and relatively increased proportion of recharge from regional recharge areas in dry season, whereas local groundwater flow systems were preferentially developed in wet season. Denitrification is commonly observed in groundwater during the dry season, with positive Excess-N₂ concentrations and phenomena that N₂O concentrations initially accumulate with progress of denitrification but later decrease due to enhanced N₂O reduction. In the wet season, nitrification is the dominant process in groundwater, with only a small portion of groundwater exhibiting denitrification, resulting in positive Excess-N₂ concentrations. In this case, N₂O concentrations initially increase during nitrification but later decline due to incomplete denitrification. Quantitative results based on δSP-N₂O isotopes indicated that the maximum contribution of nitrification in groundwater during the wet season ranged from 52.8% to 100%, with an average of 77.3%. The contributions from denitrification and N₂O reduction in wet season are limited, which is consistent with results identified by nitrate and ammonium isotopes. Spatially, due to more reducing redox environment in regional groundwater flow systems, the denitrification progress (DP) in most groundwater in discharge zones exceeds 99%, with denitrified NO₃⁻ concentrations reaching up to 25.72 mg/L, significantly higher than the average DP values in recharge zones (27.7%) and transition zones (31.6%).

How to cite: Huang, X.: Identification of nitrification and denitrification along groundwater flow paths using dissolved N2, Ar, and N2O in typical groundwater flow systems in the Qingyi River basin, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1233, https://doi.org/10.5194/egusphere-egu25-1233, 2025.

Climate change is expected to alter the frequency and intensity of extreme events, modifying the natural disturbance regimes to which ecosystems are currently adapted. Here, we present a spatially explicit risk index for mangroves and their associated biodiversity and ecosystem services based on projected frequency changes of tropical cyclone wind speeds and rates of relative sea level rise under SSPs 245, 370 and 585 by 2100.

To compute the risk index, we calculate the relative change of tropical cyclone frequency across different wind speed intensity categories based on probabilistic tropical cyclone tracks downscaled from 3 different CMIP6 models of varying climate sensitivity. This data is then combined with thresholds of sea level rise which are estimated to exceed mangrove adaptive capacity and mapped onto global mangrove extents.

Globally, approximately half of the total mangrove area (40-56% depending on the SSP) will be at high to severe levels of risk due to climate-modified tropical cyclone disturbance regimes. Further, we find mangrove areas with high levels of biodiversity and ecosystem services provision, including coastal protection for people and assets, carbon sequestration, and fishery benefits, are at proportionally higher levels of risk than mangrove forests generally. We also identify mangrove areas which are projected to experience non-analog tropical cyclone disturbances in the future. Our findings emphasize the need to anticipate changes in natural disturbance regimes to adapt ecosystem management, sustain ecosystem services in the future, and fully realize mangroves’ potential as nature-based solutions (NBS).

How to cite: Hülsen, S., Dee, L., Kropf, C., Meiler, S., and Bresch, D.: Mangroves and their services are at risk from climate-modified tropical cyclones and sea level rise , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1419, https://doi.org/10.5194/egusphere-egu25-1419, 2025.

   Abstract

This study explores advanced remote sensing, geophysical, and geospatial methodologies applied to the geologically diverse Aït Semgane region in Morocco. A multi-disciplinary approach was adopted, combining (1) automated lineament extraction using Digital Elevation Models (DEMs) and various topographic indices, (2) lithological classification leveraging machine learning algorithms on multispectral data, and (3) the integration of magnetic data to enhance geological interpretation.

For lineament analysis, approaches such as the Topographic Position Index (TPI), Hillshade, and shading models were applied to datasets including SRTM, ALOS PALSAR, and Sentinel-1 InSAR. Results highlighted the TPI method’s high sensitivity in detecting tectonic features, especially in NE-SW and E-W orientations, aligning with established geological knowledge. Cartographic analysis revealed fault density concentrations in the NW and southern sectors, confirming the tectonic complexity of the region.

Lithological classification was conducted using Support Vector Machines (SVM), Random Trees (RT), and Artificial Neural Networks (ANN) applied to Landsat 9 and Sentinel-2 data. SVM, particularly with Minimum Noise Fraction (MNF) transformation, consistently outperformed other algorithms, achieving high classification accuracies and well-defined lithological boundaries. The integration of dimensionality reduction techniques like MNF proved crucial for enhancing classification quality, while PCA showed limited efficacy.

Magnetic data were incorporated to validate and refine the tectonic and lithological interpretations, offering additional insights into subsurface structures and enhancing the understanding of fault systems and mineralized zones.

This research demonstrates the synergy between automated lineament extraction, machine learning-based lithological mapping, and magnetic data for improving geological analysis. The methodologies applied here have practical implications for mineral exploration and tectonic studies, offering robust tools for mapping complex terrains. Future research will aim to refine dimensionality reduction techniques, explore hyperspectral datasets, and further integrate geophysical data to enhance geological mapping accuracy.

How to cite: El-Omairi, M. A. and El Garouani, A.: Integrating Automated Lineament Extraction, Magnetic Data, and Machine Learning-Based Lithological Mapping in the Anti Atlas, Morocco, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2041, https://doi.org/10.5194/egusphere-egu25-2041, 2025.

Tidal wetland reclamation could profoundly alter ecological function and ecosystem service provision, but its impacts on sediment microbial communities and functions remain poorly understood. We investigated spatial and seasonal patterns of greenhouse gases (GHGs) production response to land-use changes in mangrove wetlands and unraveled the underlying mechanisms by integrating environmental parameters and microbial communities. Land-use changes substantially reduced microbial community richness and diversity and shaped their composition. Converting mangrove to drier orchard and vegetable field reduced sediment organic matter, carbon GHGs production rates, and microbial network complexity and stability, while increased N₂O production rates. Converting mangrove to chronically flooded aquaculture pond increased sediment CH₄ production rates, but reduced N₂O and CO₂ production rates. Although increasing anthropogenic disturbance in aquaculture pond have reduced microbial community richness and diversity compared to native mangrove wetland, they have increased complexity of species associations resulting in a more complex and stable network. Microbial community richness and network complexity and stability were strongly related to CH₄ and N₂O production rates, but not significantly associated with CO₂ production rates, suggesting microbial community richness, network complexity and stability are better predictors of the specialized soil/sediment functions CH₄ and N₂O production). Therefore, preserving microbial “interaction” could be important to mitigate the negative effects of microbial community richness and diversity loss caused by human activities. Furthermore, as the residual bait accumulation is a severe issue in aquaculture activities, we especially focused on the influence of bait input at time scale through a 90-day incubation experiment, aiming to observe temporal variations of physicochemical properties, sediment microbial community, and GHGs production in response to different amounts of bait input. The results showed that dissolved oxygen of overlying water was profoundly decreased owing to bait input, while dissolved organic carbon of overlying water and several sediment properties (e.g., organic matter, sulfide, and ammonium) varied in reverse patterns. Meanwhile, bait input strongly altered microbial compositions from aerobic, slow-growing, and oligotrophic to anaerobic, fast-growing, and copiotrophic. Moreover, both GHGs production and global warming potential were enhanced by bait input, implying that aquaculture ecosystem is an important hotspot for global GHGs emission. Overall, bait input triggered quick responses of physicochemical properties, sediment microbial community, and GHGs production, followed by long-term resilience of the ecosystem. Future research should comprehensively consider microbial diversity, species composition and interaction strength, functions, and environmental conditions to accurately predict soil/sediment functioning and emphasize the necessity of sustainable assessment and effective management.

How to cite: Lin, G. and Lin, X.: Responses of greenhouse gases production to land-use change and the underlying microbial mechanisms in mangrove wetlands, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2079, https://doi.org/10.5194/egusphere-egu25-2079, 2025.

Forested upstream watersheds support clean freshwater and maintaining stable hydrological conditions of ecosystem services. The associations between vegetation growth and climatic variations play a vital role on hydrological regimes that are region-dependent, but the associations of climate-phenology-hydrology have rarely been investigated in tropical/subtropical regions particularly. In this analysis, the hydroclimate records (1991-2020) at two long-term studied forest watersheds, Fushan (FS) and Leinhuachi (LHC) experimental forest, Taiwan were used, and showed that the incidences of meteorological and hydrological droughts are becoming prominent after 2001. We further investigated the effects of monthly climate variables (temperature and precipitation) on vegetation growth using monthly PV (photosynthetic vegetation fraction) of a watershed derived from MODIS (Moderate Resolution Imaging Spectroradiometer), and examined the effects of spring and summer rainfall on the variations of vegetation phenological patterns and subsequent watershed streamflow during 2001–2020. The PV and temperature showed a linear relationship without time-lag effect (R² = 0.51-0.57, p < 0.001), whereas PV and precipitation exhibited no time-lag in FS but a log-linear relationship with 2-month lag (R² = 0.15-0.59, p < 0.001) existed in LHC, indicating the accumulation of rainfall during relatively dry season (winter-spring) was critical for vegetation growth. Structural equation modeling (SEM) revealed that earlier start of growing season (SOS) caused by relatively high spring rainfall (February-March) led to longer growing season (LOS) and higher P-Q deficit (precipitation minus runoff) during the growing season in LHC. Nevertheless, the large amount of precipitation during growing season has no effect on the end of growing season (EOS), LOS and P-Q deficit. Neither EOS has influence on LOS and P-Q deficit. However, these patterns were not found in FS. Understanding the vegetation responses to climatic variations is required for future hydrologic regime projections, especially under changing climate.

How to cite: Chang, C.-T., Lee, J.-Y., Chiang, J.-M., Wang, H.-C., Huang, C., and Huang, J.-C.: Hydrological responses to vegetation-climate interactions at two subtropical forested watersheds of Taiwan, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2383, https://doi.org/10.5194/egusphere-egu25-2383, 2025.

Surfactants are extensively utilized across agriculture, pharmaceuticals, and environmental remediation due to their ability to modify surface and interfacial properties. In horticulture, wetting agents and synthetic surfactants are commonly employed to mitigate water repellency in organic growing media, particularly peat-based substrates. These agents are known to aid the substrate’s wettability and improve physical and hydraulic properties, optimizing plant growth and productivity. However, environmental persistence and the potential ecotoxicity of synthetic surfactants have raised significant concerns, highlighting the need for sustainable alternatives. Biosurfactants, particularly rhamnolipids, have gained considerable attention for their biodegradability and surface-active properties both at the scientific and commercial levels. Despite their potential, a comprehensive understanding of the interaction between rhamnolipid and peat essential for assessing its environmental fate and behavior is inadequate. In this regard, the main objective of this study is to quantify the sorption and desorption dynamics of rhamnolipid in peat using batch equilibrium and kinetic experiments to evaluate its suitability as a surfactant for horticultural systems, optimize application strategies, and assess the transport behavior and environmental implications of residual surfactants. Kinetic analysis revealed rapid initial adsorption followed by a gradual approach to equilibrium, with the adsorption and desorption kinetics being well described by the Elovich equation, indicating a chemisorption-dominated process. Furthermore, desorption followed both the Elovich and pseudo-first-order models, illustrating a complex and rate-dependent release process likely influenced by heterogeneous retention of rhamnolipid on the peat surface. Equilibrium analysis demonstrated that the adsorption data were best fitted by the Freundlich model, reflecting the heterogeneous nature of the peat surface and the complexity of its adsorption sites. Sequential desorption experiments exhibited notable hysteresis with reduced desorption efficiency, suggesting strong retention of rhamnolipid on the peat particles. These findings highlight the potential of rhamnolipid as a sustainable alternative to synthetic surfactants for mitigating water repellency in peat-based growing media. Equilibrium and kinetic modeling results will be presented with a comprehensive discussion of their practical implications, providing critical insights into their environmental significance and potential applications in horticultural systems.

Keywords: Water repellant peat, sorption, rhamnolipid biosurfactant

How to cite: Duggireddy, R. and Arye, G.: Sorption Behavior of Rhamnolipid Biosurfactant on Peat, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2449, https://doi.org/10.5194/egusphere-egu25-2449, 2025.

Human activities have increased nitrogen (N) and phosphorus (P) deposition, disrupting microbial activity and altering N-P cycling. Understanding how nutrient limitations and additions affect soil microbes is critical for predicting ecosystem succession and mitigating greenhouse gas emissions. Leveraging long-term N-P addition experiments in a subtropical forest, we developed an enhanced Microbial-ENzyme Decomposition (MEND) model by incorporating an enzyme-mediated P module. Following rigorous calibration and validation with multi-source data, we found that N-P addition has antagonistic effects on main fluxes, with P application mitigating N stimulation of fluxes and partially reducing N₂O emissions. On this basis, we refined the nitrogen saturation hypothesis (NSH) for subtropical ecosystems by attributing divergent nitrification patterns to ammonia inhibition, and we expanded the hypothesis to encompass denitrification and N fixation. By integrating microbiome data, we demonstrated the intrinsic effects of N addition on N cycle through differential expression of genes due to community change, while P addition can counteract effects of N increase by alleviating microbial P limitations. Additionally, we highlight the significance of microbial-enzyme activities feedback in regulating P cycle to maintain ecological balance. Integrating microbially-enabled C-N-P model with diverse experimental data, particularly microbiome information, enhances interpretability and reveals ecosystem mechanisms beyond direct experimental observation.

How to cite: Lv, Z.: Refining the nitrogen saturation hypothesis by accounting for microbial roles in nitrogen and phosphorus cycling, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2779, https://doi.org/10.5194/egusphere-egu25-2779, 2025.

Inland waters are an important source of greenhouse gas methane (CH₄). The production of CH₄ is influenced by various factors, including the concentration of dissolved organic matter (DOM), redox conditions, and the composition of microbial communities, with clear spatiotemporal heterogeneity in inland waters. Refractory DOM (RDOM) can resist rapid biodegradation and preserve up to thousands of years; therefore, it is important for assessing the natural carbon sequestration potential of aquatic ecosystems. As a critical part of carbon biogeochemical processes in inland waters, the production of CH₄ and RDOM depends on the microbial successive processing of organic carbon. However, it is unclear yet the link of these two processes and the underlying microbial regulation mechanisms. Therefore, a large-scale survey was conducted in China’s inland waters, with the measurement of CH₄ concentrations, DOM chemical composition, microbial community composition, and relative environmental parameters mainly by chromatographic, optical, mass spectrometric, and high-throughput sequencing analyses, to clarify the abovementioned questions. Here, we found a synchronous production of CH₄ and RDOM linked by microbial consortia in inland waters. The increasing microbial cooperation driven by the keystone taxa (mainly Fluviicola and Polynucleobacter) could promote the transformation of labile DOM into RDOM and meanwhile benefit methanogenic microbial communities to produce CH₄. This process was also influenced by environmental factors such as total nitrogen and dissolved oxygen concentrations. Future studies need to combine more field investigations and laboratory control experiments to fully understand these complex processes. This study deepened the understanding of microbial-driven carbon transformation and highlighted the role of microbial keystone taxa in these processes, providing some useful references for the future laboratory control experiments (e.g., the selection of microbial species). Considering that CH₄ emission and RDOM production are closely related to the carbon source-sink relationship, this finding will help to more accurately evaluate the budget in inland aquatic ecosystems.

How to cite: Shi, X., Li, W., Wang, B., Yang, M., and Liu, C.-Q.: Keystone taxa drive the synchronous production of methane and refractory dissolved organic matter in inland waters, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4681, https://doi.org/10.5194/egusphere-egu25-4681, 2025.

Pollution places an 'everlasting' burden on brownfields, with a lot of money going towards the management of sites where nothing happens. Action is administratively unattractive, and managers and area developers find it difficult to connect. The development of the surrounding area is also halted. This limitation is becoming increasingly urgent with the growing spatial pressure due to the energy transition, climate adaptation, and housing needs. However, much more is possible than has been achieved so far; redevelopment is often indeed possible.

Public and private parties can work on upgrading brownfields. This can also generate money to better manage risks. In many places, developing parks to make surrounding residential areas more attractive is popular. Parks also play a role in climate adaptation and increasing biodiversity. Solar panels can be installed along the edges of the park in such a way that greenery is also possible underneath.

Altogether, there are twelve known functions that can upgrade brownfields. The value increases if two or more functions enable each other, such as greenery and solar panels. Upgrading brownfields can be done singly, but can also be multiple by stacking functions. What does this yield, and how do you do that, especially how do you finance a multiple project? The paper discusses the multiple redevelopment of former landfills and particularly the financing thereof.

How to cite: van der Heijden, J.: Multiple Redevelopment of Brownfields, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4724, https://doi.org/10.5194/egusphere-egu25-4724, 2025.

Abstract
Peatlands are important global terrestrial carbon (C) sink. Most of Irish peatlands have been 
influenced in past by anthropogenic management, primarily through drainage for forestry, 
agriculture, or energy and horticultural extraction. Given the recent Irish peatland restoration 
activities, it is essential to deepen our understanding of the key drivers of peatland C-dynamics 
and to improve methodologies for reporting and verifying terrestrial CO₂ removals/emissions 
from drained and restored peatlands. The dependency of CO₂ fluxes on water-table (WT) levels 
in peatland ecosystems, under different land-use (LU), has been recognised in existing literature 
[1], indicating on the importance of accounting for WT variable in predictive models. This study 
focuses on assessing the application of random forest (RF) to predict WT in total eight Irish 
peatland sites under different LU (natural, rewetted, forest, grassland), which were monitored - 
i.e. low-level Irish blanket-bog sites from Co. Mayo and raised-bog sites from Co. Offaly [2]. The 
RF was chosen due to its ability to effectively manage mixed-data (numerical and categorical) and 
to provide robust predictions without the need for extensive data-preprocessing. Used were the 
data from ca. 2017 to 2020 on-site measurements [2], as well as the selected geospatial data 
derived from E-OBS daily grided-meteorological dataset [4]. The RF was applied to a number of 
numerical and categorical variables, by splitting the data into training- and testing-datasets. 
Hyperparameter tuning was done using ‘caret’ R-package [5]. Model evaluation (using 
performance metrics) was conducted on WT-predictions from testing-dataset. While findings 
from this study on selected eight Irish peatland sites indicate a relatively good potential of RF to 
predict WT (R² = 0.78), the work highlights the importance of assessing the ‘variable importance’ 
to reduce the number of variables in the model for practical applicability purposes, as well as to 
include more sites.

Acknowledgements
The authors are grateful to the Irish Environmental Protection Agency (EPA) for funding projects 
CO2PEAT (2022-CE-1100) and AUGER (2015-CCRP-MS.30) [EPA Research Programmes 2021-
2030 and 2014–2020], and to University of Limerick funding.

References
[1] Tiemeyer, B., et al., 2020. A new methodology for organic soils in national greenhouse gas inventories: Data synthesis, derivation and application,
Ecological Indicators, Vol. 109, 105838,  https://doi.org/10.1016/j.ecolind.2019.105838.
[2] Renou-Wilson, F., et. al, 2022. Peatland Properties Influencing Greenhouse Gas  Emissions and Removal (AUGER Project) (2015-CCRP-MS.30), EPA Research Report, Irish Environmental Protection Agency (EPA) https://www.epa.ie/publications/research/climate-change/Research_Report_401.pdf.
[3] Premrov, A., et.al, 2023. Insights into the CO2PEAT project: Improving methodologies for reporting and verifying terrestrial CO₂ removals and emissions from Irish peatlands. IGRM2023, Belfast, UK. https://www.researchgate.net/publication/369061601_Insights_into_the_CO2PEAT_project_Im
proving_methodologies_for_reporting_and_verifying_terrestrial_CO2_removals_and_emissions
_from_Irish_peatlands.
[4] Copernicus Climate Change Service, Climate Data Store, (2020): E-OBS daily gridded meteorological data for Europe from 1950 to present derived from in-situ observations. Copernicus Climate Change Service (C3S) Climate Data Store (CDS). https://doi.org/10.24381/cds.151d3ec6.
[5] Kuhn, M. 2008. Building Predictive Models in R Using the caret Package. Journal of Statistical Software, 28(5), 1–26. https://doi.org/10.18637/jss.v028.i05.

How to cite: Premrov, A., Yeluripati, J., Renou-Wilson, F., Walz, K., Byrne, K. A., Wilson, D., Hyde, B., and Saunders, M.: Assessing the application of random forest (RF) to predict water-table (WT) in selected Irish peatlands, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5122, https://doi.org/10.5194/egusphere-egu25-5122, 2025.

Gap dynamics is one of the key drivers of forest succession in temperate forests. The primary successional trajectory involves the transition from early to late successional species, each with distinct trait characteristics. I will present a modeling approach to forest successional dynamics based on scaling plant traits from individual to community levels. In this work, the shade tolerance index is statistically linked with plant traits that characterize early and late successional species using the U.S. Forest Inventory dataset. Discrete and continuous mathematical models, represented by Markov chains and autoregressive models, are employed to predict forest dynamics. An individual-based model is also used to assess the robustness of this scaling approach under different disturbance regimes. Overall, modeling forest successional dynamics based on the scaling of shade tolerance-related functional traits from the individual to the ecosystem level addresses major limitations of models based on the traditional stand age metric.

How to cite: Strigul, N.: Plant Trait-Based Modeling of Forest Succession, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6451, https://doi.org/10.5194/egusphere-egu25-6451, 2025.

Global Ecosystem Dynamics Investigation (GEDI) mission, operating from International Space Station, is a full-waveform LiDAR measuring vertical 3-dimensional structure of terrestrial ecosystems. The vertical canopy cover (CC) available from the GEDI L2B product has applications in forest ecosystem, forest health and climate change studies, and management practices. Some studies have assessed the accuracy and uncertainty of the GEDI vertical canopy cover profile product using aerial LiDAR scans and in-situ measurements. However, in-situ measurements taken using angle-of-view effectively produces canopy closure whereas GEDI measures vertical CC. Cajanus tube, regarded as ideal canopy cover measurement technique, is time consuming and impractical for larger areas. In this study, suitable in-situ canopy cover measurement methodologies were assessed alongside GEDI vertical CC. Canopy cover measurements were taken under GEDI footprints in the Indian Western Himalayan region using spherical densiometer, hemispherical photographs and digital canopy photographs with narrow angle-of-view. The plot dimensions were adjusted to accommodate horizontal geolocation uncertainty of GEDI version 2 data products. Following data collection, measurement techniques were assessed based on R-squared, RMSE and MAE.

How to cite: Paygude, A., Pande, H., and Tiwari, P. S.: Assessment of In-situ Canopy Cover Measurement Techniques and GEDI Vertical Canopy Cover in the Indian Western Himalayan Region, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7236, https://doi.org/10.5194/egusphere-egu25-7236, 2025.

Bound biomarkers, which are covalently linked to kerogen or asphaltene macrostructures, exhibit enhanced stability against mixing effects, contamination, and biodegradation. Although previous studies have noted that the results of bound and free biomarkers in assessing sedimentary environment and maturity are not exactly consistent, specific criteria for assessing bound biomarkers have not been proposed. In this study, microscale sealed vessel catalytic hydrogenation (MSSV-Hy) was used to extract bound biomarkers from shale and compare them with free biomarkers. The study demonstrates the reliability of bound biomarkers indices in evaluating depositional environments and maturity, and it systematically compares the differences between bound and free biomarkers. The results revealed that the maturity assessment of bound biomarkers is lower than that of free biomarkers. Additionally, C29 regular steranes are selectively consumed during rapid heating, resulting in a decrease in the input parameters from terrigenous sources. Adjusted criteria for bound biomarkers can more accurately evaluate the sedimentary environment and maturity of shale.

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How to cite: Yuan, L.: Application of Bound Biomarkers in the Evaluating the Deposition Environment and Maturity of Shale, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7582, https://doi.org/10.5194/egusphere-egu25-7582, 2025.

The seagrass meadows are critical for organic carbon storage and play a significant role in mitigating climate change. However, the ongoing degradation of the seagrass meadows in Thailand reduces their ability to sequester carbon effectively, potentially contributing to greenhouse gas (GHG) emissions. This study examines variations in carbon storage, carbon metabolism, and GHG emissions across degraded, healthy seagrass and bare sand areas along Andaman Sea, Thailand. The average carbon storage within the surface sediment (top 10 cm) varies across seagrass conditions, with the highest carbon storage in heavy degraded (365.2 ± 206 g C m^-2), followed by bare sand (289.5 ± 236 g C m^-2) and healthy seagrass (86.47 ± 5.8 g C m^-2). Furthermore, degraded seagrass and bare sand exhibited heterotrophic ecosystem functions with an average NCP value of 0.44 ± 0.49 and -0.13 ± 0.79 mmol C m⁻² d⁻¹, respectively. Conversely, healthy seagrass maintained autotrophic ecosystem functions with NCP 1.30 ± 0.508 mmol C m⁻² d⁻¹. The average total carbon sink varied among seagrass conditions, with the highest in degraded seagrass (4328 ± 2395 CO₂-eq m⁻² d⁻¹), compared to bare sand (3981 ± 4120 CO₂-eq m⁻² d⁻¹) and healthy seagrass (1630 ± 0 CO₂-eq m⁻² d⁻¹). The study also revealed that CH₄ emissions dominated GHG fluxes in all seagrass conditions, with the highest mean CH₄ fluxes recorded in degraded seagrass (1.16 ± 0.51 µmol m⁻² h⁻¹), followed by bare sand (1.02 ± 0.41 µmol m⁻² h⁻¹) and healthy seagrass (0.48 ± 0.07 µmol m⁻² h⁻¹). On the other hand, the CO₂ emissions remained consistently low in both seagrass meadows (healthy and degraded) and bare sand areas. These findings are important to indicate and provide the baseline of GHG emissions for healthy and degraded tropical seagrass meadows.

Keywords: Blue carbon, Climate Change, Emission, Greenhouse gas, Seagrass meadows

How to cite: Halim, M., Stankovic, M., and Prathep, A.: Estimating the Potential Greenhouse Gas Emission from Degraded Seagrass Meadows: A Case Study from Thailand's Seagrass Ecosystems, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7982, https://doi.org/10.5194/egusphere-egu25-7982, 2025.

Open-cast lignite mining significantly disrupts cultivated soils. Restoration and re-cultivation processes enable the conversion of these disturbed areas back into productive land. These processes involve mixing original topsoil (~20%) with parent material loess (~80%), diluting the organic carbon (C) and nitrogen (N) pools, as well as the soil's biological parameters. To restore soil fertility and physical structure, Phase I includes the cultivation of alfalfa to replenish C and N, re-establish biological functions, and the addition of mineral fertiliser (N:P:K, 15:15:15 kg ha^-1). Following two to three years of Phase I, the restoration transitions to Phase II for three to five years, with an initial application of green waste compost (30 t ha^-1) and annual basal mineral fertiliser (N:P:K, 200:80:60 kg ha^-1). Phase III then involves returning the land to farmers with a typical rotation including sugar beet-winter wheat and a mix of organic and mineral fertilisation.

Previous studies have shown that soil C recovery and several key biological functions have only partially recovered, even after more than 50 years since re-cultivation. However, the evolution of P cycling, especially microbial-mediated P cycling, along this gradient remains unknown. This study aims to investigate interactions between soil P, soil microorganisms, and soil properties that affect microbial P cycling and P availability to plants following mining activity.

Hedley fractionation was employed to estimate various P pool sizes, while ion-exchange kinetics (IEK) assessed P exchangeability and reactivity in eight soils (soils restored from 2022 – year 0 – Phase I, 2020 – year 2 – Phase I, 2018 – year 5 – Phase II, 2014 – year 9 – Phase III, 2006– year 17 – Phase III, 1979 – year 44 – Phase III and 1964 – year 59 – Phase III and an original soil undisturbed). In three key soils (year 0 - Phase I; year 59 - Phase III; original undisturbed soil), ¹⁸O-labeled water was used in incubation to determine the degree of ¹⁸O integration within microbial biomass and in various P fractions.

In Phase I, a decrease in the relative size of the most labile-P pool was observed. In Phases II and III, this proportion increased, notably with a larger NaOH-extractable-P increase. P exchangeability decreased during Phase I, then significantly increased in older soils, surpassing that of the original undisturbed soil. Preliminary results indicate microbial P processing is highly correlated with total soil organic C. For instance, microbial P processing was nearly non-existent in newly formed soil (organic C: 0.54 g kg^-1) and was found to be twice as low in 59-year-old soil (organic C: 1.24 g kg^-1) compared to the original soil (organic C: 1.62 g kg^-1).

The current findings demonstrate that despite measured P levels surpassing those of the original soil in the oldest soils, biologically-driven P cycling has not fully recovered more than 50 years after soil re-cultivation.

How to cite: Raymond, N. S., Tamburini, F., Oberson, A., Reichel, R., and Mueller, C. W.: Microbial phosphorus processing in a gradient of agricultural soil development following mining activity, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8511, https://doi.org/10.5194/egusphere-egu25-8511, 2025.

The increasing frequency and intensity of drought events make them a growing threat for plants that are sensitive to water scarcity. It is therefore important to understand how plants react to drought stress. The willow trees from the short-rotation coppices (SRC) on the DTU-Risø Campus in Denmark (DK-RCW) are particularly sensitive to water shortage as they are rainfed. We address the following question: how do extremely dry conditions affect the willows growth? We study the plants response mechanisms to periods of water scarcity and examine how these responses impact their gross primary productivity (GPP). There is a particular relevance to this in the current context of global warming, where the SRC are used to produce bioenergy and can store carbon to mitigate climate change.

Field measurements were carried out at the DK-RCW site to gather information on canopy structure (leaf area index). These results were integrated into a modelled relationship with carbon flux data from an eddy covariance flux tower located onsite and providing continuous CO₂ and H₂O flux data in more than 10 years. The simple empirical model was used to contrast the GPP’s sensitivity to stomatal and non-stomatal processes by comparison of extreme drought conditions (summer 2018 in Denmark) and wetter conditions (summers 2015 and 2021). These years represent the same stage of the rotational cycle.

This new model enables us to highlight two complementary responses to drought: the trees immediately react by adapting their physiology (stomatal resistance, increased sensitivity to vapour pressure deficit under drought), but also by changing the canopy structure as the drought increases (reduction of the leaf area index) and other responses on canopy photosynthetic capacity. High vapour pressure deficit and the reduction of the leaf area index both reduced the photosynthesis of willow trees under dry conditions. The simulated data imply limited drought recovery after the dry period had ended. For these reasons, the carbon uptake by the willow SRC is lower during droughts and thus limits the SRC productivity and carbon sink strength. We conclude from the very clear results from this case study that different drought response mechanisms must be considered when trying to understand and predict plant responses to extreme drought.

How to cite: Jaujay, M. and Ibrom, A.: Drought sensitivity of gross primary productivity in willow: effects from physiological versus structural responses, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10635, https://doi.org/10.5194/egusphere-egu25-10635, 2025.

Many dioecious plants are dominant foundational species (e.g., grasses, poplars, ginkgoes) that structure ecosystems and provide essential resources for diverse ecological communities. Due to their higher nutrient demands and reproductive costs, female plants generally appear more sensitive to environmental changes, such as increased temperatures and drought conditions. The soil ecosystem is critical for providing the substrate, nutrients, and habitat for terrestrial plant communities to exist. Male and female plants are likely to interact with the soil environment differently, with implications for ecosystem functioning. Recent research has shown that female and male plants differ in their soil microbial diversity and community composition. However, how plant sex affects soil communities is still unknown. This study investigated how female and male plants of Ilex vomitoria differ in fungal diversity and composition and subsequent cascading effects on soil arthropods. Fungal operational taxonomic units (OTUs) were identified from DNA sequencing data, and arthropods were extracted and identified from 91 soil samples collected under the canopies of female and male Ilex vomitoria individuals across three locations in southeastern Texas, USA. We found that male plants of I. vomitoria exhibit higher fungal diversity compared to female plants, with both sexes associating with distinct fungal communities. Conversely, soil arthropod diversity and community composition were affected by location but not plant sex. Our results provide valuable insights into the ecological interactions of dioecious plants, emphasizing the role of plant sex as a key trait that influences soil biodiversity and the associated functioning of ecosystems.

How to cite: Bradley Jimenez, R.: Ecological interactions in dioecious plants: implications for soil fungi and arthropods, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13963, https://doi.org/10.5194/egusphere-egu25-13963, 2025.

Tidal Marshes are wetland ecosystems at the marine-terrestrial interface which serve as strong sinks for atmospheric carbon dioxide and large reservoirs of soil organic carbon (SOC). However, tidal marsh soils also produce and emit the potent greenhouse gas methane (CH₄). Previous work has demonstrated that CH₄ flux is inversely related to salinity, and that methane flux is negligible compared to carbon dioxide (CO₂) uptake in marshes with salinities of >18 parts per thousand (ppt). However, in lower salinity tidal marshes, CH₄ flux is highly variable, and can spike sharply following the depletion of sulfate supply. In order to better understand drivers of methane flux across a range of salinities, we established three transects along estuarine gradients in Rhode Island and Connecticut, USA. At landward and seaward sites along each transect, we measured methane flux, salinity, and conducted various porewater and soil chemical analyses. We found that methane flux was significantly higher and more variable in marshes where salinity is < 18 ppt. The highest magnitude methane fluxes occurred when sulfate was nearly depleted in marsh porewater, indicating that sulfate abundance dampens methane production, but demonstrating the need for further investigation into processes governing sulfate depletion and replenishment in salt marshes, and the degree to which salinity is a reliable proxy for sulfate concentration. Additionally, the lack of spatial data products which delineate tidal marshes according to salinity complicates efforts to estimate methane budgets in tidal estuaries. Our results indicate that spatial differences in salinity should inform wetland mapping in order to facilitate estimations of greenhouse gas budgets, but more high-resolution monitoring of salinity is needed to accurately delineate map units.

How to cite: Norton, M., Moseman-Valtierra, S., and Stolt, M.: Greenhouse Gas Flux in Coastal Salt Marshes: Field Measurements along Estuarine Gradients in Northeastern USA, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14217, https://doi.org/10.5194/egusphere-egu25-14217, 2025.

         Blue carbon ecosystems (mangroves, seagrass beds, and salt marshes) are one of the most effective carbon sinks on Earth and are critical to climate change mitigation and adaptation. Hainan Province in China accounts for 82% of the country's mangrove area and 64% of the country's seagrass bed area. Hainan's blue carbon plays an important role in local and national carbon sink enhancement efforts. From the perspective of economics, Hainan's blue carbon system plays a major supporting role in the local economy. Existing research on the protection of China's blue carbon ecosystems focuses on carbon sink accounting and economic valuation, and rarely involves microeconomic impact analysis of blue carbon protection actions. In particular, there are few studies specifically conducted on the impact on residents' livelihoods and well-being in Hainan.

        In this context, we are attempting to conduct research in Hainan Province to answer the following questions: What impact does the protection and restoration of Hainan's blue carbon ecosystem have on the livelihoods of its coastal communities? We refined this question into three points: First, what are the livelihood sources and livelihood structures of Hainan's coastal and non-coastal communities; what changes have occurred around 2020? Second, has Hainan's special action on the protection and restoration of blue carbon ecosystems had an impact on the livelihoods of coastal communities? Third, through what channels does Hainan's special action on the protection and restoration of blue carbon ecosystems affect the livelihoods of coastal communities?

        According to preliminary research, Hainan Province's special action for the protection and restoration of blue carbon ecosystems has a two-way impact on the livelihoods of coastal communities. On the one hand, blue carbon protection can maintain and promote the local fishery economy and tourism; on the other hand, due to restrictive regulations on the relevant use of marine resources at the policy level, the protection and restoration of mangroves may have a negative impact on fisheries. Maintaining a balance between fishermen's livelihoods and blue carbon protection may be one of the difficulties in blue carbon conservation. Treating the special action for the protection and restoration of blue carbon ecosystems as a quasi-natural experiment, we are going to conduct policy evaluation in our study. We will conduct a community questionnaire survey and introduce the propensity matching difference-in-difference (PSM-DID) model to reveal the net effect of Hainan's blue carbon ecosystem protection on the livelihoods of coastal communities.

How to cite: Chen, Y.: Study on the Impact of Blue Carbon Ecosystem Protection on the Livelihoods of Coastal Communities in Hainan Province, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14443, https://doi.org/10.5194/egusphere-egu25-14443, 2025.

Alkalinity enhancement in rivers is a proposed carbon dioxide removal strategy which leverages physical and biogeochemical properties of rivers to promote uptake of atmospheric carbon dioxide. Robust monitoring, reporting and verification of carbon dioxide removal is necessary to instill trust in carbon credits and market activity stemming from river alkalinity enhancement. Rivers have the unique characteristic of reflecting integrated watershed characteristics along a one-dimensional trajectory. Depending on the size of the river, alkalinity dosing location and quantity, transit distance to the ocean and availability of monitoring locations, carbon dioxide uptake can be quantified through a hybrid approach leveraging direct measurements and models. In this poster, we propose a flexible, multiscale quantification framework which can be adapted to a wide range of rivers and deployment scenarios. 

How to cite: Yin, J., He, J., Sutherland, K., and Gill, S.: A flexible, multiscale quantification framework for river alkalinity enhancement, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14511, https://doi.org/10.5194/egusphere-egu25-14511, 2025.

Seagrass ecosystems are vital for coastal resilience, biodiversity, and as critical carbon sinks. With global seagrass declines, restoration has emerged as a key strategy for ecological and carbon recovery. Although through seagrass restoration, various ecosystem services return, there is a lack of information on the return of the carbon sequestration and accumulation. This study aims to assess the potential recovery of blue carbon benefits through seagrass restoration across various sites in Thailand. We analyzed carbon stocks and accumulation rates in restored Enhalus acoroides meadows at four sites, evaluating spatial variability in carbon recovery in restored versus natural meadows and unvegetated sediment. Despite successful seagrass establishment, the organic carbon (OC) content (%) within the surface sediment (top 20 cm) was not significantly different among restored, natural seagrass meadows, and bare sand, averaging 0.8 ± 0.1%, 0.9 ± 0.2%, and 0.9 ± 0.2% respectively. Although significant differences in OC content (%) were observed between sites, no differences were noted between the habitat types within each site. Predominantly sandy sediment (over 90%) with minimal mud content (1% or less) were found at all sites. The highest organic carbon stock in surface sediment was in unvegetated sediment, averaging 16.8 ± 3.4 Mg C ha^-1. Significant differences in OC stocks were also observed across all site comparisons, with higher stocks generally found in bare sand compared to restored and natural seagrass meadows. Sediment accumulation profiles, indicated by the absence of excess ²¹⁰Pb, suggest a lack of net fine sediment accumulation over the past decade or mixing of the upper sediment, precluding reliable sedimentation rate estimation. These findings suggest that these restored meadows are not forming depositional environments contributing to significant additional carbon sequestration, as evidenced by the minimal increase in OC stocks across the sites. Additionally, the low OC content (%) and minimal mud presence suggest overall low sedimentation rates, even in natural seagrass meadows. These results highlight the complexity of achieving carbon sequestration goals through seagrass restoration, emphasizing the need for site-specific restoration strategies that consider local sediment dynamics and ecological conditions to enhance carbon storage capabilities.

Keywords: organic carbon, carbon additionality, carbon accumulation, seagrass, restoration

How to cite: Stankovic, M., Kaewsrikhaw, R., Masqué, P., Vanderklift, M. A., Upanoi, T., and Prathep, A.: Lack of blue carbon recovery in restored tropical seagrass ecosystems, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14608, https://doi.org/10.5194/egusphere-egu25-14608, 2025.

Disturbances resulting from anthropogenic global change pose ongoing threats to plant biodiversity. Functional trait-based approaches enable ecologists to observe species-level stress responses with implications for community-level adaptations to disturbances. DRAGNet (Disturbance and Resources Across Global Grasslands) leverages grassland restoration to explore the mechanisms driving disturbance recovery and community assembly. In this single-site study, we examine how plant composition and traits vary across disturbance (tillage) and soil resource (NPK+) gradients. Plant composition will be surveyed in 28 plots, with root and soil samples extracted for trait analysis and soil nutrient testing. We predict that plants in disturbed, nutrient-enriched plots will exhibit divergent functional traits, including reduced root biomass and specific root length, alongside changes in above-ground traits. Preliminary data illustrates the impact disturbance can have on community composition, particularly by promoting invasive species (PERMANOVA, p = 0.0576). This finding underscores the influence of disturbance on plant community assembly and highlights the potential vulnerability of restored grasslands to invasive species proliferation under human-induced disturbances. This study aims to uncover the root functional traits driving the recovery of a restored grassland across both soil disturbance and resource gradients.

How to cite: Campbell, A., Sullivan, L., Celestin, M., and McCary, M.: Getting Out from Under: The Belowground Response of a Restored Grassland to Soil Disturbance and Resource Addition, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14964, https://doi.org/10.5194/egusphere-egu25-14964, 2025.

Oceanic islands have high biodiversity due to high rates of endemicity, which is now severely threatened by global change, including biological invasions. Invasive plants are predicted to displace native plants via vigorous resource use associated with fast growth rates and population expansion. The corresponding dynamics associated with invasive plant litter offer important insights to bridge live foliage traits associated with competition with invasive plant effects on ecosystem function via litter decomposition. Evidence has accumulated to support the prediction that invasive species produce higher quality litter than native species, which decomposes more rapidly, in turn providing positive feedback that facilitates their expansion. However, litter quality can vary among and within species across climate gradients, which is likely to contribute to spatial variation in native-invasive plant interactions. In this study, we synthesize a large body of litter trait data using systematic review methods and quantitative analyses, to investigate litter trait differences between native island plants and non-native plants established in natural habitats across steep elevation (7.5 – 2660 m) and mean annual rainfall (272 – 6362 mm) gradients of the Hawaiian Islands. We found that litter traits are highly variable in both native and invasive species, with considerable overlap in multivariate trait space. Intraspecific and interspecific differences were the main sources of litter trait variation, which explained 40% and 41% of the total variance, respectively. Nonetheless, as predicted, invasive plants had litter that tended to be of higher nutritional quality and lower toughness than native plants, although this difference explained only 8% of the total variance across all traits. Interestingly, litter traits varied significantly with respect to temperature and rainfall, and the patterns differed between native and invasive plants. These results corroborate previous studies on live foliage traits that climate mediates invasive-native plant interactions across the heterogeneous environment of Hawaii. These patterns emphasize the importance of considering litter as part of the functional syndrome of plants and for a better understanding of how invasive plants may alter their novel ecosystems.

How to cite: Satdichanh, M., Harrigan, W., Ostertag, R., and Barton, K.: Plant litter trait variation between native and nonnative species across steep climate gradient in Hawaiian Islands, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14991, https://doi.org/10.5194/egusphere-egu25-14991, 2025.

Plant-insect herbivore interactions are essential in shaping forest ecosystem health. The resource availability hypothesis (RAH) and the leaf economics spectrum (LES) theory predict that species in high-resource environments tend to adopt a "fast" strategy but are more susceptible to herbivory. However, this contradicts reports of increased insect herbivory in the context of global drought intensification, and hinders accurate prediction about how different plant species respond to herbivorous insect feeding.

To fill this knowledge gap, we conducted an observational study in two temperate forests dominated by Quercus mongolica and Betula platyphylla in eastern China to compare their leaf herbivory patterns and explore possible mechanisms. We measured three leaf herbivory proxies (consumed leaf area, percent consumed, and herbivory frequency), some leaf traits (leaf area, specific leaf area, leaf water content, leaf nitrogen, phosphorus and non-structural carbohydrate contents), and soil properties (pH, soil water content, soil organic carbon content, soil nitrogen and phosphorus contents).

We found that Q. mongolica, growing in poorer soil environments with lower water and nutrient contents, experienced higher leaf herbivory than B. platyphylla. Regarding leaf traits, Q. mongolica had a higher leaf area and non-structural carbohydrate content, but lower specific leaf area, leaf nutrient and water contents than B. platyphylla. At the leaf level, leaf area, rather than specific leaf area, of both tree species was positively correlated with leaf herbivory. At the tree level, species-specific patterns emerged, i.e., leaf herbivory of B. platyphylla was positively related to leaf area and negatively related to leaf nitrogen and water contents and soil phosphorus content, whereas that of Q. mongolica was only positively affected by soil phosphorus content.

These findings challenge the predictions of RAH and LES theory, as Q. mongolica that grows in resource-poorer soil environments with a conservative strategy suffers higher leaf herbivory than B. platyphylla, shedding some light on the proverb that trouble follows the needy. Moreover, water-related factors (i.e., leaf and soil water contents) and leaf area showed an important effect on driving interspecific and intraspecific leaf herbivory variations here, implying that climate-induced droughts may exacerbate herbivore pressure in temperate forests.

How to cite: Zhao, C. and Tian, D.: Trouble follows the needy: more severe leaf herbivory in the resource-poorer temperate oak forest than in the birch forest, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17774, https://doi.org/10.5194/egusphere-egu25-17774, 2025.

Optimizing carbon use efficiency (CUE) and water use efficiency (WUE) is a critical challenge for temperate forests worldwide, particularly under changing climatic conditions. CUE refers to the proportion of carbon assimilated during photosynthesis that contributes to biomass, while WUE quantifies the carbon gained per unit of water lost through transpiration. The region of Wallonia, Belgium, with temperate forests covering 33% of its land, serves as an exemplary case for analyzing the relationship between CUE and WUE under varying ecological and climatic conditions. Globally, the coupling of CUE and WUE remains insufficiently understood, especially at the species level. This study investigates the dynamics of CUE and WUE across several dominant tree species in Wallonia. It utilizes outputs from the CARAIB dynamic vegetation model to evaluate species-specific responses to thinning practices and climate scenarios (RCP 8.5 and RCP 2.6) over the period 1980 to 2070.

Our analysis distinguishes between the isohydric and anisohydric behaviors of tree species, emphasizing their contrasting long-term responses to climatic changes and their influence on ecosystem efficiency. Trees such as Abies and Picea tend to be isohydric. They conserve water by closing their stomata early during drought. They benefit from thinning practices initiated at 40 years, with intervals of 3–9 years designed to manage competition as they mature. Conversely, trees like Quercus and Populus tend to be anisohydric. They maintain photosynthesis under stress by keeping their stomata open. Populus requires earlier thinning interventions, typically starting at 30 years, with shorter regrowth periods of 15 years to optimize light penetration and nutrient availability. In contrast, Quercus thinning is initiated at 40 years, with regrowth periods of 30 years, to support their growth and optimize resource utilization. Thinning reduces competition and reallocates resources, modulating trade-offs between WUE and CUE while supporting species-specific growth under varying climatic stressors. Tailored thinning practices enhance resource availability for both isohydric and anisohydric species. Isohydric species gain from improved water availability, complementing their inherent drought resilience, while anisohydric species benefit from increased carbon assimilation through enhanced access to light and nutrients.

These findings underscore the importance of aligning species composition and management strategies with localized environmental conditions to bolster forest resilience. With this study, we investigate species-specific management strategies to support sustainable forestry, identifying species that are better adapted to changing climatic conditions and capable of maintaining vital ecosystem services.

How to cite: Verma, A., Lanssens, B., Tölle, M., Chaudhari, T., Hambuckers, A., and Francois, L.: Quantifying Carbon and Water Use Efficiencies of Forest Ecosystems in Wallonia, Belgium: Insights from Species-Specific Responses to Thinning and Climate Change , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18429, https://doi.org/10.5194/egusphere-egu25-18429, 2025.

