Understanding the exchange processes between terrestrial ecosystems and the atmosphere above is crucial for mitigating climate change and promoting ecosystem resilience. Over the past decade, I have investigated the land-atmosphere interactions with regard to energy, water vapor, and CO₂ fluxes in various ecosystems, including forests, croplands, and grasslands, at different spatial and temporal scales. In this lecture, I will present recent results of a near-natural mixed-beech forest in the National Park Hainich in central Germany. Based on a comprehensive long-term dataset of eddy covariance flux observations, we conducted statistical time series analysis to investigate the exchange processes of this diverse, near-natural ecosystem. Furthermore, in collaborations with various partner institutions additional observations are being obtained at this flux study site, such as drone imagery, terrestrial laser scans, vegetation optical depth, forest biomass inventory, phenological photos, and on tree-scale records of stem growth, sapflow and leaf water potential. Using this multi-scale dataset, we aim to improve our understanding of the link between forest exchange processes and tree response dynamics, as well as the impact of extreme weather events (e.g., droughts).

The Hainich forest represents a large carbon sink prevailing throughout the past 26 years. However, the ongoing warming trend is altering the start and duration of the growing season of trees and the herbal layer. Tree vitality is being impacted by diseases and recent drought events such as in 2018-2020 have changed the forest’s processes and dynamics. We observed an increase in the canopy gap fraction in 2021 indicating a significant increase in tree mortality. Surviving trees were affected differently by the droughts depending on their species, age, and competition. In particular, the growth of older and larger trees (mostly ash), was impaired during and after the drought period, resulting in a reduction of the overall CO₂ uptake strength of the forest ecosystem between 2018 and 2022. However, about half of the observed trees, mostly suppressed, vital beech trees, showed a positive growth trend during and after the drought period. The given structural diversity influences the responses and resilience of individual trees and the entire ecosystem. The comprehensive dataset further provides an opportunity to investigate the influence of climate and soil characteristics and of forest management on flux exchange processes within multi-site comparison studies.

How to cite: Klosterhalfen, A.: Flux exchange of a near-natural temperate deciduous forest under drought stress, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12627, https://doi.org/10.5194/egusphere-egu26-12627, 2026.

Roughly 90% of the organic carbon (OC) buried in the global ocean is stored in muddy sediments along continental margins. Estuarine "hotspots" are especially important, with deltas accounting for about 40% of this burial and fjords for around 12%. To understand the sources and fate of OC in aquatic systems, researchers have widely applied molecular biomarkers and bulk geochemical proxies. In my work, I will explore the application of both bulk analytical techniques and molecular biomarkers to investigate how environmental changes across the land–to-ocean aquatic continuum (LOAC) are influencing OC burial and long-term carbon sequestration.  These muds produced by rock weathering play a critical role in the global carbon cycle by binding and shielding OC from degradation. The quantity and characteristics of OC stored in these muds influence the extent, duration, and mechanisms of carbon sequestration.

Human activities, including dam construction, levee building, and climate change, have profoundly reshaped patterns of mud accumulation and organic carbon (OC) storage across diverse environments. I demonstrate that climate warming has generally increased mud–OC fluxes through processes such as glacier melt, enhanced erosion, and dam-driven sediment burial, although these effects vary regionally. From 1950 to 2010, dams reduced global riverine sediment delivery to the oceans by approximately 49%, despite rising upstream sediment loads, trapping an estimated ~60 TgC yr⁻¹ of organic carbon. At the same time, global coastal wetlands experienced a net loss of about 4,000 km² between 1999 and 2019, yet they continue to sequester substantial amounts of carbon (up to ~60 TgC yr⁻¹). In the Arctic, warming has accelerated permafrost erosion, mobilizing roughly 14 TgC yr⁻¹. Together, these examples highlight the complex and often competing influences of human activity and climate change on river systems and the global carbon cycle, with coastal zones emerging as both highly vulnerable and critically important for carbon sequestration. However, whether these changes ultimately enhance or diminish long-term OC storage remains uncertain, given the complexity and variability of the processes and timescales involved.

How to cite: Bianchi, T.: Carbon Processing in the Land-to-Ocean Aquatic Continuum (LOAC): Challenges in the 21st Century, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12722, https://doi.org/10.5194/egusphere-egu26-12722, 2026.

The Cumbrian Wildlife Trust (CWT) is undertaking the most ambitious attempt to revive Britain’s lost temperate rainforest in Skiddaw, northern Lake District, over the next 100 years. This involves the restoration of native Atlantic tree and treeless communities, including peatland in the area. There are ongoing ecological surveys to map the current vegetation and assess peatland status to establish baseline for detailed framework to restore degraded bogs. In collaboration with the CWT, this study employs different lines of palaeoecological evidence to investigate Skiddaw bog’s ecological history, the degree of its degradation over time, and the role of climatic and anthropogenic factors in shaping the landscape. This long-term perspective complements ongoing ecological appraisals by establishing a comprehensive baseline to predict changes in the bog and develop robust restoration and conservation frameworks against future warming climates.

How to cite: Adeleye, M., Essell, H., Handley, J., and Arizpe, A.: Long-term peatland ecological assessment in England’s largest national park (Lake District) for restoration under changing climates, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-257, https://doi.org/10.5194/egusphere-egu26-257, 2026.

In recent years, the triple-oxygen isotopic composition (Δ′¹⁷O) of CO₂ has emerged as a powerful tracer of atmospheric carbon cycling. The Δ′¹⁷O signature of tropospheric CO₂ is controlled by key processes, including global biosphere-atmosphere CO₂ exchange, tropospheric residence times, and stratosphere-troposphere mixing, each of which modifies CO₂ composition through dynamic isotopic fractionation. High-precision measurement of Δ′¹⁷O is essential for constraining models that predict future changes in atmospheric CO₂, yet current datasets remain limited owing to extreme low abundance of ¹⁷O and the considerable analytical challenges involved for accurate and precise isotopic measurement. A further obstacle is the absence of a well-constrained global background Δ′¹⁷O value for atmospheric CO₂ that restricts proper evaluation of deviations arising from diverse source contributions. As a result, model predictions of tropospheric Δ′¹⁷O(CO₂) often diverge substantially from observational constraints.