An accurate representation of biomass burning aerosol emissions is essential in climate and Earth System Models to capture aerosol properties and their interactions. The sources of regional smoke plumes include the widespread prevalence of numerous small fires, which are  common across Savanahs, and larger more episodic wildfires, such as the extreme Californian wildfire event of September 2020. Capturing emissions from such a diverse range of fire activity is a major challenge and some atmospheric models, including the UK Earth System Model (UKESM) have scaled up aerosol emissions to ensure modelled AOD match observations. Past evaluations have struggled to provide a clear answer as to how to reconcile emissions and modelled aerosols, with contrasting outcomes for different regions and/or assessments of seasonal means versus individual smoke plumes. Our modelling study leverages observational data from the unprecedented wildfires in September 2020 to identify potential issues in capturing the aerosol from large / extreme wildfires in the global modelling system of UKESM. Running in nudged mode and with daily emissions from GFED4.1s emissions enables a realistic simulation of the thick smoke plumes that ensued across the continent and out into the Pacific, with little overall bias in AODs between UKESM and co-located observations (AERONET, VIRS, MAIAC). However, scaling emissions by a factor of 2 provides better agreement globally and across regions dominated by smaller fires. We therefore develop a means of differentiating between small and large fires based on the daily dry matter (fuel) consumption and apply this to enable scaling of emissions from small fires that seem to otherwise be underestimated in the model, whilst avoiding scaling those from large fires. Our results indicate a way forward to ensure a global simulation of biomass burning aerosol and fidelity in modelling extreme events.

How to cite: Johnson, B., Quaze, L., and Haywood, J.: Evaluating aerosol emissions from wildfires in the UK Earth System Model: What we have learnt from modelling the extreme wildfires in California during September 2020 , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18758, https://doi.org/10.5194/egusphere-egu25-18758, 2025.

The field of Blue Carbon research has traditionally focused on the carbon sequestration capacity of coastal vegetated habitats, despite these habitats comprising only a small fraction of oceanic sediment. However, continental shelf sediments also play a significant role in carbon sequestration and represent a significantly larger surface area. While the majority of organic carbon deposited in the shelf sediment is initially fixated by phytoplankton, and then potentially cycled through other marine organisms, some of it is originated from coastal and terrestrial producers, such as marine macroalgae, then transported, deposited and sequestered into shelf sedimentary basins. In this study, we investigated the sedimentary organic carbon (OC) stocks and sequestration rates at two sites of the continental shelf of Portugal, each adjacent to major wetland systems dominated by saltmash and seagrasses: the northern site is located off the Sado estuary at the Arrábida coast where macroalgae forests are also present, and the southern site off the Ria Formosa coastal lagoon. We also assessed the contributions of marine and terrestrial primary producers to sedimentary OC using various proxies such as C/N ratios, carbon isotopic signature (δ13 C), magnetic susceptibility, lipid contents and sedimentary DNA metabarcoding. Our findings revealed similar OC sequestration rates at both sites (23.3 ± 7.1 g OC m⁻² yr⁻¹ and 20.9 ± 5.7 g OC m⁻² yr⁻¹ for the northern and southern sites, respectively) and comparable OC stocks in the top 25 cm of sediment (29.5 ± 2.33 g OC cm⁻² and 21.1 ± 3.01 g OC cm⁻², respectively). Clear differences were observed on the contributions of terrestrial versus marine sources to the sediment organic matter, with the northern site showing lower terrestrial contribution as opposed to the southern site. This conclusion is supported by the different proxies used. For example, the northern site consistently exhibited higher OC contents at comparable particle sizes, indicative of a greater deposition rate of organic carbon not adhered to sediment particles, typical of oceanic primary productivity. Sedimentary DNA metabarcoding detected seagrass and saltmarsh genetic material in sedimentary organic matter from both sites, indicating that detritus from the two wetlands are being exported to the continental shelf. Further investigation is needed to quantify the relative magnitude of this export. Understanding this process is essential to accurately assess the role of coastal vegetated habitats in the global carbon cycle, as current estimates focus solely on in-situ sequestration and often overlook the potential contribution of exported organic matter. Our study highlights the need to expand our perspective on the interconnectedness of coastal and oceanic carbon dynamics.

How to cite: Martins, M., Magalhães, V., Salgueiro, E., Cordeiro, L. G., Abrantes, F., Masqué, P., de los Santos, C. B., and Santos, R.: Carbon accumulation, storage and provenance in the Portuguese continental shelf , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19205, https://doi.org/10.5194/egusphere-egu25-19205, 2025.

Dredging of the fairway in the Ems estuary was driven by the need to accommodate the increasing draft of ships. This modification has had negative effects on the sediment balance and ecology of the estuary. The fairway deepening results in strong alterations of the tidal dynamics, such as tidal amplitude and duration, as well as hydrodynamics such as current velocity and turbulence. This results in increased fine sediment input, which, at high suspended sediment concentrations, contributes to the formation of fluid mud—a mixture of silt, clay, and organic matter. The dynamics of fluid mud, particularly the differences between spring and neap tides, are not yet fully understood.

We investigated the formation, dispersion, and entrainment of fluid mud during the semi-diurnal tidal cycle. Therefore, the influence of flow velocity and salinity at different water depths, and the differences between spring and neap tides based on two dedicated measurement campaigns in 2023 was analyzed using high-resolution spatiotemporal monitoring data. Salinity data were used as an indicator of stable stratification. Additionally, sediment samples have been collected using a sediment corer to analyze the composition and properties of the fluid mud layer.

Our Spring-neap tide analysis showed a reduction of the flow cross-section during neap tide leading to differences in hydrodynamics between spring and neap tide driven by high sediment concentrations and fluid mud occurrence. During neap tide fluid mud was found to cover a larger fraction of the water column than during spring tide. This further highlights the strong influence of flow velocity on the dynamics of fluid mud and the need to include spring-neap considerations for future sediment management plans for the Ems.

How to cite: Lehn, J., Slabon, A., Holthusen, D., Rovelli, L., Fiskal, A., Hoffmann, T., and Borgsmüller, C.: Spring-neap tidal variation of fluid mud occurrence in the hyper-turbid Ems estuary , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19333, https://doi.org/10.5194/egusphere-egu25-19333, 2025.

The use of substrates combined with biochar has been highlighted in agricultural and horticultural production, including the cultivation of Raphanus sativus L. (radish), due to the benefits in water retention, nutrient supply and stimulation of root development. This study evaluated the growth and development of radishes under different combinations of substrates with biochar, with or without microbial inoculation. The experiment was carried out between November 2024 and January 2025, in a greenhouse with automatic temperature control (18-42 °C) at the Federal University of São Paulo, São José dos Campos Campus. The treatments included: A) Substrate with biochar (SB-control); B) Substrate (S-control); C) Substrate with biochar inoculated with MELRC (SBI-MELRC); D) Substrate inoculated with MELRC (SI-MELRC); E) Substrate with biochar inoculated with MEU (SBI-MEU); F) Substrate inoculated with MEU (SI-MEU); G) Substrate with biochar inoculated with TSB (SBI-TSB); and H) Substrate inoculated with TSB (SITSB). The variables analyzed were number of leaves (NF), leaf area (AF), total length (CT), tuber weight (PT), tuber diameter (DT), root length (CR), fresh root mass (MFR), tuber height (HT) and root dry mass (MSR). Data were submitted to analysis of variance (ANOVA) and regression, and significant differences were evaluated by the F test at probability levels of 0.01 and 0.05. The results indicated that treatment D (SI-MELRC) had the greatest positive impact on all variables evaluated, standing out as the best combination for the development of Raphanus sativus L. The use of substrates combined with biochar and microbial inoculation showed promise in the cultivation of Raphanus sativus L. (radish), promoting significant improvements in the growth and development variables evaluated. Among the treatments tested, the substrate inoculated with MELRC (SI-MELRC) stood out, presenting the best results in all variables analyzed. These findings reinforce the potential of biochar as a substrate conditioner and highlight the importance of microbial inoculation to maximize the benefits of this system. Future studies can explore the replicability of the results under field conditions and with other agricultural crops.

Keywords: biochar, Raphanus sativus L., radish cultivation, microbial inoculation, substrate conditioner, agricultural production.

How to cite: da Paixão Oliveira, L. and Dos Anjos Verzutti Fonseca, J. and the OLIVEIRA, Lorena da Paixão1; FONSECA, Dos Anjos Verzutti; CORTEZ, Christian Zenichi de Oliveira Ueji 1, Alexandre UEZU2 , SANTOS, Erika³; ARÁN, Diego³ e ESPOSITO, Elisa1 .: Effects of Biochar Substrate and Microbial Inoculation on the Development of Raphanus sativus L. , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20449, https://doi.org/10.5194/egusphere-egu25-20449, 2025.

Organic inputs in grasslands are known to enhance soil carbon sequestration. However, it remains unclear whether long-term organic inputs lead to greenhouse gas (GHG) emissions, specifically methane (CH₄) from livestock and nitrous oxide (N₂O) from soils, that outweigh the benefits of carbon sequestration. Addressing this issue is crucial, as it directly impacts the evaluation of organic farming practices for sustainable land management and climate change mitigation. In this study, we employed the process-based Denitrification-Decomposition (DNDC) model to estimate the fluxes of major greenhouse gases (GHGs) in a long-term grassland silage experiment established in 1969. The model was validated against measured data, effectively capturing the dynamics of N₂O emissions, soil temperature, biomass, and soil organic carbon (SOC). Simulations under different IPCC Shared Socioeconomic Pathway (SSP) scenarios of altered temperature, CO₂ concentrations, and radiative forcing were conducted. Treatments with high levels of cattle manure and pig manure under the SSP1-2.6 scenario exhibited a net GHG sink, whereas conventional fertilization resulted in a net GHG source under both SSP1-2.6 and SSP2-4.5. Grass yields decreased under conventional fertilization in both SSP2-4.5 and SSP5-8.5 scenarios. However, the application of organic matter inputs resulted in yield increases across all scenarios. These findings highlight the potential of organic farming practices, especially with high organic inputs, to mitigate GHG emissions and enhance productivity in grassland ecosystems. Therefore, adopting organic farming practices with adequate organic inputs could serve as a sustainable strategy for balancing food production and environmental conservation.

How to cite: Meng, X., Khalil, I., and Osborne, B.: Enhancing crop yield, carbon sequestration, and greenhouse gas mitigation through organic matter inputs: long-term grassland farming observations and DNDC model predictions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20890, https://doi.org/10.5194/egusphere-egu25-20890, 2025.

There is interest in biogeochemical cycling and ecosystem functioning in the Clarion Clipperton Zone (CCZ, equatorial Pacific) due to the possibility in the near future of deep sea mining of polymetallic nodules. A set of important processes and ecosystem services relate to the fixation, export and deposition in sediment of organic carbon (C). This is important to understand both as a mechanism for C sequestration, and also as a set of processes which feeds deep sea biological communities. However, due to the remote nature of the CCZ, and the considerable resource required, it has rarely been possible to directly observe the coupling between processes from the sea surface all the way through the water column to the fate of organic C in sediments, nor how those linked processes vary over time or in response to mining disturbance.

Here we present data on C fixation, export, sediment composition and relationships with benthic community biomass. We show clear coupling between surface productivity, export and sinking flux, but that sediment organic C concentrations are not always closely coupled to water column processes. Repeated measurements over a period of ~18 months show inter-annual variability at the seafloor, rather than a stable seasonal pattern. Organic C delivery to the sediment is reflected in the biomass of faunal groups, with different temporal responses in the different groups (macrofauna, metazoan meiofauna and foraminifera) linked to factors such as competition, predation pressure and life cycle differences. Changes in sediment total organic carbon following a mining vehicle test will also be considered.

How to cite: Woulds, C., Lough, A., and Homoky, W. and the Carbon fixation, export, sedimentation and utilisation Team: Temporal variability in organic carbon fixation, export, sedimentation and utilisation in the Clarion Clipperton Zone, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-21501, https://doi.org/10.5194/egusphere-egu25-21501, 2025.

Large-scale, frequent forest fires have a detrimental effect on the environment, the quality of the air, and human health. In the present study, from 2001 to 2020, March (1,857.5 counts/month) and April (922.8 counts/month) saw around 70% of the region's annual forest fires. Unusually high numbers of forest fires have been reported in some years, including 2009, 2012, and 2017. A thorough investigation is conducted into the contribution of numerous climate extremes and persistently rising temperatures to the rise in forest fire activity over central India. Forest fire activity doubled and tripled during the non-fire (July–January) and forest fire (February–June) seasons, respectively, over the warmer period from 2006 to 2020. A severe heat wave, an unusual drought, and an exceptionally powerful El Nino occurred in central India between 2015 JASONDJ and 2018 FMAMJ. These events are thought to have contributed to an upsurge in forest fires. The quinquennial spatiotemporal changes in forest fire characteristics, including average fire intensity and fire count density, were also evaluated. Significantly high soil temperature, low soil moisture content, poor evapotranspiration, and low normalized difference vegetation index are statistically associated with high near-surface air temperature and low precipitation during FMAMJ. This makes the climate much drier, which encourages a lot of forest fires in the Central Indian region.

How to cite: Sonwani, S., Saxena, P., and Jain, M.: Forest Fire Variability Over the Central India Region from 2001–2020, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1122, https://doi.org/10.5194/egusphere-egu25-1122, 2025.

China is a significant region for crop cultivation. For a long time, there has been a common practice of burning crop residues during the post-harvest period (from May to October). The smoke emitted from straw burning contains both types of ozone precursors, including nitrogen oxides (NO_x=NO+NO₂) and volatile organic compounds (VOCs), and can be transported over long distances. During the transport process, secondary formation or consumption of ozone precursors occurs within the smoke plumes. After the smoke plume mixes with the atmosphere in the downwind urban area, it will lead to changes in the local ozone formation sensitivity. However, due to the nonlinear relationship between ozone and its precursors, the changes in ozone levels in downwind cities are not as straightforward as expected.

Here, we explore the temporal evolution of urban ozone and its precursors on smoke-affected days using multi-source satellite-derived fire event tracking datasets, which are screened by a semi-quantitative absorbing aerosol index (AAI), tropospheric NO₂ and HCHO columns measurements from OMI, fire points from Himawari-8, and ground-level O₃ monitoring dataset. We aimed to understand the associations between urban ground-level O₃ concentrations and crop residue burning events in China. Our analysis revealed that no consistent changes were shown in urban O₃ on smoke-affected days. In addition, there was an increase in NO₂, while HCHO and O₃ decreased in cities after mixing with smoke that had taken a long transport time. Our findings suggest that the O₃ formation sensitivity within aged smoke tends to be controlled by VOC-limited regime. We hypothesize that the large amount of NO_x carried by aged smoke consumes urban VOCs and O₃, while producing NO₂ locally. When fresh smoke, which is mainly controlled by the NO_x-limited regime, enters urban environments rich in NO_x, it leads to an increase in O₃ concentration. Our analysis may contribute to an improved understanding of the influence of straw burning on urban ozone levels in China.

How to cite: Wang, W., van der A, R., Ding, J., Cheng, T., and Wang, C.: Exploring the effect of straw burning on urban ozone levels based on multi-source satellites in northern China, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1314, https://doi.org/10.5194/egusphere-egu25-1314, 2025.

The global wildland fire management community faces pressing climate change and operational challenges and requires improved capabilities in existing modelling tools or the development of novel decision support tools to limit the negative impact of wildfires and to increase use of prescribed burning where appropriate. This presentation will discuss limitations in the existing approaches to incorporating fuel structure effects in different model types (empirical, semi-empirical, detailed physics-based). In particular, novel experimental data will be presented addressing previously identified limitations [1] in the description of surface fuel beds in one of the most widely-used semi-empirical models; the Rothermel model, which underpins many current operational models.

The Rothermel model [2] involves a conservation of energy approach, incorporating separate terms to describe energy release rate in the combustion zone (reaction intensity) and energy transferred to the unburnt fuel (propagating flux), and incorporates a number of empirical closure terms.  The reaction intensity is empirically based, with the underpinning experimental measurements described in Frandsen and Rothermel [3]. By measuring the mass loss rate in a section of a fuel bed, Frandsen and Rothermel were able to characterize the intensity distribution within the combustion zone. However, the interacting effects of simultaneously varying fuel loading and packing ratio were not systematically considered, complicating efforts to understand the interacting effects of fuel loading and bulk density.

This study presents a series of laboratory-based flame spread experiments (no wind) involving excelsior fuel beds of varying structural conditions (Fuel Height: 0.02 to 0.12 m, Bulk Density: 3.3 to 20 kg/m³, Fuel Loading: 0.2 to 0.4 kg). The reaction intensity was calculated via a similar procedure to that described by Frandsen & Rothermel [2] as ‘Method 2’, in which the longitudinal length of the mass measurement region is greater than or equal to the combustion zone depth.

Clear trends in the peak mass loss rate and profile with bulk density were observed with a significant reduction at lower fuel loadings (0.2 kg/m²), and the reaction time was observed to increase at higher bulk densities along with a lengthening in the reaction intensity distribution region (further behind the combustion wave front). These results, along with existing observations of the trailing, in-depth combustion region in porous fuel beds, can be used to further investigate the observed tendency for underprediction of spread rates when the Rothermel model is applied to compressed fuel bed scenarios and has practical implications for other fire behaviour modelling applications. For example, improved characterisation of the overall combustion wave may enable improved modelling of smoke generation, surface-to-crown fire transition, and fuel consumption (e.g. to evaluate prescribed fire effectiveness).

[1] Z. Campbell-Lochrie, M. Gallagher, N. Skowronski, R.M. Hadden, The effect of fuel bed structure on Rothermel model performance, Int. J. of Wildland Fire. 33 (2023).

[2] R.C. Rothermel, A Mathematical Model for Predicting Fire Spread in Wildland Fuels, Research Paper INT-115, USDA Forest Service.,1972.

[3] W.H. Frandsen, R.C. Rothermel, Measuring the energy-release rate of a spreading fire, Combust Flame 19 (1972) 17–24.

How to cite: Campbell-Lochrie, Z.: Revisting Intensity of Combustion Waves to Address Outstanding Issues in Wildfire Modelling, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1390, https://doi.org/10.5194/egusphere-egu25-1390, 2025.

How to cite: Muth, L., Vogel, B., Vogel, H., and Hoshyaripour, G.: Modeling Fire-Atmosphere Feedbacks: Insights from the 2019/2020 Australian Wildfires, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1707, https://doi.org/10.5194/egusphere-egu25-1707, 2025.

How to cite: Wang, J., Li, J., Zhao, J., Zhong, X., Wang, M., He, J., and Yue, C.: Spatiotemporal changes in global cropland fire activity from 2003 to 2020, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1776, https://doi.org/10.5194/egusphere-egu25-1776, 2025.

Southeast Asia experiences widespread wildfires and biomass burning events during the dry season (January to April), leading to poor air quality, haze, and smog. NASA conducted the Airborne and Satellite Investigation of Asian Air Quality (ASIA-AQ) flight campaign in February and March 2024 to study the contribution of smoke to urban air quality through a multi-faceted observational approach (aircraft, satellite, and ground). The campaign deployed the NASA DC-8 aircraft, equipped with instruments from the Langley Aerosol Research Group (LARGE) and other teams, to measure real-time aerosol microphysical and optical properties, trace gases, and meteorological parameters. During the campaign in the Philippines, South Korea, Thailand, and Taiwan, it was noted that the northern region of Thailand was predominantly impacted by agricultural residue burning and wildfires. Here, we present the variations of vertical and horizontal profiles of aerosol properties and biomass burning tracers, alongside meteorological data to assess the impacts of local conditions and potential pollution pathways. Key findings will include observed variability in aerosols properties, the role of absorbing and scattering aerosols, boundary layer dynamics, and regional pollution transport across the ASIA-AQ domain.

How to cite: Roy, S., Gallo, F., Wiggins, E. B., Ziemba, L. D., Jordan, C., Winstead, E. L., Shook, M. A., DiGangi, J. P., Diskin, G. S., Choi, Y., Miech, J. A., Wojnowski, W., Piel, F., Swift, S. J., Wisthaler, A., and Moore, R. H.: Wildfires and biomass burning in northern Thailand: Observations from ASIA-AQ Campaign, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2016, https://doi.org/10.5194/egusphere-egu25-2016, 2025.

Incidents in nuclear facilities can lead to the emission of a radioactive plume dis-
persing into the atmosphere. In such events, the highest radionuclide concentration
is usually located near the source at distances ranging from a few meters to several
hundred meters. It is, therefore, crucial to be able to accurately predict these levels
of near-source concentrations.
One challenge arises from the thermal characteristics of the source, which regulate
the initial dispersion of the plume. In the case of a non-thermal gas release, the
dispersion of the plume is driven by atmospheric conditions, related to wind and
atmospheric instability, and is influenced by local surface characteristics such as
roughness and the presence of obstacles. In contrast, when the gas is emitted from
a hot source such as a fire, the released gas first rises in the atmosphere up to a
so-called ‘injection height’ due to buoyant forces. The injection height is reached at
a certain distance from the source and doesn’t only depends on the properties of the
hot source but also on the atmospheric conditions (e.g. downdraft effects). The gas
then disperses like in a non-thermal gas release.
While CFD modelling can offer an accurate description of the plume dispersion, its
processing speed is not suitable for use in emergency situations. In contrast, existing
analytical models can provide rapid results, but their injection height parametriza-
tions may lack comprehensive coverage. So far, analytical models have rarely been
validated against field measurements, and few field experiments have been conducted
to improve their parameterization.
The goal of this presentation is twofold, first to present a field experiment on the
atmospheric plume dispersal of a gas released from a hot source, and second to
evaluate an analytical model of plume dispersal against the experiment, with a
particular focus on the Atmospheric Transfer Coefficient of the released gas.
The field experiment was conducted in May 2024 on a flat terrain near Vire (Nor-
mandy, France), under unstable and neutral atmospheric conditions.

The source comprised a burner (PYROS) that generated a propane fire with an average heat
release rate of between 450 kW and 750 kW . Helium was injected into the plume
to serve as a tracer gas. During 15-minute observation periods, helium concentra-
tions in the air were measured at ground level at distances from the source ranging
from 40 m to 400 m, as well as at various altitudes, using air sampling points at-
tached to a rope lifted vertically by a drone. Additionally, atmospheric turbulence
characteristics were also measured using ultrasonic anemometers.
The analytical model employs Heskestad’s formulas to determine the fire character-
istics and Briggs’ dispersion parameters to characterise the Gaussian dispersion of
the plume when buoyant forces become negligible.

How to cite: Mendez, A., Manon, G., Dupont, S., and Laguionie, P.: Near-field atmospheric dispersion of a gas emitted from a hot source : a comparison between analytical modelling and in situ measurements, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2253, https://doi.org/10.5194/egusphere-egu25-2253, 2025.

In this study, we report the preliminary findings from a series of sans-human wildfire simulations using a process based dynamic global to regional vegetation model (DGVM), LPJ-GUESS v 4.1, coupled with the SIMple FIRE Model (SIMFIRE) and the wildfire combustion model (BLAZE), where we investigate the performance of the DGVM to reenact a specific wildfire instance in a Mediterranean catchment. For this, we compared the simulated burned area (BA^s) to that in the actual event (BA^o) in Manavgat, Antalya, Türkiye. The DGVM spatially captured the fire instance, albeit with a much smaller BA as a result. In July 2021, the largest single wildfire incidence for this region for the last two centuries occurred. The wildfire scorched an area of 60.000 ha.s where the dominant vegetation types were fire adapted dry conifer forests (mainly Pinus brutia) and Mediterranean shrubs. Previous years’ precipitation patterns had encouraged fuel build up, and the extreme heat of the summer of 2021, coupled with the seasonal drought and strong winds provided suitable environmental conditions for the wildfire’s spread. The ignitions in this specific case were intentional, majority were targeted arsons, and a plausible reason behind the ultimate extent of the BA. Here, we show the simulation results from our sans-human model runs using ERA5-Land reanalysis dataset, and compare BA^s to BA^o for this catchment for 2021. Our ultimate aim in these series of experiments where the ignition source is non-human is initially to decipher the dynamics, and later to develop a methodology to assess the human influence in BA in Mediterranean type ecosystems in the Eastern Mediterranean Basin, under a changing climate. 

How to cite: Ekberzade, B., Avcıoğlu, A., and Görüm, T.: Determining the human signal in burned area under a changing climate, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2313, https://doi.org/10.5194/egusphere-egu25-2313, 2025.

Forest and vegetation fires are one of the major sources of air pollution and have triggered air quality issues in many regions of Pacific Asia. Here we isolate the fire-specific PM_2.5 from monitoring concentrations using an observation-driven approach in the region. The total PM_2.5 in Pacific Asia exhibited a rapid declining trend from 2014 to 2021, while fire-specific PM_2.5 decreased in early years but begun to reverse, leading to an increasing proportions of fire-specific PM_2.5 in recent years. The inconsistency between the decreasing number of fire points and the rising levels of fire-specific PM_2.5 may be attributed to a shift in dominant sources of fire emissions in Pacific Asia, moving from anthropogenic agriculture fires to wildfires. Fire-related PM_2.5 poses a significant public health threat in Pacific Asia, contributing to approximately 334,300 premature deaths each year. Our assessment highlights the disproportionate impact of fire-specific PM_2.5 on poverty populations, indicating a pressing need for more attentions and researches in these regions. Based on the positive correlation between vapor pressure deficit and fire-specific PM_2.5, this study suggests that without further regulation and policy intervention, the contributions of fire-specific PM_2.5 to air pollution in Pacific Asia are likely to continue increasing under the influence of future climate change.

How to cite: Lu, H., Xie, M., Wang, N., and Liu, B.: The contribution of fires to PM2.5 and population exposure in Pacific Asia, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2467, https://doi.org/10.5194/egusphere-egu25-2467, 2025.

How to cite: Engle, B., Bratoev, I., Crowley, M. A., Zhu, Y., and Senf, C.: Identifying Ignition Drivers of Lightning-Ignited Wildfires in Boreal Forests, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3090, https://doi.org/10.5194/egusphere-egu25-3090, 2025.

Biomass-burning organic aerosol(s) (BBOA) are rich in brown carbon (BrC), which significantly absorbs solar irradiation and potentially accelerates global warming. Despite its importance, the multiphase photochemistry of BBOA after light absorption remains poorly understood due to challenges in determining the oxidant concentrations and the reaction kinetics within aerosol particles. In this study, we explored the photochemical reactivity of BBOA particles in multiphase S(IV) oxidation to sulfate. We found that sulfate formation in BBOA particles is predominantly driven by photosensitization involving the triplet excited states (³BBOA^*) instead of iron, nitrate, and S(IV) photochemistry. Rates in BBOA particles are three orders of magnitude higher than those observed in the bulk solution, primarily due to the fast interfacial reactions. Our results highlight that the chemistry of ³BBOA^* in particles can greatly contribute to the formation of sulfate, as an example of the secondary pollutants. Photosensitization of BBOA will likely become increasingly crucial due to the intensified global wildfires.

How to cite: Liang, Z., Zhou, L., Chang, Y., Qin, Y., and Chan, C. K.: Biomass Burning Organic Aerosols as a Pool of Atmospheric Reactive Triplets to Drive Multiphase Sulfate Formation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3113, https://doi.org/10.5194/egusphere-egu25-3113, 2025.

Synchronous fires, that is fires co-occurring at different geographical locations within a few days of each other, challenge the distribution of firefighting resources among regions and can have more severe impacts on human health, infrastructure and environmental systems than individual fire events. However, so far very little is known about the occurrence, spatial patterns and the atmospheric drivers of synchronous fires in Europe.

In this work, we use fire observations from a global fire event dataset FRYv2.0 to (1) detect fire synchronicity between ten European regions during 2001–2020 and (2) link the occurrence of synchronous fires to seven dominant European-Atlantic weather regimes. To detect fire synchronicity, we apply complex network theory and an event synchronicity statistical framework to identify significant links between the ten regions. To analyze the relationship between synchronous fire events and dominant weather regimes, we use a conditional probability-based measure calculating the dependency of synchronous fires –between each region pair– on seven common European weather regimes. We perform 2000 block permutations to test the statistical significance of these dependencies. Lastly, we use the CERRA reanalysis data to analyze the seasonal anomalies of relevant atmospheric variables under each weather regime, including temperature, wind speed, precipitation and relative humidity.

We find multiple significant connections between regions across Europe showing fire synchronicity in spring, summer and fall. We show that (1) northern and western regions in Europe experience fire synchronicity in spring under the influence of blocking regimes (i.e., European and Scandinavian Blocking) which promote warm and dry conditions; (2) eastern regions show fire synchronicity in spring and fall during the Zonal Regime under warm and dry conditions; and (3) fire synchronicity in southern regions are significantly modulated by Scandinavian Troughs due to positive wind speed anomalies and dry conditions in spring and fall as well as by Atlantic Ridges due to positive wind speed anomalies in summer.

Our work reveals significant fire synchronicity across Europe with significant links to atmospheric circulation patterns. As the seven weather regimes have predictability on weekly to monthly time scales, our work might help to develop early warning systems for elevated risks of synchronous fires under climate change and improve fire emergency preparedness across different European regions. 

How to cite: Li, X., Wood, R., and Brunner, M.: Linking fire synchronicity in Europe to persistent weather regimes, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3285, https://doi.org/10.5194/egusphere-egu25-3285, 2025.

The recovery time of ecosystems following wildfire significantly influences carbon sequestration rates, land-atmosphere exchanges, and hydrological processes. Post-fire recovery has been studied at local scales but there is a lack of comprehensive global-scale analyses. We used solar-induced chlorophyll fluorescence (SIF) to quantify the recovery of photosynthetic activity after more than 10,000 fires from diverse ecosystems. We used the relaxed lasso technique to identify key determinants of the length of time required for post-fire recovery, and used these to build a linear regression model. Our results show that vegetation characteristics, fire properties, and post-fire climatic conditions all influence recovery time. Gross primary production (GPP) is the most important determinant of recovery time: ecosystems with higher GPP recover faster. Fires with greater intensity and duration, which cause more extensive vegetation damage, are associated with longer recovery times. Post-fire climate also affects recovery time: anomalously high temperatures and temperature seasonality, and increased number of dry days, cause slower recovery, while above-average precipitation accelerates recovery. Recovery times vary between different biomes, potentially reflecting variations in plant fire adaptations: ecosystems with a higher abundance of resprouting plants recover more rapidly. These findings provide a global perspective on how vegetation responds to fire disturbances, offering insights into carbon and water cycle dynamics under changing climatic conditions.

How to cite: Shen, Y., Prentice, C., and Harrison, S.: Global Drivers of Post-Fire Ecosystem Recovery: Insights from Solar-Induced Chlorophyll Fluorescence, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3308, https://doi.org/10.5194/egusphere-egu25-3308, 2025.

Lightning-induced ignitions play a major role shaping the frequency, patterns and characteristics of wildfires in several regions across the globe, including extreme wildfire events (e.g., Góis wildfire in 2017 in Portugal) and fire seasons, such as 2019-20 in Australia, 2020 in California, and 2023 in Canada. The attention to lightning-ignited wildfires has been growing in recent years. Studies on LIWs frequently associate lightning and wildfire data to discern or approximate the place and moment of fire ignition. This typically requires to select the lightning strike responsible for the ignition.

Currently, several methods are applied to select the most likely lightning strike causing the ignition. However, this selection is complicated by, at least, two aspects. First, the spatial uncertainty of fire and lightning data (e.g., the location errors of detected lightning events). Second, the holdover phenomenon. Holdover time, commonly defined as the time between lightning-induced fire ignition and fire detection, can range from a few minutes to several days, and more rarely to some weeks or even months. Long holdover times are associated to the presence of a smoldering phase that hinders the detection of these lightning fires.

Here, we present a novel method that uses location accuracy information from lightning location networks, as well as expected distributions of holdover time, to assess the probabilities of lightning igniting wildfires. Our method computes a probability metric, which is the product of two independent probabilities: a spatial and a temporal probability. The spatial component assesses the probability of a cloud-to-ground lightning event striking within a given area surrounding the fire discovery point, while the temporal component evaluates the probability of a lightning-ignited wildfire undergoing a certain holdover time. The lightning event with the maximum probability metric value is then selected as the most likely ignition source. We applied this method in three study areas: Switzerland, Catalonia (Spain), and California and Nevada (USA). The results were compared with lightning selections identified by the index of proximity, one of the currently most common methods to select the most likely ignition source of lightning-induced wildfires.

The initial results indicate that the probability metric yields a different selection of lightning events, in comparison with the index of proximity, for a great proportion of wildfires, with considerable differences across the study areas. We suggest that the probability metric provides a solid alternative to current methods. The probability metric offers some advantages: (1) it simplifies some methodological decisions despite the need for additional computations; (2) it is flexible and can be adapted to different types of lightning and fire data (e.g., fire perimeters); (3) it has a more robust theoretical basis than current methods; and (4) the lightning selection can be enhanced over time due to continuous improvements in lightning and fire databases.

How to cite: Moris, J. V., Hunt, H. G. P., Álvarez-Álvarez, P., Conedera, M., Gordillo-Vázquez, F. J., Lapierre, J., Pérez-Invernón, F. J., Pineda, N., Pezzatti, G. B., Veraverbeke, S., and Ascoli, D.: A new probabilistic method to identify fire-igniting lightning events, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3335, https://doi.org/10.5194/egusphere-egu25-3335, 2025.

How to cite: Gincheva, A., Torres-Vázquez, M. Á., Di Giuseppe, F., Moreno Torreira, A., Jerez, S., and Turco, M.: Rising Synchronicity of Extreme Fire Weather Across Europe in a Warming Climate , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4352, https://doi.org/10.5194/egusphere-egu25-4352, 2025.

How to cite: Liu, Y., Qian, Y., and Wang, M.: Fire–precipitation interactions amplify the quasi-biennial variability in fires over southern Mexico and Central America , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5454, https://doi.org/10.5194/egusphere-egu25-5454, 2025.

Open biomass burning affects many aspects of the Earth system, including atmospheric chemistry and composition. Due to its impact on human health, we focus on the contribution of biomass burning emissions to fine particulate matter (PM_2.5) concentrations on a global, annual mean basis, particularly the lesser-studied secondary inorganic component. We use the EMEP MSC-W WRF atmospheric chemistry transport model to show that biomass burning leads to increased ammonium nitrate (NH₄NO₃) concentrations in densely populated regions not necessarily associated with large-scale fire activity. This is prominent in the eastern USA, northwestern Europe, the Indo-Gangetic Plane and eastern China, where NH₄NO₃ contributes between 29 and 51% to annual mean biomass burning-derived PM_2.5. Pyrogenic CO and NO_x (NO and NO₂) emissions alter the global-scale oxidising capacity of the atmosphere, affecting how local-scale anthropogenic NO_x and NH₃ emissions lead to formation of NH₄NO₃. These teleconnections can locally increase, by up to a factor of two, the contribution of biomass burning emissions to PM_2.5 concentrations, which measurements alone cannot detect. This will become relatively more important as anthropogenic sources of PM_2.5 are reduced, and with potentially intensified biomass burning occurrences under climate change.

How to cite: Tan, D. Y. T., Heal, M. R., Vieno, M., Stevenson, D. S., Reis, S., and Nemitz, E.: Changes in atmospheric oxidising capacity cause teleconnections between biomass burning and NH4NO3 formation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6847, https://doi.org/10.5194/egusphere-egu25-6847, 2025.

Wildfires pose a significant threat to ecosystems, human life, and infrastructure, particularly in South America, where diverse climatic and environmental factors contribute to their occurrence. Climate change has exacerbated extreme weather conditions such as intense heat and drought, leading to a global increase in the frequency and intensity of wildfires. Countries like Brazil have experienced significant rises in wildfire damage, highlighting the urgent need for predictive models that accurately assess future wildfire risks to mitigate their impact effectively. This thesis addresses this need by developing a wildfire risk prediction system leveraging deep learning methods and remote sensing data.

Using Earth Observation (EO) APIs, the system avoids downloading and storing vast amounts of satellite imagery, enabling efficient data acquisition and preprocessing. The study focuses on key variables that influence wildfire activity, including dynamic variables such as Land Surface Temperature (LST), Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), radiation, Leaf Area Index (LAI), evapotranspiration (ET), wind speed, and temperature, as well as static variables like land cover, Digital Elevation Model (DEM), and population density. The system is designed to predict wildfire risk for the next day and up to eight days, offering a robust tool for proactive wildfire management.

Given the stochastic and nonlinear nature of wildfire phenomena, this research employs advanced deep learning techniques, including Random Forests (RF), Long Short-Term Memory networks (LSTM), and Convolutional LSTM (ConvLSTM) models, to predict wildfire risk in near real-time. Active fire data from MODIS products, along with their burn dates, serve as the basis for training datasets. Non-fire points are generated by mapping the land cover distribution of fire points, ensuring balanced datasets for model training. Variables are extracted and classified into dynamic and static categories to capture both temporal variability and fixed geographical characteristics.

The objectives of this research are threefold: (1) to investigate existing remote sensing-based wildfire management methodologies and identify enhancements through the integration of data cubes and deep learning; (2) to develop a scalable platform for efficient data acquisition, preprocessing, and risk prediction using deep learning algorithms; and (3) to evaluate the system’s accuracy, efficiency, and scalability with real-world datasets and disaster scenarios.

Preliminary results highlight the effectiveness of integrating remote sensing data with deep learning models for wildfire risk prediction. Dynamic variables such as EVI, LST, and NDVI, along with human influence factors like Global Human Modification Index (gHM), emerged as key predictors, demonstrating the interplay of environmental and anthropogenic drivers in wildfire occurrences. Seasonal analysis from 2021 to 2024 revealed a strong correlation between fire activity, elevated temperatures, and declining vegetation indices from November to April. The Random Forest model achieved 83% accuracy, while the LSTM model showed promise with 75% accuracy, emphasizing the potential of both static and temporal data. These findings lay a robust foundation for enhancing wildfire risk management through advanced machine-learning approaches.

How to cite: Sanchez Vargas, J. A., Heisig, J., Painho, M., and Gharun, M.: Development of a Wildfire Risk Prediction System based on Deep Learning Methods and Remote Sensing, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7107, https://doi.org/10.5194/egusphere-egu25-7107, 2025.

Wildfire smoke is increasingly recognized as a significant source of air pollution that leads to public health issues. Over the past few decades, air pollution in Canada has been reduced due to effective regulations. However, fine particulate emissions (i.e., particles with an aerodynamic diameter of less than 2.5 μm (PM_2.5)) from wildfires have shown upward trends as climate change exacerbates the frequency and likelihood of wildfires. According to the Canadian Interagency Forest Fire Centre (CIFFC) in 2021, there were 18% more fire starts and nearly a 61% increase in the total area burned compared to the past 10-year average in Canada. The emissions inventories used for modeling the impact of fires on air quality and climate exhibit several discrepancies in emissions estimates, primarily due to the different types of satellite products used for identifying fires and measuring burned area, as well as differences in emission factors describing the vegetative fuels burned. This variability of fire emission inventories leads to uncertainties in  predicting air quality. Using the GEOS-Chem chemical transport model, we studied how differences in emissions estimates among three commonly used global biomass burning inventories—the Global Fire Emissions Database 4 (GFED4), the Global Fire Assimilation System (GFAS), and the Quick-Fire Emissions Database 2 (QFED2)—and a newly developed  regional biomass burning emission inventory, the Canadian Forest Fire Emissions Prediction System (CFFEPS), affect modeled concentrations of PM_2.5 during the 2021 wildfire season in Canada. To examine the sensitivity of simulated PM_2.5 to different biomass burning emission datasets, we compared them with ground based PM_2.5 data from 70 NAPS (National Air Pollution Surveillance) stations across Canada, from east to west. The simulated PM_2.5 concentrations showed significant variation in model performance based on the geographic location of the monitoring stations, particularly between the western and eastern regions of Canada. These findings indicate the importance of considering the strengths and weaknesses of each fire inventory, as some inventories may more accurately represent fire emissions in certain regions than others.

How to cite: Ashraf, S., Hayes, P., Stevens, R., and Chen, J.: Evaluating the Effect of Variability in Biomass Burning Emissions Inventories on Modeled Smoke Concentrations: Insights from the 2021 Canadian Wildfire Season, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7351, https://doi.org/10.5194/egusphere-egu25-7351, 2025.

Vegetation fires are well known as an important source of aerosol particles originating from the combustion of carbonaceous material. Much less known is that these fires can also efficiently inject soil-dust particles into the atmosphere, raised by the strong fire-induced winds. These soil-dust particles and the likely co-emitted biogenic particles are potent cloud condensation nuclei (CCN) and ice nucleating particles (INPs), and can substantially alter the cloud microphysics and thus impact the Earth’s radiation budget. Fires are an integral component of the Earth system that affect different landscapes around the globe. As they are supposed to get more frequent and more severe along with the ongoing global warming, a better knowledge of these specific fire emissions is crucial to understand their impacts on weather and climate.

Therefore, this work investigates the potential of wildfires to emit soil-dust particles on a global scale as a part of the newly established Leibniz ScienceCampus “BioSmoke” (‘smoke and bioaerosols in a changing climate’). As this particular dust emission pathway is not considered by the state-of-the-art dust emission models, a parameterization describing fire-induced dust emission fluxes has been developed and implemented into the global aerosol-climate model ICON-HAM. Fire-dust emissions are modelled as a function of the fire radiative power (FRP), the ambient wind conditions, and further soil-surface properties, including the soil type and a vegetation-dependent surface roughness correction.

Multi-year ICON-HAM simulations have revealed that fire-related dust emissions can account for up to one fifth of the total global dust emissions with strong regional and seasonal variations, both as the result of a varying fire activity and the local soil-surface conditions that can foster or impede also fire-dust emission significantly. In regions where the classic wind-driven dust emissions from arid, unvegetated soil surfaces are rather low but wildfires occur frequently, e.g., in large parts of the Southern hemisphere, fire-related dust emissions can add substantially to the atmospheric aerosol load and affect the local radiation budget there.

How to cite: Wagner, R., Tegen, I., and Schepanski, K.: Vegetation fires as a source of soil-dust particles – a global model perspective, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8307, https://doi.org/10.5194/egusphere-egu25-8307, 2025.

Recent advancements in machine learning (ML) have significantly broadened its applications, including the potential to transition from forecasting fire weather to predicting actual fire activity. In this study, we demonstrate the feasibility of this transition using an operational forecasting system. By integrating data on human and natural ignitions along with observed fire activity, data-driven models effectively address the persistent overprediction of fire danger in fuel-limited biomes. This results in fewer false alarms and more informative outputs compared to traditional methods.

A key factor driving this improvement is the availability of global datasets for fuel dynamics and fire detection, which were not accessible during the development of earlier physics-based models. We find that the enhanced predictive skill of ML models stems largely from the comprehensive characterization of fire processes provided by these datasets, rather than from the complexity of the ML methods themselves.

As enthusiasm gather around  data-driven approaches, our findings highlight the critical importance of high-quality training data in improving forecast accuracy. While the rapid advancement of ML techniques generates excitement, there is a risk of undervaluing the essential role of data acquisition and, where necessary, its creation through physical modeling. Our results underscore that investing in robust datasets is indispensable and should not be overlooked in the pursuit of  very complex algorithm.

How to cite: Di Giuseppe, F., Mc Norton, J., Wetterhall, F., and Lombardi, A.: The real drivers of the ML revolution in fire forecasting, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8637, https://doi.org/10.5194/egusphere-egu25-8637, 2025.

The Copernicus Atmosphere Monitoring Service CAMS is using ECMWF's Integrated Forecasting System IFS-COMPO with fire emissions from its Global Fire Assimilations System GFAS to monitor and forecast the effect of smoke from vegetation fires, resp. biomass burning, on atmospheric composition. The simulated atmospheric composition fields are routinely validated against observations including from satellites, aircraft and ground stations.

The emissions calculation by the operational GFAS version 1.2 have recently been updated for use in the upcoming HTAP3 multi-model, multi-pollutant study of fire impacts (Whaley et al. 2024), creating the dataset GFAS4HTAP. It is based on the dry matter burnt estimates of GFASv1.2, and uses an updated spurious signal mask, ESA CCI land cover data for 2018, a global peat map (Xu et al. 2018) and emission factors from NEIVA (Shahid et al. 2024) to calculate emission fluxes for various smoke constituents for 2003-2024. An additional GFAS-based dataset has been created by calibration against GFED5beta.

Global comparisons of dry matter, resp. biomass, combustion rates of the three GFAS-based inventories with GFED4s, GFED5beta, and the two variants of FINN2.5 reveal that these inventories can be roughly classified into one group of "traditional" inventories with lower fire activity, resp. emissions, and another of "more recent" inventories with higher fire activity. The pyrogenic carbon monoxide emission estimates from an inversion of satellite observations of atmospheric composition (Zheng et al. 2019) lie between these two groups in terms of global annual values. However, at a global level, they are more consistent with the "more recent" inventories during the late boreal summer peak of the global fire activity and with the "traditional" inventories during periods of lower fire activity.

In order to gain more insight from independent validation, we here present simulations with IFS-COMPO for 2019 based on the three GFAS-based inventories and compare these with atmospheric observations of carbon monoxide, nitrogen dioxide and aerosol optical depth. We find that the best agreement of simulation and observations is achieved by different inventories for different regions, seasons and smoke constituents. However, the emissions of the GFAS4HTAP dataset appears to lead to the overall most balanced atmospheric composition simulation. This supports the group of "traditional" inventories mentioned above.

How to cite: Kaiser, J., Huijnen, V., Remy, S., Ytre-Eide, M. A., De Jong, M. C., Zheng, B., and Wiedinmyer, C.: Evaluation of fire emissions for HTAP3 with CAMS GFAS and IFS-COMPO, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8708, https://doi.org/10.5194/egusphere-egu25-8708, 2025.

As the climate warmings, the frequency and intensity of wildfires have escalated in recent decades.  While the adverse effects of wildfires on air quality are well-documented, their influence on atmospheric ozone in China remains unclear. Here, we apply deep learning and a trajectory-fire interception method (TFIM) to estimate wildfire contributions to ozone concentrations in Chinese cities from 2015 to 2023. Our findings indicate that wildfires influenced 15.1 ± 9.3% of all days during this period, with a wildfire-induced ozone concentration averaging 6.8 μg m-³. Over the nine-year study period, these concentrations exhibited a modest upward trend, increasing by 0.091 μg m⁻³ annually. Regions such as Southwest China, the Qinghai-Tibet Plateau, and Northwest China experienced the highest levels of wildfire-induced ozone. We further utilize SHapley Additive exPlanations algorithms to investigate driving factor behind wildfire-induced ozone. The burnt area, aging hour, and injection height of smoke have a large effect on wildfire-induced ozone concentrations. Finally, we evaluated the health impacts of wildfire-induced ozone, highlighting its significant implications for public health in affected regions.

How to cite: Liu, S.: Explainable deep learning reveal the contribution of wildfire to ozone in China, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8751, https://doi.org/10.5194/egusphere-egu25-8751, 2025.

Fires as a disturbance regime are an important component of ecosystems, and are involved in many feedback loops within these systems such as climate-carbon feedbacks. The changing climate can influence fire regimes in multiple ways, both directly and indirectly. For example, changing weather patterns can directly alter the occurrence and timing of fire weather days. Weather patterns also influence vegetation growth and ecosystem composition, leading to changes in fuel availability and flammability. Meanwhile, humans also partially shape fire regimes via accidental and managed ignitions as well as various suppression measures.