To address this gap, we have initiated high-precision measurements of δ¹³C, δ¹⁸O, and Δ′¹⁷O in atmospheric CO₂ using TILDAS (Tunable Infrared Direct Laser Absorption Spectroscopy) at the Stable Light Isotope Laboratory in University of Cape Town, South Africa. Bi-monthly air samples have been collected at the Global Atmospheric Watch (GAW) Cape Point station, South Africa, since December 2024. Given the station’s location, sampling is preferentially conducted under south-easterly wind conditions to minimize local anthropogenic influence. CO₂ is extracted, purified, and analysed with a precision of ±10 ppm (1σ). We will present the Δ′¹⁷O record and evaluate its correspondence with existing predictive models. We will also discuss perturbation of local Δ′¹⁷O values by regional fluxes, such as anthropogenic inputs or seasonal biospheric exchange. This initiative aims to provide the first annual Δ′¹⁷O (CO₂) baseline from the Southern Hemisphere and improve the accuracy of predictive models of the carbon cycle.

How to cite: Ghoshmaulik, S., Labuschagne, C., and Hare, V.: Insights into global carbon cycling using bi-monthly measurements of triple oxygen isotopes in CO₂ from Cape Point, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-644, https://doi.org/10.5194/egusphere-egu26-644, 2026.

The rapid technological developments of recent years have enabled new methods for acquiring aerial photographs and high-spectral-resolution imagery. In this context, unmanned aerial vehicles (UAVs) offer significant potential for high-resolution Land Use/Land Cover (LULC) mapping, allowing clear distinction between natural and human-made features. UAV-based approaches provide high accuracy, faster data acquisition, and cost-effective solutions for detailed LULC analyses. However, there is a fertile ground in evaluating different methodological approaches and testing different algorithms for obtaining robust and transferable results. To this end, the present study aims at comparing two advanced classification techniques for mapping agricultural areas using multispectral UAV data over a typical agricultural site. The area selected for the study consists of crops and agricultural land located near the town of Amygdales, in the regional unit of Grevena. The two techniques are SVM (Support Vector Machines) and MLC (Maximum Likelihood Classification). In overall, results showed that the SVM proved to be more accurate with an overall accuracy of 79.45% compared to 78.91% for MLC, while both methods achieved a Kappa coefficient of 0.72. The statistical significance of the findings was further confirmed from the Mc-Nemar statistical significance results which were also computed. The results evidenced the capability of both methods obtaining LULC maps at very high spatial resolution. All in all, the methodological approach presented herein provides potentially a low-cost solution in mapping agricultural areas at very high spatial resolution which may be also fully transferable and reproducible to other locations too, which offer potentially important pathways to be used in precision agriculture applications. Such information can be of practical value to both farmers and decision-makers in reaching the most appropriate decisions for field management.

Keywords: Precision Agriculture, Mapping, UAVs, Classification, Machine Learning, Support Vector Machine, Maximum Likelihood

Acknowledgement

The participation of George P. Petropoulos study is financial supported by supported by the ACCELERATE MSCA SE program of the European Union’s Horizon research and innovation program under grant agreement No. 101182930.

How to cite: Charisoulis, P., Petropoulos, G. P., Detsikas, S. E., Volianaki, E., and Litke, A.: Evaluating different methodological approaches for very high spatial resolution mapping of agricultural areas exploiting UAV data: a case study from Greek agricultural site, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1693, https://doi.org/10.5194/egusphere-egu26-1693, 2026.

 Resource Use Efficiency (RUE) serves as a critical indicator of forest ecosystem functionality, reflecting the efficiency of forests in utilizing light, water, and carbon for biomass production. This study investigates the spatiotemporal dynamics of RUE across 14 major Indian forest types from 2014 to 2023 by integrating Light Use Efficiency (LUE), Water Use Efficiency (WUE), and Carbon Use Efficiency (CUE) derived from MODIS satellite products. Using an eco-hydrogeological framework coupled with Random Forest modeling, the study evaluates the influence of climatic, topographic, and hydrological variables on forest productivity. Results reveal considerable spatial heterogeneity and temporal variation in RUE, with the highest efficiencies observed in wet evergreen and semi-evergreen forests and the lowest in dry deciduous and thorn forests. WUE demonstrated substantial variability across forest types and years, particularly impacted by the 2016 drought. CUE was strongly influenced by elevation (R2 = 0.82), and slope emerged as a limiting factor in drier ecosystems. The study highlights that subtropical pine and montane forests exhibit resilience and adaptive efficiency, while arid-zone forests remain vulnerable to climatic stressors. These findings provide actionable insights for sitespecific sustainable forest management and climate resilience planning in India’s diverse forest landscapes. 

How to cite: Raj, A. and Kumar, R.:  Resource Use Efficiency (RUE) Dynamics of Indian Forests Through an Eco-Hydrogeological Approach Using Machine Learning , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2734, https://doi.org/10.5194/egusphere-egu26-2734, 2026.

Organic soils, especially peat soils, store large amounts of carbon and are therefore considered a significant source of greenhouse gas (GHG) emissions, disproportionately contributing to land-use emission estimates in countries with extensive organic soil areas. When synthesising emission factors (EFs), data are typically stratified by broad climate zones such as temperate and boreal. However, given the spatial distribution of available forest-soil GHG data, such stratification is suboptimal. Temperate forest soils remain less studied than boreal soils, although recent research has expanded the number of temperate estimates from 8 used in the IPCC default EF compilation to at least 91, with the most recent flux data originating from the Baltic states (56 sites). When deriving EFs for specific applications, it is preferable to pool data from regions with similar climatic conditions rather than restricting analyses to unnecessarily small datasets defined by national borders or aggregating data across overly broad and climatically diverse zones.

We reassessed forest-soil GHG emissions in the Baltic states by supplementing regional data with additional sites sharing the same Dfb climate zone under the Köppen–Geiger climate classification. This approach expanded the dataset from 56 to 98 sites, improving EF accuracy and enhancing comparability between neighbouring GHG emission estimates, regardless of whether countries rely solely on domestic data. While such analyses typically focus on drained organic soils, we also included undrained soils to support the establishment of emission baselines for assessing forest management impacts.