In this study, we use 35 years of remote sensing data to establish global pyromes; regions of similar fire regimes, via their fire characteristics. This length of data period allows for the allocation of pyromes across multiple time segments, and for changes in their prevalence and spatial distribution to be observed. We have found that the majority of pyrome transitions occurring are shifts towards smaller or less frequent fires, and these transitions are widespread across the globe. However, some regions such as the Northern high latitudes, the Western United States, and Northern Australia are shown to experience larger or more frequent fires in the final observation segment of the study.

Following on from this, we use statistical methods to investigate relationships between pyromes and a wide variety of non-fire properties, including climate, vegetation, and human influence. This allows for inference of the most relevant drivers of pyrome change, both climatic and non-climatic. Initial results suggest for example, that population density is a more important predictor for pyromes with small and medium sized fires. However, there are significant challenges to disentangling the effects of such complex drivers within a relatively short observational period. Nevertheless, it is possible to build a picture of plausible fire regime evolution in regions with shifting environmental components.

How to cite: Butler, E., Sippel, S., and Bastos, A.: Global fire regimes, their non-fire characteristics, and changes in time., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9010, https://doi.org/10.5194/egusphere-egu25-9010, 2025.

Wildfires have a significant influence on the Earth system through perturbing the carbon cycle and also emitting large quantities of short lived climate forcers (SLCFs) such as aerosol precursors (black and organic carbon) and gases that can lead to ozone formation (carbon monoxide, nitrogen oxides). SLCFs are important as they affect the Earth’s radiative balance, influencing climate, and also can have important impacts on air quality in the near-surface atmosphere. Climate change and human interference also have important effects on the size, magnitude and duration of wildfires, which are important to understand further, particularly in the context of a changing climate. Such influences are potentially important in the northern high latitudes, where wildfires have been increasing in magnitude and frequency over the last few decades. Here, we present an evaluation of the representation of high latitude wildfires in a configuration of UKESM with an interactive fire module (INFERNO) coupled to chemistry, aerosol and radiation schemes.  We also show results from sensitivity studies analysing the influence of model process drivers on high latitude wildfires and their impacts on atmospheric composition over the recent past, including from changes in climate, socio-economic factors and underlying vegetation properties.

The baseline configuration of UKESM coupled with INFERNO shows an underestimation of burnt area from high latitude wildfires over the period 2000 to 2015 compared to that reported by GFED4s. The sensitivity scenarios show that this underestimation is found to be strongly driven by the human suppression factor included within INFERNO. The underestimation in burnt area is also reflected in the emission of SLCFs from high latitude wildfires e.g. CO, with implications for both climate and air quality. The INFERNO fire scheme does not currently include the representation of peat fires, which are important sources in the high latitude. When we include a representation of SLCF emissions from high latitude peat fires, the magnitude and temporal variability of such emissions are much improved in the model and compare better with those in GFED4s. Including this additional source also increases the contribution of wildfires to particulate air pollution and the degradation in surface air quality simulated by the model over the northern high latitudes. The interactive fire model coupled within UKESM is shown to underestimate high latitude wildfires due to missing sources and the representation of human interactions in this region. This has important consequences for regional air quality and climate in an area of the world experiencing rapid changes to its climate.

How to cite: Turnock, S., Teixeira, J., Burton, C., Blackford, K., Arnold, S., and O'Connor, F.: The Sensitivity of High Latitude Wildfires and their impacts on Atmospheric Composition to underlying driving processes in the UK’s Earth System Model (UKESM), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9049, https://doi.org/10.5194/egusphere-egu25-9049, 2025.

The backscattering linear depolarization ratio (LDR) is a key parameter to identify particle types. Previous studies on smoke LDR have shown significant differences in their measurements, with the magnitudes varying widely under different study scenarios. Single-particle models involving internally mixed black carbon (BC) are applied to assess the LDR of smoke aerosols. However, handicaps have been found to apply such models to describe the bulk optical properties of aerosols, because of their overlook of the contribution of externally mixed organic carbon (OC) to the LDR. Smoke aerosols typically consist of a low proportion of BC particle population and a high proportion of externally mixed OC particle population. If the spherical assumption is applied to the calculation of smoke LDRs, the LDRs turned to be extremely low even approach zero. This leads to difficulties in explaining the observed variability and higher levels of smoke LDR. We conducted a prescribed burning experiment in Xichang, Sichuan Province, China, and did onsite measurement on the LDR of smoke at a wavelength (λ) of 532 nm using atmospheric laser lidar. Field smoke particles were collected using a single-particle sampler and the morphology of particles was then characterized by the transmission electron microscope (TEM). The results indicated that the LDR of local smoke varied between 0 and 20.1%, with rapid fluctuations. The TEM images confirmed the coexistence of both internally mixed BC and externally mixed OC in the smoke aerosols, with OC displaying an ellipsoidal morphology even on copper grids. Using the discrete dipole approximation, we subsequently evaluated the LDR of individual BC and OC. Based on light scattering theory, we further quantified the bulk LDRs of the aerosol aerosols. The results shown that the smoke LDR ranged from 0.0% to 28.2% in λ = 532 nm while accounting for the effect of externally mixed OC. The LDR is slightly influenced by BC and is significantly affected by the externally mixed OC. Furthermore, the LDR is primarily governed by the morphology and particle size distribution of the externally mixed OC. It is concluded that the high levels and rapid variations in the LDRs of smoke can be largely attributed by the non-sphericity and particle size distribution of externally mixed OC. This study advances the methodologies for LDR measurements and evaluations of smoke aerosols from biomass burning.

How to cite: Qin, Z., Zhang, Q., Wang, H., and Zhang, Y.: The role of non-sphericity of externally mixed organic carbon in altering the backscattering linear depolarization ratio of smoke aerosols from biomass burning, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9452, https://doi.org/10.5194/egusphere-egu25-9452, 2025.

Fire is a natural phenomenon that modulates form, function, diversity and distribution of plant species affecting ecosystem dynamics. Global warming and land use change are altering fire regimens potentially threating ecosystem functioning and species persistence. However, pyrogeographical studies aiming to understand differences across fire regimens are usually not considering the role played of plant functional traits. Here, based on a recent pyroregionalization in Italy and using species distribution data from the Italian National Forest Inventory and trait values from public databases we assessed if: 1) species distribution across different pyroregions is affected by fire regime, 2) species in different pyroregions exhibit distinct fire-related trait values, and, if so, 3) trait differences suggest better abilities to cope with fire in species distributed in more fire-prone regions (e.g. thicker bark). Our results tend to positively answer our questions suggesting the necessity of including fire-related traits when studying pyroregions. Noticeably, our study showed that the most fire-prone pyroregions collapse into one region from a functional perspective, with species characterized by highly similar trait values and indicative of fire adaptations.

How to cite: Costa-Saura, J. M., Midolo, G., Ricotta, C., Baudena, M., Calfapietra, C., Elia, M., Fiorucci, P., Mereu, S., Sirca, C., Spano, D., Vivaldo, G., and Ottaviani, G.: Fire proneness of Mediterranean pyroregions is positively linked to tree functional traits indicative of fire-modulated responses, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10591, https://doi.org/10.5194/egusphere-egu25-10591, 2025.

Wildfires are an increasing concern for climate change, air quality and recognized for their substantial impacts on atmospheric composition. In addition to significant emissions of carbon dioxide (CO₂) and particular matter (PM), biomass burning events are characterized by substantial non-CO₂ emissions, which encompass a wide range of species. These emissions significantly influence atmospheric chemistry at a regional to global scale. Particularly in regions with ample fuel sources and hot, dry, or windy meteorological conditions, surface fires can lead to high-intensity crown fires and frequent downwind spotting. In certain circumstances, the intense formation of crown fires triggers the development of pyrocumulonimbus (PyroCb) atop smoke columns, which ascend to the upper troposphere and lower stratosphere (UTLS) and thus promote the dispersion of the fire emissions within wide regions. On August 2, 2019, the Williams Flats Fire ignited due to lightning from early morning thunderstorms in eastern Washington, USA. The main fire activity occurred between August 2 and August 9. On August 8, the high intensity crown fires led to the formation of a PyroCb. This event was observed and probed by the joint NOAA and NASA FIREX-AQ field campaign, providing a unique observation dataset. In this study, we utilize the Weather Research and Forecasting Model (WRF) to assess the impact of the Williams Flats fires on the atmospheric composition. In particular, we couple the representation of detailed multi-phase chemistry (WRF-CHEM) with WRF’s fire spread model (WRF-FIRE), employing WRF’s Large Eddy Simulation capabilities to resolve turbulence at resolutions of 100 m. In this presentation, results from WRF-FIRE-CHEM simulations with and without aqueous-phase chemistry will be shown to isolate its effects on the long-range transport of trace gases and aerosols.

How to cite: Rosanka, S., Juliano, T., Carlton, A. M., and Barth, M.: Large eddy simulations of the Williams Flat Fire: Aqueous chemistry in pyrocumulous clouds, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12104, https://doi.org/10.5194/egusphere-egu25-12104, 2025.

Machine learning (ML) models are widely used to predict wildfire occurrence and susceptibility (Brys et al., 2025). However, while these models excel at prediction, they often fail to provide insights into their inner workings or uncover the causal pathways driving wildfires. This study addresses this limitation by extending ML models beyond prediction to explore the drivers and causal pathways underlying wildfire occurrence. Our primary aim is to identify meaningful, interpretable patterns from wildfire data.

We developed a novel multi-stage clustering methodology inspired by Cooper et al. (2021) and Cohen et al. (2024). This approach integrates feature attribution (SHAP values), dimensionality reduction (UMAP), hierarchical clustering (HDBSCAN), and causal discovery methods: PC and FCI (Spirtes et al., 2001), and DirectLiNGAM (Shimizu et al., 2011). The causal methods were enhanced with prior background knowledge to derive meaningful insights. We used datasets from Italy (Cilli et al., 2022) and the Netherlands.

A central feature of our methodology is the use of SHAP values to define subgroups and derive causal pathways. SHAP values reduce noise in the feature space while preserving critical information for clustering. By reducing multidimensional SHAP values to two dimensions with UMAP, we improved clustering performance and interpretability. The resulting clusters were described using concise, non-overlapping decision rules based on the original variables, eliminating the need for manual filtering commonly required in clustering raw feature space. The identified clusters revealed specific relationships between wildfire drivers and occurrence. For each cluster, we applied advanced causal discovery techniques to derive probable causal pathways, aligning the findings with the knowledge of stakeholders and domain experts. These actionable and interpretable explanations offer practical utility.

Findings from the case studies demonstrate that supervised clustering effectively characterizes wildfire occurrence by linking it to influencing factors. Furthermore, the approach provides valuable insights into cluster-specific causal pathways. The methodology translates complex relationships into simple causal logic, offering stakeholders and domain experts the necessary context to understand the model's behavior.

Brys, C., La Red Martínez, D.L. & Marinelli, M. Machine learning methods for wildfire risk assessment. Earth Science Informatics 18, 148 (2025). https://doi.org/10.1007/s12145-024-01690-z

Cilli, R., Elia, M., D’Este, M., Giannico, V., Amoroso, N., Sanesi, G., Lombardi, A., Pantaleo, E., Monaco, A., Tangaro, S., Bellotti, R. & Lafortezza, R. (2022). Explainable artificial intelligence (XAI) detects wildfire occurrence in the Mediterranean countries of Southern Europe. Scientific Reports 12, 16349. https://doi.org/10.1038/s41598-022-20347-9

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How to cite: Korving, H. and Van Marle, M.: Decoding Wildfires - Extracting Interpretations and Causal Pathways of Catalysts for Wildfire Occurrence from Machine Learning Models, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12889, https://doi.org/10.5194/egusphere-egu25-12889, 2025.

Rising temperatures and changing climate conditions have increased wildfire risk across the world, including in regions such as The Netherlands that have not historically faced these threats. With this trend expected to continue, understanding risk perceptions among individuals with little to no wildfire experience becomes crucial for mitigating the impacts and designing effective risk communication strategies.

Recent advancements in Artificial Intelligence (AI) wildfire mapping tools have proven highly effective in identifying areas susceptible to wildfires, particularly in detecting low-probability incidents by uncovering subtle patterns often missed by traditional methods. For example, machine learning (ML) wildfire risk maps developed by MEJOR Technologies have accurately predicted wildfire locations in The Netherlands in the past. Despite the potential, the use of these tools as communication instruments to improve wildfire risk perception among the public remains largely unexplored.

Through an online randomised experiment conducted among a sample of residents in the Veluwe area of The Netherlands, we empirically assess how AI-generated labelling (AI label, ML label, or no label) and information presentation formats (map, text, or combined) affect individuals’ perceived wildfire risk. Additionally, we investigate whether perceived trustworthiness in technologies and emotion mediate these effects, providing deeper insights into the cognitive and affective processes that shape how individuals in this area perceive wildfire risk. By leveraging our results, policy makers and AI mapping developers can design effective communication interventions and improve public preparedness in the face of wildfires. While our findings are specific to wildfires in the Veluwe area, they may also hold relevance for understanding the perception of other low-probability hazards among individuals with little to no prior exposure.

How to cite: Mijailovic, M., Ranucci, A., Geib, C., Nardelli, B., Koppen, E., Tamura, F., and Kandathil Parambil, P.: Using AI-enabled wildfire risk maps to communicate risk: the role of labelling, information presentation, perceived trustworthiness and emotion in shaping perceived risk in Veluwe, Netherlands, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13378, https://doi.org/10.5194/egusphere-egu25-13378, 2025.

There are multiple feedback mechanisms between wildfires and climate, such as temperature, emissions, cloud interactions, deposition, and land cover changes. Wildfires can also have large societal and ecological impacts and are considered as an extreme climate event. Despite this, most Earth System Models have, until recently, used prescribed fire emissions and fire plume injection heights for input into their atmospheric models that were unresponsive to climate changes. Fire plume heights, in particular, have a great influence on the radiative forcing and long-range transport of pollutants. This presentation will show recent results from global modelling of interactive fires (land-atmosphere) in the Canadian Earth System Model (CanESM), with a focus on key wildfire characteristics, such as aerosol emissions and fire plume height. These model improvements introduce the capacity to more accurately simulate future projections of wildfire characteristics under different climate scenarios. The upcoming applications of these improvements include experiments for the Hemispheric Transport of Air Pollution (HTAP) Fires project, AerChemMIP2, and Aerocom. HTAP Fires is a multi-model, multi-pollutant study with the goal of improving global fire modelling and using the multi-model ensembles to provide estimates of fire-related pollution for impact studies and policy makers.

How to cite: Whaley, C., Digby, R., Arora, V., Chen, J., Makar, P., Anderson, K., Griffin, D., Keating, T., Butler, T., Kaminski, J., and Wu, R.: Modelling interactive fires: climate-fire feedbacks on fire characteristics and multi-model projects, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13774, https://doi.org/10.5194/egusphere-egu25-13774, 2025.

Fire plays a critical role in the Earth system, both as a driver and responder to climate change. Variations in vegetation cover and ignition patterns, influenced by climate, affect fire behavior, while fire emissions impact climate by altering radiative fluxes and cloud properties. Despite these interactions, most global climate models fail to fully represent the dynamic interplay between vegetation, fire, and climate. In this study, we leverage the prognostic fire module from GFDL’s Land Model (LM4.1), which includes dynamic vegetation processes, to interactively calculate biomass burning emissions and injection heights. Emissions are then coupled with the atmospheric chemistry and aerosol component (AM4.1) in GFDL’s Earth System Model version 4.1 (ESM4.1). The model calculates fire radiative power (FRP) from fire spread rates and fuel content, using it alongside atmospheric parameters like boundary layer height and Brunt-Väisälä frequency in the Sofiev injection height scheme. Fire emissions are calculated using carbon release rates from biomass estimated by the land model and emission factors from Akagi et al. (2011) and Andreae and Merlet (2001), and these emissions are integrated directly into the atmospheric model for interactive coupling. 

We conducted a coupled simulation in AMIP mode and compared the modeled emissions with the observation-based Global Fire Emissions Database (GFED4.1s). Preliminary results show a promising agreement for global fire emissions of trace gases and aerosols during the 1997–2014 period, with seasonal variability falling within the error margins of observed emissions. We then compared results from interactive fire emissions experiment with a fixed fire emission experiment to analyze the direct radiative effects of fire-emitted aerosols. By treating fire emissions as an interactive component of the Earth system, rather than as a prescribed external forcing, this approach enables a more comprehensive representation of fire-climate feedback and enhances the assessment of radiative effects from fire aerosols.

How to cite: Pouyaei, A., Ginoux, P., Shevliakova, E., and Malyshev, S.: Interactive Fire Emissions Coupled with Climate and Chemistry in GFDL’s Earth System Model version 4.1, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13861, https://doi.org/10.5194/egusphere-egu25-13861, 2025.

Wildfires emit a complex mixture of trace gases and aerosols that significantly impact air quality, climate, and atmospheric chemistry. Key trace gases include carbon dioxide (CO₂), carbon monoxide (CO), nitric oxide (NO), methane (CH₄), and volatile organic compounds (VOCs). Wildfire-generated aerosols predominantly consist of organic carbon (OC), black carbon (BC), and secondary organic aerosols (SOA). Over recent decades, the frequency and intensity of wildfires, particularly in the western United States, have risen due to warmer temperatures and prolonged periods of drought. This trend has led to increased fire activity and smoke emissions, causing wildfires to be a growing contributor to regional and global aerosol forcing, in turn affecting the Earth's radiation budget and climate system. However, substantial uncertainties remain in estimating the composition and quantity of wildfire emissions.

Large variability in biomass burning aerosol estimates across different fire emission inventories poses challenges for accurate air quality and climate impact assessments. To address these challenges, we leverage observational data from the FIREX-AQ and WE-CAN campaigns to investigate how wildfire characteristics such as individual fire size, fire radiative power, and fuel composition influence the chemical composition of wildfire emissions, particularly VOCs. We then develop and apply an artificial neural network in tandem with dimensionality reduction methods to estimate smoke chemistry utilizing fire characteristics. Our machine learning model's results are compared with existing observations and current fire emission inventories to improve our understanding of wildfire emissions and their impacts.

How to cite: Zhang, Y., Barth, M., Emmons, L., Kelp, M., Juliano, T., Tang, W., Hornbrook, R., and Apel, E.: Understanding Wildfire Emissions: From Composition to Variability, and their Link to Fire Characteristics , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14193, https://doi.org/10.5194/egusphere-egu25-14193, 2025.

In 2024, Bolivia experienced the worst year of fires since 2002, when Aqua MODIS began collecting data. According to estimates, more than 15 million hectares were burned this year. A sunphotometer sitting in the Bolivian lowlands recorded AOD values higher than two for several continuous days indicating the degradation of the air quality in the region. A unique set of instruments located in the Bolivian Andes recorded the transport of smoke produced by this biomass burning. Very high values of atmospheric tracers like carbon monoxide, equivalent black carbon, and others have been measured as high as 5240 m asl  at the Chacaltaya GAW station (CHC, 16.35ºS, 68.13ºW, 5240 m asl) and other sites around it both in the Altiplano and adjacent high altitude valleys. Although transport to these sites was observed previously, usually the events lasted one or two days. However, in 2024 longer periods of consecutive days with smoke arriving from the lowlands were observed for a second year in a row. Similar high values were observed in CHC in October of 2023, a year with less than half of fires in the country. The conditions that led to the transport of smoke to the mountains in the Andean Cordillera will be discussed, as well as the possible effects of the associated deforestation in terms of water availability for the central Andes.

How to cite: Andrade, M., Ticona, L., Velarde, F., Guzman, D., Blacutt, L., Forno, R., Gutierrez, R., Moreno, I., Avila, F., Uzu, G., Goloub, P., Ramonet, M., Laurent, O., Wiedensohler, A., Weinhold, K., Krejci, R., Aliaga, D., Whiteman, D., and Laj, P.: Intense transport of smoke to the Central Andes: Insights from a unique set of instruments located in the Bolivian Andean Cordillera, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14573, https://doi.org/10.5194/egusphere-egu25-14573, 2025.

The temporal coverage from ˜2000 to present of global burned area satellite observations limits many aspects of fire research. As a result, global fire models are often being used to investigate past and future fire behaviour. Unfortunately, the limited temporal coverage of the observations also hinders the development and evaluation of these fire models. The current generation of global fire models are capable of simulating some characteristics of regional fire behaviour, such as mean state and seasonality, well. However, the performance of these models differs greatly from region to region, and aspects such as extreme fire behaviour are not well represented yet.

Here, we propose a new, data-driven fire model that predicts burned area from the same input parameters that are passed to global fire models. We trained LSTMs to model burned area from GFED5. We split our data according to the IPCC regions and perform a region-based cross-validation, that is, we train different LSTMs on different region-splits of the data. We then compose the predictions of these different models so that for each region the predictions are made by LSTMs that have never seen any data during training and validation from that region before. Our model outperforms all fire models on a global scale and in most IPCC regions. With our model, we can improve our understanding of past fire behavior and simulate future fire trends.

How to cite: Lampe, S., Gudmundsson, L., Kraft, B., Le Saux, B., Hantson, S., Kelley, D., Humphrey, V., Chuvieco, E., and Thiery, W.: Modelling global burned area with deep learning, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15236, https://doi.org/10.5194/egusphere-egu25-15236, 2025.

In recent years, large wildfires have spread in Arctic regions as a consequence of ongoing climate change. Arctic organic soils are comparatively shallow but may be ancient, thus thousands of years old carbon may be released in smoldering and deeply burning fires. In Greenland, a land known for its icy expanse, fires are extremely rare. However, in summer 2019, the second-largest wildfire ever recorded on the island occurred at the Kangerluarsuk Tulleq fjord in southwestern Greenland. This study aims to produce pioneering in-field data on this tundra fire, focusing on three key aspects: 1) combustion, 2) burn depth, and 3) the age of the carbon released. Understanding whether the released carbon is modern or old is crucial due to different implications for the global carbon cycle and climate. To estimate carbon losses from the Kangerluarsuk Tulleq tundra fire, we established 14 sampling plots in burned areas and at unburned control sites. The selection of sampling plots was guided by a differenced Normalized Burn Ratio (dNBR) map generated using Sentinel-2 data and field reconnaissance. Within each plot, we assessed fire severity to estimate the above-ground carbon loss. For below-ground carbon loss estimation and burn depth analysis, organic soil samples were collected at burned plots and compared with unburned ones. To explore the vegetation succession and burned vegetation type, organic soil profiles (n=10) were extracted down to the mineral ground using a soil box corer and were studied by light-microscopy. Subsamples (n=20) from burned soil horizons were selected for radiocarbon dating to determine the age of carbon released in the fire. Our preliminary results suggest that soil carbon loss was higher than previously reported at an Alaskan tundra fire site with a mean value of 6.718 ± 0.9 kg of C m^-2. The mean burn depth was 9.0 ± 1.8 cm, and soil thaw depths during the 2024 summer were approximately 24 cm deeper in the 2019 burned area compared to unburned tundra. Expected radiocarbon results will indicate the maximum age of the carbon released by the fire. Vegetation succession measurements show that post-fire surfaces were predominantly colonized by pioneering non-Sphagnum bryophytes, Cyperaceae, and Ericaceae. The acquired results are first of a kind from a Greenland tundra fire and produce essential data for global climate modeling to assess the climate impacts of increasing Arctic wildfires.

How to cite: Granqvist, S., Diaz, L., Veraverbeke, S., Pilkama, E., Väliranta, M., and Ruppel, M.: Carbon emissions of an unprecedented Greenland wildfire, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15318, https://doi.org/10.5194/egusphere-egu25-15318, 2025.

Peatland fires pose significant environmental and societal challenges. We recently advanced the Canadian Fire Weather Index (FWI) system for northern peatlands by integrating peatland-specific hydrological data derived from assimilating Soil Moisture and Ocean Salinity (SMOS) L-band brightness temperature observations into the NASA Catchment Land Surface model with its peatland modules, ‘PEATCLSM’. This novel FWI_peat (Mortelmans et al. 2024) was evaluated using satellite-based fire presence data over boreal peatlands from 2010 through 2018, demonstrating improved estimation of peatland fire presence.

Here, we extend the use of this renewed FWI_peat system by integrating it into a machine learning framework to gain deeper insights into when, where, and why peatlands burn. We utilize an XGBoost algorithm trained on peatland burned area data from 2012-2023, incorporating a suite of predictors, including (i) peatland distribution characteristics, (ii) peatland groundwater table, (iii) lightning occurrence, (iv) meteorological data, (v) vegetation properties, and (vi) socio-economic factors. This approach enables proactive fire risk management strategies and contributes to a comprehensive assessment of peatland fire vulnerability and resilience. Preliminary results indicate the importance of peatland groundwater table and lightning occurrence in estimating peat burned area.

Mortelmans, J., Felsberg, A., De Lannoy, G. J. M., Veraverbeke, S., Field, R. D., Andela, N., and Bechtold, M.: Improving the fire weather index system for peatlands using peat-specific hydrological input data, Nat. Hazards Earth Syst. Sci., 24, 445–464, https://doi.org/10.5194/nhess-24-445-2024, 2024.

How to cite: Mortelmans, J., De Lannoy, G., Dunmire, D., Veraverbeke, S., Waddington, J., Scholten, R., and Bechtold, M.: Modeling peat burned area and understanding its drivers with machine learning, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15841, https://doi.org/10.5194/egusphere-egu25-15841, 2025.

The recent surge in forest fires has significantly impacted atmospheric chemistry, carbon cycles, and climate. Wildfires release CO₂ along with various reactive species such as CO, volatile organics, and nitrogen oxides. While the effects of CO₂ emissions on the carbon cycle and climate, as well as the impact of reactive species emissions on air quality and health, have been extensively studied, this research demonstrates that reactive species emitted from wildfires create a positive climate feedback through the “fire-chemistry-methane” mechanism. In this process, chemical reactions of reactive carbon species suppress the concentration of hydroxyl radicals, extending the lifetime of heat-trapping methane. The significance of this feedback is suggested by observations of multiple proxy gases for global atmospheric oxidation (i.e., methyl chloroform, methane, and CO) during recent extreme forest fire events. By coupling a fire-ecosystem model and an atmospheric chemistry model, we quantify the effect of this feedback in the future. We find that additional warming caused by this mechanism rivals that of wetland methane feedback and fire CO₂ feedback by the 2050s under an intermediate climate scenario. Our analysis highlights the critical role of atmospheric chemistry in regulating fire-climate interactions and the methane budget.

How to cite: Chen, W., Zhang, Y., Zou, Y., and Zhang, Z.: Climate feedback of forest fires amplified by atmospheric chemistry, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16179, https://doi.org/10.5194/egusphere-egu25-16179, 2025.

Wildfires have shaped ecosystems for millions of years, with plant functional traits playing a key role in fire behaviour and severity. Morphological and physiological traits, particularly at the leaf and shoot levels, influence flammability by determining fuel composition and structure within both canopy and litter layers. These traits are hypothesized not only to affect critical fire dynamics, such as the likelihood of surface fires transitioning into crown fires, with significant consequences for fire intensity and ecosystem impacts, but also influence the evolution of fire-related traits.

This study investigates how leaf- and shoot-level morphology influences flammability in canopy and litter contexts across six dominant conifer families: Araucariaceae, Cupressaceae, Pinaceae, Podocarpaceae, Taxaceae, and Taxodiaceae. Flammability properties were assessed using fire calorimetry to measure ignitability, flame spread, and variability in the rate of energy release from combustion. Results indicate that while shed plant parts (e.g., leaves and shoots) shape fire behaviour by influencing bulk density, aeration, and flame spread rate—ultimately affecting burn sustainability and total energy release—shoot-level traits in isolation, including leaf shape and the arrangement of leaves within shoots, do not consistently predict flammability in canopy material.

Our findings highlight the dynamic interplay between plant morphology, fire regimes, and evolutionary pressures. Traits such as leaf size, shape, and arrangement contribute to fuel structure, driving patterns of fire behaviour that influence long-term plant fitness and survival. This underscores the importance of reconciling fire behaviour, plant functional traits, and the evolutionary history of fire adaptations across phylogenies.

With global change drivers intensifying fire regimes, understanding the relationship between plant flammability, fire regimes, and the acquisition of fire-related traits is increasingly critical. Non-fire-adapted species may face heightened extinction risks, threatening ecosystem stability. Quantifying the intrinsic flammability of plant traits is therefore essential for informing fire management, guiding conservation strategies, and ensuring the long-term sustainability of vegetative communities in a changing climate.

How to cite: Koll, R. and Belcher, C.: Morphological drivers of flammability in canopy and litter contexts across conifer families, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16840, https://doi.org/10.5194/egusphere-egu25-16840, 2025.

The interactions of different components of the Earth system, such as between the biosphere and the atmosphere, are still poorly understood. A major issue is understanding the consequences of increasing wildfire  activity in a changing climate. Smoke particles and gases emitted from such fires affect air quality and the Earth’s radiation balance, and can potentially affect the formation of clouds and precipitation. Understanding links between biodiversity and type of vegetation, smoke emission and the atmospheric distribution and processing of these particles and gases is key for assessing potential impacts and future changes. Addressing the depth of processes in the interconnected atmosphere-climate-vegetation system requires a combination of expertise from various scientific disciplines. The new Leibniz ScienceCampus “Smoke and bioaerosols: Release, processes, and impacts in a changing climate” (BioSmoke) located in Leipzig, Germany will combine expertise in atmospheric and biodiversity research as well as atmospheric processes at several research institutions including the Leibniz Institute for Tropospheric Research and Leipzig University to study effects of the release of aerosol particles from vegetation. To this end, combustion experiments in the laboratory, field measurements of aerosol properties, and remote sensing and modelling of particle emission, transport, and atmospheric effects are envisioned. We will present an overview of the planned projects within the ScienceCampus.

How to cite: Tegen, I., Wagner, R., and Tesche, M.: Introducing the Leibniz Science Campus “Smoke and bioaerosols: Release, processes, and impacts in a changing climate”, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17284, https://doi.org/10.5194/egusphere-egu25-17284, 2025.

South eastern Mediterranean region of Türkiye is well known with intense industrialization, shipping activities, agriculture and livestock production in addition to urban emission sources, thus struggle with significant air pollution problems. In addition to criteria pollutants, combination of these sources also results in high ammonia (NH₃) levels in the region.

NH₃ is released into the atmosphere mainly from agriculture, including nitrogen-based fertilizer applications and livestock farming as well as from several industries and from biomass burning. Atmospheric NH₃ plays a significant role in the formation of secondary inorganic particulate matter (PM), which negatively impacts on human health and ecosystems and indirectly influences climate change by altering radiative forcing. Climate change has increased the frequency and intensity of wildfires globally, which became another significant source of NH₃ over the Eastern Mediterranean, because the region is among the most sensitive regions. Besides wildfires, agricultural residue burning, although prohibited, also contributes to overall NH₃ levels.

Biomass burning contributes to atmospheric pollutants, as the combustion process emits nitrogen and carbon compounds from organic matter. In this study, multi-satellite derived retrievals were utilized, including IASI Level-2 NH₃ and CO, TROPOMI Level-2 NO₂, CO, and HCHO along with VIIRS S-NPP Fire Radiative Power product to investigate biomass burning related NH₃ levels. Products were processed at a 1x1km² gridded resolution to analyse spatio-temporal variations from 2019 to 2023, especially focusing on intense fire time intervals. While NH₃ levels were generally high during the summer over the region, the 2021 summer stood out with exceptionally high levels, coinciding with intense wildfires recorded that year. Similarly, CO levels revealed elevated levels during the same period, further strengthening the common impact of these extreme events. Further, fires detected over some areas by the VIIRS product were associated with residue-burning practices, as the area predominantly consists of agricultural lands.

The aim of the study is to investigate the impacts of fire-related NH₃ levels and quantify NH₃ enhancements during these fire events in the region. In this context, NH₃ to other pollutant ratios will be examined and temporal variation between different biomes will be classified. Air quality and climate change impact studies over the Mediterranean are critically important, with the absence of ground-based NH₃ measurements, satellite retrievals have to be utilized more to investigate the sensitivity of the region to extreme biomass burning events with the growing impacts of climate change.

Keywords: ammonia, carbon monoxide, nitrogen dioxide, biomass burning, wildfires

Acknowledgements: IASI is a joint mission of EUMETSAT and the Centre National d'Etudes Spatiales (CNES, France). The authors acknowledge the AERIS data infrastructure for providing access to the IASI data in this study and ULB-LATMOS for the development of the retrieval algorithms. This study was supported by the Scientific and Technological Research Council of Türkiye under the grant number 123Y364.

How to cite: Saracoglu, S., Alban, A. M., Tokgoz, S., and Kaynak, B.: Investigation of the intense wildfire events and NH3 levels over the Eastern Mediterranean, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17646, https://doi.org/10.5194/egusphere-egu25-17646, 2025.

Within the framework of the project PolarRES  (POLAR Regions in the Earth System) we assess the impact of climate change on the ecosystems of the terrestrial northern high latitudes by making use of a range of high resolution regional climate simulations. These regional simulations were themselves driven by global climate simulations selected following the storyline approach described in Levine et al. 2024 from the set of CMIP6 SSP3-7.0 simulations, namely NorESM2-MM and CNRM-ESM2-1. These define two extremes in the climatic envelope of the CMIP6 simulations. While NorESM2-MM shows a high warming of the Barents-Kara seas but a low Arctic tropospheric warming CNRM-ESM2-1 shows the opposite. The storyline approach is a comprehensive way of defining pathways for physical outcomes of climate change that are observable in the region of interest and can directly be linked to certain consequences.

The 2^nd generation Dynamic Global Vegetation Model (DGVM) LPJ-GUESS with its wildfire model SIMFIRE-BLAZE was applied using the high-resolution meteorological forcing from the regional climate models (RCMs) to investigate the potential impacts on both vegetation and the development of wildfires as well as the role of uncertainty implied by the variability of the forcing data.

It can clearly be stated that wildfire activity will increase significantly under the given scenarios driven mainly by shifts in vegetation distribution, i.e. northward migration of both treeline as well as shrubs and grasses. These effects differ regionally, depending on both, the storyline and the RCMs.

We present the findings from an envelope of potential future climate forcings depicting the impact of climate depending on the regionally observable effects of Arctic tropospheric warming and the Barents-Kara Seas warming, making use of the storyline approach as a comprehensive indicator for regional future change.

The results of this assessment will directly influence the research conducted in the project GreenFeedBack (GREENhouse gas fluxes and earth-system FEEDBACKs), which focusses on enhancing the knowledge on GHG dynamics in the boreal high latitude terrestrial and marine ecosystems.

Levine, X. Jet al. : Storylines of summer Arctic climate change constrained by Barents–Kara seas and Arctic tropospheric warming for climate risk assessment, Earth Syst. Dynam., 15, 1161–1177, https://doi.org/10.5194/esd-15-1161-2024, 2024

How to cite: Nieradzik, L., Lee, H., Levine, X., Miller, P., Mooney, P., Mottram, R., and Wårlind, D.: Assessing the impact of climate change on boreal high latitude wildfire using a storyline approach, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17962, https://doi.org/10.5194/egusphere-egu25-17962, 2025.

For thirty years, the European Research Infrastructure IAGOS (In-Service Aircraft for a Global Observing System) has been equipping commercial aircraft with instruments to measure atmospheric composition on long-haul flights around the world.  Ten aircraft are currently equipped with IAGOS instruments to measure ozone, and the precursors carbon monoxide and nitrous oxides from the surface to the upper-troposphere during landing and take-off at worldwide airports,  and at cruise altitude where we observe the long-range transport of polluted airmasses. We analyse the transport of biomass burning pollutants from the intense Canadian wildfire seasons of 2023 and 2024 which impacted air-quality in North America and in Europe, and the extreme wildfires over the Amazon in 2024 that impacted air quality in South American cities.  The significance of these events is interpreted within the context of the 30-year climatology. The events will be compared with forecasts and analyses from the Copernicus Atmosphere Monitoring Service's global and regional models (projects CAMS2_82 and CAMS2_83) and we further  highlight the role of IAGOS  in developing air-quality networks in susceptible urban areas (project RI-URBANS) and the impacts of heatwaves and wildfires on air-quality in a changing climate (project IRISCC).

How to cite: Bennouna, Y., Clark, H., Wolff, P., Thouret, V., Blot, R., Nédélec, P., and Boulanger, D.: Impact of wildfires on air quality as seen by IAGOS in-situ measurements, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18252, https://doi.org/10.5194/egusphere-egu25-18252, 2025.

Whilst global burned area continues to decline, recent climate warming has led to an increase in the occurrence and intensity of extreme fires. Humanity must adapt to this new reality. Two proposed management options are a) prescribed livestock grazing, and b) prescribed fire use. Both methods promise cost-efficient means to reduce fire intensity, fire-induced vegetation mortality, and carbon emissions by reducing and fragmenting fuel loads. However, at present, there has been no systematic global assessment of the efficacy of these interventions. Reasons for this include a lack of data to understand their present-day distribution and impact as well as a lack of formal model structures to represent their uptake under future scenarios.

Here, we present two applications of the newly developed global, agent-based Wildfire Human Agency Model (WHAM!)¹ to assess the potential effect of prescribed grazing and prescribed fire as adaptations to future fire regimes. Firstly, to explore the effect of prescribed livestock grazing on global fire regimes, we share a representation of livestock grazing intensity in WHAM! and its integration with the generalised linear models of Haas et al., (²). Secondly, we present work on a tight coupling of WHAM! with the JULES-INFERNO dynamic global vegetation model, focusing on parameterisation of how managed human fire use reduces fire-induced vegetation mortality.

Overall, early results suggest both management options already play a significant role in reducing global fire intensity and highlight the importance of considering dynamic human responses to a changing climate in global projections of future fire regimes.

¹Perkins, O… et al. (2024). GMD.

²Haas, O. et al., (2022). Env. Res let.

How to cite: Perkins, O., Haas, O., Kasoar, M., Kelley, D., Teixeira, J. C. M., Voulgarakis, A., and Millington, J. D. A.: Adapting to fire in a warming climate: towards global assessment of prescribed grazing and prescribed fire, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18640, https://doi.org/10.5194/egusphere-egu25-18640, 2025.

Wildfires exert a important influence on the chemical composition of the atmosphere, thereby impacting air quality, ecosystem, and climate forcing. The substantial emission of pollutants from such fires, coupled with their long-range transport, has the potential to counteract the progress achieved in reducing anthropogenic emissions. Numerous studies show that the increase in the frequency and intensity of fires offsets the general trend towards improved air quality observed in regions influenced by wildfires. These studies also caution of an increasing risk of the population being exposed to extreme levels of aerosols and ozone. In addition to their regional impacts, the plumes from the most intense fires can be transported on a continental or even hemispheric scale, thereby imposing health constraints on regions that are not generally affected by widespread, frequent or intense fires.

The northern hemisphere is home to a group of biomes that are particularly sensitive to hydro-meteorological conditions, and therefore to the effects of climate change on burned areas. The majority of the most intense fires of the last two decades have occurred in North America and in the boreal regions of Asia.

This study assesses the impact of fires on the variability of total CO, total PAN and AOD in the Northern Hemisphere using 16 years (2008-2023) of observations from the IASI/MetOp and MODIS/Terra and Aqua satellite instruments. More specifically, the variability in the number of detected plumes of extreme values of CO, PAN and aerosol from fires is studied.

The trajectories of these plumes are estimated using only satellite observations and are used to assess the contribution of the different regions of the Northern Hemisphere to the variability of atmospheric composition. The potential impact of the long-range transport of the identified plumes on air quality is estimated using observations of the altitude of the plumes obtained from both active CALIOP observations and passive IASI observations.

The chemical composition of the identified plumes is characterised using IASI observations of ammonia (NH₃), formic acid (HCOOH), methanol (CH₃OH) and ozone (O₃).

How to cite: Ehret, A., Turquety, S., Lecomte, G., Franco, B., George, M., Clarisse, L., Van Damme, M., Clerbaux, C., and Coheur, P.: Satellite observation of long-range transport of wildfires plumes in the northern hemisphere in 2008-2023, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18688, https://doi.org/10.5194/egusphere-egu25-18688, 2025.

Peatlands, despite covering only 3% of the terrestrial surface, are one of the world's most important carbon storage environments, accumulating around 25% of the total soil carbon. However, climate change is increasing the vulnerability of these carbon-rich ecosystems to fire, with potentially severe implications for the global climate. Warmer and drier conditions, driven by climate change, are expected to intensify and increase the frequency of peat fires, potentially transforming peatlands from carbon sinks into net sources of greenhouse gas emissions. Such a shift could trigger a positive feedback loop, accelerating climate change through the release of vast amounts of sequestered carbon into the atmosphere.

While incorporating peatland fire feedbacks into Earth System Models (ESMs) is essential for accurate climate projections, the majority of the existing models lack a representation of peat fires, limiting their ability to predict future climate dynamics effectively. Understanding the smouldering behaviour of organic soils, their ignition probability, and how these processes can be represented at a global scale is essential. The current state-of-the-art approach to compute peat combustibility, established by Frandsen (1997) and applied in recent peat fire modelling efforts (e.g., INFERNO-peat), relies on a parameterization derived from a single peat type, hampering its global applicability. Frandsen (1997), by conducting experiments on natural peat samples developed an empirical model for smouldering ignition probability based on three key properties of peat: moisture content, inorganic content, and bulk density.

Our study proposes an improved method for calculating peat combustibility by optimizing the coefficients in Frandsen’s model and investigating the ignition limits of diverse peat samples. The optimization process utilized experimental data from seven distinct peat types. First, we established through inverse modelling a link between inorganic content, bulk density and critical moisture content, the moisture threshold above which smouldering cannot be self-sustained. Then we determined the probability distribution of self-sustained smouldering, as a function of moisture content, around the critical moisture content, also employing inverse modelling. The combination of both optimizations yielded consistent coefficients, providing a more robust framework for modelling peat ignition probability.

By improving the representation of peat ignition probability using experimental data from both previous studies and our own experiments, this work aims to upgrade the simulation of peat fires in fire models and ESMs, enhancing our understanding of the impacts of such fires on future atmospheric composition, radiative forcing, and climate.

How to cite: Tarasi, D., Kasoar, M., Mulyasih, H., Castagna, A., Rein, G., and Voulgarakis, A.: An improved approach for simulating peat ignition probability using experimental data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18848, https://doi.org/10.5194/egusphere-egu25-18848, 2025.

Globally, approximately half of landscape fire emissions originate from savannas and grasslands. Furthermore, our observations in South Africa indicated major secondary aerosol formation in near-fire plume ageing. However, the measurements in South Africa are affected by anthropogenic emissions from the Highveld region, except for a clean sector towards the semi-arid Karoo region. Aiming for a savanna environment with minimal anthropogenic influence we set up a new measurement site in the Okavango delta area in northern Botswana in August 2024.

For the active savanna fire season in 2024, we operated online measurements of aerosol chemical composition with an aerosol chemical speciation monitor (ACSM), an online gas chromatograph coupled to an MS detector (GC-MS) for volatile organic compounds and a single particle soot photometer (SP2) for refractive BC. Measurements of aerosol particle size distribution with a differential mobility particle sizer (DMPS), aerosol absorption with a multi angle absorption photometer (MAAP), as well as CO and CO₂ concentrations will continue for the next couple of years at least.

For fresh plumes, initial analysis shows a strong decrease in submicron aerosol emission factor (EF_PM1) with increasing modified combustion efficiency, i.e. with increasing flaming fraction. The EF_PM1 values are in good agreement with previous observations in southern African savanna and with recent laboratory experiments that we carried out in collaboration with University of Eastern Finland. Analysis of ageing effects on the fire plumes in a clean savanna environment is ongoing.

How to cite: Vakkari, V., Mmereki, B. T., Koolebogile, D., van Niekerk, C. P. E., Le, V., Letsatle, M., Jaars, K., and van Zyl, P. G.: A new measurement site in northern Botswana to observe savanna fire plumes, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19104, https://doi.org/10.5194/egusphere-egu25-19104, 2025.

Wildfires increasingly threaten European ecosystems and communities, highlighting the necessity for effective predictive metrics to enhance fire risk management strategies. This study aims to compare the effectiveness of Vapor Pressure Deficit (VPD) and the Fire Weather Index (FWI) in forecasting wildfire occurrence and the extent of burned areas across various European forest types. Utilizing the European Forest Fire Information System (EFFIS) for comprehensive fire event data and the ERA5 reanalysis dataset from the European Centre for Medium-Range Weather Forecasts (ECMWF) for meteorological variables, daily VPD and FWI values will be derived for multiple fire seasons spanning from 2000 to 2024.

The research will explore how VPD and FWI each predict wildfire occurrence and burned area, with a focus on different forest types are categorized according to the CORINE Land Cover classification into broadleaf, conifer, and mixed forests while encompassing a range of climatic regions across Europe. VPD calculation methods are generally more straightforward and require fewer input parameters. In contrast FWI system is more complex, requiring a broader range of input data to compute its numerous indices.

By comparing these two metrics across diverse forest types and biomes, the study seeks to determine the most effective indicators for wildfire prediction in Europe. The findings are intended to inform policymakers and fire management agencies, aiding in the development of targeted early warning systems and adaptive fire management strategies. This comparative assessment will contribute to a deeper understanding of the climatic drivers of wildfires and support efforts to mitigate their impacts under changing environmental conditions.

How to cite: Shatto, C. and Samimi, C.: Comparative Assessment of Vapor Pressure Deficit and Fire Weather Index in Predicting Wildfire Occurrence and Burned Area Across European Forest Types Using EFFIS and ERA5 Data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19262, https://doi.org/10.5194/egusphere-egu25-19262, 2025.

Rural fires are recurrent in Southern Europe due to climate conditions, land use change, or a combination of both. Wet and mild winters and dry and warm summers favour the growth of vegetation and its subsequent low moisture content, increasing fuel availability. In Portugal, between 15 and 20 September 2024, severe wildfires burned more than 145,000 hectares and caused the death of more than 9 people. In Greece a major fire, stated as the largest recorded in the EU, started near the city of Alexandroupolis on August 21, with around 80.000 hectares burnt, mainly affecting the Dadia Forest and causing the death of almost two tens of migrants. Despite the crucial role played by dry fuel conditions fostering the propagation of wildfires, favourable meteorological conditions and fuel accumulation are related to the recorded fire activity and burned area. The influence of spring meteorological conditions on fire season burned area through their effect on fuel accumulation and dryness is assessed. The link between hot temperature and water availability in spring and the increased risk of summer flammability and fire spread through their influence on vegetation gross productivity is evaluated using satellite-derived data. The important role of fuel accumulation during the early growing season in fire-prone regions is highlighted in the case of Portugal in 2024 and Greece in 2023 and reinforces the crucial importance of fuel management for the definition of effective fire prevention measures in the context of warmer and drier conditions forecasted for southern European Countries.

Acknowledgements: This work is supported by the Portuguese Fundação para a Ciência e Tecnologia, FCT, I.P./MCTES through national funds (PIDDAC): UID/50019/2025 and LA/P/0068/2020 https://doi.org/10.54499/LA/P/0068/2020 and also on behalf of DHEFEUS -2022.09185.PTDC and the project FAIR- 2022.01660.PTDC).

How to cite: Gouveia, C., Finuras, M., Russo, A., and Ermitão, T.: The role of dry and heat extremes on vegetation dynamics in the recent fire seasons in Southern Europe, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19493, https://doi.org/10.5194/egusphere-egu25-19493, 2025.

After a wildfire event, ashes and pollutants from burns are transported to public supply reservoirs and other water systems, altering the physical and chemical properties of the water. Turbidity is a water parameter that can be applied in environmental monitoring studies to assess water quality in  public supply reservoirs, especially in fire-prone regions such as the Brazilian Cerrado. So, this work aims to answer the following question: What is the impact of the increase in burned area on water turbidity in public supply reservoirs? This study aims to investigate the relationship between environmental variables obtained through remote sensing, such as the burned area product (MODIS-MCD64A1) and turbidity data derived from the red band (620-670 nm) of MODIS Terra Surface Reflectance (Daily Global, 250m resolution), using a global algorithm and statistical analyses to derive insights over the period from 2001 to 2023 in public supply reservoirs of Cerrado.There is variability in both positive and negative turbidity anomalies from 2001 to 2023. However, in some years, positive turbidity anomalies were observed along burned areas. The insights provide the initial understanding of the relationship between burned areas and water quality, and also provide valuable support for water supply managers and the public. 

How to cite: da Silva Nemirovsky, A. K., Augusto Sander de Carvalho, L., and Libonati, R.: Assessing increased turbidity in reservoirs due to wildfires, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20164, https://doi.org/10.5194/egusphere-egu25-20164, 2025.

Indonesia is currently one of the three largest contributors of carbon emissions from land use and land cover change (LULCC) globally, together with Brazil and the Democratic Republic of the Congo. However, until recently, there was only limited reliable data available on LULCC across Indonesia, leading to a lack of agreement on drivers, magnitude, and trends in carbon emissions between different estimates. Accurate LULCC should improve robustness and reduce the uncertainties of carbon dioxide (CO2) emissions from Land Use Change (ELUC) estimation. Here, we assess several cropland datasets that are used to estimate ELUC in Dynamic Global Vegetation Models (DGVMs) and Bookkeeping models (BKMs). Available cropland datasets are generally categorized as either census-based such as the Food and Agricultural Organization (FAO) annual statistical dataset, or satellite-based such as the Mapbiomas dataset, which is derived from Landsat Satellite images. Our results show that census-based and satellite-based estimates have little agreement on temporal variability and cropland area changes. In some islands, they show spatial similarity, but differences appear in the main islands such as Kalimantan, Sumatra and Java. These differences lead to spatio-temporal uncertainty in carbon emissions. The different land cover forcings (census-based vs satellite-based) in a single model (JULES-ES) result in ELUC uncertainties of about 0.08 [0.06 to 0.11]  PgC/yr. Furthermore, we found that uncertainties in ELUC estimates are also due to differences in the carbon cycle models in DGVMs, as DGVMs driven by the same land cover dataset show differences in ELUC estimates of 0.12 ± 0.02 PgC/yr with 95% confidence level and range [-0.04 to 0.35] PgC/yr. This is consistent with other product such as BKMs that estimates 0.14 [0.12 to 0.15] PgC/yr with both steady trend. We also compare emissions with those from the National Greenhouse Gas Inventory (NGHGI) product. The NGHGI estimates (based on BUR3; periodic official government report on Greenhouses Gas to UNFCCC) have much lower carbon emissions (0.06 ± 0.06 PgC/yr), though with an increasing trend. These numbers double when we include emissions from peat fire and peat drainage: the DGVM ensemble indicates emissions of 0.23 ± 0.05 PgC/yr and BKMs indicate emissions of 0.24 [0.22-0.25] PgC/yr. In contrast, emissions based on the Indonesian NGHGI remain much lower (BUR2: 0.18±0.07 PgC/yr BUR3: 0.13 ± 0.10 PgC/yr). Furthermore, emission peaks occur in year of moderate-to-strong El Nino events. Several improvements might reduce uncertainties in carbon emissions from LULCC in Indonesia, such as: combination of satellite-based dataset with census-based dataset, inclusion of peat-related emissions in DGVMs and potentially explicit inclusion of palm oil in the models as this is a major crop in Indonesia. Overall, the analysis shows that carbon emissions have no decreasing trend in Indonesia, Therefore, deforestation and forest fire prevention remain vital for Indonesia. 

How to cite: Brasika, I. B. M., Friedlingstein, P., Sitch, S., O'Sullivan, M., Duran-Rojas, M. C., Rosan, T. M., Goldewijk, K. K., Pongratz, J., Schwingshackl, C., Chini, L., and Hurtt, G.: Uncertainties in carbon emissions from land use and land cover change in Indonesia, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-267, https://doi.org/10.5194/egusphere-egu25-267, 2025.

North Atlantic tropical cyclones (i.e. hurricanes) are observed to drive intense air-sea CO₂ exchange and trigger primary production by phytoplankton. However, Earth system models (ESMs) with coarse spatial resolution are not able to capture such effects. Here, we address this limitation and resolve the impacts of hurricanes on the ocean carbon cycle in an ESM for the first time. We present the first 1-year global, coupled, high-resolution (5 km ocean, 5 km atmosphere) ESM simulation including ocean biogeochemistry with the ICON (ICOsahedral Non-hydrostatic) model framework. Our simulation realistically reproduces the effects of hurricanes at: 1) instantaneously increasing air-sea CO2 fluxes by a factor of 10-30 due to strong surface winds (>58 m/s, hurricane category 4); 2) promoting longer-lasting surface ocean cooling by 2-4°C, and thus decreasing surface ocean partial pressure of CO₂ (pCO₂); and 3) triggering large-scale phytoplankton blooms, spatially modulated by mesoscale ocean eddies. We show that the hurricane-driven sea-surface cooling is mainly caused by extreme latent heat loss (>1200 W/m²), whose impact on decreasing pCO₂ outweighs the mixing and upwelling of dissolved inorganic carbon. Our simulated hurricanes contribute to inverting the direction of the local air-sea pCO₂ imbalance, thus promoting ocean CO₂ uptake. Intense wind speeds also trigger vertical diffusion of nutrients, as well as near-inertial oscillations, which become the dominant mode of subsurface ocean variability in the wake of the cyclones. While the proportion of intense tropical cyclones is projected to increase with climate change, their future role in the ocean carbon cycle remains unclear. Resolving tropical cyclones in ESMs will allow us to better understand their response and impact to ongoing climate change at regional and global scales.

How to cite: Nielsen, D. M., Chegini, F., Serra, N., U. Kumar, A., Brueggemann, N., Hohenegger, C., and Ilyina, T.: Hurricanes trigger ocean CO2 uptake and phytoplankton bloom in a high-resolution Earth system model simulation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1596, https://doi.org/10.5194/egusphere-egu25-1596, 2025.

Siberia’s extensive wetlands, permafrost, and boreal forests are significant sources of methane, positioning this region as crucial for global methane (CH₄) monitoring. However, Siberia remains sparsely monitored by atmospheric and ecosystem observatories, highlighting the need to leverage existing datasets to refine CH₄ budgets with better spatial and temporal precision. Utilising the ZOtino Tall Tower Observatory (ZOTTO; 60°48' N, 89°21' E) dataset, which provides continuous, high-resolution CH₄ mole fraction and meteorological measurements from six heights up to 301 meters, combined with ERA5 meteorological data at 60°75' N, 89°25' E, we conducted a comprehensive analysis of long-term trends and variations in atmospheric CH₄ at ZOTTO, examining its diurnal and seasonal patterns from 2010 to 2021. Our analysis reveals a significant increase in the summer diurnal amplitude of CH₄, which could be driven by both forest and meteorological dynamics, through the effects of daytime mixing and nighttime stability on the CH₄ mole fraction, and ecosystem CH₄ flux. We found that while atmospheric dynamics showed no significant trends contributing to this diurnal amplitude increase, there was an increasing trend in nighttime CH₄ ecosystem flux in summer (predominantly August) over the 11-year period, with high emissions predominantly originating from the west and southwest of the station. Additionally, episodic high methane CH₄ was observed in 2012 and 2019, linked to wildfires, and in 2016, attributed to enhanced wetland activity. Lastly, there were significant positive correlations between the calculated CH₄ surface flux and soil temperature and moisture at ZOTTO.

How to cite: Tran, D. A., Vilà-Guerau de Arellano, J., Luijkx, I., Botía, S., Faassen, K., Gerbig, C., and Zaehle, S.: Increasing Methane Summer Diurnal Amplitude in Siberia: A 2010–2021 Analysis from the ZOtino Tall Tower Observatory (ZOTTO), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2043, https://doi.org/10.5194/egusphere-egu25-2043, 2025.

Ocean fronts are dynamic features that play a critical role in regulating marine ecosystems and influencing global carbon cycles. These regions, characterized by strong horizontal gradients in temperature, salinity, and other properties, enhance vertical mixing and advection, driving increased nutrient supply that supports elevated primary production. Despite their importance, the impacts of changing ocean fronts on the budget and trends of ocean CO₂ uptake remain insufficiently understood. In this study, we perform a comprehensive global analysis of ocean fronts using 20 years of satellite observations (2003–2023), identifying key regions of intense frontal activity and areas undergoing rapid changes in frontal dynamics. Our results show that nearly 50% of global ocean CO₂ uptake occurs in these key frontal areas, underscoring their disproportionate role in the ocean’s carbon sink. Furthermore, we observe that trends in sea surface chlorophyll concentration—a proxy for primary production—and ocean CO₂ uptake are strongly correlated with local changes in frontal activity. Our findings provide critical insights into the role of ocean fronts as modulators of global biogeochemical processes and air-sea CO₂ exchanges. By linking ocean fronts to changes in primary production and air-sea CO₂ exchange, this study contributes to a more detailed understanding of how changing ocean dynamics may influence carbon cycles under future climate scenarios.

How to cite: Yang, K., Meyer, A., Strutton, P. G., and Fischer, A. M.: Global trends in ocean fronts: impacts on air-sea CO2 flux and chlorophyll concentrations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2215, https://doi.org/10.5194/egusphere-egu25-2215, 2025.

Tropical wetlands account for ∼20% of the global total methane (CH₄) emissions, but uncertainties remain in emission estimation due to the inaccurate representation of wetland spatiotemporal variations. Based on the latest satellite observational inundation data, we constructed a model to map the long-term time series of wetland extents over the Sudd floodplain, which has recently been identified as an important source of wetland CH₄ emissions. Our analysis reveals an annual, total wetland extent of 5.73 ± 2.05 × 10⁴ km²  for 2003–2022, with a notable accelerated expansion rate of 1.19 × 10⁴ km² yr⁻¹ during 2019–2022 driven by anomalous upstream precipitation patterns. We found that current wetland products generally report smaller wetland areas, resulting in a systematic underestimation of wetland CH₄ emissions from the Sudd wetland. Our study highlights the pivotal role of comprehensively characterizing the seasonal and interannual dynamics of wetland extent to accurately estimate CH₄ emissions from tropical floodplains.

How to cite: Dong, B., Peng, S., Liu, G., Pu, T., Gerlein‐Safdi, C., Prigent, C., and Lin, X.: Underestimation of Methane Emissions From the Sudd Wetland: Unraveling the Impact of Wetland Extent Dynamics, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2466, https://doi.org/10.5194/egusphere-egu25-2466, 2025.

China is among the top nitrous oxide (N₂O)-emitting countries, but existing national inventories do not provide full-scale emissions including both natural and anthropogenic sources. We conducted a four-decade (1980–2020) of comprehensive quantification of Chinese N₂O inventory using empirical emission factor method for anthropogenic sources and two up-to-date process-based models for natural sources. Total N₂O emissions peaked at 2287.4 (1774.8–2799.9) Gg N₂O yr^-1 in 2018, and agriculture-developed regions, like the East, Northeast, and Central, were the top N₂O-emitting regions. Agricultural N₂O emissions have started to decrease after 2016 due to the decline of nitrogen fertilization applications, while, industrial and energetic sources have been dramatically increasing after 2005. N₂O emissions from agriculture, industry, energy, and waste represented 49.3%, 26.4%, 17.5%, and 6.7% of the anthropogenic emissions in 2020, respectively, which revealed that it is imperative to prioritize N₂O emission mitigation in agriculture, industry, and energy. Natural N₂O sources, dominated by forests, have been steadily growing from 317.3 (290.3–344.1) Gg N₂O yr^-1 in 1980 to 376.2 (335.5–407.2) Gg N₂O yr^-1 in 2020. Our study produces a Full-scale Annual N₂O dataset in China (FAN2020), providing emergent counting to refine the current national N₂O inventories.

How to cite: Liang, M., Zhou, Z., Ren, P., Xiao, H., Xu, R., Hu, Z., Piao, S., Tian, H., Tong, Q., Zhou, F., Wei, J., and Yuan, W.: Four decades of full-scale nitrous oxide emission inventory in China, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6054, https://doi.org/10.5194/egusphere-egu25-6054, 2025.

Since June 2018, ground-based remote sensing measurements are performed at the suburban Xianghe site in China, situated in the heart of the densely populated Beijing-Tianjin-Hebei megalopolis. These observations are performed with Fourier Transform Infrared (FTIR) spectrometers and provide  column-averaged dry-air concentrations of gases such as CO₂, CH₄ and CO. They are affiliated to the international Total Column Carbon Observing Network (TCCON). Co-located with these measurements is a PICARRO cavity ring-down spectroscopy (CRDS) analyser observing in situ concentrations of CO₂ and CH₄ at an altitude of 60 m.

To gain a better understanding of the causes of the observed temporal variabilities at this site, we employed the Weather Research and Forecasting model coupled with Chemistry in its greenhouse gas configuration (WRF-GHG). Our study analyses both column-averaged (XCO₂) and surface in situ CO₂ concentrations and simultaneously evaluates the model’s performance at Xianghe.  The CO₂ exchange with the biosphere is simulated with the integrated Vegetation Photosynthesis and Respiration Model (VPRM), while the anthropogenic emissions are taken from the global CAMS-GLOB-ANT inventory and transported in separate tracers according to their source sector. 

The model shows good performance, achieving correlation coefficients of 0.70 for XCO₂ and 0.75 for afternoon in situ concentrations. For XCO₂, a mean bias of -1.43 ppm relative to TCCON is found, primarily attributed to biases in the CAMS reanalysis used as initial and lateral boundary conditions. Anthropogenic emissions from the industry and energy sectors emerged as dominant contributors to CO₂ concentrations, alongside the biosphere, which acts as a sink for XCO₂ from April to September and becomes a source for the rest of the year. Synoptic weather patterns were shown to strongly determine the variation in CO₂ levels, with enhanced impacts during summer due to the large spatial and temporal heterogeneity of biogenic fluxes in the region. Near the surface, the observed large diurnal variation associated to the evolution of the planetary boundary layer is  relatively well simulated by WRF-GHG.

Our analysis demonstrates the utility of WRF-GHG in simulating both column and surface CO₂ concentrations, offering insights into the sectoral and meteorological drivers of variability at Xianghe and its surrounding region.

How to cite: Callewaert, S., De Mazière, M., Zhou, M., Wang, T., Langerock, B., Wang, P., and Mahieu, E.: Analysis of ground-based column and in situ surface concentrations of CO2 at Xianghe, China, using WRF-Chem simulations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6416, https://doi.org/10.5194/egusphere-egu25-6416, 2025.

Sailboats expand the observational network of sea surface partial pressure of CO₂ (pCO₂), particularly in the undersampled Southern Ocean through regularly repeating circumnavigations, however, their added value to the fCO₂-product based ocean sink estimate (S_ocean) has thus far not been quantified. Here, we show through an observing system simulation study with different sampling schemes how integrating sailboat data from different race tracks improves air-sea CO₂ flux estimates.
We find that neural network reconstruction of the air-sea CO₂ flux used within the Global Carbon Budget, when reconstructing a model that mimics present-day real-world sampling, underestimates the ocean carbon sink. This is consistent with recent studies on the interior accumulation of carbon. Increased and continuous sampling by sailboats reveals a stronger carbon sink and improves present-day estimates from 0.06 to -0.02 mol C m⁻² yr⁻¹ (0.99 μatm to -0.32 μatm for the fCO₂ estimate), particularly in the Southern Ocean between 40°S and 60°S. The improvement in reconstructions persists even when data from three circumnavigation tracks contain artificial measurement biases. However, the additional data remains insufficient to correct the overestimated air-sea CO₂ flux trend. While sailboat data has the potential to improve air-sea CO₂ flux reconstructions, expanding the observational network and maintaining long-term time series is crucial to minimize discrepancies between fCO₂-products and Global Ocean Biogeochemical Models.

How to cite: Behncke, J., Landschützer, P., Chegini, F., and Ilyina, T.: Improved air-sea CO2 flux estimates by adding sailboat measurements , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6427, https://doi.org/10.5194/egusphere-egu25-6427, 2025.

Monitoring ecosystem carbon dioxide (CO₂) exchange is crucial for assessing the impacts of climate extremes and constructing carbon budgets to inform land management and enforce international climate treaties. To this end, we present here gridded hourly ecosystem CO₂ fluxes upscaled from eddy covariance observations at 0.1° × 0.1° resolution and updated at low latency. Sentinel-2 indices are used to drive a modified Vegetation Photosynthesis Respiration Model (VPRM) following Bazzi et al. (2024) with a restructured Ecosystem Respiration equation and explicit soil moisture stress functions. VPRM parameters are optimized to half-hourly eddy covariance Net Ecosystem Exchange (NEE) and Gross Primary Production (GPP) datasets for each of 36 FLUXNET sites. Additionally we modify the temperature dependence of GPP by optimizing minimum and maximum temperatures as parameters and estimating optimum temperatures from mean annual temperature. We find these temperature modifications reduce RMSE for NEE and GPP respectively by 11% and 12% overall, 16% and 18% at evergreen needleleaf forests, 14% and 12% at grasslands, and 12% and 16% at mixed forests. Using site data on meteorology and vegetation, we train a random forest to produce mapped VPRM parameters representing the spatial heterogeneity in ecosystem characteristics. Gridded VPRM NEE estimates are presented based on both modeled parameter maps and multi-site optimizations by plant functional type, and upscaled products can be produced within hours of satellite data availability.

[1] Bazzi, H. et al. "Assimilating Sentinel-2 data in a modified vegetation photosynthesis and respiration model (VPRM) to improve the simulation of croplands CO₂ fluxes in Europe." International Journal of Applied Earth Observation and Geoinformation 127 (2024): 103666.

How to cite: Briner, O., Bazzi, H., Ciais, P., and Santaren, D.: Upscaling near-real-time biospheric CO2 fluxes over Europe with a modified Vegetation Photosynthesis Respiration Model (VPRM), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6908, https://doi.org/10.5194/egusphere-egu25-6908, 2025.

The atmospheric carbon dioxide (CO2) concentration has been increasing rapidly since the Industrial Revolution, which has led to unequivocal global warming and crucial environmental change. It is extremely important to investigate the interactions among atmospheric CO2, the physical climate  system, and the carbon cycle of the underlying surface for a better understanding of the Earth system. Earth system models are widely used to investigate these interactions via coupled carbon–climate simulations. The Chinese Academy of Sciences Earth System Model version 2 (CAS-ESM2.0) has successfully fixed a two-way coupling of atmospheric CO2 with the climate and carbon cycle on land and in the ocean. Using CAS-ESM2.0, we  conducted a coupled carbon–climate simulation by following the CMIP6 proposal of a historical emissions-driven experiment. This paper examines the modeled CO2 by comparison with observed CO2 at the sites of Mauna Loa and Barrow, and the Greenhouse Gases Observing Satellite (GOSAT) CO2 product. The results showed that CAS-ESM2.0 agrees very well with observations in reproducing the increasing trend of annual CO2 during the period 1850–2014, and in capturing the seasonal cycle of CO2 at the two baseline sites, as well as over northern high latitudes. These agreements illustrate a good ability of CAS-ESM2.0 in simulating carbon–climate interactions, even though uncertainties remain in the processes involved. This paper reports an important stage of the development of CAS-ESM with the coupling of carbon and climate, which will provide significant scientific support for climate research and China’s goal of carbon neutrality.

How to cite: Zhu, J., He, J., Ji, D., Li, Y., Zhang, H., Zhang, M., Zeng, X., Fei, K., and Jin, J.: Coupled Simultion of Atmospheric CO2 in CAS-ESM, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7573, https://doi.org/10.5194/egusphere-egu25-7573, 2025.

Lakes, as a fundamental component of the Earth's surface system, play a crucial role in the carbon cycle, closely linked to climate change. However, understanding carbon flux in Qinghai-Tibet Plateau (QTP) lakes is restricted by environmental factors and limited observations, hindering insights into regional and global climate change. Continuous annual carbon dioxide (CO₂) flux, encompassing ice-covered periods, has been monitored in the largest freshwater lake on the QTP. Utilizing continuous eddy system data, the characteristics and mechanisms influencing carbon flux at various temporal scales in this lake were investigated. Findings revealed Ngoring Lake as predominantly a carbon sink year-round, with two CO₂ absorption peaks in spring and autumn, respectively. These peaks were associated with mixing state triggered by cooling processes. In spring, as temperatures rose above the lake water's maximum density temperature (3.98 ℃ for freshwater lake), subsequent rapid cooling and mixing occurred upon ice melt. In autumn, cooling and mixing were induced by decreasing air and water temperatures alongside strong winds. These cooling processes facilitated significant CO₂ absorption. As the lake transitioned from stratification to mixing, lake mixing played a dominant role. Biochemical reactions driven by water temperature play a dominant role during stable stratification and complete mixing phases.

How to cite: Wang, M., Wen, L., Li, Z., Meng, X., and Su, D.: Characteristics of carbon sink and the influence factors in Ngoring Lake, Qinghai-Tibet Plateau, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7650, https://doi.org/10.5194/egusphere-egu25-7650, 2025.

Freeze-thaw periods contribute disproportionately to annual N₂O emissionsrepresenting a critical yet understudied component of its global budget. Understanding drivers of these hot moments and their sensitivity to climate change is essential, but their episodic nature and great spatiotemporal variability pose substantial challenges. Combining cross-ecoregion soil core incubations with in-situ automated measurements, we explored snow regime shift effects on N₂O emissions. Our findings revealed ~50-day pulse emissions during freeze-thaw periods, accounting for over 50% of annual fluxes, increasing nonlinearly with snow depth. Emissions were regulated by water-filled pore space (WFPS) thresholds: below 43%, soil moisture dominated; at 43%–66%, moisture and microbial attributes jointly triggered emissions; above 66%, microbial attributes, particularly N enzyme kinetics, prevailed. Hotspots of freeze-thaw-induced emissions were linked to high root production and microbial activity in cold, humid grasslands. This hierarchical control of WFPS and microbial processes provides a framework for predicting the location and magnitude of freeze-thaw-induced N₂O pulses, improving N₂O accounting and informing mitigation strategies.

How to cite: Liu, L. and Luo, J.: Moisture-microbial interaction amplifies N2O emission hot moments under deepened snow in grasslands, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7905, https://doi.org/10.5194/egusphere-egu25-7905, 2025.

Scenarios to keep global warming below 2°C include significant decreases in short lived atmospheric methane to allow time for the much longer-lived atmospheric CO₂ to decrease more slowly. A methane decrease during the 2020s decade has been built into SSP scenarios and the need for this is reinforced by recent studies [Reisinger, 2024; Shindell et al., 2024]. In reality, the atmospheric methane burden has been growing very rapidly since 2006.

Atmospheric methane destruction is predominantly through oxidation by hydroxyl (OH). There is now evidence that since 1997, OH has been increasing in the Southern Hemisphere [Morgenstern et al., 2025]. This is based on 30 years of data for cosmic-ray produced ¹⁴C in atmospheric carbon monoxide (CO). Although most atmospheric chemistry models expect an increase in OH, the observed Southern Hemisphere increase of about +5% per decade is significantly greater than expected. Unfortunately, ¹⁴CO data in the Northern Hemisphere are insufficient to compare with models there.

The increase in methane removal rate inferred from the ¹⁴CO data means that methane sources are larger than prior estimates based on an almost-constant removal rate. If so, this new finding reduces a long standing discrepancy between “top-down” estimates of methane emissions from wetlands and consistently larger “bottom-up” estimates [Saunois et al., 2024].

While the increasing availability of satellite data is leading to better determination of methane’s source distribution, it is also necessary to differentiate between fossil fuel and biogenic sources. The positive trend of atmospheric δ¹³C_CH4 for two centuries prior to 2006 reflected methane emissions from fossil fuel sources, but the strongly negative trend in δ¹³C_CH4 since 2006 is primarily driven by biogenic sources such as wetlands and agriculture [Michel et al., 2024]. The magnitude of the source increase, particularly when the OH increase is taken into account, implies strong growth in wetland emissions, especially from northern tropical Africa.

More recent δ¹³C_CH4 data for 2023 have shown flattening of its post-2006 trend at many Northern Hemisphere sites. While something similar was seen in 2012 this apparent shift in methane sources now appears more pronounced.

Given the urgency of reducing atmospheric methane to keep to the 2°C target, the recent changes in δ¹³C_CH4 show atmospheric methane is in a very dynamic period of change. Future changes in the global methane budget may be less predictable than is currently assumed.

References:

Michel, S.E., Lan, X., Miller, J., et al, 2024: Rapid shift in methane carbon isotopes suggests microbial emissions drove record high atmospheric methane growth in 2020–2022. Proceedings of the National Academy of Sciences - PNAS, 121(44), e2411212121.

Morgenstern, O., Moss, R., Manning, M., et al, 2025: Radiocarbon monoxide indicates increasing atmospheric oxidizing capacity. Nature Communications, 16, 249.

Reisinger, A., 2024: Why addressing methane emissions is a non-negotiable part of effective climate policy. Frontiers in Science, 2, 5.

Saunois, M., et al., 2024: Global Methane Budget 2000-2020. Earth System Science Data, https://doi.org/10.5194/essd-2024-115 Discussion started: 6 June 2024, 147.

Shindell, D., Sadavarte, P., Aben, I., et al , 2024: The methane imperative. Frontiers in Science, 2, 1349770.

How to cite: Manning, M., Lan, X. (., Michel, S., and Nisbet, E.: New advances and new questions for atmospheric methane, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7918, https://doi.org/10.5194/egusphere-egu25-7918, 2025.

The global methane pledge (GMP) aims to cut methane (CH₄) emissions across all sectors by at least 30 percent below 2020 levels by 2030, which can thereby provide benefits in air quality and health, as well as in climate, relative to not cutting the emissions. We have used a fully coupled Earth system model (ESM) with interactive CH₄ sources and sinks to study the future levels and trends of global atmospheric CH₄ concentrations under different emission scenarios. Fully coupled simulations have been performed from 1995 to 2050, using multispecies emissions from the ECLIPSE V6b emissions database supplemented by new anthropogenic methane emissions estimates for Current Legislation (CLE), Maximum Feasible Reduction (MFR) and Global Methane Pledge (GMP) from IIASA/GAINS to simulate the future evolution of CH₄ levels. In the baseline CLE scenario, global anthropogenic CH₄ emissions increase from 298 Tg in year 2000 to 335 Tg in 2015, then continues to increase to 430 Tg in 2050 under CLE. Under MFR, anthropogenic CH₄emissions first drop to 240 Tg in 2030, then slightly decrease to 220 Tg in 2050, while under the GMP scenario, they first drop to 300 Tg in 2030, then slightly increase to 320 Tg in 2050.

Preliminary results show that the interactive simulation slightly underestimates the observations on average by 2% between 1995-2022. All scenarios show an increase in the global CH₄ concentrations, from 1.8 ppm in the present-day CH₄ to 1.9 ppm (6%) in 2050 in the MFR scenario, 2.2 ppm (22%) in the CLE scenario, and 2.1 ppm (17%) in the GMP scenario. In addition, while anthropogenic CH₄ emissions decrease, all simulations predict increasing wetland CH₄emissions, by up to 10% in 2050 compared to 2020. Corresponding atmospheric CH₄ lifetimes also increase in all simulations from 8.4 years in 2020 to lowest 8.5 years in CLE, 9.2 years in MFR, and 9.4 years in GMP. The increasing CH₄ lifetime and concentrations in all scenarios despite reductions in emissions highlights that the response of concentrations are not necessarily linear with the changes in emissions as the chemistry is non-linear, and dependent on the oxidative capacity of the atmosphere due to other species such as CO and VOCs. In addition, missing sinks in ESMs such as halogens chlorine can lead to less chemical removal and longer lifetime compared to the box model.

We will further present the impact of these scenarios on the global surface temperatures and evaluate if the GMP will achieve its goal by 2050. However, preliminary results, compared with the recent 2021 AMAP SLCF assessment, suggest that despite the reduction in emissions, the atmospheric global CH₄ levels simulated in the present study may not fulfil the larger goals of the GMP such as decreasing global CH₄ concentrations and avoiding a 0.2°C warming by 2050 relative to 2020. However, reductions in emissions can still be achieved, which can lead to benefits in air quality and health. This work was accomplished through the Reduc(h4)e project funded by the Nordic Council of Ministers-and contributes to ongoing AMAP assessment work.

How to cite: Im, U., Tsigaridis, K., Bauer, S., Shindell, D., Olivié, D., Wilson, S., Sørensen, L. L., Langen, P., Eckhardt, S., Isaksson, L. H., Klimont, Z., and Bruhwiler, L.: Evolution of atmospheric methane under the global methane pledge: insights from an Earth system model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8281, https://doi.org/10.5194/egusphere-egu25-8281, 2025.

Vegetation acts as an essential land-based carbon sink, which can be affected by military conflicts and wars through landscape fires that can cover large territories and will lead to additional greenhouse gas (GHG) emissions into the atmosphere. To investigate this impact, we spatially analyzed the effect of the ongoing Russo–Ukrainian War on the GHG emissions from landscape fires and determined the change to the carbon sequestration capacity of the forests. Using remotely sensed data from 2022–2023, we first identified the fire perimeters in the territory of Ukraine. We then classified the burned areas into coniferous and deciduous forests, croplands, and other landscapes, and evaluated the distribution of the fires according to their intensity based on the differenced normalized burn ratio. We used several fire weather condition indices and calculated the attribution factor to identify the share of fires that were war related and were thus not caused by natural factors or human activity that would be typical in times of peace. We estimated the war-related biomass losses during the first two years of the war, considering the landcover type, the species and the age structure of the forest stands, the fire intensity, and the biomass content. The corresponding GHG emissions in the immediate term were estimated to be 9.08 Mt carbon dioxide equivalent (CO₂e), with a relative uncertainty of ±46% (95% confidence interval). The estimated future (long-term) biomass losses due to current forest fires and their corresponding GHG emissions were calculated to be 16.86 Mt CO₂e (±21%). Finally, losses in the carbon sequestration capacity of the burned forests during the first five years following the landscape fires were estimated to be 2.9 Mt CO₂e.

How to cite: Vasylyshyn, R., Bun, R., Myroniuk, V., de Klerk, L., Soshenskyi, O., Zibtsev, S., Krakovska, S., See, L., Shlapak, M., Blyshchyk, V., Kryshtop, L., Romanchuk, Z., Yashchun, O., Kalchuk, E., and Rymarenko, Y.: Quantifying greenhouse gas emissions from landscape fires due to the Russo–Ukrainian War and the impact on the carbon sequestration capacity of forests, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9043, https://doi.org/10.5194/egusphere-egu25-9043, 2025.

The Terrestrial Ecosystem Research Network (TERN) OzFlux group operates a network of eddy covariance stations that collect long-term atmospheric and soil measurements for monitoring and understanding changes in climate and the environment. Ideally, all data collected would be gap-free, however, all real data has gaps where instruments have not recorded measurements or data has been discarded due to low turbulence. To allow this data to be used as a continuous time-series in further analysis, the missing data is gap-filled using PyFluxPro. The standard community approach uses a predefined set of variables (drivers) for gap-filling, which are the same variables for all stations irrespective of location. However, the stations are located in a large range of climate zones, hence the standard gap-filling drivers might not be ideal for all sites. This is because the drivers were chosen for a small set of initial sites and might not be representative for a heating and drying climate.

To identify which drivers were best suited for each station, we developed a random forest model to objectively assess the relative importance of input variables used to gap-fill ustar, carbon, and energy fluxes. We trained this model on the published TERN OzFlux data for all available Australian sites using a large range of input variables. This model then determined the relative importance of variables, mean absolute errors, and R² for the accuracy of the model prediction for a target variable at each site. Next, we grouped the variables into atmospheric, energy, turbulence and soil categories of drivers, which highlighted a distinct variation in the contribution of each category of driver across sites. To assess the ecological significance of these trends, the model importances were sorted by the aridity index and grouped by the Köppen-Geiger classification of each site. There is a notable shift in the importance of energy, turbulence, and soil groups with decreasing aridity, and driver contributions were generally consistent within Köppen-Geiger classifications. Reprocessing the gap-filling of a representative subsample of sites demonstrated a marked improvement in predicting the gap-filled target variables, highlighting that this approach can inform driver selection at new and established sites and will improve the understanding of the ecological significance of different drivers in various climate regions.

How to cite: Lieff, N., Metzen, D., Ewenz, C., Isaac, P., McHugh, I., and Griebel, A.: Assessing the optimal drivers for flux data gap-filling using random forest networks, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9368, https://doi.org/10.5194/egusphere-egu25-9368, 2025.

Methane (CH₄) emissions from the Tibetan Plateau, often referred to as the "Third Pole," are critical to understanding global methane dynamics due to the region's extensive wetland ecosystems and unique environmental characteristics. However, quantifying CH₄ fluxes in this region is challenging due to sparse observational data, complex topography, and highly variable climatic and hydrological conditions. This study introduces a high-resolution machine learning framework tailored for the Tibetan Plateau by integrating satellite-based observations, ground measurements, and modeled data. The framework incorporates a diverse set of environmental drivers, including temperature, soil moisture, vegetation indices, and hydrological factors. This approach aims to address spatial and temporal gaps in methane flux estimates while capturing the complex interactions governing CH₄ emissions in high-altitude mountainous ecosystems.

How to cite: Zhang, Z.: High-Resolution Wetland Methane Flux Modeling for the Tibetan Plateau Using Machine Learning, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10099, https://doi.org/10.5194/egusphere-egu25-10099, 2025.

As the oceans warm and acidify, the calcification of coral reefs declines, with net calcium carbonate dissolution projected even under moderate emissions scenarios. The impact of this on the global carbon cycle is however yet to be accounted for. We use a synthesis of the sensitivity of coral reef calcification to climate change, alongside reef distribution products to estimate alkalinity and dissolved inorganic carbon fluxes resulting from reductions in reef calcification. Using the global ocean biogeochemical model NEMO-PISCES, we simulate the impact of these fluxes on ocean carbon uptake under different emissions scenarios, accounting for uncertainty in present-day calcification rates.

Reductions in global coral reef carbonate production could enhance the ocean anthropogenic carbon sink by 0.34 PgC yr^-1by mid-century (0.13 PgC yr^-1 median estimate) with cumulative ocean carbon uptake up to 110 PgC greater by 2300 (46 PgC median estimate). Under medium to high emissions scenarios, two critical aspects emerge: (i) the full potential for coral reef degradation to affect carbon fluxes is reached within decades, and (ii) air-sea carbon fluxes remain substantial for centuries, due to the imbalance between carbon and alkalinity sinks/sources for the global ocean.

Accounting for the coral reef feedback into Earth system models could revise upward remaining carbon budget estimates, increasing the likelihood of achieving net-zero emissions without relying on negative emissions. The coral reef feedback could have a 21st-century impact comparable in magnitude to boreal forest dieback, though opposite in sign. This underscores a critical paradox: conserving calcifying organisms, such as coral reefs, may counteract a natural mechanism for mitigating climate change, but at the cost of protecting vital biodiversity. This challenges the "all-carbon" framework often used to address environmental issues, highlighting the complex trade-offs between carbon cycle regulation and biodiversity conservation.

How to cite: Planchat, A., Kwiatkowski, L., Pyolle, M., Laufkötter, C., and Bopp, L.: Declining coral calcification to enhance twenty-first century ocean carbon uptake by gigatons, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10326, https://doi.org/10.5194/egusphere-egu25-10326, 2025.

Tropical wetlands are one of the largest natural methane sources but lack of in-situ observations and uncertainty in wetland extent leads to large uncertainly. In this study we analyze the methane budget from three major river basins in South America: the Orinoco, the Amazon, and the Pantanal basins using two atmospheric inversions:  the CAMS-CH₄inversion, which assimilates satellite and in-situ data and the CarboScope methane inversion system constrained by in-situ data only. We make a comparative analysis focusing on the seasonal cycle, interannual variability, and the total methane budget from 2000 to 2019.

The budget difference in posterior estimates between CAMS-CH₄ and CarboScope for these basins are as follows: Amazon Basin: -18.03 TgCH₄/yr, Pantanal Basin: -11.65 TgCH₄/yr, Orinoco Basin: -0.96 TgCH_4/yr.  All together the total flux difference is -30.56 TgCH₄/yr, indicating that CarboScope estimates larger total methane fluxes than the CAMS-CH₄ inversion. Note that a similar difference (30.98 TgCH₄/year) is also seen in the prior fluxes, suggesting that the optimization does not reduce the prior difference in the regions of interest.  While the Amazon Basin emits largest amount of methane, the Orinoco Basin exhibits the highest emissions per unit area, with 21.2 mgCH₄/m²/day. In comparison, Amazon and Pantanal basins have emission of 19.26 mgCH₄/m²/day and 13.36 mgCH₄/m²/day. This shows the significant contribution of the smallest basin, in terms of methane flux density. Not surprisingly, both models indicate that wetlands are the primary methane source in the Amazon and Orinoco basins (~80%). In the Pantanal, CAMS-CH4 shows equal contributions from wetlands and anthropogenic sources, whereas CarboScope attributes dominance to anthropogenic emissions. Interestingly, seasonal patterns differ between the two models. In CAMS-CH₄ there is a strong seasonality, with maximum methane emissions occurring during the wet season across all basins, in CarboScope, there is a double-peak in the Amazon Basin during March (wet) and August (dry). Finally, we investigate the inundation patterns and their relationship to methane emissions trends in these basins, as well as the factors influencing interannual variability to enhance our understanding of the processes driving these emissions.

How to cite: Wagh, S., Basso, L., Fleischmann, A., Amaral, J., Melack, J., Asperen, H., Hantson, S., Schäfer, T., and Botia, S.: Methane budget, seasonality and interannual variability of the three major river basins in Tropical South America, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10374, https://doi.org/10.5194/egusphere-egu25-10374, 2025.

Methane (CH₄) emissions from South America have been estimated to account for approximately 15% of global emissions over the past decade. While natural emissions are predominantly driven by wetlands, anthropogenic emissions include contributions from livestock and landfills. However, bottom-up estimates remain highly uncertain, particularly for wetland contributions. The top-down approach, based on atmospheric transport inverse modeling, offers a critical tool for enhancing the monitoring of regional CH₄ emissions. Given the sparse network of in-situ measurements and limited aircraft campaigns in the region, satellite observations of total column methane mixing ratios (XCH₄) provide a valuable source of observations for inverse modeling.

The TROPOspheric Monitoring Instrument (TROPOMI) aboard the Sentinel-5 Precursor (S5P) satellite, launched in 2017, provides XCH₄ with global daily coverage and a relatively high (5.5×7 km²) horizontal resolution. Three different products are derived from the raw spectra measurements and are used in this study: the official product by SRON, the WFMD product by the University of Bremen and the BLENDED product by the University of Harvard. While widely used for detecting localized methane plumes linked to super-emitters, TROPOMI CH₄ data also support regional and global flux inversions, enabling improved mapping of CH₄ emissions. In 2019, TROPOMI provided over 4 million observations across South America, though with uneven spatial coverage, particularly limited over the tropical region due to cloud cover.

We assimilate the TROPOMI XCH₄observations into regional atmospheric inversions of CH₄ emissions over South America at a 0.2°×0.2° resolution, for 2019. The inversions are performed with the CHIMERE transport model coupled with the inverse modeling platform Community Inversion Framework (CIF). We first compare prior emission dataset, evaluating sector-specific uncertainties and spatial-temporal correlations within the background error covariance (B). The study then assesses system sensitivity to key input datasets and parametrization, including deep convection modeling, prior datasets and TROPOMI product selection, and optimization parameters. Additionally, the response of simulated XCH₄ to sectoral contributions is analyzed. Particular focus is given over the tropical region and especially the Amazon basin, where extensive wetland emissions and low satellite observation coverage pose significant challenges. Finally, posterior CH₄ emission budgets are presented at local, country, and regional scale, with detailed analysis of sectoral contributions from livestock, landfills, and wetlands, offering insights into the drivers of South America’s methane emissions.

How to cite: Sicsik-Paré, A., Pison, I., Fortems-Cheiney, A., Broquet, G., Potier, E., Martinez, A., Utreras-Diaz, F., and Berchet, A.: Tracking methane across South America: an inversion of TROPOMI satellite observations to quantify emissions and sectoral contributions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11802, https://doi.org/10.5194/egusphere-egu25-11802, 2025.

Recent studies highlight the critical role of methane emissions from tropical wetlands in driving the accelerated atmospheric CH₄ growth rate observed in the last decade. The Amazon lowland region, where up to 30% of the area can be seasonally flooded, is one of the largest natural methane sources. The total methane flux estimates for the Amazon basin from top-down and bottom-up approaches converge at 31–46 TgCH₄/year. However, understanding methane emission trends and interannual variability—such as inundation extent and seasonality—requires improved attribution of emissions to specific wetland types and habitats. In this study, we present a refined bottom-up estimate of methane fluxes for the lowland Amazon that addresses key challenges to regionalizing fluxes in the basin: i) the large seasonal variation in inundated areas and habitats, ii) the diversity of aquatic ecosystems across the Amazon, and iii) the spatiotemporal variability of methane fluxes. 

We link local methane flux measurements collected during more than 20 years of field campaigns to specific river and wetland types and incorporate seasonal variability in inundation extent using dynamic remote sensing products (i.e. open water data from the Global Surface Water for lakes, Global River Width from Landsat (GRWL) for rivers, and wetland inundation extent from the High-Resolution Surface WAterFraction (SWAF-HR, based on SMOS L-band imagery) for the Amazon basin, and (4) GIEMS-D15 (merge of multiple satellites) for the remaining portions of South America). Wetland types (herbaceous and woody vegetation) were obtained from the JERS-1 L-band based classification of Hess et al. (2015) for the Amazon Basin and ESA-CCI land cover for the rest of South America. The magnitude and seasonal variability of our bottom-up fluxes are evaluated against fluxes derived from atmospheric CH₄ mole fraction measurements at two Amazonian sites, whose footprints go beyond the Amazon Basin. While our product successfully captures the seasonal variability at both sites, it underestimates the overall magnitude of emissions compared to other estimates, even when accounting for emissions from flooded forest tree stems. Our findings represent an important improvement of bottom-up estimates representing the diversity of wetland habitats and processes driving methane emissions, but further work is needed to understand the mismatch with other methane emissions products.

How to cite: Botía, S., Santos Fleischmann, A., Santamaria Basso, L., Wagh, S., Lavric, J., Al Bitar, A., and Melack, J.: Refining methane emission estimates in the Amazon basin: Addressing spatiotemporal variability and habitat diversity, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12730, https://doi.org/10.5194/egusphere-egu25-12730, 2025.

2025 started with the launch of the H-Europe project IM⁴CA to enhance the quantification and understanding of methane emissions and sinks. A consortium of 25 partners joins forces to investigate pressing questions about the evolution atmospheric methane levels in recent decades, to reduce the uncertainty in future projections and design efficient solutions for monitoring and mitigating emissions in and outside of Europe. It will build new measurement and modelling infrastructure for improved monitoring of the progress toward short- and long-term emission reduction targets, with a prominent role for existing and upcoming satellite missions for measuring atmospheric composition and land surface properties.

The changing European methane emissions are an important focus of the project, which we keep track of with help of eastward extensions of the ICOS monitoring network in Poland and Romania. Intensive measurement campaigns in Rumania are conducted combining surface, aircraft, and total column measurements to improve the accuracy of emission quantification techniques using satellite data. The world-wide applicability of these techniques will extend the impact of our campaigns far beyond European borders.

Besides changing anthropogenic emissions, climate impacts on natural sources and sinks of methane are an important focus of IM⁴CA also. The four-year research program will initiate new measurement infrastructure in Congo to help characterize emissions from tropical wetlands in Africa. Campaigns will be conducted in Northern Scandinavia along a transect of disappearing permafrost to investigate impacts on vegetation and methane emissions using techniques that can be applied to high-resolution satellite instruments for circumpolar emission mapping.

This presentation will provide an overview of the planned activities and goals of IM⁴CA. The project offers a great opportunity to learn about methane in a cooperative spirit and to reach out and provide support to those who can turn knowledge about methane into climate action.    

How to cite: Houweling, S., Petrescu, R., Zaidi, M., Roeckmann, T., Paris, J.-D., Sachs, T., Aalto, T., Gloor, M., Boesch, H., Stohl, A., Denier van der Gon, H., Saunois, M., Thompson, R., Gromov, S., Höglund-Isakkson, L., and Koffi, E.: Let’s Investigate Methane for Climate Action, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13556, https://doi.org/10.5194/egusphere-egu25-13556, 2025.

The dynamics of dissolved inorganic carbon (DIC), stable carbon isotopes of DIC (δ¹³C_DIC), and anthropogenic CO₂ (CO_2ant) in the upper 500 m of the water column were examined in two upwelling-favourable regions: the Sri Lankan Dome (SLD) and the central Bay of Bengal (BOB) in the Northern Indian Ocean over the period 1995 to 2016. This study aimed to investigate the spatiotemporal variability of these carbon parameters and assess the influence of CO_2ant in these oceanic environments. Data from the GLODAPv2.2022 database, including cruise-based biogeochemical bottle measurements, were utilized to examine temporal trends in DIC and δ¹³C_DIC. The TrOCA (Tracer combining Oxygen, Carbon, and Alkalinity) approach was employed to calculate CO_2ant. Although DIC concentrations showed minimal variability across the water column in both the SLD and central BOB, significant fluctuations in CO_2ant and δ¹³C_DIC were observed in the upper 50 m in both regions between 1995 and 2016. Specifically, δ¹³C_DIC values in the upper 50 m decreased by 0.45 ‰ (at a rate of 0.021 ‰ yr^-1) in the SLD and by 0.41 ‰ (at a rate of 0.02 ‰ yr^-1) in the central BOB over the study period. This decline is likely attributable to the combined effects of upwelling of remineralized DIC and increased CO_2ant invasion in the upper 50 m of these oceanic regions, occurring at rates of 0.93 µmol kg^-1 yr^-1 in the SLD and 1.97 µmol kg^-1 yr^-1 in the central BOB. Additionally, a weaker correlation between δ¹³C_DIC and CO_2ant was observed in the central BOB, whereas a stronger correlation in the SLDsuggests that the invasion of isotopically lighter CO_2ant contributed significantly to the observed depletion of δ¹³C_DIC in both regions from 1995 to 2016. These findings underscore the significant role of anthropogenic CO₂ in influencing carbon dynamics in the upper ocean of these upwelling-prone regions.