Average annual organic-soil emissions in the Dfb climate zone  (mean ± SE, per hectare of forest) were estimated at 0.22 ± 0.18 t CO₂-C, 1.17 ± 1.58 kg CH₄, and 2.82 ± 0.59 kg N₂O for drained soils, and −0.60 ± 0.37 t CO₂-C, 92.88 ± 78.05 kg CH₄, and 2.81 ± 1.07 kg N₂O for undrained soils. Expressed as CO₂ equivalents using AR5 GWPs, total emissions were 1.59 ± 0.46 t CO₂ eq. for drained and 1.15 ± 6.70 t CO₂ eq. for undrained soils. Owing to high natural variability between site-level fluxes, the effect of drainage on GHG emissions remains uncertain. Although the mean difference between drained and undrained soils (0.44 t CO₂ eq.) may indicate a long-term drainage effect, this estimate is highly doubtful. The dataset indicated that simple averaging across all sites is not well suited to deriving EFs, as CO₂ emissions from drained organic soils showed dependence on nutrient status and linkage to dominant tree species and stand age. Drained soils in young stands tended to act as emission sources, whereas older stands increasingly functioned as carbon sinks, with a transition at approximately 25 years of stand age. However, additional observations are required to accurately quantify this dynamic across the forest growth cycle. To illustrate the implications for national upscaling, we derived a Latvia-specific drained organic-soil CO₂ EF that accounts for the distribution of dominant tree species and stand types characterising soil nutrient availability, yielding a weighted EF of 0.14 t CO₂-C ha⁻¹ yr⁻¹.

This work was supported by PeatTransform with co-funding from the European Union and the State Budget of Latvia (6.1.1.2/1/25/A/001).

How to cite: Butlers, A., Bārdule, A., Lazdiņš, A., and Kamil-Sardar, M.: Synthesis of greenhouse gas emission factors for forest organic soils in the Dfb zone of the Köppen–Geiger climate classification, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3062, https://doi.org/10.5194/egusphere-egu26-3062, 2026.

Monitoring the fractional cover of vegetation and bare soil is essential for sustainable land management, soil erosion control, and precision agriculture. However, accurately estimating these fractions from conventional satellite imagery is challenging due to mixed ground cover and limitations such as cloud contamination and coarse spatiotemporal resolution. High-resolution UAV imagery provides an effective solution by capturing fine-scale heterogeneity, enabling the application of spectral mixture modeling techniques to decompose each pixel into proportions of vegetation, bare soil, and other components. Understanding how GSD influences the performance of such mixture models is critical for optimizing UAV-based monitoring strategies and ensuring reliable, quantitative estimates of soil and vegetation fractions for informed land management decisions.

The objective of this study is to evaluate the sensitivity of fractional vegetation estimates to different ground sampling distances (GSDs) derived from unmanned aerial vehicle (UAV) imagery. Multispectral data were acquired using a UAV equipped with RGB, near-infrared, red, and red-edge sensors, flown at altitudes of 40 m, 80 m, and 120 m above ground level. The study area is a heterogeneous vineyard located in Drama, Macedonia, northern Greece. Image acquisition took place on 30 July 2025, under stable atmospheric and illumination conditions.

An object-based image analysis (OBIA) approach was applied to the UAV imagery, and the data were classified into three main land cover classes: photosynthetic vegetation, non-photosynthetic vegetation, and bare soil. Fractional vegetation cover estimates derived at each flight altitude were compared in order to assess the influence of spatial resolution on classification performance and vegetation fraction retrieval. Validation of the classification results was performed using an independent dataset generated through direct photo interpretation, allowing for an objective assessment of accuracy across the different GSDs.

This contribution aims to evaluate the effects of different ground sampling distances (GSDs) on the estimation of fractional vegetation cover (FVC) using multispectral UAV imagery over commercial vineyards in Northern Greece. The study highlights the influence of spatial resolution on canopy representation, particularly in young or sparsely developed vineyards, and supports the development of robust UAV-based tools for precision viticulture

Keywords: UAV, Vineyard, Fractional Vegetation Cover , ACCELERATE

Acknowledgement: This study is supported by ACCELERATE research project which has received funding from the European Union’s Horizon  research and innovation program under grant agreement No.101182930.

How to cite: Tselos, G.-N., Detsikas, S. E., Petropoulos, G. P., Grigoriadis, K., Polychronos, V., Mamagiannou, E.-M., Balomenou, P., Ramnalis, D., and Masouridis, P.: Assessing the effect of different ground sampling distances for drone-based mapping of fractional cover: a case study from a vineyard field in Northern Greece , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3144, https://doi.org/10.5194/egusphere-egu26-3144, 2026.

Bamboo expansion constitutes a significant process altering forest ecosystem structure and function. However, quantitative research remains scarce on how its long-term evolution influences the critical relationship between ecosystem productivity and biodiversity. This study aims to evaluate the long-term ecological effects of bamboo expansion in Wuyishan National Park (a biodiversity hotspot in China).

By analysing Landsat time-series imagery (1986–2020) and existing land cover dynamic classification maps, seven land cover types—including bamboo forests and broad-leaved forests—were identified. Analysis of surface classification results revealed an overall upward trend in bamboo forest area, with expansion primarily occurring at the expense of broad-leaved forests. Notably, 48% of the newly added bamboo forest area resulted from the conversion of broad-leaved forests.

To assess ecosystem responses to bamboo expansion, spectral diversity was quantified using Rao's Q index (functional diversity) and Shannon index (species diversity), calculated from NDVI and NDMVI. Ecosystem productivity was characterised via habitat indices (DHIs) derived from NDVI time series. Results indicate that regional ecosystem productivity has steadily increased, whereas spectral diversity has markedly declined, with both Rao's Q and Shannon indices showing significant downward trends. Specifically, bamboo forest patches exhibited higher Cumulative DHI (8.8 ± 0.65) than broadleaf forests, yet lower Rao's Q indices (0.010 ± 0.004), whereas broadleaf forests recorded (8.7 ± 0.69) and (0.011 ± 0.003), respectively. Moreover, farmland and tea plantations exhibited abnormally high Rao's Q values, likely attributable to fragmentation and edge effects (small patches embedded within forest backgrounds) rather than genuine species richness.

The study employed Theil–Sen trend estimation and Mann–Kendall significance testing to investigate correlations between bamboo forest area changes and biodiversity. Results revealed a significant negative correlation between bamboo forest expansion and spectral diversity indices (R²≈−0.36), suggesting bamboo encroachment may diminish biodiversity.

The observed trend of increasing productivity coupled with declining spectral diversity warrants further analysis to elucidate underlying drivers. Future research should integrate additional vegetation indices and morphological parameters for diversity calculations. Furthermore, long-term assessments of animal habitat suitability and ecosystem stability require combined ground-truthing and modelling approaches.

How to cite: Shi, W., Zhang, Q., and Qiu, F.: Bamboo Expansion Drives Divergence in Productivity and Spectral Diversity in Wuyishan National Park over Nearly Four Decades, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3212, https://doi.org/10.5194/egusphere-egu26-3212, 2026.

Java Island is experiencing severe degradation of natural mangrove forests due to anthropogenic pressure, particularly in Probolinggo Regency. Although restoration programs have been widely implemented, the success rate remains very limited due to unsuitable planting technique and suboptimal species selection. This study provides the first baseline ecological assessment of vegetation status and estimation of carbon stock to support more effective restoration planning. Using a quantitative random sampling method, data on species identification, vegetation height, and diameter at breast height (DBH) were collected from 33 plots across eight sub-districts. Avicennia marina, Rhizophora mucronata, and Avicennia alba, are the dominant species with relative abundance varied by location. Saplings represented the most abundant growth stage, while trees exhibited the lowest abundance, indicating high past historical degradation. The westernmost sub-district exhibited the lowest Shannon–Wiener diversity index (H' = 0.9), suggesting higher anthropogenic pressures than others. Species richness, evenness, and dominance remain substantially varies across sub-districts. The total estimated carbon stock was 292 Mg C ha⁻¹, comparatively low for Indonesian mangroves ecosystems. The natural mangrove forests in Probolinggo Regency are in early-mid successional stage, reflecting strong past degradation. These findings highlight the urgency of restoration program to improve the total carbon stock across all sub-districts, particularly western areas, with careful consideration of site-species suitability. 

This research was conducted at the Warm-Temperate and Subtropical Forest Research Center, National Institute of Forest Science (Project No. FE-2022-04-2025).

How to cite: Qurani, C. G., Rizal, M., and Sugiana, I. P.: Baseline ecological insights of vegetation assessment and carbon stock estimation in natural mangrove forests of Probolinggo Regency, Indonesia, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6317, https://doi.org/10.5194/egusphere-egu26-6317, 2026.

Stable carbon and nitrogen isotopes are widely applied to infer plant water-use efficiency and nutrient dynamics; however, their physiological interpretation remains uncertain when isotopic signals are not supported by functional measurements. Here, we combine elemental and isotopic analysis (EA-IRMS; δ¹³C, δ¹⁵N, %C, %N and C/N ratio) with fast chlorophyll a fluorescence assessed in vivo through the JIP-test (Handy-PEA) to resolve the physiological meaning of isotopic variability across two genotypes and three geographical contexts of typical Italian red chicory.
In December 2024, leaves and roots of two Cichorium intybus cultivars (“Rosso precoce di Chioggia” and “Rosso precoce di Treviso”) were sampled across three sites, resulting in four genotype–site combinations. Plants were collected at their areas of origin, as defined by Protected Geographical Indication (PGI, Chioggia and Treviso), and outside the PGI area in Massenzatica (Ferrara, Italy), where both cultivars are cultivated in a sandy coastal soil. Isotopic and elemental analyses revealed a pronounced site-dependent differentiation. Leaf and root δ¹³C values varied among sites, indicating substantial long-term differences in C discrimination, related to the balance between transpiration and CO₂ assimilation, which seemed more favourable in Chioggia. δ¹⁵N further discriminated sites and cultivars, highlighting marked differences in N dynamics and internal allocation, although without clear attribution to specific sources.
To assess whether isotopic shifts reflected adaptive regulation or functional impairment, chlorophyll fluorescence transients (OJIP) were analysed using JIP-test parameters. All samples exhibited the typical polyphasic OJIP pattern, yet clear differences emerged between cultivars and sites. Across the entire induction curve, the Treviso PGI transient were consistently higher at the J and I steps than the other samples. This pattern was associated with increased light absorption and energy dissipation per photosystem II reaction centre (ABS/RC, DI₀/RC), reduced electron transport efficiency (ET₀/RC), and lower probabilities of electron transfer to photosystem I end acceptors (ψ(RE₀), δ(RE₀)), indicating a tendency to over-reduce the electron transport chain, probably driven by downstream limitations in electron utilisation.
Overall, our results demonstrate that a more negative δ¹³C, while implicating a better water use efficiency, does not necessarily reflect an overall better plant adaptation, which could be affected by  some biochemical photosynthetic constraints. Integrating EA-IRMS with JIP-test fluorescence analysis provides a robust framework to discriminate between stomatal regulation and biochemical limitation, improving the mechanistic interpretation of isotopic markers for geographical fingerprinting and genotypic differentiation in climate-sensitive agroecosystems.

This research was allowed by phD fellowship granted by EUROPEAN SOCIAL FUND P L U S - The ESF+ 2021-2027
Programme of the Regione Emilia Romagna

How to cite: Martina, A., Ferroni, L., and Marrocchino, E.: From isotopic fingerprints to functional diagnosis in Italian red chicory: linking δ¹³C and δ¹⁵N to photosynthetic performance across geography and genotype, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8969, https://doi.org/10.5194/egusphere-egu26-8969, 2026.

Sustaining rice productivity in intensive rice-rice systems requires comprehensive soil management, with diagnosis of key soil physical, chemical, and biological indicators that need attention. In a 16-year long-term experiment (established in 2005-06 and ongoing) of the irrigated double rice system of Eastern India, we investigated the effect of key soil drivers on rice productivity.

The experiment assessed the effect of control (no N fertilizer application), imbalanced fertilization (N/NP/PK), balanced and recommended NPK and 150% NPK, NPK with lime, micronutrient additions (Zn with/without S or B), and integrated nutrient management with FYM (with/without lime), Composite surface soil samples (0-15cm) were collected after harvest of the 32^nd rice season for evaluation of soil physical, chemical, and biological properties. Rice grain yield after the 32^nd season was recorded at 14% grain moisture.  