How to cite: Kaluthotage, P., Silva, A., Dheerasinghe, M., and Kokuhennadige, H.: Temporal variability in dissolved inorganic carbon, δ13CDIC, and anthropogenic CO2 in the North Indian Ocean from 1995 to 2016: assessing the influence of anthropogenic CO2, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14051, https://doi.org/10.5194/egusphere-egu25-14051, 2025.

Tropical South America plays a critical role in the global carbon cycle. On one hand, the Amazon stores large stocks of carbon (150-200 PgC), representing 50% of the tropical rainforest biomass.  On the other hand, the semiarid biomes of the neighbouring Cerrado and the Caatinga contribute largely to the inter-annual variability of the global land carbon sink. Both biomes are experiencing large threats due to deforestation, forest degradation, agricultural expansion and climate variability. While these threats in the Amazon have been largely studied, vegetation loss and associated carbon emissions from the Cerrado and Caatinga biomes have been somewhat overlooked. As a result, the mean and long-term trend in net carbon exchange in both biomes remains largely unknown. In this talk, I will give an overview of recent estimates in net carbon exchange and their uncertainty range for the Amazon and the Cerrado and Caatinga biomes. I will particularly focus on the development of the 2023/2024 drought and the carbon cycle response in the region. For this we leverage multiple data streams, from bottom-up models and top-down inversion systems, to remotely-sensed vegetation dynamics and in-situ flux and atmospheric measurements. I finalize highlighting the spatial heterogeneity of carbon fluxes across the region and emphasize on the remaining challenges to reduce the uncertainty in carbon cycle estimates and the need for enhanced atmospheric monitoring networks to improve our understanding of biome-specific drivers of net carbon exchange.

How to cite: Botía, S. and the Amazon drought 2023 team: Net carbon exchange in the Amazon, Cerrado, and Caatinga: Challenges and Insights from the 2023/2024 Drought, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14074, https://doi.org/10.5194/egusphere-egu25-14074, 2025.

Methane emissions from the aquatic environment exhibit distinct characteristics: while oceans, covering 70% of Earth’s surface, emit 9 Tg of methane annually, freshwater wetlands, which occupy only 2% of Earth’s surface, emit 150-200 Tg per year. This significant contrast raises important questions about the underlying mechanisms and potential strategies to mitigate methane emissions in these water systems. In this work, we explore the challenges and opportunities of methane mitigation in both freshwater and marine environments. 

For freshwater wetlands, existing projections of future methane emissions usually neglect feedbacks associated with global biogeochemical cycles. Here, we employ data-driven approaches to estimate both current and future wetland emissions, considering the effects of changing meteorology and biogeochemical feedbacks arising from atmospheric sulfate deposition and CO₂ fertilization. We show that, under low-CO₂ scenarios (1.5 and 2°C warming pathways), the suppressive effect of sulfate deposition on wetland methane emissions largely diminishes by 2100 due to clean air policies, resulting in an additional emission increase of 7 ± 2 Tg a^-1. This increase account for 35% and 22% of total wetland emission changes under 1.5 and 2°C warming pathways, a factor not yet considered by current Integrated Assessment Models.

For marine waters, we assess the methane emissions from mariculture’s aquatic environment at 10-km resolution globally, using measurements from research cruises and satellite-observed net primary productivity. Mariculture’s aquatic emission intensity is estimated to be 1–6 gCH₄ per kg of carcass weight (CW), >95% lower than freshwater systems, due to suppressed microbial production in marine waters and inefficient ventilation to the atmosphere. The life-cycle assessment shows that mariculture’s carbon footprints are ~40% lower than those of freshwater aquaculture, suggesting considerable climate benefits of mariculture expansion to meet future protein needs.

How to cite: Shen, L., Zhuang, M., Peng, S., Gauci, V., Wei, W., Wu, L., and MacLeod, M.: Challenges and opportunities in atmospheric methane mitigation from freshwater and marine environments, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14801, https://doi.org/10.5194/egusphere-egu25-14801, 2025.

The global ocean plays a critical role in mitigating climate change by sequestering atmospheric CO₂, removing approximately 26% of anthropogenic carbon emissions since the Industrial Revolution. While significant progress has been made in estimating open-ocean anthropogenic carbon (C_anthro), the coastal ocean remains less understood due to its dynamic nature and complex processes and shortage of long-term high-quality datasets. Hence it is challenging to quantify the coastal anthropogenic carbon from the observation data. In this study, we propose a regional empirical regression-based anthropogenic carbon estimation approach (RECA) tailored for coastal regions. Using synthetic data from six different global ocean biogeochemical models, we evaluate the uncertainties in C_anthro estimation and assess the contributions of non-steady-state natural and anthropogenic components to estimation biases in the four North American coast oceans. We also compare RECA with established regression-based methods (CAREER and eMLR(C*)) that are widely used in open-ocean regions to determine their applicability in coastal settings. Our results demonstrate that RECA effectively captures overall C_anthro with minimal large-scale biases. However, subregional analyses reveal challenges in separating anthropogenic and natural CO₂ signals, emphasizing the influence of natural variability. This study provides a unified framework for high-resolution C_anthro estimation in coastal waters, evaluates its uncertainties, and paves the way for improved coastal carbon monitoring and climate action.

How to cite: Li, X. and Carter, B.: Regional method to quantify coastal anthropogenic carbon changes, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14803, https://doi.org/10.5194/egusphere-egu25-14803, 2025.

How to cite: Ward, R., Tenkanen, M., Tsuruta, A., Hyvärinen, S., Mengistu, A., Lindqvist, H., Tamminen, J., Markkanen, T., Raivonen, M., Leppänen, A., and Aalto, T.: Assessing Bottom-Up and Top-Down Methane Emission Estimates in Northern High Latitude Regions (2018–2021) , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15075, https://doi.org/10.5194/egusphere-egu25-15075, 2025.

The global ocean uptake of anthropogenic CO2 is sensitive to the uptake in the Southern Ocean, which accounts for 40-50% of the total uptake. At the same time, the Southern Ocean is the windiest region on the planet and experiences storms all year round. These storms, in turn, play an important role for the CO2 uptake in the Southern Ocean, because they can trigger outgassing of CO2 to the atmosphere. Storms induce outgassing by stirring the mixed layer via wind forcing, which leads to entrainment of waters rich in dissolved inorganic carbon into the mixed layer and elevates ocean pCO2 at the air-sea interface. However, since storms occur on synoptic time scales, such outgassing events are highly localised and short lived. Recent work based on in-situ measurements suggests that the magnitude of storm-induced outgassing and its contribution to the total Southern Ocean CO2 air-sea flux may have been severely underestimated by previous modelling studies, which do not sufficiently resolve storms and outgassing events. In this study, we take advantage of a cutting-edge simulation conducted with a fully-coupled, global, atmosphere-ocean model (ICON) with ocean biogeochemistry. Running on the assumption that the smaller grid spacing of 5 km better resolves storms and variability in wind forcing, we analyse the simulated contribution of storm-induced outgassing to the Southern Ocean uptake of CO2. 

How to cite: Kumar, A., Nielsen, D., Serra, N., Chegini, F., Jungclaus, J., and Ilyina, T.: The contribution of storm-induced outgassing to the CO2 air-sea flux in the Southern Ocean in a high-resolution, atmosphere-ocean simulation with ICON, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15314, https://doi.org/10.5194/egusphere-egu25-15314, 2025.

The ocean is an important sink for anthropogenic carbon dioxide (CO₂), but recent data from the Global Carbon Budget (GCB) highlight discrepancies in ocean carbon uptake estimates. Since the early 2000s, reconstructions of in-water CO₂ fugacity (fCO₂) using advanced interpolation techniques (data-products) have shown a growing divergence from estimates derived from global hindcast model simulations. This offsets in the mean flux amounts to approximately 0.49 GtC per year in the decade 2014-2023. The reasons for this discrepancy are not fully understood but may stem from a combination of factors including insufficient data coverage, uncertainties in scaling measurement-based estimates, and errors in model simulations. Previous studies suggests that biases in the fCO₂ data-products from the under-sampled Southern Hemisphere, may contribute significantly to this gap.

To address these concerns, the Surface Ocean CO₂ Mapping project has launched its second phase (SOCOMv2). This initiative aims to identify and quantify the accuracy and uncertainties related to data availability, changing observational networks, and input data. SOCOMv2 includes four key experiments: 1) a comprehensive geospatial uncertainty analysis, and three subsampling studies employing: 2) GCB hindcast simulations to capture true climate variability, 3) large ensemble simulations representing multiple climate states, and 4) idealized carbon uptake scenarios without climate variation. These efforts aim to provide a clearer understanding of the underlying factors contributing to the observed discrepancies in ocean carbon uptake estimates.

Results from the GCB subsampling hindcast simulation experiments reveal that individual fCO₂ data-product reconstructions can significantly overestimate or underestimate both the annual mean and the trend of the ocean carbon sink relative to the models ‘truth’. Nonetheless, the ensemble mean of the fCO₂ data-products tends to exhibit only a small overestimation of the model ‘truth’ ocean carbon sink. These discrepancies highlight the impact of limited data coverage and the inherent challenges of extrapolating from sparse measurements but cannot fully explain the observed divergence between models and fCO₂ reconstructions in the GCB.

SOCOMv2 aims to improve the accuracy and precision of ocean carbon flux estimates, contributing to improved observational approaches and guiding policy development for climate mitigation. SOCOMv2 efforts have been driven by the community, with supporting funding within a larger European Space Agency ocean carbon study (Ocean Carbon for Climate).

How to cite: Roobaert, A., Ford, D. J., Rödenbeck, C., Gruber, N., Hauck, J., Fay, A. R., Heimdal, T. H., Behncke, J., Shaum, A., Luke, G., Watson, A., Djeutchouang, L. M., Mohanan, S., Gehlen, M., Jersild, A., Zeng, J., Iida, Y., Chevallier, F., McKinley, G. A., and Shutler, J. D. and the SOCOMv2 team: SOCOMv2: On the strengths and limits of pCO2 interpolations products to estimate the ocean carbon sink, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15370, https://doi.org/10.5194/egusphere-egu25-15370, 2025.

Atmospheric methane (CH₄) is a significant greenhouse gas with a warming potential 84 times greater than that of CO₂ over a 20-year time horizon. Given its relatively short atmospheric lifetime of approximately 10 years and its high warming potential, reducing anthropogenic methane emissions is crucial for limiting near-term increases in global temperatures. Methane is emitted from both natural and anthropogenic sources and is primarily consumed through reactions with hydroxyl (OH) radicals in the atmosphere. To a lesser extent, it is also removed through soil interactions. The limited understanding of the interplay between sources and sinks leads to an unclear explanation of the interannual variability in atmospheric methane concentrations over the past decades. Moreover, there are growing concerns about the possibility that climate change could amplify natural CH₄ fluxes. Here we present an inverse model-based reanalysis of global CH₄ emissions (2018-2021). To achieve this, we employ the TM5-4DVAR inverse model system, which is driven by ECMWF-ERA5 meteorological data at a resolution of 1° x 1° for both latitude and longitude, and encompasses 137 vertical levels. This four-dimensional inverse system generates monthly global fields of CH₄ fluxes across four source categories: wetlands, rice fields, biomass burning, and anthropogenic activities. The methane fluxes are optimized using high-resolution surface-based measurements from the NOAA Earth System Research Laboratory (ESRL) global cooperative air sampling network, as well as column-averaged dry mixing ratio XCH₄ data from the GOSAT satellite. The primary aim of this work is to identify the major geographical areas and source categories driving the interannual variability and trends of global CH₄ fluxes during the study period. Moreover, the temporal variability of natural methane fluxes is analysed in relation to physical parameters to investigate how natural CH₄ emissions respond to climate factors (e.g. temperature).

How to cite: Graziosi, F., Manca, G., Segato, D., Dobricic, S., and Arriga, N.: Inverse modelling of global CH4 emissions using surface based measurements and GOSAT satellites retrievals., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15454, https://doi.org/10.5194/egusphere-egu25-15454, 2025.

Reaching the Paris Agreement temperature goals of no higher than +1.5°C or +2.0°C of global mean temperature change is quickly becoming difficult to reach by the end of the century. Not making the Paris Agreement temperature targets will impact all aspects of human society.

Around 1/3^rd of global mean surface temperature changes, is estimated to be caused by methane making it the second most powerful greenhouse gas released anthropogenically.  Anthropogenic sources emit 349 Tg of methane per year and are responsible for more than 50% of global methane emissions. The main emitters are the energy sector (>36% of emissions) and agriculture (40%). Fortunately, methane is a short-lived greenhouse gas, and removal of anthropogenic emissions sources may dramatically change the global concentrations on decadal timescales.

In response to the unlikelihood that methane emissions will be attenuated sufficiently in the coming decade by production reductions, methane emission mitigation technologies are under development. However, these technologies are yet to be rolled out on an industrial scale. New methane mitigation technologies can reduce a 50 ppm emissions source at ~60% efficiency and require an air volume rate of 4.36e13 m3/yr to remove 1 Tg CH4 per year. The volume of air required to process low concentrations to make a substantive impact on total emissions is major roadblock to their implementation. For example, for CO2 capture—a related carbon mitigation method—many test technologies are constructing large independent ventilation facilities. However, novel methane emission mitigation technologies are currently being tested and evaluated in several countries. These new technologies may capture CH4 and/or convert CH4 to molecules with less radiative forcing potential.

Here, we propose using dairy cow barns as a viable pathway for methane emission mitigation by utilizing existing infrastructure while targeting a major source of agricultural methane. Currently, there are ~264 M dairy cows worldwide. In Europe, there are 23 M dairy cows, and ~33% are housed in barns annually. For example, 70% of Denmark’s and 90% of Italy’s dairy cows are housed annually. For the health and welfare of the animals, barns are ventilated to maintain comfortable temperature and humidities, as well as ventilate abhorrent gases, such as methane. Standards for ventilation require 400 m3/hr/cow (high heat situations require 2500 m3/hr/cow), which is 3.5e6 m3/cow annually. A dairy cow emits between 55-100 kg CH4 per year. Which translates to 0.4-0.9 Tg CH4 per year for the ~7.59 M housed dairy cows in the European Union. The amount of air estimated to move through the EU dairy barns is 2.66e13 m3/yr and is within the estimated amount of air required to remove 1 Tg of CH4 from emerging technologies (4.36e13 m3/yr).  Implementation of this type of methane mitigation is feasible and with additional air recycling, potentially capture methane emissions from dairy cow barns.

How to cite: Buzan, J., Terhaar, J., Joos, F., Iversen, N., and Roslev, P.: Mitigation and implications of methane emissions from dairy cow barns, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15780, https://doi.org/10.5194/egusphere-egu25-15780, 2025.

Accurate simulation of regional carbon dioxide (CO₂) concentrations is essential for understanding carbon flux dynamics, refining emission inventories, and supporting climate mitigation policies. Using the WRF-Chem-VPRM model at 3 km resolution, this study simulated CO₂ concentrations in Jiangsu Province, China, with hourly outputs. Model verification against nine ground-based CO₂ monitoring stations confirmed its reliability.
Before integrating emission inventories into the model, we conducted a comprehensive analysis of six widely used emission inventories (ODIAC, EDGAR, MEIC, CHRED, GID, GRACED), revealing significant discrepancies in total emissions and spatial patterns in China. Provincial-scale annual carbon emissions discrepancies reached 52%, whereas urban-scale discrepancies averaged 137%, attributed to differences in emission proxies and spatial resolution. 
Sensitivity experiments for July and December 2022, representing summer and winter, assessed the impacts of spatial, temporal, and vertical allocation processes. Vertical allocation coefficients emerged as a critical factor, particularly under stable nighttime boundary layer conditions, where deviations exceeded 50 ppm. Their influence equaled or even surpassed that of emission inventory selection, underscoring the necessity of precise vertical parameterization.
Spatial allocation discrepancies primarily affected urban concentrations, where dense and diverse sources contributed to higher variability. Winter simulations exhibited increased uncertainties due to heightened heating emissions and limited vertical mixing.
These findings highlight the importance of refining vertical and spatial allocation in emission inventories to improve regional CO₂ modeling. The study provides insights for advancing carbon inversion methodologies and supporting robust Monitoring, Reporting, and Verification (MRV) systems in urbanizing regions.
Emission inventories analyzed include:
•    ODIAC: Open-source Data Inventory for Anthropogenic CO₂,
•    EDGAR: The Emissions Database for Global Atmospheric Research,
•    MEIC: The Multi-resolution Emission Inventory for China,
•    CHRED: China High-resolution Emission Database,
•    GID: Global Infrastructure emissions Detector,
•    GRACED: Global Gridded Daily CO₂ Emissions Dataset.

How to cite: Feng, W., Tang, X., Zhu, J., and Zhou, X.: High-Resolution simulation of  CO2 Concentrations Over Jiangsu Province in China Based on WRF-Chem-VPRM and Six Emission Inventories, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16464, https://doi.org/10.5194/egusphere-egu25-16464, 2025.

Atmospheric oxygen (O₂) allows to separate the natural and anthropogenic components in the atmospheric CO₂ signal, thereby providing additional constraints on these processes in the global carbon cycle. This is enabled through the ratio of O₂ and CO₂ in carbon cycle processes: the Exchange Ratio (ER). This ER signal has distinct values for combustion of different fossil fuel types, as well as between photosynthesis and respiration processes. Using these ER signals, we aim to further explore the potential of using atmospheric O₂ observations in CO₂ emission verification. For that, we are developing a global scale data assimilation system that can, next to CO₂, assimilate O₂ observations. This is our new multi-tracer implementation, specifically aimed at decadal and annual timescales: the CarbonTracker Europe Long Window system. Additionally, we implemented O₂ and the O₂/CO₂ exchange ratios into the Simple Biosphere model (SiB4) to further understand the influence of biosphere exchange on using Atmospheric Potential Oxygen (APO) as a tracer for fossil fuel emissions. We will present the results from this biosphere O₂ and CO₂ modelling to get a first theoretical assessment of the variability of the biosphere O₂ and CO₂ ER signals, both over space (related to the plant functional types) and time (related to seasonal patterns). These biosphere model results, are subsequently used in our first attempt of atmospheric inverse estimates of CO₂ fluxes using O₂ as a tracer. Finally, we will show our progress towards understanding the implications of the variability in the ERs for photosynthesis and respiration on APO calculations, as well as their influence on fossil fuel estimates using atmospheric O₂.

How to cite: Faassen, K., Hooghiem, J., van der Woude, A., van den Berg, A.-W., Hilman, B., Hulsman, L., Kaushik, A., de Kok, R., van de Sande, M., Peters, W., and Luijkx, I.: Using atmospheric O2 to disentangle the natural and anthropogenic CO2 signals , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16559, https://doi.org/10.5194/egusphere-egu25-16559, 2025.

The functions of terrestrial ecosystems are various, and recent study suggests the major three functions which are carbon, water, and energy cycling. They are all originated from land, the fundamental components of terrestrial ecosystems. Land consists of major five land cover: cropland, grassland, built-up area, wetland, and forest land. Forest land is described as high potential to remove Greenhouse gases under climate change era and thus the forest carbon management has been raised for effective land management in terms of carbon removal. Korean peninsula, South Korea and North Korea, has undergone the severe war between them and it damaged the whole territory, which consists of more than 60% of forest land. Therefore, two countries tried to revegetate and implemented forestation plans for recover the forest land over 50 years. Therefore, this study assessed the forest carbon management on the Korean Peninsula using Net Primary Productivity(NPP) from the 1980s to 2010s. To estimate NPP, Carnegie-Ames-Stanford Approach(CASA) model was applied. The study adopted the carbon demand and supply method for assessment. We defined carbon demand as amount of carbon loss from forest land in previous year due to forest land changes, and carbon supply as amount of newly updated carbon sink from forest land due to afforestation. According to research findings, even though South Korea achieved successful forest expansion, it only focused on the amount of forest area rather the quality of carbon management. However, the situation in North Korea described not only the failure of increasing forest area but also forest carbon management. Further research would be analyzed the outcomes with forest plans in South Korea and North Korea.

How to cite: Kim, W., Song, C., and Lee, W.-K.: Assessment of Forest Carbon Management Using Net Primary Productivity on the Korean Peninsula, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17087, https://doi.org/10.5194/egusphere-egu25-17087, 2025.

The climate change over the Mediterranean region poses serious concerns about the role of open vegetation fires in the emissions of climate-altering species. The aim of this work is to review the current methodologies for quantifying the emissions of greenhouse gases and black carbon from open vegetation fires, as well as the data provided by four state-of-the-art inventories of emissions of carbon dioxide (CO₂), methane (CH₄), nitrous oxide (N₂O) and black carbon (BC) in the Mediterranean region for the period 2003–2020.

A limited number of studies specifically addressed the quantification of emissions from open fires in the Mediterranean region. Our data review of fire emissions in the Mediterranean region, where “top-down” methods have not yet implemented, reveals discrepancies across the four inventories examined (GFED v4.1s, GFAS v1.2, FINN v2.5, and EDGAR v8.0). Among these, FINN v2.5 consistently reported the highest emissions, while GFED v4.1s reported the lowest. We observed that the relative ranking of total emissions between the inventories varied for the species considered (e.g. CO₂ vs. CH₄) and that different proportions of emissions were attributed to the individual countries included in the Mediterranean domain. We argued that these differences were related to the different spatial resolutions of the input data used to detect the occurrence of fires, the different approaches to calculating the amount of fuel available, and the emission factors used.

The three inventories reporting wildfire emissions were consistent in identifying the occurrence of peaks in the emissions for the years 2007, 2012 and 2017. We hypothesized that La Niña events could partially contribute to triggering the occurrence of these emission peaks.To increase the accuracy and consistency of climate-altering emission data related to open vegetation fires in the Mediterranean region, we recommend to integrate bottom-up approaches with top-down inversion methods based on satellite and in-situ atmospheric observations.

How to cite: Hundal, R. A., Annadate, S., Cesari, R., Collalti, A., Maione, M., and Cristofanelli, P.: Emissions of climate-altering species from open vegetation fires in the Mediterranean region - A review on methods and data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18709, https://doi.org/10.5194/egusphere-egu25-18709, 2025.

In this case study, we derive and compare estimates of annual net community production (NCP) in the Greenland Sea from Argo float data of nitrate, oxygen, and dissolved inorganic carbon (DIC). We added tracers of the inorganic carbon system, nitrate, dissolved oxygen, and air-sea gas exchange to the 1-D Price-Weller-Pinkel mixing model (Price et al., 1986) tuned to the Greenland Sea (Moore et al., 2015; Brakstad et al., 2019). By reinitializing the model with every Argo profile, we were able to estimate NCP as the difference between the abiotic model output and the Argo profiles. This method has previously been employed in various other regions (Plant et al. 2016;  Briggs et al. 2017, Mork et al. 2024). While we here compare NCP estimates from both nitrate, oxygen, and DIC, previous work has considered maximum two of these concurrently. Through our comparison, we discovered quantitative discrepancies in the NCP and annual NCP (ANCP) estimates. These results were sensitive to trends in the raw data and artefacts deriving from processes that were unresolved in the model, such as internal waves. Effects from internal waves were challenging to remove without introducing new artefacts. Qualitatively, the NCP seasonal cycle was well resolved: the summer of 2019, NCP fluctuated between periods of weak net biological production and periods of weak net heterotrophy. NCP was close to zero through winter, before two strong blooms were observed in late April and May 2020. However, the amplitude of the NCP signal from DIC was somewhat larger than from nitrate and oxygen. DIC derived NCP also exhibited stronger signs of remineralization from November 2019 to January 2020 compared to the two other estimates. Thus, this work shows the importance of careful consideration when utilizing biogeochemical Argo data in the Greenland Sea.

How to cite: Sælemyr, I., Olsen, A., Becker, M., Lauvset, S. K., Mork, K. A., Brakstad, A., and Fransner, F.: Net community production in the Greenland Sea: a comparative case study using Argo data of nitrate, oxygen, and DIC, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18920, https://doi.org/10.5194/egusphere-egu25-18920, 2025.

Global ocean biogeochemistry models are a key tool for estimating the global ocean carbon uptake. These models are designed to represent the most important processes of the ocean carbon cycle, but the idealized process representation, uncertainties in the initialization of model variables and in the atmospheric forcing lead to errors in their estimates. To improve the agreement with observations, we use ensemble-based data assimilation into the ocean biogeochemistry model FESOM2.1-REcoM3. In addition to the recently implemented assimilation of temperature and salinity observations, which improves the physical model state and indirectly influences biogeochemical variables, we extend the set-up further. Here, we explicitly include the assimilation of biogeochemical observations. Specifically, in-situ sea surface pCO₂ measurements, remotely sensed chlorophyll-a, and in-situ measurements of dissolved inorganic carbon, alkalinity, oxygen, and nitrate, are assimilated to reduce the uncertainty stemming from the ecosystem model. This directly affects the modelled air-sea CO₂ flux. Here, we present an updated estimate of the ocean carbon uptake for the period 2010–2020 and compare it to prior estimates.

How to cite: Bunsen, F., Nerger, L., and Hauck, J.: Assessing the recent ocean carbon sink with data assimilation into a global ocean biogeochemistry model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19322, https://doi.org/10.5194/egusphere-egu25-19322, 2025.

In 2023, sea-surface temperatures (SST) reached record highs. Historically, the years with highest global mean SST anomalies were associated with a slight increase in oceanic CO₂ uptake, primarily due to reduced CO₂ outgassing from the tropics during El Niño. In contrast, our observation-based estimates reveal that the global non-polar ocean absorbed about 10% less carbon in 2023 than expected (+0.16±0.28 PgC yr^-1).

This weakening of the ocean carbon sink occurred although the CO₂ outgassing in the tropics was indeed as low as expected. Instead, the decline in CO₂ uptake was concentrated entirely in the extratropics, driven largely by elevated SSTs in the Northern Hemisphere. While thermally induced reductions in CO₂ uptake are well-documented in the extratropics, our analysis using two ocean biogeochemical models highlights a mitigating process in the subtropical North Atlantic: the depletion of dissolved inorganic carbon in the surface mixed layer. Such negative feedbacks caused an overall muted response of the ocean carbon sink to the record high SSTs, but this resilience may not persist under long-term warming or more severe SST extremes.

By the time of this presentation, we anticipate confirming – or refining – our expectation that the ocean carbon sink in 2024 remained unusually weak, because the CO₂ outgassing from the tropics revived, whereas remaining high SSTs in the extratropics continued to suppress the CO₂ uptake.

How to cite: Müller, J. D., Gruber, N., Schneuwly, A., Bakker, D. C. E., Gehlen, M., Gregor, L., Hauck, J., Landschützer, P., and McKinley, G. A.: The ocean carbon sink under record-high sea surfacetemperatures in 2023/24, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-21437, https://doi.org/10.5194/egusphere-egu25-21437, 2025.

Nitrogen-based inorganic fertilizers have been crucial in crop production globally. For a long time, SSA agriculture has been characterised by low fertilizer use and negative nutrient balances. However, recently fertilizer use has increased drastically. Unfortunately, increased use of synthetic N fertilizers alters soil properties directly and indirectly, and N losses to the ecosystem contribute to environmental degradation and climate change. Limited studies have focused on the effect of increased N application rates on agricultural soils in the tropical highlands. It is crucial to investigate and understand N flows in tropical soils to predict potential ecological impacts of increased synthetic N-fertilizer use while meeting the food demand in SSA.

This study aimed to investigate the effects of increasing N rates on soil N dynamics, chemical properties and N use efficiency in maize-monocrop systems in the tropical highlands of the Rift Valley region, Kenya. A field experiment consisting of six N-fertilizer rates (0, 25, 50, 75, 100 and 125 kg N ha^-1) in triplicate was set up in Eldoret, Kenya. Soil samples were collected at depths of 0-20, 20-40 and 40-60 cm throughout the maize cropping season and analysed for mineral N (NH₄⁺-N and NO₃^--N), soil organic carbon and pH. Results indicate a significant change in the soil chemistry due to fertilisation. The response magnitude varied across the three soil depths. For instance, NO₃^- -N increased with increased N application rate, which peaked at 14 (55.81 mg kg^-1) and 42 (34.99 mg kg^-1) days after treatment application in the top 20 cm and 20-40 cm depths, respectively. Similar trends were also observed in the NH₄⁺-N concentration across different depths, with high N application rates tending to exhibit relatively high concentrations compared to treatments with lower N rates. We also observed a considerable decline in soil pH for plots treated with N fertilizer in the first 14 days, which then stabilized and rose gradually throughout the maize growing stages. However, the lower fertilizer plots tended to have higher pH in contrast to the other treatments. There was also a consistent increase in soil organic carbon (SOC), with slight fluctuations, throughout the cropping season.  

These results indicated low mineral N movement below the effective root zone depth during the active growth phase of the crop. Thus, a clear indicator of increased plant uptake and implies a reduced risk of loss through leaching in Ferralsols. We also expect that meteorological conditions coupled with crop phenological processes to play a significant role in the soil chemistry variability, as exhibited by the differences in response to the treatments. We will therefore consider crop phenological processes and how they influence soil nutrient cycles. The results of this study will help to inform sustainable N use in maize cropping systems and further improve understanding of N cycle in tropical soils.  

How to cite: Oluoch, K. C., Otinga, A., Njoroge, R., Mutua, S., Ouma, T., Agredazywczuk, P., Barthel, M., Six, J., Leitner, S., Oduor, C., and Harris, E.: Effects of N fertilization on soil chemistry dynamics in Ferralsols of the High Potential Maize Zone, Kenya , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-466, https://doi.org/10.5194/egusphere-egu25-466, 2025.

Particulate nitrate (pNO₃^-) and its precursor gas nitrogen oxide (NO_x) are among the most significant reactive nitrogen species in the atmosphere. NO_x emissions over the Indian sub-continent especially the Indo-Gangetic Plain (IGP) have increased rapidly over the past decades. NO_x, an atmospheric gaseous pollutant, plays important roles in the formation of tropospheric ozone, recycling of hydroxyl radicals (OH), etc. It also serves as a precursor to pNO₃^- formation. This has significant implications for air quality, climate, and human health. Rapid accumulation of pNO₃^- can also increase PM load by aiding in secondary aerosol formations. Identification of the major sources of NO_x and the formation pathways of pNO₃^- is crucial for improving the accuracy of air quality models and effective mitigation strategies. In the atmosphere, pNO₃^- is known to form mainly via four distinct pathways: (P1) oxidation of NO₂ by OH in gas phase, (P2) hydrolysis of N₂O₅ on existing aerosols, (P3) reaction between NO₃ radicals and VOCs, and (P4) reaction of NO₃ radical and ClO. However, studies on the sources and formation pathways of pNO₃^- are limited pertaining to the Indian subcontinent as well as the globe. Dual isotopes (δ¹⁵N and δ¹⁸O) of pNO₃^- are an excellent tool to understand the formation mechanisms and sources of pNO₃^- precursor (NO_x) in the atmosphere. In this study, diurnal samples of PM_2.5 were collected over a semi-urban site (Patiala) in the IGP during a large-scale paddy residue burning period (October-November). Dual isotopes (δ¹⁵N and δ¹⁸O) of pNO₃^- along with other major ions were measured. Average δ¹⁸O and δ¹⁵N of pNO₃^- were 57.2 ± 8 ‰and -1.9 ± 5 ‰, respectively. Significant diurnal differences in δ¹⁸O-NO₃^- and δ¹⁵N-NO₃^- were observed. δ¹⁵N-NO₃^- and δ¹⁸O-NO₃^- were -5.0 ± 2.4‰, 52.1 ± 6.2‰ and -0.13 ± 5.7‰, 60.0 ± 8.4‰ during day and night-time respectively. Enriched δ¹⁵N-NO₃^- during night-time was due to enhanced gas-particle partitioning owing to lower temperature. A significant negative correlation between Nitrate Oxidation Ratio (NOR), and temperature further supported the above statement. Stable isotope mixing model (MixSIAR) was used to estimate the contribution of different pathways to pNO₃^- formation and sources. The major pathways contributing to the formation of pNO₃^-  were  P1(OH)  (~ 92%) followed by P2 (N₂O₅) (~ 5%). P3 (VOCs) and P4 (ClO) had negligible contributions of ~1.3 and ~1.5% respectively. Relative contributions of P1 and P2 during day and night-time were calculated. P1 and P2 contributed to 95% and 5%, and 77% and 23% during day and night-time respectively. Presence of pNO₃^- formed via P1 during night-time could be due to the higher lifetime of pNO₃^- compared to sampling duration. Source apportionment showed biomass burning (32%) and traffic exhaust (35%) were the major contributors followed by combustion (18%) and soil emissions (15%) during the study period. Our study, first of its kind over India, is important for elucidating the formation mechanism of pNO₃^- from its precursor gas. Such studies are helpful in planning and developing mitigation strategies aiming to reduce NO_x pollution over a specific region. 

How to cite: Shaw, C., Mandal, R., Singh, A., Sanyal, P., and Rastogi, N.: Insights into the sources of precursor and formation pathways of particulate NO3- during paddy-residue burning period through dual isotope proxies, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-880, https://doi.org/10.5194/egusphere-egu25-880, 2025.

There are several nitrogen-sensitive areas in Europe, some more sensitive than others, and the Mediterranean climate zone is where many of the highly sensitive areas are. One of these areas is Portugal, where very few studies focus on this issue. The lack of infrastructure to monitor nitrogen concentrations and deposition in the country, as well as policies to enforce nitrogen emission reductions, poses a challenge, as ammonia is the most critical pollutant to fulfil Portugal's future emission goals.
Currently, modelling is the only cost-effective option to effectively study nitrogen deposition in the Mediterranean. Due to the extent of agriculture in these areas, nitrogen (N) deposition assessments have been conducted for many years in other countries, such as the Netherlands and Germany, using Chemistry Transport Models (CTMs) to assess the dry deposition of reduced and oxidised N. Among these CTMs, LOTOS-EUROS is regarded as one of the most advanced models that includes a compensation point parametrization for ammonia. However, applying this model to a Mediterranean area requires some adaptation since its deposition parameters are mostly based on studies from North-Western Europe. Since vegetation parameters influence the surface resistance of gas-phase deposition, and this resistance is crucial for gas deposition, using these models in climates different from where they were initially developed will likely lead to inaccurate results. Due to this, there is a need for a CTM that better represents different climate zones. 
Here, we use a new version of the LOTOS-EUROS model incorporating a three-tiered vegetation approach. The three tiers considered are Tier 1—climate zones; Tier 2—land use classes; and Tier 3—vegetation type. This method incorporates 140 combinations of land use and vegetation types, allowing us to differentiate the Mediterranean from the standard temperate climate by changing vegetation parameters.
With this study, we aim to adapt and enhance the dry deposition module of LOTOS-EUROS by including specifications for the Mediterranean climate and vegetation. To achieve this goal, sensitivity runs were performed for multiple vegetation and climate-specific parameters to assess which are the most influential variables for the study region. Then, the most sensitive parameters were analysed to understand the variations.
This work found that adapting the maximum stomatal conductance is highly prone to introduce changes in the modelled deposition fluxes and concentrations of oxidised and reduced nitrogen and ozone. Maximum and minimum vapour pressure deficit and maximum, optimal and minimum temperature were also among the most susceptible to cause impacts in the model results over the Mediterranean. Also, the start and end of the growing season greatly impacted the modelled deposition fluxes since the growing season starts earlier and finishes later in the Mediterranean. Hence, adapting the deposition parameters to the Mediterranean climate and vegetation significantly impacts the modelled concentration and deposition fluxes of oxidised and reduced nitrogen compounds and ozone.

How to cite: Barreirinha, A., Banzhaf, S., Russo, M., Thürkow, M., Schaap, M., and Monteiro, A.: Investigating the sensitivity of modelled nitrogen inputs in the Mediterranean to dry deposition parameters, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1042, https://doi.org/10.5194/egusphere-egu25-1042, 2025.

How to cite: Helm, D., Dammers, E., Gama, C., Schaap, M., and Monteiro, A.: Emissions of ammonia and nitrogen dioxide over the Iberian Peninsula estimated with satellite observations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1143, https://doi.org/10.5194/egusphere-egu25-1143, 2025.

Nitrogen policy in the Netherlands has a long history. Since the 70’s of the last century, various measures have been implemented in an attempt to reduce emissions of different nitrogen compounds. A few examples of a wide range of measures implemented since then are the introduction of catalytic converters removing nitrogen oxides from fossil fuel burning, shallow injection of manure into the soil reducing ammonia emissions to air and lowering of the manure application rates. In 2019, the European High Court judged that the Dutch nitrogen policy with respect to nitrogen deposition onto protected nature areas was not in accordance with the European Habitats Directive. All infrastructural developments came to a halt: building houses, roads, etc. stopped. With a new Minister on Nitrogen in place since 2021, the focus became a drastic reduction of nitrogen emissions to get the nitrogen deposition below the nitrogen critical loads for 74% of the protected (Natura 2000) nature areas, which is laid down in a nitrogen law. This requires a drastic change in activities in and around these nature areas, mainly (but not exclusively) focusing on the agricultural sector. This because the contribution to the total nitrogen deposition of this sector is on average 50% in the Netherlands. To help policymakers take measures as efficiently as possible, RIVM has developed a tool that maps the origin of the nitrogen deposition in each nature area. In this presentation, the tool will be presented and it will be shown how the tool can help the government, provinces and other stakeholders to take dedicated regional measures to reduce the nitrogen emissions and eventually reduce the nitrogen deposition in nature areas.

How to cite: Wichink Kruit, R., Brandt, K., Bleeker, A., and van der Maas, W.: Determining the origin of nitrogen deposition in nature areas, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1792, https://doi.org/10.5194/egusphere-egu25-1792, 2025.

South Asian nations are facing the challenge of increasing nitrogen pollution with the Indo-Gangetic Plain having some of the highest levels of atmospheric ammonia pollution globally. However, there is a lack of in-country research to evaluate the possible impact of nitrogen-related pollutants on South Asian biodiversity. In the Himalayas, there is an opportunity to utilize lichens from natural habitats to establish field-based references for better future tracking of changes in ecosystem health relevant to the wider South Asian region. In this study, we assessed the natural chemical variability of two lichens (Usnea spp. and Hypotrachyna spp.) based on thallus nitrogen and metal ion contents along with their physico-chemical and oxidative responses in two 1-km long transects from two forests of Nepal representing local gradients. Our results revealed a moderate concentration of total Kjeldalh nitrogen (0.36-0.98 % DM in Chandragiri, KTM and 0.57-2.04 % DM in Ghorepani, ACA), as well as ammonium (40.42-159.84 mg/L in Chandragiri, KTM and 80.60-280.64 mg/L in Ghorepani, ACA) and considerable amount of metal ions in both lichens, though with the highest values for lichens collected from the Ghorepani, ACA (from Western Nepal). A noteworthy background concentration of atmospheric ammonia was also observed at both sites. The highest variation in physico-chemical responses, such as electrical conductivity, chlorophyll content, chlorophyll degradation, chlorophyll fluorescence, and phenolic content was observed in the lichens from the same area, consistent with the higher levels of air pollution. Moreover, there appeared to be associated impacts on oxidative responses such as radical scavenging and catalase activities. Furthermore, the metal ions in the lichen thalli were found to originate from both anthropogenic and natural sources in Chandragiri, KTM and few of the metal ions were deposited from long-range transport mechanisms in Ghorepani, ACA, which signifies the diverse sources of pollution in the study areas. The sampling line-wise variation in thallus chemistry signifies the local pollution gradient in both sites. Further, environmental covariables (slope, elevation, crown settings, wind pattern) were observed to affect the lichen abundance and accumulation of nitrogen and metal ions. In comparison, Hypotrachyna spp. showed greater potential to accumulate pollutants and variability in physico-chemical and oxidative responses. From this study, we conclude that a range of physico-chemical and biochemical responses of the target lichens can be used as proxies for the bioindication of nitrogen and metal ion pollution to assess lichen’s health and ecological functioning. Wider studies covering large spatial extent and cellular mechanisms of lichen response are now recommended to fully understand the functional biology explaining contrasting responses between lichen species in different geographic settings of Nepal and South Asia.

Keywords: Lichens; Bioindicators; Pollution; Ecosystem; Reference

How to cite: Pradhan, S. P., Bista, H., Lamsal, B., Pandey, B. P., Baniya, C. B., Deshpande, A., Sharma, S., and Sutton, M. A.: Contrasting physico-chemical and oxidative relationships to thalli nitrogen and metal ion contents in Usnea spp. and Hypotrachyna spp. from Himalayan forests of Nepal., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1999, https://doi.org/10.5194/egusphere-egu25-1999, 2025.

How to cite: Zamanian, K., Taghizadeh-Mehrjardi, R., Tao, J., Fan, L., Raza, S., Guggenberger, G., and Kuzyakov, Y.: Acidification of European croplands by nitrogen fertilization: Consequences for carbonate losses, and soil health, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2297, https://doi.org/10.5194/egusphere-egu25-2297, 2025.

The input of nitrogen (N) into forests through atmospheric deposition has been determined for the main forest types within the ICP Forests Level II monitoring network and the Swedish Throughfall Monitoring Network (SWETHRO) since the 1990s from measured concentrations in continuously collected precipitation (bulk deposition) and throughfall (below tree canopy) samples. Recently, aggregated data sets have been created, containing gap-filled monthly and annual bulk and throughfall depositions (including stemflow in beech stands) for more than 500 forest stands. Total deposition was calculated from throughfall deposition accounting for canopy exchange. Here, we present trends for throughfall deposition of inorganic N, including ammonium (NH₄⁺-N) and nitrate (NO₃^--N), for plots with a complete time series, during the period 2000-2020 and in the first and last decade separately. Furthermore, we highlight and discuss spatial trends of total inorganic N deposition across Europe.

How to cite: Verstraeten, A., Schmitz, A., Marchetto, A., Clarke, N., Thimonier, A., Hilgers, C., Prescher, A.-K., Kirchner, T., Hansen, K., Jakovljević, T., Iacoban, C., de Vries, W., Ahrends, B., Meesenburg, H., Pihl Karlsson, G., Karlsson, P. E., and Waldner, P.: Trends of inorganic nitrogen deposition in European forests during the period 2000-2020, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3079, https://doi.org/10.5194/egusphere-egu25-3079, 2025.

In recent years, vehicle-based, multiple-gas mobile sensing platforms have been developed and extensively utilized for greenhouse gases (GHGs) and air pollutant emission studies. Closed-path analyzers are currently the primary equipment used for plume observations. However, the closed-path approach, poses sampling challenges for the species such as water vapor (H₂O) and ammonia (NH₃) that readily adsorb and desorb from the instrument inlets, tubings, and optical cells. Due to the different adsorption characteristics of each gas, the plume signals generated during the sampling process may become desynchronized. In addition, many mobile systems are deployed on fuel-powered vehicles, which emit exhaust that can contaminate the detected plume signals. These issues can increase the complexities in subsequent data processing tasks.

This work reports the field deployment of a multiple trace gas plume sensing platform, equipped with open-path N₂O, CH₄, H₂O and NH₃ quantum-cascade laser analyzers (model HT8500, HT8600P, HT8700, respectively) with a 10 Hz sampling time resolution. The plume monitoring system with a total power consumption of no more than 150W allows it to be easily driven by an electric vehicle. Utilizing the open-path N₂O/CH₄/H₂O/NH₃ gas analyzers eliminates the need for a pressure-controlled enclosed gas cell, the associated tubing systems, and power- hungry pump. The ambient air flows unrestricted through the optical path, enabling analyzers to achieve high temporal resolution, high response rates, and reduced sampling artifacts and power consumption compared to their closed-path gas analyzer counterparts. This open-path configuration not only eliminates the influence of exhaust emission signals from vehicles using fossil fuel engines, but also achieves perfect plume synchronization, which is crucial for the real-time identification of diffuse sources using correlations between different molecules in measured plumes.

The mobile platform has been field deployed in different field experiments including livestock farms, ammonia plants, cold storage facilities, wastewater treatment plants, and urban traffic roads in China. Our study has identified a substantial increase in ammonia concentrations adjacent to rivers, with an average increment of ~37 ppb relative to a few ppb background concentration. We observed that the peak methane concentration near a wastewater treatment plant reached 7539 ppb. Furthermore, the ratio of methane plume signal intensity to ammonia plume signal intensity in the vicinity of industrial areas is ~10, as opposed to non-industrial areas where this ratio is significantly reduced. The synchronized plume significantly enhances the efficiency of extracting effective plume data from the raw signals acquired from different gas analyzers.

How to cite: Hu, S., Shen, W., Jiang, R., Wilson, D., Lin, T.-J., and Wang, Y.: Synchronized N2O/CH4/H2O/NH3 plume mobile measurement system based on low-power open-path laser analyzers, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3928, https://doi.org/10.5194/egusphere-egu25-3928, 2025.

Nitrogen holds a crucial place in maintaining the sustainability of the food-energy-water (FEW) nexus, essential pillars underpinning human society. Its vital role spans across food production, energy generation, and the preservation of water quality. Here based on CHANS model, we show that comprehensive nitrogen management strategies offer the dual benefits of satisfying China's food requirements and boosting nitrogen energy production from straw by 1 million tonnes (26%) compared to the baseline year of 2020. Simultaneously, these strategies could lead to a reduction of 8 million tonnes (-31%) in nitrogen fertilizer usage, a decrease of 3.8 million tonnes (-46%) in nitrogen-induced water pollution, and a halving of water consumption in agriculture, all relative to 2020 levels. These transformative changes within the FEW nexus could result in national societal gains of around US$140 billion, against a net investment of just US$8 billion. This emphasizes the cost-effectiveness of such strategies and highlights their significant potential in assisting China to meet multiple sustainable development goals, especially those related to hunger relief, clean energy advancement, and the protection of aquatic ecosystems.

How to cite: Chen, B.: Managing nitrogen to achieve sustainable food-energy-water nexus in China, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4076, https://doi.org/10.5194/egusphere-egu25-4076, 2025.

Deposition of reactive nitrogen causes detrimental environmental effects, including biodiversity loss, eutrophication, and soil acidification. Measuring and modeling the biosphere-atmosphere exchange of ammonia, the most abundant reduced nitrogen species, is complex due to its high reactivity and solubility, often leading to systematic discrepancies between model predictions and observations. This study aims to determine whether three state-of-the-art exchange schemes for NH₃ can accurately model NH₃ exchange in a dune ecosystem and detect factors causing the uncertainties in these schemes. The selected schemes are DEPAC by Van Zanten et al. (2010), and the schemes by Massad et al. (2010) and Zhang et al. (2010). Validation against one year of gradient flux measurements revealed that the Zhang scheme represented the NH₃ deposition at Solleveld best, whereas the DEPAC scheme overestimated the total deposition while the Massad scheme underestimated the total deposition. Yet, none of these schemes captured the emission events at Solleveld, pointing to considerable uncertainty in the compensation point parameterization and possibly in the modeling of NH₃ desorption processes from wet surface layers. The sensitivity analysis further reinforced these results, showing how uncertainty in essential model parameters in the external resistance (R_w) and compensation point parameterization propagated into diverging model outcomes. These outcomes underscore the need to improve our mechanistic understanding of surface equilibria represented by compensation points, including the adsorption-desorption mechanism at the external water layer. Specific recommendations are provided for future modeling approaches and measurement setups to support this goal.