To identify key soil drivers, an interpretable machine learning framework was used, specifically a conditional random forest-based yield model, permutation-based variable importance, and accumulated local effect (ALE) plots. The model described the yield variability very well (mean RMSE 305 kg ha^-1, R² 0.88, MAE 254 kg ha^-1). Variable importance screening highlighted total K, protease, and urease activities, as well as permanganate-oxidizable carbon (POC), as dominant predictors. ALE-based effect sizes suggested these properties accounted for ~400 (total K), ~250 (protease), ~200 (urease), and ~140 (POC) kg yield variability.

Overall, the results indicate that potassium dynamics are a primary constraint in intensive rice-rice systems, with risks associated with continuous K mining, and emphasize the importance of routine monitoring of biological activity indicators for long-term sustainability.

Keywords: Conditional random forest; Soil quality index (SQI); Long-term fertilizer application; K-dynamics; Soil enzymes; Cattle manure

How to cite: Garnaik, S., Samant, P. K., Mandal, M., Wanjari, R. H., Sinha, N. K., Mohanty, M., and Lenka, N. K.: How Soil Quality Affects Long-Term Rice Productivity, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11249, https://doi.org/10.5194/egusphere-egu26-11249, 2026.

Support Vector Machine (SVM) classifiers are widely used for satellite-based crop mapping, yet hyperparameter tuning is often treated as a black-box process, with limited insight into how individual parameters influence classification performance. This limitation becomes critical when deploying SVM models across heterogeneous agricultural landscapes, where robustness and transferability are required. This study systematically investigates the sensitivity of SVM hyperparameters for crop type discrimination using Sentinel-2 NDVI time series over the Al Haouz plain in central Morocco, a heterogeneous irrigated agricultural region comprising winter cereals and perennial orchards. An exhaustive grid search was conducted across multiple orders of magnitude for the regularization parameter C (0.01–1000) and the RBF kernel coefficient γ (0.001–10). Model performance was evaluated using F1-score, Recall, and Overall Accuracy for six crop classes with contrasting phenological patterns.

Results reveal a pronounced asymmetry in hyperparameter influence. The regularization parameter C exhibits a high degree of robustness: once a moderate threshold is reached (C ≥ 1), classification performance stabilizes and remains insensitive to further increases. In contrast, γ shows a narrow optimal range (0.1–1.0), beyond which performance rapidly deteriorates. High γ values induce overfitting, particularly among crops with similar seasonal dynamics, as evidenced by persistent confusion between citrus and olive classes. The optimal configuration (C = 1, γ = 1) achieved an F1-score of 0.80 and an Overall Accuracy of 81%. More importantly, sensitivity analysis demonstrates that γ plays a dominant role in model calibration. These findings provide practical guidance for deploying robust SVM classifiers in data-limited agricultural contexts, where extensive hyperparameter tuning is often impractical.

How to cite: Ben zhair, F., Elyoussfi, H., Alami Machichi, M., Azamz, R., El Kasri, J., Boufous, B., and Belaqziz, S.: Hyperparameter Sensitivity Analysis of Support Vector Machine for Crop Type Classification Using Sentinel-2 NDVI Time Series, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12087, https://doi.org/10.5194/egusphere-egu26-12087, 2026.

Estuarine systems are crucial in deciphering coastal ocean dynamics and biogeochemistry, including the vital role they play as ecological sequesters of greenhouse gases. We present a modelling framework that combines the Estuary Box Model (EBM) with the Biogeochemical Flux Model (BFM) to simulate the interplay between physical dynamics and biogeochemical processes. The EBM is a robust, yet simplified model that represents estuarine hydrodynamics, addressing salinity, temperature, and freshwater discharge variations. The BFM simulates nutrient cycling, microbial interactions, phytoplankton dynamics, organic matter mineralization and particulate sedimentation across chemical functional families and living functional groups. To realistically simulate estuarine scenarios, the passive tracer transport equation was adapted to include explicit biogeochemical reaction terms within a time-varying estuarine simplified control volume, furthermore, accounting for riverine nutrient inputs, vertical mixing, tidal exchange and various biological feedback. Additional alterations were made to accommodate burial and sequestration parameters better representing estuarine zones.
The coupled framework was applied to the Po di Goro estuary in northern Italy, and the simulations were conducted for the period 2010 to 2023. The results were validated by comparing the Chlorophyll concentration outputs against satellite and in-situ buoy observations. The outcomes show a strong correlation between phytoplankton biomass and residence time during periods of algal blooms, whereas a rapid shift to zooplankton propelled top-down grazing control during prolonged periods of stable conditions. The model effectively replicates the organic matter sedimentation dynamics typical of deltaic environments, offering insights into the scale and factors controlling the burial and sequestration of organic matter in these ecosystems. The coupled EBM-BFM system is a highly computationally efficient and scalable framework for understanding the estuarine ecosystem drivers, with important potential applications in biogeochemical variability, nutrient retention, and climate-driven changes in coastal zones.

How to cite: Santhoshkumar, S., Verri, G., Vigiak, O., Niroumand, M., Riminucci, F., Silvestri, S., and Mentaschi, L.: A computationally efficient framework for modelling estuarine biogeochemistry, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12306, https://doi.org/10.5194/egusphere-egu26-12306, 2026.

The European Environment Agency data on nitrates levels gives us a ratio of 8:1 for nitrates in groundwater versus river water, when we analyse the data across 27 countries. The “missing” nitrate, at an average of about 89%, matches the levels of “missing” nitrate due to capture of nitrate on the river bottom, by microbes known as diatoms, which take up 65-95% of the water nitrate load.

Diatoms convert nitrate to ammonium in daily cycles, that are linked to sunlight and Oxygen abundance, encountered in typical river and lake conditions.

We can identify that the major pathway of nitrate into rivers and lakes is through groundwater feeds, which average 25% of surface waterway volumes worldwide -because their nitrate levels dwarf those from any other source. We can also identify that the main mechanism of nitrates removal in river bottoms is diatom capture, where diatoms take up the bulk loads of nitrate arriving in the groundwaters beneath.

Diatoms' virtual monopoly on nitrates conversion may allow us to control N2O and global warming levels, by intercepting the conveyor belt system of nitrates to diatoms in waterways. We can capture and repurpose the nutrient for use as farm fertilizer and harvest diatom ammonium as a carrier for Hydrogen fuel. Diatoms are already farmed commercially for fish food, showing they are amenable to farming, and they are already a source of soil conditioner for farms. Ammonium is harvested in wastewater plants for Hydrogen fuel purposes already, and diatoms offer a low carbon method of ammonium production.

The junction between the UN, EEA and microbial data also allows us to calculate the world processing levels of nitrate in terms of both natural and human produced components. We obtain a range around 300,000 kilotons per annum as being processed by surface waters worldwide from all sources. About 120,000 kilotons of the load comes from human produced sources.

Ammonium nutrient from diatom nitrate conversion is quickly absorbed by aquatic plants and riverside trees, but there is a risk of high levels on hot days in lowered Oxygen conditions. Trees draw up around 1000 litres a day of groundwaters in river basins, so that ammonium and nitrates consumption by trees is additionally a main mechanism of Nitrogen reduction around the riverbed.

How to cite: Hall, C., Smith, D., Munro, A., and Sgroi, A.: Microbial breakthroughs in 2022 now allow us to link United Nations water volumes with EEA nitrates data, to reveal world nitrates processing loads in kilotons, including how much nitrate is from natural sources, and how much is from human activity., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13318, https://doi.org/10.5194/egusphere-egu26-13318, 2026.

Twenty years of MODIS satellite data (2002-2022), TROPOMI glyoxal observations (2018-2022), and ground-based isoprene measurements were used to examine vegetation greenness (NDVI) and atmospheric glyoxal over Houston, Texas. Biogenically produced glyoxal grew by 51% between 2018 and 2022, despite a 2% per decade decrease in summer vegetation greenness and continued urbanization. Ambient mixing ratios of isoprene, the main biogenic glyoxal precursor, paradoxically dropped by 14% within the same time frame. Temperature (+0.68°C/year), ozone (+28%), and photochemical oxidants all significantly increased over this time, according to analysis of concurrent environmental data. The results indicate that higher temperature-driven isoprene emissions (+35%) and accelerated photochemical oxidation (+10%) overcame the declining vegetation signal, resulting in net increases in atmospheric glyoxal. This suggests that Houston's remaining flora is experiencing temperature-driven changes in biogenic volatile organic compound (VOC) emissions per unit area, even while its greenness has reduced.

Keywords: MODIS NDVI; TROPOMI glyoxal; Isoprene emissions; Photochemical oxidation

How to cite: Bibi, S. and Rappenglück, B.: Vegetation Dynamics and Atmospheric Glyoxal in Houston, Texas (2018-2022), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13501, https://doi.org/10.5194/egusphere-egu26-13501, 2026.

Stubble burning after harvest is known to degrade soil organic carbon (SOC). However, research on its long-term impacts on SOC is scarce and inconclusive. To address this gap, we introduce a data-driven modeling approach for SOC quantification by integrating remote sensing data with machine learning models to quantify changes in SOC during 2004-2021 across burnt rice areas in Punjab, India. This involved synthesizing literature to obtain SOC values pre- and post-burning, as well as intersecting MODIS burnt areas with rice crop maps to identify stubble burning areas in Punjab from 2004 to 2021. Post synthesis and identification, MODIS satellite band values were extracted for the synthesized experimental plots on pre- and post-burning dates. Further, remote sensing indices, which are sensitive to SOC changes such as NDVI, NBR, RECI, and BSI, were calculated for the pre- and post-burning dates. Using these indices and band values as predictors and literature-derived observed SOC values as response variables, multiple machine learning models were trained, whereby an R² value of 0.3 was obtained. While further efforts are required to improve model accuracy, our study revealed a significant decline in SOC from 2004 to 2018, ranging from 0.1  to 12.5 %,  whereas from 2019 to 2021, SOC increased by 0.7 to 7 % in various districts in Punjab. More specifically, these districts-Sangrur, Ludhiana, and Kapurthala have had the most significant decline from 2014 to 2018, whereas Rupnagar, Patiala, and Fatehgarh Sahib exhibit the highest increase in SOC from 2019 to 2021. The decline in SOC could be attributed to accelerated mineralization driven by combustion and the loss of SOC in the form of CO₂ emissions. Whereas the increase in SOC could be attributed to a reduction in stubble burning and incomplete combustion of residue, leading to the return of unburnt organic matter to the soil. These findings highlight the efficacy of integrating remote sensing frameworks with data-driven machine learning models in monitoring SOC and other aspects of soil health.

How to cite: Hoojon, J., Narayanan, M., and Ilampooranan, I.: Data-driven modelling to quantify soil organic carbon in burnt croplands: An integration of remote sensing and machine learning , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13704, https://doi.org/10.5194/egusphere-egu26-13704, 2026.

Drylands are mostly covered by biocrusts and are sensitive to climate change, which will likely affect nitrogen (N) transformation. However, it remains unclear the response of N transformation-related variables (N transformation rates, microbial biomass, and enzyme activity) to warming in biocrust-dominated dryland ecosystems. Here, we examined three soil cover types (bare soil, cyanobacteria- and moss-dominated soil) over a full year as we conducted a warming treatment (open top chambers) in the Tengger Desert. In order to quantify the response of N transformation-related variables to warming, we defined the warming effects (WEs) as the increment of N transformation-related variable per-unit variation of temperature. Our results showed that the presence of biocrusts can significantly increase the WEs of soil N mineralization rates (Rmin), nitrification rates (Rnit), the content of microbial biomass carbon (MBC) and nitrogen (MBN), and the activities of soil nitrate reductase (S-NR) and urease (S-UE). Microbial biomass under biocrusts was more sensitive to warming followed by enzyme activity. Meanwhile, the WEs in spring and fall were higher than those in winter and summer. The cumulative rainfall was the driving factor affecting the seasonal change of WEs. Therefore, the defining and studying warming effects expand our understanding of seasonal dynamics of N transformation, microbial biomass and enzyme activity, and emphasize the important roles of biocrusts as modulators of N cycling under climate change in dryland ecosystems.

How to cite: Hu, R. and Zhang, Z.: Biocrusts mediate seasonal warming effects of soil N transformation in drylands, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15468, https://doi.org/10.5194/egusphere-egu26-15468, 2026.

Kathmandu has undergone significant urbanization over the past decade, resulting in consistently warmer peri-urban regions compared to nearby rural landscapes due to the urban heat island effect. This study examines how baseline warming interacts with monsoon droughts to affect grassland ecosystems.