How to cite: Jongenelen, T., van Zanten, M., Dammers, E., Wichink Kruit, R., Hensen, A., Geers, L., and Erisman, J. W.: Validation and uncertainty quantification of three state-of-the-art ammonia surface exchange schemes using NH3 flux measurements in a dune ecosystem, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4177, https://doi.org/10.5194/egusphere-egu25-4177, 2025.

Mass emergence of periodic cicadas (Magicicada spp.) represents a unique ecosystem disturbance with potential impacts on forest soil biogeochemistry and greenhouse gas emissions. During the 2021 Brood X emergence in Indiana, USA, we investigated how cicada emergence and subsequent decomposition affected soil microbial communities and their production of nitrous oxide (N₂O) and ammonia (NH₃). Using a combination of field measurements and controlled laboratory experiments, we discovered that the interface between cicada carcasses and soil surfaces creates hotspots of enhanced microbial nutrient cycling, leading to significant pulses of N₂O and NH₃ after approximately 10-15 days. Our study revealed that dissimilatory nitrate reduction to ammonia (DNRA) was the primary mechanism driving these emissions, evidenced by increased abundance of DNRA taxa on cicada carcass surfaces (the necrobiome) coinciding with peak gas fluxes. Notably, the abundance of Serratia marcescens, a bacteria capable of both chitin degradation and DNRA, was significantly positively associated with N₂O pulses. Analysis of 16S rRNA amplicon sequencing data showed distinct microbial community compositions between soil and cicada necrobiome samples, with significantly higher abundances of chitinolytic and DNRA taxa in the necrobiome. Time series decomposition experiments demonstrated that soil respiration rates and nitrogen cycling were significantly enhanced in cicada-amended soils. Quantitative PCR revealed that bacterial ammonia oxidisers dominated over archaeal counterparts in soil samples, while the cicada necrobiome was characterised by high abundances of heterotrophic nitrifiers. The emergence tunnels created by cicadas also influenced soil conditions, potentially creating microsites that favour DNRA over conventional denitrification. While individual emergence events may contribute relatively small amounts of nitrogen compared to annual atmospheric deposition, the predictable nature and geographic extent of cicada emergences suggest they may represent an overlooked yet significant contributor to forest nitrogen cycling and greenhouse gas emissions. Our findings provide new insights into the complex microbiological mechanisms driving biogeochemical pulses following mass mortality events and highlight the need to consider periodic ecosystem disturbances in climate change models.

How to cite: Mushinski, R., Purchase, M., Phillips, R., Raff, J., Phelps, A., Huenupi, E., and Lau, J.: Periodic Cicada Mass Mortality Events Drive Microbial-Mediated Gas Pulses from Forest Soils, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5842, https://doi.org/10.5194/egusphere-egu25-5842, 2025.

Reduced tillage is often considered as an agroecological practice that promotes soil organic carbon (SOC) sequestration in the topsoil, offering potential for climate change mitigation. However, effective mitigation requires a comprehensive understanding of trade-offs among SOC stocks, greenhouse gas emissions, and crop yields. As climate change alters carbon and nitrogen cycling, these trade-offs must be evaluated under current and experimentally induced extreme conditions to assess the effectiveness of reduced tillage in a changing climate. In this study, we measured crop yields, soil carbon stocks and soil CO₂ and N₂O fluxes in a conventional tillage (CT) vs. reduced tillage (RT) field trial in central Germany. The long-term trial runs since 1970 in a field with Luvisol soil (73% silt, 15% clay, and 6.6 pH). The mean annual precipitation is 611±120 mm and the mean annual temperature is 9.6±0.7°C. The field trial follows a randomized block design and consists of 16 plots: eight under CT with inversion ploughing to a depth of 27-30 cm, and eight under RT with non-inversion harrowing to a depth of 7-10 cm. In 2022-23 and in 2023-24 we cultivated winter wheat and winter barley respectively. In February 2023, rain-out shelters (area =2 m × 2 m) designed to intercept 50% of the precipitation were installed in half of the plots, and we initiated the soil flux measurements with static chambers over permanently installed rings and portable gas analyzers. We measured crop yields in both years, and SOC in samples from 0-90 cm at 10 cm intervals sampled in August 2023. SOC traits were examined with by-size fractionation to particulate and mineral-associated organic matter and an incubation experiment with an automated respirometer. Winter wheat yield did not differ between tillage and precipitation treatments but, in the second year of our experiment, winter barley yield was lower under rainfall exclusion than ambient precipitation in the RT fields only (50% precipitation: 0.26±0.05 kg m^-2 vs. 100% precipitation: 0.52±0.02 kg m^-2). Regarding SOC, we found that fields under RT had higher stocks in the 0-10 cm depth than under CT (RT: 1.93±0.03 kg m^-2 vs. CT: 1.53±0.02 kg m^-2), but the opposite occurred in the 20-30 cm depth (RT: 1.16±0.04 kg m^-2 vs. CT: 1.58±0.06 kg m^-2). Comparing SOC stocks at 0-90 cm, there was no difference between the two tillage systems. Field soil N₂O fluxes did not differ significantly between tillage and precipitation treatments when considering block, plot and date as random effects. In contrast, field soil CO₂ fluxes were significantly lower in RT than CT fields under ambient precipitation but this did not result in higher SOC stocks under RT. Rainfall exclusion led to higher soil CO₂ fluxes both in the RT (in average, 50%: 32.0±1.0 mg CO₂-C m^-2 h^-1 vs. 100%: 30.6±0.9 mg CO₂-C m^-2 h^-1) and CT (in average, 50%: 30.1±1.1 mg CO₂-C m^-2 h^-1 vs. 100%: 24.2±0.7 mg CO₂-C m^-2 h^-1) fields. Based on the above, RT seems to have no climate change mitigation potential in a productive fine textured soil of temperate central Europe.

How to cite: Apostolakis, A., Englert, P., Daka, O. L., Siebert, S., and Meijide, A.: Trade-offs between crop yield, soil organic carbon and greenhouse gas emissions under reduced tillage and rainfall exclusion, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6623, https://doi.org/10.5194/egusphere-egu25-6623, 2025.

Tropical peatlands are crucial for global nitrogen (N) cycling because they store large amounts of carbon and N. This study, conducted in November 2023, investigated the dynamics of N₂O emissions from Amazonian peatland forests in Peru. It focused specifically on two peatland forest sites in Iquitos: the Quistococha and Zungarococha forests. We conducted static chamber gas measurements to assess soil greenhouse gas (GHG) fluxes. Additionally, we took soil samples for physical and chemical properties and soil microbiome (DNA & RNA). In order to investigate the source processes for N₂O production and consumption, we applied ¹⁵N isotopes as tracers in soil. We also took samples for natural abundance of ¹⁵N in N₂O gas. Our results indicate that both forests exhibited different trends in soil GHG fluxes and N substrates. Quistococha had higher levels of soil nitrate and ammonium compared to Zungarococha, which correlated with increased N₂O emissions from Quistococha. A similar pattern was observed for CO₂ emissions, with Quistococha producing higher levels than Zungarococha. Contrastingly, Zungarococha had higher soil moisture levels, which aligned with its lower N₂O emissions. This forest also showed greater soil N₂ emissions, suggesting the potential for complete denitrification. However, this site was also a significant source of CH₄ emissions due to its higher soil moisture, which supports methanogenic activity. Overall, the two sites demonstrated distinct behaviors: Quistococha was a source of N₂O and CO₂, influenced by intermediate soil moisture. Zungarococha emitted higher levels of CH₄ and N₂ due to its high soil moisture conditions. The patterns in N₂O fluxes are further supported by ¹⁵N isotopic mapping, correlating N₂O emissions with their source processes. The site preference values fall within the denitrification zone at Zungarococha and the nitrification zone, with some hybrid processes in Quistococha.  The microbiome analyses show similar results, with denitrifying microbes dominating the Zungarococha soil and nitrifying microbes dominating the Quistococha soil.

How to cite: Masta, M., Kazmi, F. A., Espenberg, M., Pärn, J., Soosaar, K., and Mander, Ü.: Dynamics of N2O emissions from Amazonian tropical peat forest and partitioning N-processes using 15N isotopes., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6740, https://doi.org/10.5194/egusphere-egu25-6740, 2025.

Soil organic matter (SOM) consists of carbon and nitrogen, both of which can contribute to the production of nitrous oxide (N2O). Currently, there is ample focus on increasing soil carbon content as a strategy for climate mitigation. Yet, the role of SOM on N2O production is poorly understood. We will present field flux N2O measurements from a hillslope cultivated to cereals with a natural gradient in SOM, pH and soil moisture. Additionally, eight rain exclusion shelters (~50% drought) were installed along the gradient, and N2O fluxes were measured both under 50% reduced and normal rainfall conditions. N2O fluxes have been measured for two growing seasons and will be presented alongside with soil and yield characteristics.

How to cite: Dörsch, P. and Kjær, S. T.: Influence of soil organic matter and reduced rainfall on nitrous oxide emissions along a cultivated hillslope , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7923, https://doi.org/10.5194/egusphere-egu25-7923, 2025.

Despite reduction of nitrogen emissions, deposition in German forests remain high. Eutrophication of ecosystems thus remains an important issue of scientific and socio-political interest. Here we analyse data from 78 intensive forest monitoring (Level II) sites operated by the forest research institutes of the German federal states as part of the ICP Forests network (International Co-operative Programme on Assessment and Monitoring of Air Pollution Effects on Forests). In the 2013-2022 period, mean annual bulk open field (inorganic + organic) deposition was between 4.4 and 13.5 kg N ha^-1 a^-1. Over the past twenty years, N deposition decreased by about 40 % which corresponds to a decrease of 2.5 % per year compared to the deposition in 2010. The decrease in N-NO₃ (-3.1 % per year) was slightly higher than the decrease in N-NH₄ (-2.7 %). Organic N deposition decreased by only 0.7 % per year. Canopy budget models show that N deposition (wet + dry + occult) to forest sites was between 10 and 31 kg N ha^-1 a^-1 over the same period.

The deposition data is used for reporting duties such as the German federal states’ core indicators of environmental quality (LIKI) and for scientific research e.g. to evaluate changes in biodiversity, dynamics of nutrient cycles and ensuing vulnerability of ecosystem services, or effects on tree vitality. We used the data to assess the impact of N deposition on foliar N concentrations, an import indicator of tree nutrition status. Tree nutrition influences vitality and trees’ resilience to climate extremes. A deterioration of foliar nutrients has been observed in forest ecosystems across Europe. At the German Level II sites, all main tree species (European beech, Norway spruce, Scots pine, sessile and pedunculate oak) show a significant decrease in foliar N concentration of 0.2-0.3 % per year. Besides nitrogen deposition, the reduction has been linked to various environmental factors, including increasing temperatures and changing precipitation patterns, as well as, the increase in atmospheric CO₂ concentrations. At the spatial scale, nutrient availability can be explained by various site conditions such as parent material. Nonetheless, weak positive but significant relationships between mean foliar N and total N deposition for beech, oak, and pine for the 2013-2022 time period show that atmospheric deposition can explain part of the spatial variability between forest sites. The results indicate the importance of assessing deposition, trophy classes, and climate conditions at the same sites to fully understand their interaction.

How to cite: Krüger, I., Schmitz, A., Stadelmann, C., and Sanders, T.: Decreasing N deposition leads to significant decrease in foliar N concentrations in forest trees, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8269, https://doi.org/10.5194/egusphere-egu25-8269, 2025.

Effective management of carbon (C) and nitrogen (N) in agricultural soils is crucial for mitigating greenhouse gas (GHG) emissions, particularly nitrous oxide (N₂O) and carbon dioxide (CO₂). This study investigates innovative dual C and N isotope-based methods to explore the mechanisms driving N₂O and CO₂ production and their potential mitigation, while maintaining soil fertility. By applying selectively labelled fertilizers with labelled in both fractions (¹⁵NH₄NO₃ or NH₄¹⁵NO₃) the microbial transformations of N in soil are traced, allowing for the identification of conditions that promote N₂O production or its reduction to the environmentally benign N gas (N₂).

The impact of different labile and recalcitrant C sources on N cycling and GHG emissions is investigated by applying ¹³C-labelled maize-derived plant litter and biochar. The interaction between labile-C (e.g., plant litter) and recalcitrant C (e.g., biochar) with N in soils plays a critical role in regulating microbial processes and, consequently, GHG emissions. Plant litter, as a labile C source, stimulates microbial activity, (i) enhancing N-cycling and potentially increasing N₂O emissions or, alternatively, (ii) stimulating microbial inorganic N immobilization thereby reducing N availability to gaseous and hydrological N loss processes. In contrast, recalcitrant C, such as biochar, provides a stable C form with long term C storage potential in soils. Biochar with its large specific surface area is recognized for its ability to sorb inorganic N such as ammonium and nitrate, reducing its availability for microbial processes that produce N₂O and thereby may mitigate soil N₂O emissions. However, how C inputs and N availability influence each other and affect microbial processes linked to GHG emissions remains poorly understood.

To address these challenges, a large-scale incubation study was initiated using soils sampled from a field experiment in Grabenegg, Austria, conducted by, The University of Natural Resources and Life Sciences, Vienna (BOKU) and Austrian Agency for Health and Food Safety, Vienna (AGES). One experimental soil was amended with NPK fertilizer, while the other received both NPK and hardwood- derived biochar since 2022. Soil samples were collected from the upper 10 cm of the root zone in October 2024 and used in a laboratory mesocosm experiment to trace litter-C and biochar-C processing and their effects on soil inorganic N cycling using ¹⁵N and ¹³C isotope tracing and isotope pool dilution measurements. Key measurements, including emissionsof ¹⁵N₂O, ¹⁵N₂, and ¹³CO₂, ¹³C tracing into particulate organic ¹³C, mineral-associated organic ¹³C, and microbial biomass ¹³C and, ¹⁵N tracing in, mineral-N (¹⁵NH₄, ¹⁵NO₃) and microbial ¹⁵N will be performed at various intervals over one month, and data evaluated using numerical modelling. Findings from this study will greatly contribute to optimizing climate-smart soil management practices aimed at reducing GHG emissions from soil while maintaining its fertility.  

How to cite: Bibi, S., Hafiza, B. S., Wanek, W., Vlasimsky, M., Rabello, M., Heiling, M., Dercon, G., Taru, S., Adelheid, S., and Hood-Nowotny, R.: Investigating Nitrous Oxide Pathways and Soil Carbon-Nitrogen Interactions Using Isotopic Techniques to Mitigate Greenhouse Gas Emission, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8306, https://doi.org/10.5194/egusphere-egu25-8306, 2025.

Root exudates account for up to 17% of the carbon fixed from photosynthesis and are allocated belowground, where they significantly influence microbial communities that drive nutrient cycling, particularly nitrogen in the rhizosphere. Root C exudation for nitrogen acquisition may differ between tree types. This study aimed to investigate how root exudates from English oak (Quercus robur) influence nitrogen cycling in rhizosphere soils compared to soils under alder (Alnus glutinosa). We hypothesized that oak root exudates would prime faster N transformation, given that alder tree roots host nodules for biological nitrogen fixation and thus will not invest exudate C in nitrogen acquisition. We experimented to measure gross and net nitrogen mineralization rates in soils subjected to simulated oak- and alder-specific carbon exudation rates. The study was designed using three artificial root exudate concentrations: 0, 77, and 359 µg C g⁻¹ soil day⁻¹ for alder, and 0, 187, and 814 µg C g⁻¹ soil day⁻¹ for oak. Soils were collected from the top 15 cm of the mineral layer from a four-year-old monoculture plantation of oak and alder trees in Staffordshire, England. The artificial root exudates were based on the actual root exudate rates from alder and oak trees collected during the Summer of 2022 and Spring of 2023 and contained carbohydrates, amino acids, and organic acids. Nitrogen transformation responses in the incubated soils were measured on days 15 and 30. On day 15, half of the soils were recovered from the incubation chambers and subjected to ¹⁵N-N tracer addition to determine gross N mineralization. The study revealed that higher concentrations of root exudate significantly (p<0.001) enhanced microbial activity. This was evidenced by increased soil respiration (21-fold in the oak simulation and 10-fold in the alder), microbial biomass carbon (3-fold in both tree species), and microbial biomass nitrogen (6-fold in oak and 2-fold in alder simulations) compared to the control after 30 days of incubation. These changes contributed to a 282% increase in total dissolved nitrogen in the oak and a 140% increase in the alder simulations. Root carbon inputs altered both gross and net mineralization and nitrification rates. Higher exudate concentrations over longer incubation periods elevated gross mineralization rates by up to 20-fold in the oak but reduced by up to fivefold in the alder compared to controls. Net mineralization rates increased with exudate concentration in both species. In gross nitrification, oak exudates enhanced tenfold, while alder exudates increased eightfold compared to controls after 15 days. Gross mineralization strongly correlated with net mineralization (R²_oak=0.92, R²_alder=0.76) but showed weaker correlations with net nitrification (R²_oak = 0.30, R²_alder = –0.47). Oak root exudates exhibited higher responses across gross mineralization (lnRR=3.08), net mineralization (lnRR=2.50), and gross nitrification (lnRR=1.57) compared to alder. Our results demonstrate that higher oak exudation rates enhanced nitrogen cycling compared to alder, underscoring the importance of species-specific traits in shaping carbon allocation strategies and nutrient cycling in the rhizosphere. This research highlights the critical role of root exudation in regulating soil nutrient dynamics and has broader implications for forest management.

How to cite: Kusumarini, N., Lynch, I., Cox, L., and Ullah, S.: Nitrogen transformation mediated by artificial root exudates derived from young alder and English oak trees, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9733, https://doi.org/10.5194/egusphere-egu25-9733, 2025.

Maintaining agricultural productivity while reducing soil organic carbon (SOC) loss, greenhouse gas emissions and groundwater contamination is a major challenge for European agriculture. Organic farming practices are expected to improve soil health and have increased their share of European cropland, but their effects on soil biogeochemical properties, biodiversity and nitrogen dynamics are mixed. This study uses the process-based ARMOSA crop model to assess the impact of conventional and organic farming practices on yield, SOC stock, nitrate (NO₃) leaching, and nitrous oxide (N₂O) emissions in both crop and livestock farms.

The research was carried out using simulations under current and projected future climate conditions in the South Savo region of Finland, which is characterised by a subarctic climate (Köppen-Geiger classification). The soil type was loamy sand (sand 76%, clay 4%, silt 20%) with a SOC content of 3.5%, a carbon-to-nitrogen ratio of 17, and a pH of 6.2 in the top 30 cm of the soil.

Five-year crop rotations that reflect prevalent practices in the area were designed for both crop and livestock production systems. Crop production rotations included cereals (with fodder peas in organic management), oilseed rape, and grass. Livestock farm rotations featured two years of cereals followed by a three-year fescue and timothy meadow (including clover in organic management). Nine scenarios were simulated to explore residue management and fertilisation strategies. Conventional systems used mineral fertilisers alone or combined with slurry. Organic systems used slurry, green manure, and a commercial organic fertiliser.

To evaluate the productivity and the environmental impact of these rotations, a fuzzy logic-based trade-off analysis was employed for each climate scenario. This analysis quantifies the trade-offs between crop yield, N₂O emissions, NO₃ leaching, and SOC stock changes. The result is a composite index known as the ∑ommit index. This index rates these trade-offs on a scale from 0 (poor) to 1 (excellent).  To accommodate diverse evaluation criteria, alternative versions of this trade-off analysis were implemented. Each version varies the weightings assigned to the trade-off components to mirror the perspectives and priorities of different representative stakeholder categories.

Using the ∑ommit index to evaluate a five-year rotation, rather than analysing individual cropping cycles, offers a significant advantage. This approach takes into account the interconnected effects of each cycle and its interactions with preceding and subsequent cycles. By considering these cumulative effects, the index provides a more comprehensive view of the trade-off dynamics during crop transitions. This holistic perspective is essential for making informed decisions about sustainable farming practices and long-term crop rotation strategies.

How to cite: Calone, R., Valkama, E., Acutis, M., Perego, A., Botta, M., and Bregaglio, S.: Trade-off analysis of conventional and organic crop rotations under current and future climate scenarios in Finland, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9997, https://doi.org/10.5194/egusphere-egu25-9997, 2025.

Anthropogenic activities have substantially enhanced the loadings of reactive nitrogen (Nr) in the Earth system since pre-industrial times, contributing to widespread eutrophication and air pollution. Increased Nr can also influence global climate through a variety of effects on atmospheric and land processes but the cumulative net climate effect is yet to be unravelled. Here we show that anthropogenic Nr causes a net negative direct radiative forcing of −0.34 [−0.20, −0.50] W m⁻² in the year 2019 relative to the year 1850. This net cooling effect is not only as a result of the increased terrestrial carbon sequestration, but also led by short-lived Nr components and the associated atmospheric chemical reactions, including increased aerosol loading and reduced methane lifetime induced by nitrogen oxide (NO_x). Such cooling effect is not offset by the warming effects of enhanced atmospheric nitrous oxide (N₂O) and ozone (O₃). However, despite the significant climate impacts of the short-lived nitrogen components, in particular, NO_x, the associated soil biogeochemical processes remain poorly constrained, thus leading to varied responses to N fertilizer application as well as the estimates of global soil emissions among different approaches. Our results highlight the urgent necessities to integrate knowledge between atmospheric chemistry and soil biogeochemistry to improve the understanding of the Nr climatic effects.

How to cite: Gong, C., Tian, H., Liao, H., Kou-Giesbrecht, S., Vuichard, N., Wang, Y., and Zaehle, S. and the NMIP2 contributors: Global net cooling effects of anthropogenic reactive nitrogen: the unneglectable roles of short-lived nitrogen components, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10246, https://doi.org/10.5194/egusphere-egu25-10246, 2025.

Concentrated animal feeding operations (CAFOs) are emission hotspots of ammonia (NH₃). The NH₃ emitted from these hotspots can be locally recaptured by the surrounding vegetation, mainly due to dry deposition. This deposition can either have beneficial fertilizing effects for N-limited ecosystems or pose adverse impacts on sensitive ecosystems. However, there is a lack of direct measurements of NH₃ deposition near hotspots. We conducted two field campaigns to investigate the landscape NH₃ fluxes over the barley (winter), lentil (winter), and fallow (summer) fields adjacent to an intensive beef cattle feedlot in southeast Australia. The flux measurements were segregated into periods when the measurement location was upwind of the feedlot or downwind. Upwind of the feedlot, we observed upward fluxes (surface emissions) over the fallow and barley sites with daily means (± standard error) of 0.16 ± 0.02 and 0.007 ± 0.012 μg NH₃ m^-2 s^-1, and downward fluxes (deposition) over the lentil site with a daily mean of -0.022 ± 0.007 μg NH₃ m^-2 s^-1. These measurements indicated the NH₃ compensation point for barley was approximately 6.2 μg m^-3 (equivalent to the background atmospheric NH₃ concentration), and the NH₃ compensation point for lentils was lower than 3.4 μg m^-3. Downwind of the feedlot, we observed downward fluxes at all sites with daily means of -0.57 ± 0.09 μg NH₃ m^-2 s^-1 for the barley site, -1.26 ± 0.17 μg NH₃ m^-2 s^-1 for the lentil site, and -0.58 ± 0.12 μg NH₃ m^-2 s^-1 for the fallow site; the mean deposition velocities over the barley, lentil, and fallow sites were 0.74, 0.82 and 0.78 cm s^-1. Based on the frequency of upwind and downwind periods, we estimate that the accumulated N inputs to the barley, lentil and fallow fields during each campaign were 4.5, 14.8 and 4.3 kg N ha^-1, indicating that the deposition of NH₃ emitted from the feedlot serves as a significant source of N input to its adjacent fields. Our study can provide valuable information on NH₃ exchange between vegetation and atmosphere, and extend our understanding of the fate of NH₃ emitted from hotspots.

How to cite: Wang, Q., Flesch, T. K., and Chen, D.: Landscape fluxes and dry deposition velocity of ammonia near a cattle feedlot using flux gradient approach, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10603, https://doi.org/10.5194/egusphere-egu25-10603, 2025.

The German standard VDI 3782-5 "Deposition Parameters" (German/English, www.vdi.de) provides deposition velocities and washout rates for various gaseous substances and particles. It is applied in local and mesoscale dispersion modelling, for example in the context of the German regulation on Air Quality Control (TA Luft). The current version of the standard dates from 2006. It is based on findings from a limited number of studies that led to the implementation of relatively simple descriptions and only rough estimates of atmospheric nitrogen deposition. The standard is currently undergoing a rigorous scientific revision by the authors on behalf of the VDI.

The updated standard will specify, among others, a model for the calculation of surface resistances, including compensation points for NH₃. The model is based on DEPAC (RIVM, Netherlands) and implemented in Java program (JDepac). JDepac allows parameter variations and time series calculations. Input parameters include date and time, geographical location, land use, meteorological data and, for NH₃, information on current and past loads. Default options are provided for missing input. Output quantities are, among others, resistances, deposition velocities, and deposition fluxes of NH₃, NO, NO₂, HNO₃, SO₂, O₃, Hg and particles.

JDepac is compared to various deposition measurements and results from mesoscale models. For NH₃, effects of the compensation point on the resulting deposition velocities are investigated. JDepac is used to calculate temporal averages of deposition velocities for different land use classes. In combination with dispersion calculations, effective deposition velocities are derived from the calculated deposition fluxes and concentrations. These simpler parameters are straightforward to apply in local dispersion modelling. JDepac itself allows more sophisticated calculations and can be coupled to dispersion and chemical transport models.

The updated standard VDI 3782-5 and its OpenSource tool JDepac are intended to serve as a state-of-the art, practical, and transparent reference for both local and mesoscale calculations of nitrogen deposition. In addition, the standard contains descriptions for the calculation of deposition velocities and washout rates of particles, the calculation of deposition probabilities for Lagrangian particle models, and the effects of drop displacement in wet deposition.

The updated standard is expected to serve as a useful tool for example in the decision process of facility planning and its licensing procedure conducted by local authorities, which is especially critical for the impact assessment on ecosystems under the EU Habitats Directive. In addition, the updated standard is expected to support the harmonization of air pollution modelling within the implementation of the new (2024) EU Ambient Air Quality Directive.

How to cite: Janicke, U., Banzhaf, S., Brümmer, C., Gauger, T., Krämerkämper, T., Lorentz, H., Maßmeyer, K., Mohr, K., Moravek, A., Müller, W. J., Namyslo, J., Nickel, J., Prüeß, A., Rihm, B., Schaap, M., Schmitz, A., Tilgner, A., and Trukenmüller, A.: Standardization of a resistance model for the calculation of nitrogen deposition in the updated German standard VDI 3782-5, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11361, https://doi.org/10.5194/egusphere-egu25-11361, 2025.

N₂O is a potent greenhouse gas, with ~300 times the warming potential of carbon dioxide.  The current trajectory for N₂O emissions follows the highest warming RCP8.5 scenario, with agriculture accounting for ~70% of global emissions.  As demand for food and livestock feed is expected to increase, mitigation measures which reduce agricultural N₂O emissions and simultaneously increase nitrogen use efficiency (NUE) are urgently required to limit warming below the 2°C target set by the Paris Agreement.

The promotion of biological nitrogen fixation (BNF) in crop and forage systems via the incorporation of legumes has been advocated as a N₂O mitigation strategy because it reduces synthetic N fertiliser application and increases NUE.  However, novel strategies suggest that in addition to BNF, manipulation of the soil microbiota could hold the key to N₂O mitigation.  Soybean studies have successfully identified strains of symbiotic N-fixing rhizobia which can reduce N₂O because they possess the gene encoding for nitrous oxide reductase (nosZ).  The potential of N₂O-reducing (NosZ+) rhizobia inoculums could therefore be critical to agricultural N₂O emission mitigation; however, few studies have explored other legume-rhizobia associations for NosZ+ strains.  Most notable is the complete lack of research on permanent grassland ecosystems, which cover 40% of global land surface and account for 54% of global N₂O emissions.

This study aims to investigate the potential of clover-rhizobia associations to mitigate N₂O emissions from UK grasslands and herbal leys under intercropping systems.  Soils from five different land uses were sampled from FarmED (agroecology demonstration farm) and Pudlicote Farm in the Cotswolds, UK: unfertilised permanent pasture, unfertilised clover/grass sward, herbal ley (1^st and 5^th year) and conventionally farmed winter wheat.  Native rhizobia present in the soil samples were selected by the growth and nodulation of Red Clover (Trifolium pratense) plants.  Rhizobia extracted from the harvested root nodules were cultured on yeast mannitol agar to isolate individual strains.  Strains then underwent gDNA extraction and whole-genome sequencing using the Illumina NovoSeq X platform to determine the presence of the nosZ gene.  Biogeochemical analysis of the soils was related to the presence/absence of the nosZ gene to infer potential genotype environmental controls.

Finally, identified NosZ+ strains will undergo a phenotype assessment using a soil-plant-atmosphere mesocosm experiment, whereby N₂O emissions from clover plants inoculated with NosZ+ strains will be monitored. Control strains; Rhizobium leguminosarum bv.trifolii T117 (nosZ+) and T132 (nosZ-) were obtained from the MIAE collection (INRAE, France) and will be tested alongside Bradyrhizobium diazoefficiens G49 (nosZ+) (soybean specific strain) and the identified native strains. The overall aim of the study is to create a rhizobia inoculum able to reduce N₂O emissions when included in the intercropping sequence of leys and pastures, thus contributing to Net Zero global strategies.

How to cite: Weir, K., Williamson, C., Williams, T., and Sgouridis, F.: Rhizobia inoculation to mitigate nitrous oxide (N2O) emissions from UK grasslands and herbal leys under intercropping systems., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11640, https://doi.org/10.5194/egusphere-egu25-11640, 2025.

Pollen is a critical component of the nitrogen (N) cycle in forests, but its role in N uptake, release and transformation during precipitation events remains poorly understood, contributing to uncertainties in N deposition estimates. In the frame of the COST Action CLEANFOREST a laboratory experiment was conducted to assess the biochemical activity of tree pollen and its effects on N compounds in precipitation. Pollen from green alder (Alnus viridis), pedunculate oak (Quercus robur), European beech (Fagus sylvatica), silver birch (Betula pendula), Scots pine (Pinus sylvestris) and Norway spruce (Picea abies) was suspended in a synthetic nitrate (NO₃^-) solution isotopically labelled with ¹⁵N under non-sterilized conditions and two sterilization treatments: addition of (i) thymol and (ii) a broad-spectrum antibiotic mixture (PSA) containing penicillin, streptomycin, and amphotericin B. Over one week, water samples were analysed daily for NO₃^-, nitrite (NO₂^-), ammonium (NH₄⁺) and total dissolved nitrogen (TDN) from which dissolved organic nitrogen (DON) was calculated. The results showed significant NO₃^- removal from the solution in broadleaved species, particularly oak, beech, and alder, in all treatments, but most clearly in the non-sterilized treatment. Most species showed a significant decrease in DON during the first two-three days, in all treatments, but especially in the sterilized (PSA) treatment, which was subsequently converted into NH₄⁺ (mineralization). The use of ¹⁵N as a tracer clearly shows that the labelled N was actively taken up by the pollen in both the non-sterilized and PSA-treated samples. Notably, pollen from all tree species, predominantly the broadleaves, enzymatically transformed extracellular NO₃^- into NO₂^-, highlighting its active role in the N cycle. These findings offer valuable insights into N release, uptake, and transformation during precipitation events and reveal important interactions between pollen and microorganisms. The differences observed between sterilized and non-sterilized treatments underline the significant influence of microbial activity on N conversion. By expanding our understanding of canopy-level N processes, this research contributes to improving N deposition models and introduces innovative approaches to studying the forest N cycle. Further studies are essential to clarify the mechanisms by which pollen and microbial communities influence N transformations at ecosystem scales.

Keywords: Broadleaves; Conifers; Pollen; ¹⁵N; Ammonium; Nitrate; Nitrite

How to cite: Limić, I., Bodé, S., Boeckx, P., Bauters, M., Neirynck, J., Bruffaerts, N., Marković, S., Gottardini, E., and Verstraeten, A.: The role of tree pollen in forest nitrogen cycling: A laboratory perspective, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11830, https://doi.org/10.5194/egusphere-egu25-11830, 2025.

Global changes caused by anthropogenic activities are altering the cycling of nitrogen (N) in terrestrial ecosystems. For example, droughts of increasing frequency and severity can stimulate large emission pulses of nitrous oxide (N₂O; a powerful greenhouse gas) when dry soils wet up. Further, increased fire frequency can favor the colonization of novel pyrophilous or “fire-loving” fungi on soils with the capacity to produce N₂O, yet N₂O isotopic ranges have been characterized in few fungal species, making generalizations difficult. To better understand how global changes are altering the N cycle, we studied drylands in southern California that can experience >6 months without rain, burned experimental “pyrocosms” to assess impacts of fire severity on soil biogeochemistry, and used a culture collection of pyrophilous fungi isolated from wildfire-burned soils to characterize their δ¹⁵N₂O_bulk,δN₂¹⁸O_bulk, and δ¹⁵N₂O_SP values. Despite the hot and dry conditions known to hinder denitrification, isotope tracers and natural abundance isotopologues of N₂O indicated NO₃^- was reduced within 15 minutes of wetting dry desert soils and that N₂O reduction to N₂ occurred. In post-fire environments, we found that while N₂O isotope values for Neurospora discreta and Fusarium tricinctum closely matched literature values when grown with NO₂^-, Aspergillus fumigatus, Coniochaeta hoffmannii, Holtermaniella festucosa, and R. columbienses did not. Further, Fusarium sp. δ¹⁵N₂O_bulk and δN₂¹⁸O_bulk values fell outside literature-derived values when grown with NO₃^-. Overall, we find that despite the hot and dry conditions known to make denitrification thermodynamically unfavorable in many drylands, denitrifiers can endure through hot and dry summers and are key to producing the surprisingly large N₂O emissions when dry desert soils wet up. Further, we find that novel pyrophilous fungi present an opportunity to further characterize the isotopic composition of N₂O as well as the factors controlling fungal denitrification as ecosystems are impacted by global changes.

How to cite: Homyak, P.: Drought, wildfires, and “fire-loving” fungi effects on ecosystem nitrogen cycling: Understanding global change effects on denitrification using N2O isotopologues, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12451, https://doi.org/10.5194/egusphere-egu25-12451, 2025.

Human activities such as fertilization of agricultural lands and human-induced biomass burning strongly impact nitrogen (N) dynamics and losses, with many consequences on the environment. The quantification of N budgets (N inputs and outputs) between the surface and the atmosphere is a prerequisite to understand the N biogeochemical cycle, i.e. how N is transferred from the atmosphere to the biosphere, through the soil and back to the atmosphere from surface emissions. Sub Saharan Africa (SSA) is characterized by an increase in demography, with strong impacts on biodiversity, and on the sustainability of human activities including agriculture. In Africa, the increase in demography and the associated increased fertilizer inputs (to supply growing food and energy demands) will lead to increased emissions from amended soils, which will in turn increase atmospheric N deposition and induce feedbacks to the ecosystems and the atmosphere.

In this context, the NitroAfrica project (2023-2026) is designed to study the impact of N wet deposition on the soil – plant – atmosphere continuum. We make the hypothesis that changes of wet N deposition in West African ecosystems over the 21^th centuries will induce important changes in biogenic emissions from the ecosystems to the atmosphere with impacts on regional atmospheric chemistry and further N deposition. Indeed, increasing trends of N wet deposition has already been observed, especially in the NH₄⁺ form. Three ecoclimatic zones in West Africa are studied, in Guinean (Lamto, Côte d’Ivoire), Sudanese (Korhogo, Côte d’Ivoire) and Sahelian (Dahra, Senegal) zones, where solutions with different NH₄⁺/NO₃^- partition are used to mimic the increase in N wet deposition.

Results on N (N₂O, NO) and CO₂ emissions from soils from plots amended with solutions as well as control plots will be presented. N wet deposition fluxes from recent years will also be presented within the context of existing long-term studies on N wet deposition. This comparison is particularly relevant for the Lamto station where the International Network to study Deposition and Atmospheric chemistry in Africa (INDAAF) is based and provides long-term data since 1995.

This study contributes to fill in the lack of studies in SSA, and to understand the processes involved in N emissions and deposition in tropical regions.

How to cite: Delon, C., Galy-Lacaux, C., Serça, D., Ossohou, M., Zouré, M., Barot, S., Le Roux, X., Ndiaye, O., Siélé, S., Kouassi, A., Gardrat, E., Dias-Alves, M., and Lenoir, O.: Impact of wet nitrogen deposition on soil nitrogen emissions in West African ecosystems, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12860, https://doi.org/10.5194/egusphere-egu25-12860, 2025.

High nitrogen (N) input in intensive cropping systems has resulted in significant nitrate (NO₃⁻) accumulation in agricultural soils of China. However, despite substantial N input (500-600 kg ha-1 y-1) in the Taihu Lake region, NO₃⁻ accumulation in soils and groundwater therein remains minimal with the mechanisms behind are unclear. Here, we investigated the spatiotemporal distribution and activity of dissimilatory nitrate reduction to ammonium (DNRA), anaerobic ammonium oxidation (anammox), and denitrification, and the associated microbial communities—in the vadose zones of rice-wheat, vegetable, and orchard fields of the Taihu Lake region. Results revealed NO₃⁻ content decreased progressively with soil depth, while NH₄⁺ levels increased, particularly in deeper soil layers. DNRA emerged as the primary pathway for NO₃⁻ reduction, contributing to over 50% of NO₃⁻ removal, especially in the 50–190 cm depth range. Seasonal variations indicated that DNRA activity was highest during spring and autumn, with lower rates observed in winter and summer. DNRA significantly contributed to NH₄⁺ accumulation, with rates strongly positively correlated with NH₄⁺ content, especially in rice-wheat rotation fields characterized by high OC/ NO₃⁻ ratios. Interestingly, DNRA rates were significantly negatively correlated with groundwater N₂O concentrations and the N₂O/(N₂ + N₂O) ratios. Microbial community analysis revealed that the nrfA gene, a marker for DNRA, exhibited higher diversity compared to genes related to denitrification. Additionally, the abundance of DNRA-specialist microbes was positively associated with DNRA rates, particularly in deep layer soils, emphasizing the role of microbial community composition in shaping DNRA activity. These findings demonstrate that DNRA plays a crucial role in facilitating NH₄⁺ accumulation, attenuating NO₃⁻ accumulation, and mitigating N₂O emission in the vadose zone of agricultural croplands in the Taihu Lake region.

How to cite: Shan, J., Wang, X., and Yan, X.: Hotspots and hot moments of DNRA in the Vadose Zone of Agricultural Croplands , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14072, https://doi.org/10.5194/egusphere-egu25-14072, 2025.

Increasing the grassland proportion in the crop rotation has been considered as an effective approach to sequester carbon (C) in the soil. However, its climate mitigation benefits may be overestimated because the associated impact of long-term C sequestration on nitrous oxide (N₂O) emissions remains uncertain. Mechanistic models, such as the DeNitrification and DeComposition model (DNDC v. CAN 9.5.0), are used to simulate changes in soil organic carbon (SOC) and N₂O emissions. This provides the opportunity to estimate future emission trends and to enhance our understanding of the interactions between SOC and N₂O emissions under different levels of grass/clover proportion in arable crop rotations. We hypothesize that increases in N₂O emissions will offset the benefits from the increased SOC over time. The objectives of this study are to (1) calibrate and validate the DNDC model, and (2) estimate and predict the potential tipping point at which the negative climate forcing of N₂O emissions offsets the benefits of C sequestration over long-term timescales. For this, we used long-term measurements of biomass, SOC, and N₂O emissions from two crop rotations with either two or four years of grass-clover in a six-year rotation in Denmark. Preliminary results showed that the DNDC model simulated crop biomass production with fair to high accuracy as indicated by an index of agreement (d) of 0.98, a Nash-Sutcliffe efficiency (NSE) of 1, and a normalized root mean square error (nRMSE) of less than 30%. The simulated biomass was slightly underestimated as shown by a negative mean bias error (MBE). Conversely, the simulations for N₂O fluxes and SOC exhibited poorer agreement, with d-values below 0.7 and nRMSE exceeding 30%. These findings suggest that while the DNDC model effectively predicts crop growth, including annual crops and grass/clover ley, its ability to simulate SOC and N₂O fluxes requires substantial improvement. Our future efforts will focus on refining and optimizing model parameters for SOC and N₂O, with an emphasis on calibration to enhance the model performance and the capacity to predict management-induced long-term dynamics under future climate scenarios. Results of these updated model simulations will be shown at the conference.

How to cite: Kong, M., Liu, H., Abalos, D., Grant, B. B., Smith, W. N., Zhartybayeva, A., Jensen, J. L., Eriksen, J., and Dold, C.: Estimating the Tipping Point between N2O Emissions and C Sequestration in Soil using the DNDC v. CAN Model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14338, https://doi.org/10.5194/egusphere-egu25-14338, 2025.

Atmospheric nitrogen (N) deposition is a significant driver of global change and disrupts the carbon and nitrogen cycles in ecosystems. Volatile Organic Compounds (VOCs) emitted by plants play an important role in regional air quality and the carbon cycle. This study investigates the effects of different forms and doses of N deposition on Biogenic Volatile Organic Compounds (BVOCs) emissions, photosynthesis, growth, and non-structural carbohydrate (NSC) accumulation in the widespread subtropical bamboo species-Moso bamboo (Phyllostachys edulis). A pot experiment was conducted with three N doses: 100 kg(N)·hm⁻²·a⁻¹ (L1), 200 kg(N)·hm⁻²·a⁻¹ (L2), and 0 kg(N)·hm⁻²·a⁻¹ (L0), using ammonium N (AN), nitrate N (NN), and a mixed N form (AN+NN). Dynamic headspace sampling was used to assess the effects of N deposition on BVOC emissions and the relationships between N deposition, photosynthesis, plant growth, and NSC distribution throughout the growing season.

The results indicated that N deposition increased BVOC emissions, with the highest emissions occurring under NN treatment at L1 during March and June. Isoprene (ISO) emissions were significantly enhanced under AN treatment, with L2 doses increasing ISO emissions by 99.20% compared to L1. The AN+NN treatment resulted in higher ISO emissions at L2, with increases of 76.02% and 141.69% compared to AN and NN alone, respectively. N form and dose also influenced photosynthetic pigments, with the highest total chlorophyll content observed under AN+NN at L1. Photosynthetic parameters, including net photosynthetic rate (Pn), stomatal conductance (Gs), and carboxylation efficiency (CE), were significantly higher under L1 compared to L0. A positive correlation was found between chlorophyll content and VOC emissions, with Pn, Gs, and CE strongly correlating with ISO emissions. Growth responses varied by N form. AN+NN treatment significantly promoted the growth of Phyllostachys edulis, particularly in above-ground biomass, while AN inhibited root and whip growth. Biomass of leaves and culms was significantly higher under L1 treatment, with increases of 85.60% and 38.14%, respectively, compared to L0 under AN treatment. Soluble sugar content in leaves, culms, and roots was highest at L1, with decreases observed as the N dose increased. Soluble sugars in leaves, culms, and buds increased by 24.85%, 24.92%, and 21.20% under L1 compared to L0. Starch content in leaves and culms increased initially but declined under higher N doses. AN and NN treatments at L2 reduced starch content in leaves and culms, with significant reductions observed in both N forms.

NSC content was positively correlated with ISO emissions, especially for soluble sugars. Total NSC content and soluble sugars were also positively correlated with BVOC emissions, suggesting that NSCs play a key role in plant responses to environmental stress. In conclusion, N deposition—particularly in mixed forms (AN+NN)—enhances BVOC emissions, especially ISO emissions, promotes biomass accumulation, and improves photosynthetic capacity. Lower N doses support higher ISO emissions and NSC accumulation. This study highlights that appropriate levels of N deposition can support bamboo growth and improve resilience to atmospheric changes.

How to cite: Li, L., Jiang, M., and Wang, X.: Effects of nitrogen deposition on VOCs emission and its relationship with photosynthesis, growth, accumulation and distribution of NSC in Moso bamboo tree (Phyllostachys edulis) , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14982, https://doi.org/10.5194/egusphere-egu25-14982, 2025.

Advances in manufacturing and trade have reshaped global nitrogen deposition patterns, yet their dynamics and drivers remain unclear. Here, we compile a comprehensive global nitrogen deposition database spanning 1977–2021, aggregating 52,671 site-years of data from observation networks and published articles. This database show that global nitrogen deposition to land is 92.7 Tg N in 2020. Total nitrogen deposition increases initially, stabilizing after peaking in 2015. Developing countries at low and middle latitudes emerge as new hotspots. The gross domestic product per capita is found to be highly and non-linearly correlated with global nitrogen depositiondynamic evolution, and reduced nitrogen deposition peaks higher and earlier than oxidized nitrogen deposition. Our findings underscore the need for policies that align agricultural and industrial progress to facilitate the peak shift or reduction of nitrogen deposition in developing countries and to strengthen measures to address NH₃ emission hotspots in developed countries.

How to cite: Zhu, J., Yu, G., and Wang, Q.: Changing patterns of global nitrogen deposition driven by socio-economic development, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15249, https://doi.org/10.5194/egusphere-egu25-15249, 2025.

Cover crops are recognized as a climate-smart agricultural practice that increases soil organic carbon content (SOC). As carbon (C) and nitrogen (N) cycles are coupled, an increase in SOC can impact the N cycle and nitrous oxide (N₂O) emissions. Another major driver affecting N cycling and N₂O emissions is soil moisture. With the increasing risk of summer droughts and wetter conditions during the off-season in Northern Europe, it is important to understand how drying-wetting and agricultural practices together affect N cycling and N₂O emissions.

To address this knowledge gap, we conducted a pot experiment with clay soil in controlled greenhouse conditions simulating summer drought with bare soil pots and oats sown either alone, with Italian ryegrass, or with alfalfa as plant treatments. The pots were initially watered to 70% degree of saturation to ensure that the plants start to grow, after which half the pots were let dry to 40% degree of saturation. The plants were grown for 36 days. At the end of the growth period, soil N₂O emissions were measured over three days. Following this, the pots were sampled destructively, and total N in plants, roots, and soil, as well as mineral N in soil, were analysed. Additionally, a follow-up pool-dilution incubation experiment using ¹⁵N-labelling with bare soil and soil previously covered with oats was conducted to study the effect of moisture content and rewetting on gross N transformation rates.

Contrary to our expectations, the results from the pot experiment showed that N₂O emissions in the plant treatments were higher in drought conditions than in moist conditions. This does not support our results from a cover crop field trial where reduced rainfall did not affect N₂O emissions during the growing season. However, during off-season reduced rainfall in the field led to higher N₂O emissions. Preliminary results from the incubation indicated lower N₂O emissions under drought conditions, with increased emissions upon rewetting and the highest emissions under moist conditions. The presence of plants decreased soil N₂O emissions in both experiments, but the plant species did not affect the emissions nor the total mineral N content in soil. As expected, in the pot experiment, total mineral N content in soil was higher in drought conditions than in moist soil as well as in bare soil compared with soil with growing plants. Results on the effects of drought and plants on gross N transformations during the incubation experiment with ¹⁵N labelling will be presented later.

How to cite: Turunen, P., Viinikainen, A., Koskinen, M., Simojoki, A., Karhu, K., and Pihlatie, M.: The effect of drought and rewetting on nitrogen cycling and nitrous oxide emissions in a controlled experiment with different cover crop species, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15354, https://doi.org/10.5194/egusphere-egu25-15354, 2025.