Using the Kathmandu Valley as a case study, we analyzed monsoon-season (June–October) data from 2000 to 2022, comparing land surface temperature (LST) and Normalized Difference Vegetation Index (NDVI) from MODIS, volumetric soil moisture from ERA5-Land, and reference evapotranspiration (ET₀) from Terra-Climate between peri-urban and rural grasslands. Grasslands were considered instead of agricultural regions to avoid the effects from irrigation. The premises of Tribhuvan University were chosen as the peri-urban location for their closeness to the core-city region and Changunarayan (Bhaktapur) was chosen as a rural location. The Standardized Precipitation Index (SPI-3) was derived from historical precipitation records (1980–2020) and drought years were identified by negative monsoon-mean SPI values.

The results reveal a persistent peri-urban heat penalty throughout the study period. On average, peri-urban grasslands were 0.94°C warmer than their rural counterparts. This contrast increased to 1.15°C during non-drought years but narrowed to 0.5°C during drought years, as rural grasslands experienced sharper warming related to soil moisture depletion and reduced evaporative cooling. Despite the partial thermal convergence, the peri-urban zone experienced greater ecological stress during droughts, with NDVI declining by approximately 4% relative to rural areas as soil in peri-urban region are 1.12% drier during droughts compared to rural grasslands. An average potential evapotranspiration difference of 23.6 mm exists between the region, and during droughts, the evapotranspiration is 2.66% higher in peri-urban region.

These findings demonstrate that monsoon drought reduces spatial thermal contrasts but does not eliminate peri-urban vulnerability. Persistent background heating in peri-urban landscapes results in elevated vegetation stress even when meteorological drought conditions are similar. These results highlight the importance of peri-urban land management and thermal mitigation strategies in reducing ecological stress under increasing climate variability in rapidly growing cities.

How to cite: Dahal, P. and Lamichhane, S.: Peri-urban heat amplification of monsoon drought impacts on grasslands in the Kathmandu Valley, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15799, https://doi.org/10.5194/egusphere-egu26-15799, 2026.

The intensive irrigation-linked groundwater abstraction in North China Plain (NCP) is dramatically affecting the hydrological processes and regional climate. Impacts from these anthropogenic groundwater withdrawals are evident in the fluctuation of each component in the terrestrial water cycle, the lack of groundwater sustainability, and regional climate extremes. Ensuring future groundwater security within this context will largely depend on how accurately the human activities in the Human-Earth system model were represented. However, to date, most hydrological models and land surface models either ignore the representation of human intervention or realistically model sophisticated human activity processes. In this study, we incorporated two groundwater-fed irrigation schemes in the Noah-MP model and further used realistic irrigation water use results constraining irrigation water withdrawals. We evaluate the influence of the groundwater pumping representation on the simulation of evapotranspiration and groundwater water table depth using Fluxnet-MTE ET data and observational groundwater well data, respectively. The Noah-MP simulation with groundwater-fed irrigation produced ET that matched the magnitude of observations-based Fluxnet-MTE ET values. Observational well-depth anomaly fluctuations can be reproduced in irrigated areas within the groundwater-fed simulation. In addition, the improvement of groundwater pumping also helps to improve terrestrial water storage estimates in higher resolution. We estimated that, over a seasonal cycle, groundwater-fed irrigation in the model can account for 80% of the declining terrestrial water storage trend from 2003 to 2016. Our approach and results reinforce the importance of parameterizing human activities in the Human-Earth system model and better address the water security challenges under climate change and human interventions.

How to cite: dai, D.: Modelling the groundwater pumping for agriculture in the Noah-MP model to support sustainable water management over the North China Plain, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16034, https://doi.org/10.5194/egusphere-egu26-16034, 2026.

Soil-derived N₂O represents a critical climate feedback in semi-arid agriculture. With a global warming potential (GWP) 298 times greater than CO₂, 6.2 TgN₂O-N is emitted annually from agricultural soils. The atmospheric acceleration with a growth rate >1.0 nmol mol^-1 y^-1 remains unexplained by fertilizer use alone, suggesting climate change as a critical driver of enhanced emissions, particularly through extreme precipitation and droughts. Rajasthan’s 4.6 million hectares of climate-resilient millet cultivation experience intense droughts and severe monsoon variability. Both these factors lead to drought-rewetting cycles and impact N₂O emissions, which remain unquantified at regional scales.

This study integrates satellite-derived measurements coupled with multi-model ensemble projections to model N₂O emission hotspots in the millet croplands at the district level in this state, which is a major producer of millet in India. Published millet area datasets for spatial distribution and water-filled pore space (WFPS) thresholds (80 - 95%, for optimal denitrification) with soil moisture proxies (NDVI, LST) are integrated to quantify N₂O flux. Standard precipitation index from CMIP6 models (SSP2-4.5, SSP5-8.5) is applied to quantify temporal shifts in wet and dry frequencies. 

The results indicated that the denitrification-dominated pathways have dominated during rewetting phases, with N₂O peaks lagging behind soil moisture recovery by 48–72 hours, consistent with the Birch effect. Meta-analytical synthesis suggests rewetting pulses release 5 - 10 times higher N₂O flux than constant moisture conditions. CMIP6 scenarios project 20 - 35% intensification in drought frequency by 2050, driving 15 - 25% increases in cumulative annual N₂O emissions under high-emission scenarios. The regional assessment enables evidence-based fertilizer timing and supports India’s Nationally Determined Contributions (NDCs) by quantifying emissions, thereby paving the way for more effective mitigation strategies.

How to cite: Aarav, P., Burman, P., Phartiyal, G., and Sharma, S.: Quantifying N₂O Pulses from Millet Croplands: The Role of Drought-Rewetting Cycles Observed via Remote Sensing and CMIP6, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16677, https://doi.org/10.5194/egusphere-egu26-16677, 2026.