Nitric oxide (NO) and nitrous acid (HONO) are important reactive atmospheric trace gases. As part of the nitrogen (N) cycle, ammonia oxidizing nitrifiers in soils are recognized as key producers of these gases, impacting near-surface nitrogen oxide (NO_x = NO + NO₂) and ozone (O₃) concentrations. The nitrification process results in the production of nitrite (NO₂^-), subsequently protonated in the liquid phase to form HONO, and NO, which are both emitted as gases. However, there is limited understanding of the coupled processes causing the simultaneous emission NO and HONO from drying soils incorporating ammonia oxidizing nitrifiers. Here, we combined experimental in-vitro studies of ammonia-oxidizing bacteria with a mechanistic modelling approach to investigate the mechanisms triggering gaseous NO and HONO emissions. We found out that several abiotic processes, such as NO auto-oxidation, Fe²⁺ catalysis, and soil moisture dynamics crucially influence the overall emission as well as the partitioning of reactive N. This, in turn, impacts the hydroxyl radical (OH) budget and soil N retention. Modelling allowed us to elucidate the interactions between biological and environmental processes under varying soil hydration conditions for different field scenarios, such as the effects of fertilization. This analysis suggests potential strategies for effectively managing the release of soil-derived NO_x and OH emissions.

How to cite: Weber, B., Maier, S., Weber, J., Leiva, D., Zhou, M., Qian, X., Pöschl, U., Cheng, Y., Su, H., and Kim, M.: Mechanisms of soil emissions of NO and HONO produced by ammonia-oxidizing bacteria during drying, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15383, https://doi.org/10.5194/egusphere-egu25-15383, 2025.

The use of cover crops in agriculture is one of the climate-smart practices that have multiple benefits, such as increasing SOC, reducing N losses, and increasing biodiversity. Still the question whether cover crops and their diversity increase resilience against drought, and how the combined effects of cover crops, their diversity and drought affect N₂O emissions, remain largely unknown. We study the combined effects of cover crop diversity and drought on cropland (oat) greenhouse gas emissions and belowground C and N processes in a field plot trial. The effect of drought on soil and crop C and N dynamics and greenhouse gas (CO₂, N₂O) emissions is studied with rainout shelters that remove 50% of incoming precipitation. The CO₂ and N₂O emissions are measured with the manual dark chamber method twice a week during the growing season and once a week during off-season, soil temperature and water content are measured continuously, and soil is sampled for mineral N and total C and N analysis seasonally.

The preliminary results show that reduced rainfall decreases CO₂ emissions but does not affect N₂O emissions significantly during the growing season. During off-season, reduced rainfall increases both CO₂, and particularly N₂O emissions irrespective of cover crop diversity treatments. During growing season there is a tendency of higher N₂O emissions from diverse cover crop treatments compared to oat only treatment, and during off-season, a higher cover crop diversity significantly increases N₂O emissions. Overall and in all treatments, off-season N₂O emissions dominate the annual N₂O balance. Our results highlight the need to include off-season measurements to the annual N₂O balance estimation, and when assessing the effects of cover crops and future climate change scenarios such as summer drought on annual N₂O emissions.

How to cite: Pihlatie, M., Turunen, P., Koskinen, M., Simojoki, A., Viinikainen, A., Virta, O., and Heinonsalo, J.: Cover crop diversity and summer drought increase off-season N2O emissions from Finnish agricultural soil , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15466, https://doi.org/10.5194/egusphere-egu25-15466, 2025.

Human activities have globally increased atmospheric nitrogen (N) deposition, which has enhanced the risk of ecosystem N losses. Phosphorus (P), as a macroelement required for life, is closely linked to the biogeochemical cycle of N. Therefore, quantifying how soil N cycle responds to different P supply levels is important. Here we examined the responses of soil N dynamics to altered P supply using a P addition experiment (+0, +25, +50, +100 kg P ha⁻¹ yr⁻¹) in an evergreen broadleaf mixed plantation in subtropical China. We found that P addition led to a more open soil N cycle in the forest ecosystem. The primary source of N₂O emissions in the study plots was fungal denitrification, which accounted for 41%-52% of the total N₂O emissions, based on δ¹⁸O-N₂O, δ¹⁵N^α-N₂O, δ¹⁵N^bulk-N₂O and SP measurements. Nitrogen loss by gas or water and N assimilation by plants were found to be coupled processes at +25 kg P ha⁻¹ yr⁻¹ addition level. The δ¹⁵N-NO₃⁻ and δ¹⁸O-NO₃⁻ values in runoff and leaching water from different depths were all depleted from −10‰ to +0‰ in the wet season. This result indicates that soil N has a short residence time and rapid NO₃⁻-N loss in the forest ecosystem, and with fewer nitrogen conversions according to the isotope fractionation theory. These observed varied responses of soil N transformation, gaseous loss, and liquid loss to different P supply levels provide new insights into our understanding of N-P relationships in broadleaf forest plantations.

How to cite: Ye, H., Lin, H., Ibrahim, M. M., Chen, L., Liu, Y., Bol, R., and Hou, E.: Phosphorus addition impacts on soil nitrogen dynamics in a subtropical plantation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16227, https://doi.org/10.5194/egusphere-egu25-16227, 2025.

Temperature and oxygen content in soil are the well-known drivers of macronutrient cycling, as they influence the overall conditions that regulate microbial metabolism. However, the more detailed underlying aspects affecting nutrient cycling remain insufficiently understood.

This study focuses on different wetland forest types across Europe, aiming to investigate N cycling processes, the spatial distribution of N cycling genes and the linkage with soil greenhouse gas (GHG) emissions and relevant environmental parameters. The study sites were located in Finland, Estonia, and Latvia in Northern Europe, as well as in France and Spain in Southern Europe. The Northern Europe sites consisted of drained peatlands with varying management statuses, while the Southern Europe ones were alluvial forests. Soil samples were collected from three depths (0-10, 10-20, 20-40 cm) in autumn 2023, analysed using quantitative polymerase chain reaction (qPCR), and sequenced to assess processes and communities. In all samples, soil physico-chemical parameters were also determined and simultaneously with soil sampling, in-situ GHG emission measurements were done all as a part of Horizon Europe ALFAwetlands project.  

Preliminary results of the quantification of N cycle genes revealed differences in the microbiome across wetland forest types in Europe. Ammonia-oxidizing archaea appeared to be the primary nitrifiers in the soils of the study sites, compared to ammonia-oxidizing bacteria. The alluvial forest soils revealed a higher genetic potential for the DNRA (Dissimilatory Nitrate Reduction to Ammonium) process in soil. The abundance of genes responsible for the comammox process—complete ammonia oxidation by a single microorganism—was also higher in the soils of the alluvial forests. In the rewetted peatland forest of Latvia, the soil exhibited a greater genetic potential for denitrification and DNRA processes compared to the drained peatland forests. The further analyses will be exploring the links between N cycle genes, GHG emissions, and soil physico-chemical properties.

How to cite: Kuusemets, L., Soosaar, K., Öpik, M., Aurela, M., Butlers, A., Escarmena, L., Jauhiainen, J., Juutinen, S., Kanaan, R., Larmola, T., Lazdiņš, A., Mander, Ü., Sánchez Pérez, J. M., Poblador, S., Sabater, F., Sauvage, S., Schindler, T., Ukonmaanaho, L., and Espenberg, M.: Microbial nitrogen cycling in wetland forests with varying management statuses across Europe, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17098, https://doi.org/10.5194/egusphere-egu25-17098, 2025.

We present a new Horizon Europe project titled GreenEO (2025-2029) as well as findings based on advances in modelling within the Nordic Nature & Nitrogen (Nordic Council of Ministers, 2021-2024) and the SEEDS (Horizon 2020, 2021-2023) projects. The ambition of GreenEO is to support governance approaches for the implementation of EU’s Green Deal. The implementation of which will rely on accessible, actionable environmental data for policymaking and monitoring. Success will be dependent on the usage of the latest observational data as well as on the level of uptake of these data by end-users. GreenEO addresses this by using observations from the Sentinel and newest meteorological (MTG and Metop-SG) satellites, and through co-creation with users of high-resolution services and novel indicators to directly meet user needs.

GreenEO will specifically address the environmental impacts of nitrogen deposition and advance the state of knowledge on this topic within the context of supporting the EU’s Green Deal and its ambition for protecting biodiversity.

Current data on nitrogen emissions, deposition, and biodiversity impacts are inconsistent and lack sufficient spatial resolution. GreenEO will therefore try to advance the state of knowledge in three areas:

• Using advanced satellite data, data assimilation, modeling, and ancillary data, GreenEO will estimate high-resolution nitrogen emissions (NH3, NOx). These high-resolution emissions will then be used in turn as a basis for modelling downstream impacts.
• GreenEO will advance the state of the art for nitrogen deposition modelling using findings from previous projects (Nordic Nature & Nitrogen and SEEDS projects). A bi-directional flux parameterization (Wichink-Kruit et al., 2012) was added to three regional scale air quality models (DEHM, MATCH, and EMEP) within the Nordic Nature and Nitrogen project. The findings were that this approach did not lead to consistent improvements in ambient concentration and flux modelling without commensurate improvements in land cover and vegetation data. For instance, bi-directional fluxes were shown to be highly sensitive to leaf area index (LAI) due to the dominating pathway being through external leaf water. Work within the SEEDS project to derive improved estimates of LAI by combining satellite observations of LAI in a land surface model using data assimilation, will serve as a basis for improving estimates of the bi-directional depositional fluxes of reactive nitrogen.

• GreenEO will combine these methods and data with regional scale air quality models (DEHM and EMEP) in order to model the distribution of nitrogen deposition with high accuracy. Specific attention will be paid to deposition within vulnerable habitats. Via this approach, GreenEO will improve the estimation of nitrogen deposition and critical load exceedances in vulnerable ecosystems. Collaborating with stakeholders, we will link these outputs to biodiversity indicators, like plant species richness and butterfly indices, to create a nitrogen sensitivity index. This will identify high-recovery areas and support sustainable agricultural practices.

Wichink Kruit, R. J., Schaap, M., Sauter, F. J., van Zanten, M. C., and van Pul, W. A. J.: Modeling the distribution of ammonia across Europe including bi-directional surface-atmosphere exchange, Biogeosciences, 9, 5261–5277, https://doi.org/10.5194/bg-9-5261-2012, 2012.

How to cite: Hamer, P., Frohn, L. M., Geels, C., Christensen, J., Denby, B. R., Simpson, D., Hutchings, N., Lopez-Aparicio, S., Schneider, P., Cao, T.-V., Jiminez, I., Fontenelle, T., van der A, R., Mijling, B., Ding, J., Trigo, I., Calvet, J.-C., Schante, J., Judes, T., and Tarrason, L. and the GreenEO Consortium: The GreenEO Project: Satellite-Based Services to Support Sustainable Land Use Practices Under the European Green Deal, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17316, https://doi.org/10.5194/egusphere-egu25-17316, 2025.

Soil microbial nitrous acid (HONO) production is an important source of atmospheric reactive nitrogen that affects air quality and climate. However, long-term global soil HONO emissions driven by climate change and fertilizer use have not been quantified. Here, we derive the global soil HONO emissions over the past four decades and evaluate their impacts on ozone (O₃) and vegetation. Results show that climate change and the increased fertilizer use enhanced soil HONO emissions from 9.4 Tg N in 1980 to 11.5 Tg N in 2016.  Chemistry-climate model simulations show that soil HONO emissions increased global surface O₃ mixing ratios by 2.5% (up to 29%) and vegetation risk to O₃, with increasing impact during 1980s-2016 in low-anthropogenic-emission regions. With future decreasing anthropogenic emissions, the soil HONO impact on air quality and vegetation is expected to increase. We thus recommend consideration of soil HONO emissions in strategies for mitigating global air pollution.

How to cite: Wang, Y., Li, Q., Treb, I., Wang, Y., Ren, C., Saiz-Lopez, A., Xue, L., and Wang, T.: Increasing soil nitrous acid emissions driven by climate and fertilization change aggravate global ozone pollution, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17830, https://doi.org/10.5194/egusphere-egu25-17830, 2025.

Reactive nitrogen (N) deposition presents significant environmental challenges in India, where approximately 24% of the land is forested and agriculture plays a vital role in the economy. As a major contributor from South Asia—a global reactive nitrogen emissions hotspot—India's policy actions, or inactions, have far-reaching implications. Despite ongoing clean air initiatives, the scientific community has largely neglected the effects of reactive nitrogen deposition on terrestrial ecosystems. This study aims to compile and assess the current research status on reactive nitrogen deposition in India, underscoring its importance given the country's unique geography and agricultural reliance.

The study will provide indirect estimations of reactive nitrogen deposition based on nitrogen concentration measurements from various regions across the country. While wet deposition studies offer a broader understanding, research on dry deposition remains limited. Recent efforts, such as the South Asia Nitrogen Hub project led by CEH UK, have studied the forest ecosystem to explore the impact of reactive nitrogen on lichens. However, comprehensive data on reactive nitrogen deposition across diverse ecosystems is still lacking.

This research seeks to identify existing gaps and stimulate discussion on future research directions essential for the effective management of reactive nitrogen in India's varied ecosystems. By addressing these issues, we aim to inform policy and practice to mitigate the adverse effects of reactive nitrogen deposition while promoting sustainable development in the region.

How to cite: Singh, S.: Reactive Nitrogen Deposition in India: Impacts on Terrestrial Ecosystems and Current Research Status, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17857, https://doi.org/10.5194/egusphere-egu25-17857, 2025.

Increased atmospheric nitrogen (N) deposition into sensitive ecosystems is leading to soil acidification, nutrient imbalances and biodiversity losses. Therefore, N depositions were quantified throughout Switzerland in 2000, 2014, 2019 and 2024 measuring the concentrations of seven different inorganic N compounds in wet and dry gravitational as well as in dry non-gravitational deposition. For data collection passive (diffusion tubes and bulk sampler) and active sampling systems (denuder and filter sampler) were used. From the obtained measurement data, N depositions were calculated. The wet and dry gravitational deposition was obtained directly from the bulk samples. The dry non-gravitational deposition was calculated using the inferential method. By summing up the gravitational and non-gravitational N deposition, the total N deposition was obtained and compared to the critical loads for N (CLN). The results show that N inputs in Switzerland are largely around or above the CLN, regardless of the sensitive ecosystems considered. Considerable exceedances have been found near intensive agriculture. In the long-term comparison, a decrease in oxidized N components was observed. However, the total N deposition remained stable over time. The most important processes for the N deposition are the precipitation and the dry deposition of ammonia (NH₃). In summary, the atmospheric N inputs into sensitive ecosystems in Switzerland are largely too high and therefore further measures to reduce N emissions are necessary.

We would like to thank to the Swiss Federal Office for the Environment (FOEN), Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Ostluft, the Swiss cantons and the University of Basel for financial support of the measurement campaigns. A special thank goes to the Swiss Federal Laboratories for Materials Science and Technology (EMPA) for the valuable cooperation.

How to cite: Meier, M., Ehrenmann, Z., and Seitler, E.: Atmospheric nitrogen deposition in Switzerland, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18103, https://doi.org/10.5194/egusphere-egu25-18103, 2025.

The modern global food system is the largest driver of nitrogen imbalances across the world. These problems are exacerbated by excessive and resource-intensive food demand prone to large amounts of loss and waste throughout the food system. Increasing international trade is shifting the burden and upstream nitrogen demand and downstream eutrophication impacts beyond national borders and moving beyond the safe regional boundaries for their presence in the environment. To better understand drivers and solutions to close nitrogen loops, we use the global food input-output model FABIO, which monitors the movement of biomass and the land utilized across global supply chains, encompassing 191 countries, and 130 agricultural and food products. We couple FABIO to nitrogen crop demand, livestock manure management systems, and agricultural surpluses to assess the consumption-based drivers for nitrogen emissions stemming from the agricultural system. A substantial amount of nitrogen losses can be attributed to traded commodities especially toward high-income nations. We further show how policy measures in a high-income nation (the Netherlands) related to the taxation of meat and carbon emissions from the food sector can lead to significant reduction of manure application (up to 20 kt N/yr) and nitrogen losses (over 1 kt N/yr) on a global scale. However, as the Dutch food system relies heavily on manure, there may be a concomitant increase in the need for synthetic fertilizers to account for the significant drop in manure of nearly (14 kt N/yr). We provide similar scenarios for various, more ambitious dietary changes (e.g. the EAT-Lancet diet) at the EU level that can help ameliorate global nitrogen losses, focusing in areas sensitive to terrestrial and aquatic eutrophication and acidification.

How to cite: Mogollón, J. M., Navarre, N., and Kevin Morgan-Rothschild, K.: Dutch and EU consumption-based assessments of nitrogen losses throughout the global food system, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18590, https://doi.org/10.5194/egusphere-egu25-18590, 2025.

Forests are integral to maintaining planetary health, serving as biodiversity reservoirs, carbon sink, and regulators of nutrient cycles, yet their capacity to sustain these functions is increasingly disrupted by global changes. Among them, the rise in atmospheric nitrogen (N) deposition, resulting from anthropogenic emissions of reactive N compounds during fertilizer production and fossil fuel combustion, occurs across terrestrial ecosystems and can alter microbial communities’ functional composition and diversity.

In this study, we evaluate the effects of long-term N fertilisation (simulating an increase in N deposition) on the taxonomic and functional diversity of soil microbial communities in a mature beech forest in Northern Italy. The experiment started in 2015, and it includes control (only ambient deposition, N0) and soil N addition (30 kg ha^-1 yr^-1, N30) each replicated in 3 plots. Soil biochemical variables including Nitrogen (N), Carbon (C) and Phosphorus (P) content and soluble ions were characterized for both treatments. In addition, GeoChip 5.0S, a microarray technology, was used to characterize the taxonomic and functional diversity of microbial communities.

Although no changes were detected in soil physicochemical characteristics between N30 and N0, there was a significant increase in the taxonomic richness and diversity (Shannon-Weiver and Simpson indices) in the fertilized plots. Moreover, the relative abundance of some functional genes related to the N, C and sulphur (S) cycles were significantly increased in N30 plots, whereas P cycling genes showed no significant changes between treatments. Preliminary results suggest a probable increase in the denitrification and assimilatory and dissimilatory nitrate reduction processes of the N-added soil microbiome. In addition, the results suggest an increase of both the C fixation and C degradation pathways in N30 plots. The higher stimulation of C degradation cycling genes in comparison to C fixation cycling genes, could be explained by the promotion of plant growth and the consequent increase in rhizosphere secretions and C input to the soil after N addition.

This study contributes to the description of microbial community dynamics and the resulting changes in soil biogeochemical processes in forests under increased N deposition conditions.

How to cite: López Sánchez, C., Ribas, À., Guerreri, R., Lei, J., Yang, Y., Zhou, J., and Mattana, S.: Effects of long-term nitrogen addition on changes in the functional composition of microbial communities after long-term N addition in a temperate beech forest, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18703, https://doi.org/10.5194/egusphere-egu25-18703, 2025.

Under European and International policies, organic soil amendments are highly promoted as a cost-efficient solution to improve soil C, quality, and agrosystem sustainability. Inorganic N application is an essential agronomic practice to increase and secure crop yields, however, its long-term application has led to serious environmental problems including deterioration of soil organic C, enhanced greenhouse gas emissions, and an overall decline in environmental quality. Consequently, the co-application of organic and inorganic fertilizers is advocated as a more effective and environmentally friendly fertilization regime. This study aims, to decipher the short-term N kinetics in agricultural soils amended with organic, inorganic, and a combined application of N fertilizer, with and without biochar, and to assess the trade-off balance of soil C and greenhouse gas emissions. Therefore, we investigated the short-term (90 d) soil N dynamics of sandy soil mesocosms (2 Kg) receiving municipal sewage sludge (MSS) amendments (50 t/ha), urea-N fertilization (U; 200 kg/ha), a combined application (MSS+U), without and with biochar (1.5% w/w). An unamended soil mesocosm was included as a control. The addition of urea-N (U), municipal sewage sludge (MSS), and their combined application (MSS+U) increased the availability of soil NH₄⁺ by 3x, 5x and 12x times, relative to the control, respectively. Interestingly, we observed a tremendous release of soil NO₂^- only in the urea treatment (U; 128 mg kg^-1), and not in the other remaining treatments. Throughout the incubation approx. 12.7x, 13.4x, and 19.7x more soil NO₃^- was observed for the U, MSS, and MSS+U treatment, relative to the control, respectively. Where biochar was applied, an approx. 40% reduction in soil available NO₂^- andNO₃^- was observed. Considering the gaseous emissions of CO₂ and N₂O, that are generally products of soil respiration, nitrification, and denitrification, the addition of MSS and its co-application (MSS+U), enhanced soil CO₂ by 2.4x and 2.4x, and by 13.6x and 16.9x for soil N₂O emissions, respectively. Though biochar addition reduced cumulative CO₂ emissions by 24%, for all treatments except the control. Although biochar addition decreased cumulative N₂O emission by 65% in the U, it had no effect on cumulative N₂O emission for MSS and the combined treatment (MSS+U). Fertilization by U did not affect much soil CO₂ (526 mg CO₂-C kg^-1) and N₂O (1258 μg N₂O-N kg^-1) emissions when compared to the unamended soil treatment (C). The MSS+U reduced the N₂O emission factor, by 5x when compared to MSS treatment, however, it was well above the IPPC emission factor of 1%. Municipal sewage sludge is a source of C, though we observed that MSS (74%) and the combined treatment (MSS+U, 96%) enhanced the CO₂-equivalent emissions, indicating a complete loss of the added organic C through greenhouse gas emissions. Considering our key question, whether co-application of inorganic, and organic fertilizer with biochar is a double-edged sword, we conclude that co-application should be carefully evaluated case per case, as it affects several key soil parameters differently, and therefore we should seek new ways to minimize gaseous losses thus to improve sustainability in agrosystems.

How to cite: Giannopoulos, G., Pasvadoglou, E., Kourtidis, G., Diaz-Pines, E., Sgouridis, F., Boos, A., Duelli, G., Tzanakakis, V., Aschonitis, V., Arampatzis, G., and Anastopoulos, I.: Biochar as a sustainable amendment in fertilized agricultural soils; insights and trade-offs among nitrogen kinetics, carbon sequestration, and greenhouse gas emissions., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18764, https://doi.org/10.5194/egusphere-egu25-18764, 2025.

Forests in Europe have been exposed to an increase in atmospheric deposition of nitrogen in the second half of the 20^th century that potentially lead to nitrogen saturation and elevated leaching of nitrogen from forest soils potentially impacting water quality of drinking water resources. Nitrogen dynamics of forests, however, are complexe and still not fully understood.

Atmospheric deposition, soil solution, meteorology, soils, as well as stand and site characteristics have been continuously measured and analysed at several hundred intensive monitoring plots of the Level II plot network of the International Cooperative Programme on Assessment and Monitoring of Air Pollution Effects on Forests for many years.

We used the hydrological model LWFBrook90R to calculate water fluxes through the soils of these sites and calculated nitrogen input with atmospheric deposition and output fluxes with percolating soil water. We found high long-term variations on parts of the plots. Some of these variation patterns are in the time range of changes in the tree stands, e.g. mortality and subsequent biomass decomposition. We will discuss relations of found nitrate leaching patterns with nitrogen saturation indicators suggested in literature. 

How to cite: Waldner, P., Raspe, S., Fleck, S., Zimmermann, L., Schmidt-Walter, P., Iacoban, C., De Vos, B., Cools, N., Deroo, H., Vanguelova, E., Galic, Z., Bourletsikas, A., Meesenburg, H., Schütt, T., Wohlgemuth, L., Schwärzel, K., Meusburger, K., and Nieminen, T.: Long-term variations in nitrate leaching from ICP Forests Level II plots, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19141, https://doi.org/10.5194/egusphere-egu25-19141, 2025.

Excessive nitrogen deposition from anthropogenic activities poses significant challenges to ecosystems and air quality.¹ The atmospheric deposition of ammonium and nitrate plays a critical role in regulating ecosystem productivity and driving particulate matter formation, with impacts that vary across spatial and temporal scales.

In this study, high time-resolution measurements of gas-phase nitric acid (HNO₃) and ammonia (NH₃), as well as particulate nitrate and ammonium were conducted at an agricultural site in Switzerland. These measurements were complemented by 15 years of long-term monitoring data at the same site, providing a comprehensive record of changes in atmospheric gas and aerosol species over time. Aerosol pH was estimated using the ISORROPIA thermodynamic model² and evaluated using a well-established approach based on the agreement between observed and predicted partition ratios of nitrogen species. The intensive measurement shows that the diurnal cycles of HNO₃ and NH₃ partitioning exhibited distinct patterns. HNO₃ tended to partition into the particle phase during the night, driven by cooler temperatures, while NH₃ remained predominantly in the gas phase throughout the day and night, regulated by high aerosol pH characteristics at the sampling site.

The dry deposition regimes of HNO₃ and NH₃ were investigated in relation to aerosol liquid water content and acidity following the approach of Nenes et al. (2021).³ The findings indicate that NH₃ deposition is rapid, meaning it tends to deposit near its sources, raising concerns about its localized ecological impacts. Aerosol mass formation was found to be primarily sensitive to HNO₃ concentrations. Long-term monitoring data spanning 15 years revealed that reduction in SO₂ emissions did not lead to increases in aerosol pH owing to the buffering effect of NH₃ in the NH₃-rich environment. The decline in sulfate concentration has driven a clear shift in aerosol mass sensitivity, transitioning from NH₃-sensitive to NH₃ -insensitive regime. Comparative measurements at forested sites in Switzerland provide further insight into the diurnal cycle of aerosol pH and reactive nitrogen deposition, highlighting the influence of anthropogenic activities on nitrogen dynamics across different ecosystems. These findings show the complex interplay between rapidly fluctuating diurnal aerosol acidity and reactive nitrogen deposition, offering important reference for designing effective pollutant mitigation strategies.

References:

(1) Wim de Vries.: Impacts of nitrogen emissions on ecosystems and human health: A mini review, Current Opinion in Environmental Science & Health, 2021, 21:100249, DOI: 10.1016/j.coesh.2021.100249. 

(2) Fountoukis, C. and Nenes, A.: ISORROPIA II: a computationally efficient thermodynamic equilibrium model for K⁺–Ca²⁺–Mg²⁺–NH₄⁺–Na⁺–SO₄²⁻–NO₃⁻–Cl⁻–H₂O aerosols, Atmospheric Chemistry and Physics, 7, 4639–4659, DOI:10.5194/acp-7-4639-2007, 2007.

(3) Nenes, A., Pandis, S. N., Kanakidou, M., Russell, A. G., Song, S., Vasilakos, P., and Weber, R. J.: Aerosol acidity and liquid water content regulate the dry deposition of inorganic reactive nitrogen, Atmospheric Chemistry and Physics, 21, 6023–6033 DOI:10.5194/acp-21-6023-2021, 2021.

How to cite: Zhang, J., Waseem, A., Baccarini, A., Motos, G., Hüglin, C., Yue, S., Brem, B., Simon, L., Dada, L., Violaki, K., Gysel, M., Slowik, J., and Nenes, A.: Atmospheric reactive nitrogen and its dry deposition regimes under anthropogenic influence: Insights from intensive and long-term monitoring in Switzerland, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19168, https://doi.org/10.5194/egusphere-egu25-19168, 2025.

Soil organic matter (SOM) provides crucial storage for carbon but also contains a majority of soil nitrogen. Land use intensity (LUI) may affect the particulate and mineral-associated SOM pools having repercussions on the carbon and nitrogen storage and cycling. Soil organic matter dynamics and composition plays a key role for the extent of these processes, yet its interactions remain poorly understood preventing targeted mitigation measures for carbon and nitrogen-related soil functions. Here we provide insights investigating how LUI and soil properties affect the storage of carbon and nitrogen in functional SOM pools in the topsoil (0-30 cm) of grassland soils across three different regions in Germany. Furthermore, we present a conceptual framework integrating biological, mineral, and organic nitrogen pools to disentangle nitrogen cycling processes and their interactions with organic matter dynamics.

Across the land use intensity gradient, we isolated particulate organic matter (POM), which is part of  in the >20 μm fraction, and mineral associated organic matter (MOM) in the <20 μm fraction. Random forest and mixed model analysis showed that LUI did not significantly affect SOM storage, but led to reduced C/N ratios in POM and MOM, driven by increased N fertilization intensity. Rather than land use intensity, soil properties, such as clay and iron oxide content, and soil type diversity exerted most influence on SOM.

To reconcile the influences of soil properties on soil nitrogen cycling, we provide a novel conceptual framework integrating organic matter stabilization mechanisms, microbial N uptake and release as necromass, as well important processes catalyzed by the soil microbiome including  biological nitrogen fixation pathways. Our integrative nitrogen cycling framework stimulates different disciplines towards a new perception of the nitrogen cycle in unlocking multiple organic nitrogen pools as mediated by soil type and climatic conditions.

How to cite: Schweizer, S. A., Böhm, A., Kepp, J., Kiese, R., Pacay-Barrientos, N. L., Ramm, E., Schloter, M., Schöning, I., Schrumpf, M., Schulz, S., and Dannenmann, M.: Cycling of nitrogen in soil organic matter pools in grasslands as influenced by land use intensity and soil diversity, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19982, https://doi.org/10.5194/egusphere-egu25-19982, 2025.

Nitrogen is a crucial component of nutrient dynamics in the environment and exists in multiple oxidation states. Nitrate (NO^3-) is the most stable form of all the reactive nitrogen species and has a higher residence time in groundwater. Sources of nitrate include mainly fertilizers, sewage, manure, soil organic matter, and rain. In a country like India, where agriculture covers an area of about 60% of the total land and population with 2^nd rank globally, contributes a huge fertilizer and sewage component to the environment. Also, nitrate in groundwater deteriorates the potable water quality. So, optimization of nitrogen use and sources estimation of nitrate in groundwater and surface water is very essential. Hindon River basin in the western Indo-Gangetic plain provides an opportunity to study nitrate dynamics in a huge populated and extensive agricultural area. Nitrate concentration in groundwater has been found from 0.1 ppm to 80 ppm, far apart from the permissible limit. Pre-monsoon groundwater shows higher nitrate concentration than that of post-monsoon groundwater at most of the places suggesting the dilution effect of rainwater after monsoon. Fluctuations in δ¹⁵N and δ¹⁸O values seasonally suggest a rapid change in contribution of nitrate source in groundwater. Contribution from each source of nitrate was estimated by Stable Isotope Mixing Models in R (SIMMR). As the dual isotope plot shows denitrification trend, the actual fertilizers contribution shifted towards manure and sewage end members evidenced by higher sewage and manure contributions (60-75% in pre and post-monsoon respectively) need to be optimized for sustainability.

How to cite: Jakhar, M. and Sanyal, P.: Nitrate in water: Understanding the sources using δ15N and δ18O values, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20072, https://doi.org/10.5194/egusphere-egu25-20072, 2025.

Wetlands play a complex role as both sources of greenhouse gases (GHGs) and carbon sinks, making it essential to understand their dynamics and effects on biodiversity. The increasing pressures from climate change and human activities can disrupt the natural balance of these ecosystems, potentially resulting in elevated GHG emissions. The intricate abiotic and biotic interactions that govern these processes remain poorly understood. Therefore, there is an urgent need to enhance our understanding of the factors influencing GHG production in wetlands and to improve our capacity to model these emissions on a larger scale. In this study, we investigated the emissions of N₂O, CO₂ and CH₄, with a particular focus on N₂O, which is primarily produced through the microbial process of denitrification, and for which a satisfactory large-scale model formulation is lacking. The objective of this study was to evaluate these GHG emissions under optimal conditions for denitrification and to identify unifying abiotic factors. To achieve this, we selected contrasting study sites that varied by wetland type and climate zone, thereby gathering extensive data essential for our modelling efforts.

The research was conducted across multiple wetland sites involved in the ALFAwetlands project (https://alfawetlands.eu/), a European initiative dedicated to the study and restoration of both natural and managed wetlands. A total of 21 sites were selected across five European countries, encompassing a range of climate zones from Mediterranean to arctic. These included floodplains, alluvial forests, drained forests, peatlands, and mountain peatlands (with four sites each in France and Spain, three in Belgium, and five each in Finland and Estonia). For each location, three core samples (10 cm depth and 10 cm diameter) were collected and stored in the dark at 4°C prior to conducting mesocosm experiments. The samples were then placed in a custom-designed “GHG-aquacosm”, which simulates the effect of flooding on wetlands soils. During the experiments, soil cores were submerged in heated water enriched with nitrate. GHG emissions, soil moisture, and soil temperature were continuously monitored until stabilization or end of emission.

While CO₂ and CH₄ emissions were recorded, they have not yet been analysed, as this study primarily focuses on N₂O emissions. The results indicated that N₂O emissions varied significantly based on wetland type and initial soil water content. Drained forests, located in cool sub-arctic regions in Finland, demonstrated the highest N₂O fluxes, ranging from 500 to 2000 µmol/m²·h. In contrast, floodplains and peatlands in Belgium and Estonia showed the lowest fluxes, between 5 and 150 µmol/m²·h. Significant variability was noted even among replicates, highlighting the considerable spatial heterogeneities of soils. Additionally, N2O emissions began immediately after nitrate addition, and for most sites ended 30 to 40 hours after, indicating the short temporal scale of N2O production and the challenges associated with in situ measurement. Ongoing data analysis and measurements are focused on further elucidating the spatial and temporal heterogeneities of denitrification processes, with the goal of effectively incorporating these factors into our modelling efforts.

How to cite: Crestey-Chury, T., Darnajoux, R., Kanaan, R., Aurela, M., Butlers, A., De Dobbelaer, T., Escarmena, L., Gandois, L., Jauhiainen, J., Juutinen, S., Larmola, T., Mander, Ü., Poblador, S., Raman, M., Sabater, F., Schindler, T., Soosaar, K., Ukonmaanaho, L., and Sánchez-Pérez, J.-M. and the French team (CRBE): Nitrous oxide emissions in natural and managed wetlands across Europe, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-20384, https://doi.org/10.5194/egusphere-egu25-20384, 2025.

Nitrogen (N) deposition generally reduces the temporal stability of plant community (community stability) across spatial scales. Theory predicts that community stability increases with sampling area, leading to a positive community stability–area relationship (CSAR). However, because atmospheric N deposition exhibits a temporal pattern, little is known about how the responses of community stability differ under seasonal N deposition, or whether seasonal N deposition alters the CSAR and its underlying mechanisms. Understanding this is crucial for assessing multi-scale ecological sustainability under global change. We conducted an experiment with N input during autumn, winter, or the growing season in a temperate grassland. Based on six years of survey data across nested spatial scales ranging from 0.01 to 16 m², we explored the potential impacts of seasonal N enrichment on the CSAR. Our results showed that community stability increased with sampling area, regardless of N addition. Each of the three seasonal N inputs caused a significant reduction in the CSAR intercept, while N addition in winter or the growing season also reduced the CSAR slope. Biodiversity had a stronger effect than area in maintaining the positive CSAR, and mediated the relationship between area and stability. High biodiversity preserved community stability by maintaining population stability and compensatory dynamics. By validating and extending the CSAR theory under seasonal N input, our research showed that N input in winter or the growing season caused a greater reduction in plant community stability at larger spatial scales. As global N deposition continues to increase, small-scale studies may undervalue the adverse impact of N input on stability, while large-scale studies based only on N input during the growing season may overestimate this effect. These findings highlight the need to consider both spatial scales and seasonality of N deposition for accurately predicting ecosystem responses to atmospheric N deposition.

How to cite: Zhang, Y., Stevens, C. J., Lu, W., Chen, X., Ren, Z., and Zhang, Y.: Does nitrogen deposition affect plant community stability–area relationships? The role of biodiversity, area, and seasonal N addition, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-21215, https://doi.org/10.5194/egusphere-egu25-21215, 2025.

In recent years, the severe impact of wildfires has sharply increased due to rising temperatures and drought-like conditions. Therefore, in addition to continuous wildfire monitoring, a long-term understanding of the climate-wildfire relationship is warranted. This study has explored the climate-wildfire relationship in the southern Taiwan region over the past two millennia, focusing on the influence of climate and human activities on wildfire occurrences and their subsequent impact on lake. To achieve this, carbon, nitrogen, carbon isotopic composition of organic matter, charcoal, and diatom assemblages were analysed in the Dongyuan Lake core sediments. Wildfires occurring between 1850 and 1050 cal years BP were largely caused by drier climate conditions. However, wildfires occurring during 750-500 cal years BP and from 350 cal years BP to the present, intervals characterized by wet climate conditions, coincided with a significant number of archaeological sites near Dongyuan Lake, suggesting human-induced burning in the region. The observed wet interval during 1050-750 cal years BP in southern Taiwan attributed to the Medieval Warm Period (MWP), and dry interval during 500-350 cal years BP linked to Little Ice Age (LIA). The low carbon content in Dongyuan Lake sediments coincided with peaks of charcoal accumulation, indicating the loss of carbon due to wildfires and the dilution of sediments. The principal component analysis (PCA) of diatom data showed that PC1 and PC2 represented the lake's acidic conditions, suggesting an increase in pH from 750 to 150 cal years BP. This variation in pH appeared to be linked with wildfire intensity and frequency. PC1 and PC2 also showed strong acidic conditions during the last 150 years, plausibly due to the increase in acid rain conditions in the last century.

How to cite: Rahman, A. and Wang, L. C.: Climate-fire-human interactions and their impact on the limnology conditions of the Dongyuan Lake, Southern Taiwan during the last 1800 cal years BP, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-593, https://doi.org/10.5194/egusphere-egu25-593, 2025.

The frequency and severity of wildfires are projected to increase in the Mediterranean region. Greece currently lacks a developed standardized system for identifying and prioritizing burnt areas in relation to their restoration needs. Prioritization of areas for post-fire restoration efforts using geographic information system (GIS) and remote sensing (RS) can be useful in decision-making. However, this approach is often insufficient in effectively integrating perspectives from multiple stakeholders and socio-ecological criteria. Combining qualitative methods such as interviews with GIS and RS methods can enhance the understanding of nuances in a local context. 

We designed an approach to identify high-priority areas for post-fire restoration. The identification was based on interviews with stakeholders and the application of GIS and RS. We conducted 15 interviews with stakeholders working on post-fire issues and selected criteria for the prioritization analysis based on their views. The expert interviews revealed perceptions regarding the necessity of vegetation restoration and rehabilitation efforts and helped to identify the key characteristics respondents consider essential for prioritizing burnt areas for restoration. These insights established an analysis using GIS and RS to select areas based on the identified characteristics. 

We selected the areas for restoration based on fire history, slope, and designation as part of the protected areas. The outcomes of the analysis helped to highlight three areas that potentially need special attention. We propose a prioritization system that considers the natural regeneration potential of the Mediterranean and on-the-ground socio-ecological limitations, and can help government agencies, local foresters, private consultancies, and NGOs plan restoration actions and optimize the effectiveness of restoration programs in Greece.

How to cite: Palenova, E., Veraverbeke, S., Kontos, T., and Ebert, K.: Prioritizing Areas for Post-Fire Restoration in Greece Using Mixed-Methods Spatial Analysis, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1579, https://doi.org/10.5194/egusphere-egu25-1579, 2025.

Climate warming has caused a widespread increase in extreme fire weather, making forest fires longer-lived and larger. The average forest fire size in Canada, the USA and Australia has doubled or even tripled in recent decades. In return, forest fires feed back to climate by modulating land–atmospheric carbon, nitrogen, aerosol, energy and water fluxes. However, the surface climate impacts of increasingly large fires and their implications for land management remain to be established. Here we use satellite observations to show that in temperate and boreal forests in the Northern Hemisphere, fire size persistently amplified decade-long postfire land surface warming in summer per unit burnt area. Both warming and its amplification with fire size were found to diminish with an increasing abundance of broadleaf trees, consistent with their lower fire vulnerability compared with coniferous species. Fire-size-enhanced warming may affect the success and composition of postfire stand regeneration as well as permafrost degradation, presenting previously overlooked, additional feedback effects to future climate and fire dynamics. Given the projected increase in fire size in northern forests, climate-smart forestry should aim to mitigate the climate risks of large fires, possibly by increasing the share of broadleaf trees, where appropriate, and avoiding active pyrophytes.

How to cite: Yue, C., Zhao, J., Wang, J., Hantson, S., Wang, X., He, B., Li, G., Wang, L., Zhao, H., and Luyssaert, S.: Forest fire size amplifies postfire land surface warming, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1986, https://doi.org/10.5194/egusphere-egu25-1986, 2025.

Firebrands, small pieces of burning vegetation, can be detached and transported far away from the main fire front during intense fires. The process of firebrand generation, transport and ignition of a fuel bed is known as spotting. Spotting can start new fires and plays an important role in wildfire spread, presenting critical challenges for containment strategies and risk management. This study utilizes a series of high-resolution simulations to evaluate the influence of wind speed, topographic features, fire intensity and atmospheric stability on firebrand transport and fuel ignition. By coupling a fire-atmosphere modeling with combustion and firebrand transport models, we analyze key processes affecting firebrand trajectories and ignition potential.

To obtain realistic conditions of an intense fire, we use the cloud resolving weather model MesoNH coupled with the fire propagation model ForeFire. Such coupled fire-atmosphere simulations are designed to have a computational domain of the same scale of large wildfires, here 80m resolution for 14 km wide, 28 km length and 16 km high. This coupled fire atmosphere model is run for 36 different conditions:

• Three reference wind speeds (5, 10 and 15m.s^-1)
• Three head fire heat flux (40, 80 and 120 kW.m^-2)
• Three topographies (a flat terrain, a hill and a canyon)
• Two atmospheric conditions: stable and unstable

Firebrands are modelled as point masses with three degrees of freedom (three translations), with a set of aerodynamic coefficients and a combustion model. By combining high-resolution LES simulations with detailed firebrand trajectory and combustion processes, we expect to obtain realistic firebrand trajectories.

The resulting different ground patterns distributions of potentially still burning firebrands show that high wind speeds significantly increase firebrand lofting and horizontal transport distances of up to several kilometers. The maximum spotting distance is increased when topographic elements, such as hills or canyons, are added to the simulation. Furthermore, atmospheric stability exerts a critical influence on firebrand behavior: unstable conditions encourage turbulent mixing, vortices, and upward lofting with increased maximum heights reached by the firebrands.

Our results also emphasize the interaction between fire intensity, terrain-driven wind patterns, and atmospheric conditions. This should allow to identify thresholds where long-range spotting becomes most likely. As a result, this research provides valuable insights into the mechanisms driving firebrand dynamics, advancing predictive wildfire modeling and improving hazard mitigation strategies.

These results contribute to the broader understanding of wildfire behavior and have practical implications for fire management, evacuation planning, and the development of tailored mitigation measures to address the growing threats posed by wildfires in a changing climate.

How to cite: Alonso Pinar, A., Filippi, J.-B., and Filkov, A.: Meteorological impacts on long-range spotting of firebrands, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2126, https://doi.org/10.5194/egusphere-egu25-2126, 2025.

Tropical forests are at high risk of dieback due to human-induced disturbances including forest fires, agricultural expansion, and logging. These disturbances can degrade the ecosystems, slow forest recovery, and disrupt the global carbon cycle, leading to irreversible changes or ‘tipping point’ in the Earth’s climate system – the point at which disruption to the climate potentially becomes irreversible. Early warning signals of tipping points for the Amazon rainforest and Greenland ice sheet have already been detected. Monitoring these forest ecosystems is crucial to mitigate future long-term consequences. In order to analyse the response of vegetation to disturbances, we must first identify such disturbances, ideally across the entire tropics over a long period of time. We must also carefully consider what we mean by a “disturbance” and it is not necessarily just the largest fire event. It may be that a significant disturbance is a modest fire event but in a region that does not typically experience burning or a fire event outside of the typical fire season. In both of those instances, we might expect the vegetation response to have different characteristics to those from regular, large burns.

In this study, we applied Isolation Forest (IF) algorithm to detect Burned Area (BA) anomaly and apply it to ESA FireCCI51 dataset (2001-2020) over IPCC AR6 defined land regions, with Madagascar as a case study region. IF identifies anomalies by considering how easily they can be isolated from the main distribution and allows us to introduce features beyond just the burned area itself (e.g., time and location of the fire). Explainable AI (SHAP) analysis was also performed to further understand the predicted BA anomaly. A higher number of BA anomalies were mostly linked to larger values of BA over the Tropics and in Madagascar, however, anomalies in BA are also affected by temporal and geographical factors other than the magnitude of BA. IF detected a high number of anomalies (>20) in the northern region of Madagascar which comparatively had lower BA values which could indicate deviation from seasonal fire patterns. These results were further explained by SHAP analysis which showed that BA was the main factor influencing prediction of BA anomaly but that time and location could play a significant role in some anomaly detections. This suggests that deviation from the typical fire seasonality was another factor contributing to anomaly detection. The high number of anomalies in these specific areas highlights the need for targeted fire management strategies so that policymakers can anticipate the long-term effects of climate change and human activity on tropical forests, guiding sustainable land use, conservation, and climate adaptation efforts in vulnerable regions.

How to cite: Poudel, S., Parker, R., Balzter, H., Quaife, T., and Kelley, D.: Detecting Burned Area Anomalies with Isolation Forest in the Tropics: A Focus on Madagascar , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2854, https://doi.org/10.5194/egusphere-egu25-2854, 2025.

The Mediterranean region is one of Europe’s most fire-prone and vulnerable areas, facing compounding risks from urban expansion and wildfire activity. This study examines the evolution of human exposure to wildfires in Catalonia, northeastern Spain, over three decades (1992–2021). Using high-resolution geospatial data, including fire perimeters, nighttime light (NTL) intensity as a proxy for human activity, population data, and historical settlement patterns, we analyze trends in exposure per unit of burned area (BA). Results reveal a 77% increase in human exposure per unit BA, driven by population redistribution and urban expansion into fire-prone areas, despite a non-significant decrease in BA of −0.43 km²/year.

A novel aspect of this research is the integration of NTL data to capture dynamic changes in human activity and exposure, validated against population and settlement datasets. Exposure trends were assessed using counterfactual scenarios to isolate the impact of population dynamics. Findings underscore the critical need to account for human activity changes in wildfire risk assessments, highlighting the increasing vulnerability of expanding urban landscapes in Mediterranean regions. These insights are essential for developing adaptive and proactive wildfire management strategies to mitigate future risks.

This methodology provides a replicable framework for assessing wildfire exposure in diverse geographical contexts, emphasizing the value of integrating population dynamics with environmental datasets.

This work is currently in preparation.

Acknowledgements:
This work was supported by the project ‘Climate and Wildfire Interface Study for Europe (CHASE)’ under the 6th Seed Funding Call by the European University for Well-Being (EUniWell). M.T. acknowledges funding by the Spanish Ministry of Science, Innovation and Universities through the Ramón y Cajal Grant Reference RYC2019-027115-I. M.A.T-V and M.T acknowledge funding through the project ONFIRE, Grant PID2021-123193OB-I00, funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”. AP acknowledges the support of the EU H2020 project “FirEUrisk”, Grant Agreement No. 101003890. The authors thank the Generalitat de Catalunya for access to fire perimeter data and Xavier Castro from the Forest Fire Prevention Service of the Generalitat de Catalunya for the helpful discussions on the matter.

How to cite: Torres-Vázquez, M. Á., Dalle Vaglie, M., Kettridge, N., Martellozzo, F., Miguez-Macho, G., Provenzale, A., Royé, D., Randelli, F., and Turco, M.: Human Exposure to Wildfires in Mediterranean Environments: A Case Study from Catalonia (1992–2021), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4358, https://doi.org/10.5194/egusphere-egu25-4358, 2025.

It is becoming increasingly important to understand how ecosystems will recover from wildfires, which are increasing in frequency, severity and size, especially in coniferous forests. Megafires—defined as wildfires burning exceptionally large areas—are thought to have more negative effects on ecosystems than smaller fires. However, the effects of megafires vary substantially, and one hypothesis is that intra-fire heterogeneity of burn patches can dictate the recovery of ecosystems. We evaluated the role of spatial configuration of burn patches within megafires using remote sensing data of fires and vegetation at 30x30 m resolution across 36 years and field-survey data of forest recovery in the western USA. Megafires contributed 62% of total burned area, with their frequency explaining 83% of the variation in the inter-annual burned area from 1984-2020. However, megafire size alone did not inherently result in severe ecosystem transitions, with megafires that experienced large contiguous patches of severely burned forest taking longer to recover. Field surveys illustrated delayed recovery resulted from a tree dispersal-limitation threshold of ca. 150 m, such that increasing distance from intact coniferous forest significantly delayed recovery. Machine learning image classification revealed that the rate of recovery in the severely burned areas has declined by ca. 50% from 1984-2020, with distance from seed source being more important than all climate variables analysed. Consequently, spatial configuration of high-severity burn patches within fires—which have become both larger and more compact through time—are key for assessing the effect of megafires on forest resilience.

How to cite: Pellegrini, A. and Schoenecker, J.: Spatial configuration of severely burned patches within megafires explains ecosystem resilience , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-4739, https://doi.org/10.5194/egusphere-egu25-4739, 2025.

The devastating fire events occurring during the intense fire season of 2023 have shown the importance of developing efficient fire detection methods capable of supporting the fire management activities. An enhanced configuration of the Normalized Hotspot Indices (NHI) algorithm has been developed in this direction to improve the fire mapping by satellite through near infrared (NIR) and short-wave infrared (SWIR) data (up to 20 m spatial resolution) from the Operational Land Imager (OLI/OLI2) and the Multispectral Instrument (MSI) aboard Landsat-8/9 (L8/9) and Sentinel-2 (S2) satellites, respectively. In this work, we show the results achieved by investigating the fire events occurring in California, Hawaii islands (USA), Yellowknife (Canada), Tenerife islands (Spain), Greece and Australia also through comparison with information from operational Landsat Fire and Thermal Anomaly (LFTA) product. Results of an extended validation analysis performed using information from well-established databases show that the enhanced NHI algorithm configuration enabled an accurate mapping of fire fronts with a very number of omission and commission errors. Moreover, the algorithm flagged up to 99% of fire pixels from the LFTA product over California and detected up to 70% of additional fire pixels, in night-time conditions, which better detailed the fire fronts and provided unique information about small-fire outbreaks. The effective integration of S2 (daytime) and L8/9 (daytime/night-time) observations, demonstrates that the enhanced NHI algorithm configuration may be used with success to analyse the dynamic evolution of flaming fronts by assessing/complementing information from satellite products at high-temporal/low-spatial resolution. The next implementation of the algorithm on from the Sea and Land Surface Temperature Radiometer (SLSTR) aboard Sentinel-3 satellite and the Flexible Combined Imager (FCI) of the Meteosat Third Generation (MTG) opens some interesting perspectives also regarding its usage for the near-real time monitoring of wildfires

How to cite: Mazzeo, G., Falconieri, A., Filizzola, C., Genzano, N., Pergola, N., and Marchese, F.: An enhanced NHI algorithm configuration for fire detection and mapping, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5629, https://doi.org/10.5194/egusphere-egu25-5629, 2025.

The Fire Weather Index (FWI) is a widely used metric for assessing wildfire danger, relying on sub-daily meteorological data, typically recorded at local noon. However, most climate models and observational datasets only provide daily-aggregated variables, which can introduce biases in fire weather assessments under climate change. This study evaluates how approximating noon-specific calculations impacts the trends of extreme fire weather days (FWI95d), defined as the annual number of days exceeding the 95th percentile of daily FWI values (FWI95d).

Using global data from ERA5 for 1980–2023, we find that FWI95d have increased by 65% over 44 years, corresponding to an average of 11.66 additional extreme fire weather days per year. Daily approximations consistently overestimate this trend by 5–10%, with the largest differences observed in fire-prone regions such as the western United States, southern Africa, and parts of Asia. Among the tested proxies, the combination of daily mean values for air temperature, relative humidity, precipitation, and wind speed exhibits the lower biases, while proxies involving minimum relative humidity tend to overestimate trends more significantly.

Our findings emphasize the importance of sub-daily meteorological data for accurate wildfire risk projections. In its absence, we recommend prioritizing daily mean approximations over other proxies as the least-biased alternative in the absence of noon-specific data. These results underscore the potential for misrepresentation of future fire weather risks in climate models, particularly if systematic biases introduced by daily approximations are not addressed. Future climate model intercomparison projects should prioritize the inclusion of sub-daily meteorological outputs to enhance the reliability of fire weather assessments globally.

Acknowledgements
M.T. acknowledges funding by the Spanish Ministry of Science, Innovation and Universities through the Ramón y Cajal Grant Reference RYC2019-027115-I and through the project ONFIRE, Grant PID2021-123193OB-I00, funded by MCIN/AEI/10.13039/501100011033 and by “ERDF A way of making Europe”. This work was supported by the project ‘Climate and Wildfire Interface Study for Europe (CHASE)’ under the 6th Seed Funding Call by the European University for Well-Being (EUniWell).

How to cite: Moreno, A., Matteo, A., Herrera, S., Azorin-Molina, C., Bedia, J., Provenzale, A., Dunn, R. J. H., Garnés-Morales, G., Quilcaille, Y., Ángel Torres Vázquez, M., Di Giuseppe, F., and Turco, M.: Overestimating Fire Weather Trends: Challenges in Using Daily Climate Data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6292, https://doi.org/10.5194/egusphere-egu25-6292, 2025.

Haralamb Georgescu was a Romanian architect who fleed the communist rule and settled in the USA. After a brief period in the Eastern part, he settled in Los Angeles where not only did he build his most iconic buildings, but also was featured for futuristic utopic designs. Within the Romanian funded project "Future on the past" (featured at EGU 2023), which used digital humanities methods to develop innovative mapping techniques, including ontologies, for earthquake, flood and fire, also the buildings of Haralamb Georgescu were studied. This happened in conjunction with another Romanian sister project (both ended with the PNIII framework programme on the 31.12.2024) which focused on Romanian-American relationships in the interwar time in a publication of which first results were published. Haralamb Georgescu started his career in the interwar time in Romania. 2-7 January 2025 I visited Mangalia where is his last building built in Romania. Some others built in Bucharest were mapped before, and so were those in the USA, including Los Angeles. Materials on Los Angeles were available from two sources: the Getty archives and a book of drawings of building projects, catalogue of a past exhibition at the "Ion Mincu" University of Architecture and Urbanism, which was done after the rediscovery of Haralamb Georgescu following the restoration of the Pasinetti house, the most emblematic one, featured in a magazine of the time. The mapping in Google Maps of the buildings of Haralamb Georgescu was exported and imported in arcGIS online Living Atlas, the map on US current wildfires. This way three buildings of Haralamb Georgescu were identified (Bucharest restaurant next to the Eaton forest, Lark Arrow apartments in the same area, Rinaldi convalescent hospital) next to wildfires and one on a wildfire and this was the Pasinetti House in Beverly Hills. Unfortunately searching the news confirmed the mapping as the CBS reported dogs being rescued from the lost house of Pasinetti. Besides, during the project in frame of work for COST CA18135 - Fire in the Earth System: Science & Society (FIRElinks), as working group member of group 5 Socio-economic aspects of fire and fire risk management, an ontology of fire was developed and published. This contribution will test how the findings fit into this ontology. Current work is being done in the Climate change adaptation working group of ICOMOS ISCARSAH related to the structures of monuments which includes the effects of wildfire. The architecture of Haralamb Georgescu is Modernist architecture related in typology to that of the Cyclades, and the publication from the COST action also covered the relationship to fires in Greece, specifically Paros in 2022. Some more insights on this will be included after more site visits. This is in line with the research question of the project on how vernacular architecture may render Modernist buildings which include elements inspired by it more safe, through so-called local culture, extensively studied so far for seismic events and started for flood events, but scarcely so for wildfires. The ontology in computer science understanding helps this.

How to cite: Bostenaru Dan, M.: The impact of the January 2025 Southern California fires on the buildings of Haralamb Georgescu in Los Angeles, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7664, https://doi.org/10.5194/egusphere-egu25-7664, 2025.

Wildfires can significantly alter the hydrological regime of a watershed until vegetation is reestablished and the hydrological cycle returns to its pre-disturbance state. These wildfire-induced changes can disrupt flow patterns by reducing rainfall interception and evapotranspiration due to vegetation loss. Additionally, wildfires can affect soil permeability, either through ash deposition or, in boreal regions, by facilitating permafrost thaw.

Land surface models play a critical role in understanding and predicting interactions between the Earth's surface the atmosphere. They enable detailed assessments of water, energy, and carbon cycling, which are essential for climate modeling, ecosystem management, and policy development.

In this study, we analyze surface runoff simulated by six fire-enabled ISIMIP3a land surface models for the period 1850–2019. We identify changes in the runoff coefficient between the most fire-active and least fire-active decades in the timeseries. To isolate the role of long-term climatic trends, we utilize counterfactual simulation outputs driven by detrended observational climate data, where the signal of global warming has been removed.

Our preliminary results reveal consistent patterns between the modeled results and observed runoff changes reported in other studies, though substantial variability exists among the different land surface models. This work aims to assess the ability of state-of-the-art land surface models to represent a complex interaction on the land surface, while also enhancing our understanding of the hydrological impacts of wildfires and contributing to improving the representation of fire-hydrology processes in modeling frameworks.

This work is supported by Leverhulme Centre for Wildfires, Environment, and Society through the Leverhulme Trust, grant number RC-2018-023.

How to cite: Grillakis, M. and Voulgarakis, A.: Hydrological impacts of wildfires on a global scale: An analysis based on the fire-enabled models of ISIMIP., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8889, https://doi.org/10.5194/egusphere-egu25-8889, 2025.

As an imprint of its rapid climatic transformation over the last two decades, the pan-Arctic region has experienced increasingly extreme fire events. However, a systematic and regionally comprehensive assessment of the recent extreme fire events in the pan-Arctic and the role played by human emissions is still pending. In this study, we employ an extreme event-attribution framework to assess the extent to which anthropogenic forcing affects the magnitude (Burned Area) and likelihood of favourable conditions of extreme fire events (Canadian Forest Fire Weather Index) in the pan-Arctic region throughout the 21st century. Therefore, we utilise large ensemble simulations conducted with the Community Earth System Model version 2 (CESM2), which are capable of isolating anthropogenic external climate forcings and observations from distinct remote sensing products as well as reanalysis data. Our results indicate that the presence of anthropogenic forcing throughout the 21st century was necessary to enable the observed extreme fire events in the pan-Arctic region. We find less than a 20% chance, that the extreme wildfire events occurred during recent fire seasons could have happened in the absence of human-induced external forcings. We can state that such wildfires have become 5 to 10 times more likely in comparison to pre-industrial climatic conditions. Furthermore, our findings indicate that the impact of anthropogenic forcings has significantly elevated the risk of high-latitudes experiencing severe fire-weather conditions by up to an order of magnitude. However, our study reveals the recent elevation in human-induced external forcings does not appear to be enough to explain the occurrence of observed extreme pan-Arctic wildfire events throughout the 21st century. We further explore the underlying mechanisms that drive changes in extreme fire-weather risk. We identify the relative contribution of maximum temperature, precipitation, relative humidity, and surface wind speed on the changes in extreme fire-weather risk.

How to cite: Fiedler, L., Barkhordarian, A., Brovkin, V., and Baehr, J.: Causal Attribution of Arctic Wildfire Events in the 21st Century to Anthropogenic Forcing, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9817, https://doi.org/10.5194/egusphere-egu25-9817, 2025.

The study of wildfires is crucial to understanding the Earth system, as severe wildfire events can lead to intense degradation of nature and property. The record-breaking 2023 Canadian wildfire event best represents this, with approximately 5% of the total forest area of Canada burned [1] [2], resulting in biomass burning (BB) emissions quantitatively comparable to the annual fossil fuel emissions of large nations [3], and with the highest Canadian carbon emissions on record [4]. Increased mean temperatures along with decreased humidity in the region due to climate change are considered responsible for this record series of wildfires [5], as increasing mean temperatures along with decreasing humidity in the region led to increased fire risk.

Large amounts of carbonaceous aerosols can exert substantial atmospheric radiative forcing, thus it is important to study the consequences of these emissions on large-scale atmospheric composition and meteorological behavior. In this work, global and local atmospheric impacts of this historic wildfire event are analyzed using the EC-Earth3 earth system model [6] in its standard AerChem configuration. BB emissions from the Copernicus Atmosphere Monitoring Service (CAMS) Global Fire Assimilation System (GFAS) were used as input in the model to produce two 10-member ensembles simulations, with and without the 2023 Canadian wildfire emissions. The results are analyzed, and the differences in various modelled atmospheric quantities between the two ensembles are spatially cross-correlated to determine connections between atmospheric anomalies and wildfire intrusions.

Modelled monthly changes in radiative effects, cloud cover, large-scale circulation, and temperature patterns throughout the North Hemisphere and Canada are found as a result of the 2023 BB emissions, and the mechanisms via which these can be caused are discussed and explained. These changes include the long-range transport of the BB pollutants in the troposphere and the stratosphere with marked impacts on cloud cover and on temperatures at low and high altitudes, differential cooling over the Canadian region due to a dual influence of direct and indirect effects of AOD increases, and even large-scale circulation anomalies which led to cooling as far as in Eastern Siberia. We find that the modelled temperature anomalies between the two ensembles caused by the wildfire-generated aerosols can be as intense as -5.44 °C locally, while the modelled average hemispheric temperature anomaly is equal to -0.91 °C.

[1] "Fire Statistics". Canadian Interagency Forest Fire Centre. Retrieved January 4, 2024.

[2] “The State of Canada’s Forests: Annual Report”. 2022. Canadian Minister of Natural Resources.

[3] Byrne, Brendan, et al. "Carbon emissions from the 2023 Canadian wildfires" Nature. 2024 835-839.

[4] “Copernicus: Emissions from Canadian wildfires the highest on record – smoke plume reaches Europe”. Atmosphere Monitoring Service, Copernicus. Retrieved January 4, 2024.

[5] Barnes, Clair, et al. "Climate change more than doubled the likelihood of extreme fire weather conditions in eastern Canada" 2023.

[6] Döscher, Ralf, et al. "The EC-earth3 Earth system model for the climate model intercomparison project 6." Geoscientific Model Development Discussions. 2021 1-90.

How to cite: Rosu, I.-A., Kasoar, M., Mourgela, R.-N., Boleti, E., Parrington, M., and Voulgarakis, A.: Large-scale impacts of the 2023 Canadian wildfires on the Northern Hemisphere atmosphere, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10833, https://doi.org/10.5194/egusphere-egu25-10833, 2025.

In recent years, fire activity at high latitudes has reached unprecedented levels, driven in part by global warming, which increases fire danger. Climate projections of fire risk rely on indices like the Canadian Forest Fire Weather Index (FWI), which are often derived from coarse-resolution climate models. Thus, there is the need for finer-scale fire weather projections to enable more effective planning and resource allocation as wildfire threats grow. High-resolution climate projections can be achieved through various methods, including dynamical and statistical downscaling, each potentially yielding different estimates of FWI and its future changes. We calculated the FWI based on HCLIM - Nordic Convection Permitting Climate Projections (NorCP) over Fennoscandia. The simulations include 12 x 12 km resolution models using HCLIM-ALADIN and convection-permitting simulation at 3 x 3 km resolution with HCLIM-AROME, covering both historical and future periods under the RCP8.5 scenario. Results were compared against FWI estimates from other climate datasets, such as CORDEX and statistically downscaled NASA Earth Exchange Global Daily Downscaled Projections (NEX-GDDP).

As expected, all the simulations indicate that the annual and summer mean FWI indices will increase significantly in warmer future climates, along with an increase in days with moderate and high fire weather risk. However, the magnitude of the risk depends heavily on the climate dataset used. For instance, HCLIM-AROME simulations generally show higher FWI values in the historical period even when compared to the future projections of HCLIM-ALADIN, due to generally lower summer precipitation in the former model. Additionally, there are notable regional disparities between the HCLIM simulations, with the highest FWI values observed in coastal areas of southern Finland and Sweden. According to the HCLIM-AROME simulations under the RCP8.5 scenario, these regions experience a moderate fire risk (FWI > 11) on roughly one out of three summer days, whereas HCLIM-ALADIN simulations indicate an average of 7–20 days per summer with such risk. There are also differences in the magnitude and regional distribution of FWIs calculated from HCLIM, NEX-GDDP, and CORDEX simulations. However, all future FWI predictions consistently indicate that, without effective mitigation of global warming, conditions for forest fires will worsen in the future.

How to cite: Laakso, A., Palokangas, M., Park, T., Lipponen, A., Utriainen, L., and Mielonen, T.: Assessing the Impact of Climate Change on Forest Fire Weather Index Using Downscaled Climate Model Data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12890, https://doi.org/10.5194/egusphere-egu25-12890, 2025.

How to cite: Jones, M.: Navigating the Era of Extreme Wildfires: Scientific Solutions and Future Directions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13652, https://doi.org/10.5194/egusphere-egu25-13652, 2025.

Wildfire influences the carbon cycle and impacts property, harvestable timber, and public health. The year 2023 saw a record area burned of 14.9 Mha in Canada, compared to an average of ~2 Mha between 1959 and 2015. Boreal wildfire is a critical process that is difficult to represent in land surface models. To enhance our understanding of historical and future wildfire regimes in Canada and their impact on carbon cycling we implement two methods of representing boreal wildfire in the Canadian Land Surface Scheme Including Biogeochemical Cycles (CLASSIC). These include a new dynamic wildfire model that represents fire weather and lightning ignitions as well as a fire model which is forced by historical observations of burned area. We find that in 2023 simulated wildfire emissions were eight times their 1985 - 2022 mean with consequences for the annual net carbon balance in Canada. Moving into the future we find that climate change below a 2°C global target (shared socioeconomic pathway [SSP] 126) yields burned area near modern (2004 - 2014) norms by end-century (2090 - 2100). However, under rapid climate change (SSP370/585), the end-century mean annual burned area increases 2 - 4 times, compared to present-day values, approaching the burned area seen in Canada in 2023. This work illustrates the historical implications of Canadian wildfires on the carbon cycle and the future implications of climate change for area burned in Canada.

How to cite: Curasi, S., Melton, J., Arora, V., Humphreys, E., and Whaley, C.: Canadian wildfire in a changing climate from the 2023 wildfire season to the 2100s, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13730, https://doi.org/10.5194/egusphere-egu25-13730, 2025.

Wildfires are an increasing environmental and societal threat across the Mediterranean region. While the widespread incidence of fires during recent summers has raised significant public concern, the impact of climate change on such events is challenging to quantify, and the evolving nature of extreme wildfires in general remains underexplored. Recent work has shed light on the link between extreme fire weather and climate change, particularly with respect to diagnosing uncertainties and sensitivities, but there are few studies directly linking individual wildfire events to the changing climate and its future implications.

This study employs an established statistical method applied to a large ensemble of climate model simulations as part of a seamless probabilistic approach to quantify how past, present and future risk in extreme fire weather has and will continue to change in the future. Using climate model projections to quantify the trends of likelihoods at different global warming levels offers great potential to support probabilistic assessment of future wildfire risks in a warmer world. Results reveal that fire weather conditions associated with the particularly damaging 2022 wildfires at ten independent locations across the Mediterranean regions of southern Europe and northern Africa have collectively become 80% more likely to occur compared to a century ago due to externally-forced warming temperatures. Further increases in likelihood of 60% and 80% are projected under +1.5°C and +2°C global warming levels, respectively, with the most pronounced increases observed in Spain and southern France. The findings emphasize the profound influence of climate change on the 2022-type wildfire events, manifesting the urgency of combining individual attribution studies further with future risk assessment to help enhance post-disaster resilience to the fire-prone regions.

How to cite: Liu, Z., Eden, J., Dieppois, B., Blackett, M., and Parker, R.: The Intensifying Threat of Wildfires in the Mediterranean: Quantifying the Role of Climate Change in Extreme Fire Weather Events from the Past, Present to the Future, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13777, https://doi.org/10.5194/egusphere-egu25-13777, 2025.

How to cite: Ghasemiazma, F., Trucchia, A., Meschi, G., Perello, N., Tonini, M., Degli Esposti, S., and Fiorucci, P.: Probabilistic Analysis of Extreme Wildfire events in Italy Using Data-Cube Technology, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13787, https://doi.org/10.5194/egusphere-egu25-13787, 2025.

In the United States, catastrophic wildfires have killed hundreds of people in recent years, including two high fatality events in the 2018 Camp Fire in California and the 2023 Lahaina Fire in Hawaii. These disasters were astounding not only because so many died so quickly, but also because they represent a shift in understanding of who dies in contemporary wildfires. For much of the 20^th century, the primary lives lost in wildfires were the front line firefighters at the greatest risk. Over the last two decades, however, climate change has increased the extremity of wildfire behavior and resulted in numerous catastrophic wildfire events globally where dozens of civilians were killed. Here we evaluate both the biophysical drivers of fatal wildfires in the US and the social characteristics of wildfire fatalities. Downslope winds during drought conditions at the wildland-urban interface are the primary indicators of civilian fatalities, particularly in specific forest-shrubland interface Mediterranean fuel types and in complex terrain. Social vulnerability of the resident population was also a key driver of fatalities, as older populations with lower levels of mobility struggled to evacuate with no advanced notice. Fires that killed civilians stood in stark contrast to fires that killed firefighters, which occur primarily during peak fire season during extreme heat events and in rural, relatively forested areas. These differences highlight a critical gap in understanding how to mitigate civilian wildfire fatalities.

How to cite: Kolden, C. and Abatzoglou, J.: Who dies in wildfires? Common denominators of fatal wildfires in the US, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14597, https://doi.org/10.5194/egusphere-egu25-14597, 2025.

In recent years, newly available observations, and modelling systems as well as advancements in machine learning have transformed the capabilities of fire danger prediction systems. The European Centre for Medium-Range Weather Forecasts (ECMWF) has set out to forecast wildfire probability on a global scale up to a week in advance. A key milestone was the development of the SPARKY-Fuel Characteristics dataset, released in 2024, which provides the first long-term, high-resolution record of real-time fuel status.

This study evaluates ECMWF’s operational data-driven fire prediction system over its first year. Through analysis of major wildfire events, including the extensive fires in Canada in 2023 and the fires in Los Angeles in 2025, we demonstrate the potential of data-driven methods to outperform traditional fire danger metrics. The results highlight the role of dynamic, global fuel assessments and machine learning in improving the accuracy and timeliness of fire probability forecasts.

Our findings underscore the importance of integrating both innovative data-driven approaches and key variables into operational forecasting systems, providing critical support for fire management and mitigation efforts worldwide.

How to cite: McNorton, J.: Global Data-Driven Prediction of Fire Activity, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17607, https://doi.org/10.5194/egusphere-egu25-17607, 2025.

In recent decades, surface air temperatures in the Arctic increased faster than average global temperatures. At the same time, weather conditions that favor wildfires became more frequent globally and will likely continue to do so in a warming climate. This might lead to an increase in fire activity in most areas of the world, but particularly in regions with moderate moisture supply that are rich in biomass, such as North American temperate forests and boreal forests.

Extreme wildfires potentially emit large quantities of smoke that can be elevated as high as to the stratosphere, thereby possibly leading to a long-lasting atmospheric perturbation. Smoke aerosol is mostly composed of black carbon (BC) and organic carbon (OC). While BC mainly impacts the climate by heating the atmosphere through absorption of solar radiation, OC particles are important as cloud condensation nuclei, affecting cloud and precipitation formation. In light of the rapid Arctic warming, it is crucial to understand the role of smoke aerosol from wildfires in the Arctic climate system.

Using multidecadal simulations with the global aerosol-climate model ECHAM6.3.0-HAM2.3., it is analyzed on which pathways BC and OC emitted during extreme boreal wildfire events are transported towards the Arctic and how their transport patterns differ from those of smoke particles originating from moderate boreal wildfires. The contribution from the wildfire aerosol to the total poleward aerosol flux is calculated, and it is quantified which fraction of boreal wildfire aerosol reaches the Arctic region in the course of extreme fires. Transport heights, the accurate representation of which still poses a challenge to current climate models, are compared to height-resolved measurements of smoke aerosol.

How to cite: Paul, S. and Heinold, B.: Poleward transport of smoke aerosol from extreme boreal wildfires, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18268, https://doi.org/10.5194/egusphere-egu25-18268, 2025.

The Brazilian Pantanal, renowned for its rich ecosystems and biodiversity, is under increasing threat from more frequent and intense fires. These wildfires endanger the region's ecology, wildlife, and critical role as a carbon sink. The catastrophic fires of 2020, which burned approximately 4 million hectares, highlighted the pressing need to better understand the Pantanal’s fire vulnerability and to develop effective strategies for protecting its ecosystems and carbon storage capacity.

Using the FLAME model, we evaluated the Pantanal’s fire susceptibility in the context of climate and land cover changes. Our analysis identified shifting precipitation patterns as a key driver of fire activity. Wetland cover emerged as a mitigating factor, with regions exhibiting a doubled wetland extent requiring half as much rainfall to avoid extreme burning levels. However, reducing wetland areas due to agricultural expansion and water management has significantly increased the region's fire vulnerability. The extreme fires of 2020 were linked to a critical threshold of reduced wetland extent and precipitation; without prior wetland degradation, the fires would likely have been less severe.

Our findings emphasize the necessity of integrating wetland cover dynamics and climate extremes into the Pantanal's fire management and conservation planning. This approach is vital for bolstering the region's resilience to fire and climate change, preserving its ecological integrity, and maintaining its carbon storage potential. The FLAME model facilitates the rapid assessment of burning scenarios, providing valuable insights for early preparedness and response strategies to protect this unique and irreplaceable ecosystem.

How to cite: Barbosa, M., Kelley, D., Burton, C., Libonati, R., Da Veiga, R., Ferreira, I., and Anderson, L.: Burning In Pantanal Driven By Wetland Degradation And Lower Precipitation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18657, https://doi.org/10.5194/egusphere-egu25-18657, 2025.

The 2023/24 fire season was marked by record-breaking burnt areas and carbon emissions in Canada, deadly blazes in Hawaii, extreme drought and smoke in the Amazon, burning in the Pantanal wetlands, and Europe's largest wildfire on record.  These events exemplify extreme wildfires' growing prevalence and far-reaching impacts on societies, ecosystems, and global climate systems. Each year, the emergence of such events raises urgent questions from policymakers, fire management agencies, and the public:

•   How much was climate to blame?
•   Was it caused by humans?
•   Who is affected?
•   How does this year compare to previous years?
•   Will we see more fires like this in the future?
•   What can we do to prevent or prepare for them?

The inaugural State of Wildfires report addresses these questions by systematically analysing extreme fire events from the March 2023–February 2024 fire season. It links anomalies in burned area and emissions to drivers such as high fire weather and fuel abundance. Attribution analyses revealed that climate change amplified burned area by up to 40%, 18%, and 50% in Canada, Greece, and Amazonia, respectively. The report also projects an increasing risk of future extreme fires, even under ambitious emissions pathways aimed at limiting warming to 1.5–2°C. However, impacts at these emission levels are still projected to be less severe than those in higher warming scenarios. In Canada, for example, projections suggest that fires like those of 2023 could become 6–11 times more frequent by the end of the century under medium–high emissions scenarios.

Here, we present the main insights from the report, celebrate advances in fire science that are helping to meet the challenge of extreme fires, and invite feedback from the scientific community. We seek perspectives on missing analyses, overlooked impacts, and underexplored regions to enhance future reports.

How to cite: Kelley, D. I., Jones, M. W., Burton, C., and Di Giuseppe, F. and the State of Wildfires Report Co-authors: The State of Wildfires report: an annual review of fire activity and extreme events , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19519, https://doi.org/10.5194/egusphere-egu25-19519, 2025.

Wildfires occurring under warmer and drier conditions are likely to be destructive to infrastructure causing economic losses and affecting population. While climate, represented through fire weather, has been shown to be the dominant driver of wildfires there is still a lack of analyses exploring to what extent climate influences wildfire impacts. Here we examine the statistical relationship between fire weather conditions and wildfire impacts at an interannual scale across Mediterranean Europe. To do so, we combined Fire Weather Index (FWI) with burned area from the European Forest Fire Information System, as well as wildfire economic losses and affected population extracted from the EM-DAT disaster database over the period 2000–2023. Overall, most of the wildfire impacts were dominated by a few iconic events that have occurred during extreme fire seasons. Nearly 90% of the affected population and economic losses occurred when the FWI aggregated over the fire season exceeded 23 and 30 respectively. Additionally, the analysis highlighted the FWI as the main driver of burned area, showing strong positive correlations in all analyzed countries. FWI also showed moderate positive correlations with wildfire economic losses and population affected, yet these relationships varied by country. Countries more severely impacted by wildfires, such as Portugal, Spain, and Greece, exhibited stronger correlations than those less affected. These results emphasized the importance of climate variability in enabling wildfire activity and influencing impacts across Mediterranean countries. 

How to cite: Galizia, L., Castet, C., and Rodrigues, M.: Assessing the influence of climate on wildfire impacts across Mediterranean Europe, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19925, https://doi.org/10.5194/egusphere-egu25-19925, 2025.

Transport of biodegradable organic carbon (bDOC) across land-water interfaces supports the ecological and biogeochemical functioning of northern freshwater ecosystems. Yet, we know little about how the generation and supply of terrestrial bDOC to boreal headwaters is regulated by the physical, biological, and hydrological properties of the riparian interface. We used 7-, 14- and 28- day bDOC incubations on eight occasions during the northern growing season to assess how terrestrial and aquatic bDOC concentrations differ along flowpaths connecting riparian soils to a headwater stream. We found that bDOC quantity declined along the transition from land to water, and that riparian soils had higher concentrations of bDOC compared to aquatic landscape components. Additionally, these differences corresponded to changes in the optical and chemical properties of the dissolved organic matter pool. Further, the generation of bDOC in riparian soils varied across interface types and reflected hydrogeomorphically determined differences in soil organic matter storage, groundwater level dynamics and soil microbial activity. In particular, the potential transfer of bDOC from soils to groundwater appeared largely regulated by the degree of contact between soils and lateral subsurface flowpaths. Riparian interfaces with near-constant opportunity to deliver resources laterally to streams by shallow, preferential groundwater flowpaths were found to have a relatively poor capacity to generate bDOC within local soils. At the same time, groundwater within these same interfaces had higher concentrations of bulk DOC and bDOC, likely due to connections with larger contributing hillslopes which serve as important support systems to streams during baseflow periods. Collectively, our results show that boreal headwaters are comprised of a continuum of interface types that differ in capacity to generate bDOC in near-stream soils, and in opportunity to mobilize and convey bDOC laterally. Ultimately this leads to wider variability in when and where within the broader stream network these inputs may be most important to aquatic ecosystems.

How to cite: Reidy, M., Berggren, M., Lupon, A., Laudon, H., and Sponseller, R.: Riparian zone heterogeneity influences the production and fate of biodegradable dissolved organic carbon across land-water interfaces , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1244, https://doi.org/10.5194/egusphere-egu25-1244, 2025.

Permafrost soils store about twice as much organic carbon as the atmosphere. In the future, certain permafrost regions will develop anoxic soil conditions due to thaw-induced soil subsidence and waterlogging. Under these conditions, methane (CH₄) emissions due to decomposition of newly thawed organic carbon will likely increase. The net release of CH₄ from soil depends on the availability of more energetically favorable electron acceptors than CO₂, which could on the one hand suppress methanogenesis and on the other hand act as an electron acceptor for anaerobic CH₄ oxidation. Since many common inorganic electron acceptors (sulfate, nitrate) are present only in low concentrations in permafrost soils, we hypothesize that natural organic matter (NOM) and/or ferric iron (Fe(III)) are more abundant and can act as significant electron acceptors. However, to which extent NOM fractions such as dissolved organic matter (DOM) and particulate organic matter (POM) as well as Fe(III) minerals influence methane production and methane oxidation in permafrost soils is unknown. In this project, we therefore aim (i) to characterize the redox-active moieties of DOM and POM fractions from permafrost soils, (ii) to quantify the effect of these NOM fractions on methanogenesis suppression and/or CH₄ oxidation, and (iii) to identify the microorganisms that are able to oxidize CH₄ coupled to NOM or Fe(III) reduction by performing enrichment culture experiments. To achieve this, we collected and isolated NOM from a thawing permafrost peatland in Sweden (Stordalen Mire, Abisko) across multiple thaw stages. We analyzed the changes in electron accepting and donating capacity of NOM fractions across permafrost thaw stages via mediated electrochemical reduction and oxidation, respectively. Enrichments targeting anaerobic CH₄-oxidizers were set up using an inoculum from partly thawed and fully thawed permafrost thaw stages, amended with poorly crystalline Fe(III) minerals, AQDS (a model compound for redox-active moieties in NOM) and POM. In the future, microcosm experiments with isolated NOM fractions and ¹³C-labeled CH₄ or ¹³C-labeled CO₂ will be performed in order to quantify the influence of NOM on methane oxidation or methanogenesis suppression, respectively. Spectroscopic, isotope-tracing and molecular biology techniques will be used to track the reduction of amended electron acceptors, concentration of labeled gases and the change in abundance of targeted microorganisms. Overall, this work will help to assess the role of NOM and Fe(III) in influencing CH₄ cycling in thawing permafrost peatlands.

How to cite: Voggenreiter, E., Valenzuela, E., van Grinsven, S., and Kappler, A.: Role of natural organic matter and iron(III) for methanogenesis and methane oxidation in thawing permafrost soils, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1459, https://doi.org/10.5194/egusphere-egu25-1459, 2025.

In my talk, I propose that stoichiometric imbalances between microbial metabolic needs and carbon (C) : nitrogen (N) : phosphorus (P) ratios affect reactive macronutrient flows between ecosystems and in landscapes, much like how stoichiometric imbalances of macronutrients affect organism growth and nutrient cycling at smaller scales. More specifically, I hypothesize that the mismatch between microbial C : N : P ratios and biologically reactive macronutrient ratios modulates macronutrient retention and export. When microbial C : N : P matches nutrient availability, reactive macronutrients should be retained or transformed, reducing downstream transport. Conversely, stoichiometric imbalances between microbial C : N : P and reactive macronutrient C : N : P lead to excess reactive macronutrients being exported to downstream ecosystems

These stoichiometric imbalances are strongly modified by dissolved organic matter (DOM) quantity and especially by DOM composition, which defines the microbial reactivity of DOM. With laboratory microcosm and stream mesocosm experiments, colleagues and myself provide first mechanistic evidence for the importance of DOM composition for the stoichiometric modification of macronutrient flows. Furthermore, comparing global published C : N : P data from soils, lakes, and marine ecosystems, we find evidence that microbial activity uniformly modulates reactive DOM and macronutrient ratios across environments, affecting macronutrient cycling and flows, with probable secondary effects on ecosystem functioning and eutrophication. 

The proposed concept links small-scale mechanistic understanding to ecosystem-scale patterns of macronutrient cycling in inland-water ecosystem networks. This cross-scale perspective highlights the need for integrated stoichiometric experimental and monitoring research to better understand reactive macronutrient cycling and flows, with high potential for improved macronutrient management.

How to cite: Graeber, D.: Dissolved organic matter composition may be a key modifier of ecosystem-scale macronutrient reactivity and flows across the terrestrial - aquatic continuum, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1926, https://doi.org/10.5194/egusphere-egu25-1926, 2025.

Dissolved organic carbon (DOC) plays a fundamental role for the aquatic ecosystem and the global carbon cycle. It also interferes with drinking water treatment processes. Its removal is costly and depends on its quantity and quality, i.e. its concentration and molecular composition. Riverine DOC concentrations have increased in Europe and North America in recent decades, primarily driven by reductions in acid deposition. Currently, changing climatic conditions such as increasing temperatures, heavy rainfall events and droughts are gaining importance in determining DOC concentrations. However, the specific mechanisms by which climate variability drives riverine DOC concentrations and its chemical composition at different time scales are not sufficiently understood. Therefore, reliable forecast about future developments are challenging. In forested headwater catchments, where riparian soils are major sources of DOC export, riparian soil moisture might be paramount to determine DOC quantity and quality. Soil moisture is driven by climate variability and controls subordinate and interdependent processes that can shape DOC quantity and quality. However, limited data of soil moisture from forested headwaters and specifically from their riparian zones are available. In this context, we will study the upper Rappbode catchment in the Harz mountains, which drains into Germany’s largest drinking water reservoir. We will relate high-frequency soil moisture observations at multiple depths (vertical dimension) at different riparian profiles with differing wetness characteristics (topographic dimension) to the corresponding DOC quantity and quality over temporal scales, including short-term, seasonal/annual, and long-term by modeling. We hypothesize that currently and in future patterns of soil moisture in the vertical and topographic dimension play a pivotal role as drivers of the temporal dynamics of DOC quantity and quality in riparian soils and subsequently in the corresponding surface waters. Initial results from our sampling campaigns highlight differences in riparian soil water chemistry between the locations of different wetness characteristics, but also distinct vertical heterogeneities. We will present further findings and results that improve the understanding of how soil moisture drives riverine DOC quantity and quality, with special consideration of vertical heterogeneities in the riparian profiles.  With a refined understanding of DOC dynamics, more reliable forecasts can be made to derive targeted adaptation strategies for safe drinking water supplies and to better assess future impacts on aquatic ecosystems and the global carbon cycle.

How to cite: Burkhardt, P. D., Musolff, A., and Ledesma, J. L. J.: How do vertical and topographic riparian soil moisture patterns shape headwater dissolved organic carbon dynamics?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5582, https://doi.org/10.5194/egusphere-egu25-5582, 2025.

Climate change has intensified the mobility of dissolved organic matter (DOM) from land into aquatic ecosystems leading to increased brownification and hypoxia. Constructed wetlands (CWs) offer a potential mitigation strategy but optimal wetland design with respect to DOM removal remains underexplored. This study examined how depth and water residence time (WRT) affect DOM processing in experimental CWs during summer and fall. Organic matter was added to mimic brownification, and DOM changes were tracked using fluorescence spectroscopy and microbial activity measurements. A key finding was that labile DOM degrades rapidly within the first two days. At longer WRT shallow CWs released terrestrial-like fractions potentially increasing downstream brownification, while deep CWs showed sustained DOM degradation and slower internal production, potentially reducing downstream brownification. Based on spectral ratios it was found that microbial processes dominated DOM degradation, although photodegradation played a significant role during summer. Strong correlations between bacterial processes and DOM composition, highlight the critical role of labile carbon in driving microbial activity. Bacterial production correlated strongly with labile DOM fractions (Peaks T and M), while bacterial respiration, correlated with both labile and humic-like DOM fractions. Our results suggest that CWs can be optimized as tools for mitigating climate change impacts and improving water quality, ensuring long-term ecological sustainability. In addition, our findings advocate for integrating shallow and deep systems in series to maximize carbon removal, minimize brownification, and adapt to seasonal variability.

How to cite: Sjöstedt, J., Jones, K., Borgert, J., and Liess, A.: Carbon removal mechanisms and microbial dynamics in constructed wetlands of differing depths, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-5834, https://doi.org/10.5194/egusphere-egu25-5834, 2025.

Mountain glaciers are vanishing worldwide because of climate change, triggering cascading downstream effects. Today, glaciers are recognized as stores of dissolved organic matter (DOM), which once released, can support the microbial metabolism and food webs in glacier-fed streams. This glacier-derived DOM is often reported to be ancient and highly bioavailable. However, our understanding of how such DOM may change in the future, as mountain glaciers continue to melt, remains limited.

We aimed to determine whether the quantity and quality of DOM in glacier-fed streams are shifting as glaciers retreat. Leveraging DOM data from the Vanishing Glaciers project and using a space-for-time substitution approach, we investigated how both DOM quantity and quality may change across a wide range of glacier-fed streams worldwide. We analyzed optical properties of DOM sampled as close to the glacier snout as possible in 181 glacier-fed streams draining the world’s major mountain ranges. Dissolved organic carbon (DOC) concentrations in these streams were very low (median: 146.3 ppb, interquartile range (IQR): 99.4-211.7 ppb). Parallel Factor Analysis (PARAFAC) identified six major DOM components, highlighting a dominance of proteinaceous compounds in the glacier-fed streams. Furthermore, by integrating additional optical measures, such as fluorescence (median: 1.5, IQR: 1.3-1.7), humification (median: 0.4, IQR: 0.2-0.5) and biological (median: 1.6, IQR: 1-2.3) indices, we will characterize DOM composition and potential sources. These data will be compared to glacier coverage, stream water stable isotopes, major ions, the mineralogical composition of suspended sediments and benthic chlorophyll a. Our unique large-scale dataset allows us to improve current understanding of DOM dynamics and related carbon cycling in glacier-fed aquatic ecosystems, which are now changing at an unprecedented pace because of climate change.

How to cite: Hou, J., Peter, H., Deluigi, N., LIanos-Paez, O., and Battin, T.: Climate-change impacts on dissolved organic matter in glacier-fed streams, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6561, https://doi.org/10.5194/egusphere-egu25-6561, 2025.

Land use is a primary driver of the spatial distribution of soil organic carbon (SOC) and significantly influences the terrestrial carbon cycle. This study used the SWAT-C model to simulate the export of SOC, dissolved organic carbon (DOC), and particulate organic carbon (POC) in the Wu River Basin, analyzing the effects of land use on SOC spatial distribution. Model calibration with 2012–2017 total organic carbon (TOC) data achieved Nash-Sutcliffe efficiency values above 0.7, confirming reliability. The simulated results showed an average annual TOC export of 17.3 kgC/ha, with DOC and POC contributing 10.38 kgC/ha and 6.9 kgC/ha, respectively. Bare land had the highest POC export (66.7 kgC/ha), followed by dry cropland (32.3 kgC/ha), while urban areas and coniferous forests exhibited the highest DOC exports (15.1 and 12.4 kgC/ha, respectively). SOC storage was highest in rice field (313 tonC/ha) and lowest in bare land (175 tonC/ha). Sub-watersheds dominated by bare land and dry cropland recorded TOC exports exceeding 21 kgC/ha, marking them as future SOC export hotspots. These findings highlight the significant influence of land use on SOC distribution and provide a scientific basis for ecosystem service preservation, and sustainable watershed management.

Key words: Soil organic carbon, SOC storage, SWAT-C model, land use, Taiwan

How to cite: Lin, G.-Z. and Chiang, L.-C.: Evaluating the impact of land use on soil organic carbon spatial distribution by SWAT-C model – a case study of the Wu River Basin, Taiwan, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7919, https://doi.org/10.5194/egusphere-egu25-7919, 2025.

Dissolved organic matter (DOM) is a major source of macronutrients in freshwaters, yet has variable and poorly understood bioavailability to bacteria and other organisms. Because intrinsic variation in bioavailability is caused by chemical structures of organic nutrients, DOM composition data should improve predictions of bioavailable resource pool sizes. We hypothesized that bioavailable organic carbon (C) and nitrogen (N) fractions are made up of freshly produced humic- and protein-like DOM, respectively, whereas bioavailable phosphorus (P) is linked to microbially-derived DOM with potential organophosphate content and/or to chemical structures associated with DOM-Fe-phosphate complexes. These ideas were tested in eight, unproductive and organic matter-rich stream and lake sites, where we performed C, N and P bioassays with bacteria in combination with analyses of DOM composition using fluorescence excitation-emission matrix (EEM) analysis. Bioavailable C followed the predicted patterns, with strong links to fluorescent features indicating recently produced DOM. Surprisingly, bioavailable N was poorly related to DOM composition, including protein-like fluorescence, and was instead driven mainly by the amount of inorganic N. Bioavailable P was best linked to microbially-derived organic components. The standard nutrient variables explaining most of the bioavailable total dissolved C, N and P, respectively, were dissolved organic carbon, dissolved inorganic nitrogen and total phosphorus. In addition, DOM composition variables made significant unique contributions to explaining the variance in bioavailable C (19%), N (13%) and P (18%). Overall, DOM composition analysis is a promising tool to improve prediction and develop our understanding of bioavailable macronutrients in organic matter-rich freshwaters.

How to cite: Berggren, M., Rulli, M. P. D., Bergström, A.-K., Sponseller, R. A., and Hensgens, G.: Does DOM composition help explain bioavailable macronutrient concentrations in organic matter-rich freshwaters?, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8762, https://doi.org/10.5194/egusphere-egu25-8762, 2025.

Total organic nitrogen (TON) constitutes almost 20% of the total nitrogen (TN) riverine loadings to Danish coastal waters. Thus, knowledge about the TON concentrations in streams and its spatial variation is essential to accurately assess the importance of TON for TN loadings to coastal waters and thereby achieving a more precise basis for calculation of the sources of TON in catchments.

We used environmental monitoring data from 390 stream stations across Denmark for the period 2018-2021to calculate indirectly measured annual and seasonal average TON concentrations (~1,500 samples) along with a wide range of predictor variables. TON samples showed a mean annual TON concentration in Danish streams amounting to 0.70 mg L^-1 with a standard deviation of 0.31 mg L^-1 and revealed a relatively high spatial variability.

We trained a machine learning model to learn spatial and temporal patterns in our TON data set for prediction of spatially distributed annual and seasonal average TON concentrations in Danish streams in ungauged basins. Furthermore, we utilized quantile regression to estimate the uncertainty on model predictions, and we utilized quantile regression in combination with the Shapley additive explanations (SHAP) approach to investigate how the importance and influence of predictor variables vary across TON’s entire distribution.

The annual TON concentration is modelled with a root-mean-squared error of 0.20 mg L^-1. The new national annual average TON concentration model is largely driven by the mean elevation (negative), the percentage of agricultural land (positive), the percentage of tile drained areas (positive), and the percentage of lakes (positive).

The predicted annual average TON concentrations were generally higher than the measured average annual TON concentrations, with an overall mean of 0.84 mg L^-1, probably because catchments in the training data generally had higher mean elevations (DEM) than the prediction catchments as many ungauged catchments are located near the coast

The developed model and national TON maps contribute to our understanding of annual TON concentrations in streams supporting national-scale land-use and water management.

How to cite: R. Frederiksen, R., E. Larsen, S., and Kronvang, B.: Modelling Total Organic Nitrogen Concentrations in Danish Streams using Machine Learning, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9125, https://doi.org/10.5194/egusphere-egu25-9125, 2025.