Apple flowering in the Himalayan region depends on winter chill and spring heat, which are changing under a warming climate. These changes have increased uncertainty in flowering intensity and timing across different elevations. In this study, high-resolution UAV imagery and a YOLOv8-based segmentation model were utilized to map tree-level flowering intensity across three apple orchards situated along an elevation gradient in the northwestern Himalayas. The YOLO model was found to reliably detect flower clusters and showed strong agreement with manual counts, with an R² value of 0.85. This allowed consistent comparison of flowering intensity across sites. The winter chill was estimated using the Dynamic Model, expressed as chill portions derived from ERA5 Land hourly temperature data. Spring heat accumulation was quantified using growing degree days. Flowering varied clearly with elevation. Mid-hill orchards bloomed earlier and showed lower visible flowering during UAV surveys. Higher-elevation orchards bloomed later and exhibited higher flowering intensity. The winter chill was sufficient at all sites. Flowering responses were mainly controlled by the combined effects of chill and spring heat. The results demonstrate that integrating UAV-based deep learning with climate indices provides a practical framework to assess climate-driven changes in apple phenology in mountain environments. This approach can support climate risk assessment and adaptive orchard management in the face of continued warming.

How to cite: Shukla, Y., Gupta, V., and Himanshu, S. K.: Apple Flowering Response to Climate Variability along the Himalayan Elevation Gradient, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17076, https://doi.org/10.5194/egusphere-egu26-17076, 2026.

Since 2011 in Italy the surface area cultivated with pear tree (Pyrus communis L.) decreased from 35,400 ha to approximately 23,700 ha in 2023, driven by escalating production costs, stagnant market prices, and recurrent phytopathological challenges. Additionally, this decline has been hypothesized to be causally linked to progressively unfavorable climatic conditions, characterized by rising temperatures, frequent summer heatwaves exceeding 35°C, and reduced precipitation. The objective of this study is to identify the most effective soil–plant relationships across Emilia-Romagna, which is the leading Italian region for pear production. We aim at providing a scientific basis for adaptive management strategies linked to regional pedoclimatic variability, so as to support the future of the Italian periculture.
Three experimental orchards were located in the provinces of Ferrara, Modena and Ravenna, which are key districts in Italy for periculture were set up in 2023. Agro-meteorological conditions were continuously monitored through an online automated system. Soil samples were thoroughly characterized with respect to their texture, calcium carbonate content, pH, loss on ignition LOI, multi-element profiling by X-ray fluorescence (XRF). To link soil properties with the plant performance, fast chlorophyll a fluorescence was measured in leaves in June 2025 on BA-29 grafted trees and the PI_tot (total performance index) was calculated, which represents a synthetic indicator of photosystem II efficiency.

Soils at the Modena site were predominantly sandy, deriving from Apennine sediments, whereas soils from Ferrara and Ravenna sites exhibited a higher clay content resulting in greater, water-holding capacity. XRF analyses indicate that elemental concentrations at all sites were within expected background levels. LOI and calcimetric analyses were higher in Ravenna soils compared to those from Ferrara and Modena, indicating a greater organic matter and carbonate content. At the Modena site, trees exhibited significantly lower PItot values than those observed in  Ferrara and Ravenna sites, This pattern is attributable to the higher sand fraction, which promotes rapid water drainage and reduced nutrient retention in contrast to clay-rich soils where enhanced water and nutrient availability can support improved photosynthetic performance performance. A relationship could also be envisaged found between soil organic carbon content and PItot. Because meteorological conditions were comparable and the germoplasm was uniform across the three sites, the observed differences in photosynthetic performance can be primarily ascribed to soil properties. These location-specific soil–plant correlations can inform precision agriculture practices, rootstock-scion selection, and adaptation strategies to enhance the resilience of pear orchards under changing climate conditions.

Research funded by the European Union – NextGenerationEU, Ministero dell’Università e della Ricerca - Piano Nazionale di Ripresa e Resilienza, D.M. 630/2024.

How to cite: Bigoni, M., Marrocchino, E., Viola, I., Zaccarini, M., Farinelli, A., and Ferroni, L.: Linking soil texture and organic carbon to leaf chlorophyll fluorescence in Pyrus communis orchards: a multi-site study in Emilia-Romagna, Italy , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18092, https://doi.org/10.5194/egusphere-egu26-18092, 2026.

Understanding the interactions (synergies and trade-offs) among ecosystem services (ESs) and their driving factors is crucial for sustainable ecosystem management under intensifying climate change and anthropogenic disturbances. In recent years, machine learning approaches have demonstrated strong potential in capturing nonlinear relationships and exploring the driving mechanisms of ES interactions. However, most existing studies provide unified explanations at the global scale and often overlook the spatial heterogeneity and spatial dependence inherent in geographic locations, thereby limiting the ability to reveal the differentiated effects of the same driving factors on ES synergies and trade-offs across regions. This gap becomes particularly critical in large river basins, where pronounced environmental gradients, spatial connectivity, and heterogeneous human activities jointly drive strong spatial differentiation in ecosystem processes and services.

In this study, we develop a geospatially explainable machine learning framework to more explicitly characterize the spatial variability of ES interactions and their formation mechanisms in the Yangtze River Basin, China. Specifically, six key ESs, including food supply (FS), water yield (WY), water purification (WP), soil conservation (SC), carbon sequestration (CS), and habitat quality (HQ), were quantitatively assessed for the period from 2000 to 2023. Spearman correlation analysis and geographically weighted regression (GWR) were then employed to identify the ES relationships and their spatial distribution patterns. Furthermore, the GeoShapley method was introduced to incorporate geographic location into the model interpretation process, thereby enhancing the transparency and interpretability of machine learning decisions. From a spatial interaction perspective, this approach enables the analysis and visualization of the differentiated driving effects of climate conditions, topography, land use, and human activities on ES synergies and trade-offs across different spatial locations.

This study shows that the geospatially explainable framework enhances insights into the formation mechanisms of ES interactions and provides scientific support for implementing zoned ecosystem management and targeted regulation strategies under ongoing global environmental change.

How to cite: Jiang, C., Yao, Y., and Ma, L.: Ecosystem service interactions and their driving factors based on a geospatially explainable framework: A case study in the Yangtze River Basin, China, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18238, https://doi.org/10.5194/egusphere-egu26-18238, 2026.

Droughts across India exhibit variability arising from the complex interaction between atmospheric forcing and terrestrial hydrological processes. Although precipitation deficits are generally considered the primary trigger for drought, changes in terrestrial water storage dictate how drought evolves and recovers. It is therefore essential to understand how surplus and deficits in water balance governs not only the drought periods across different hydroclimatic zones of India but also the subsequent influence on vegetation health. In this study, we analyze how water balance components regulate vegetation by assessing the elasticity of vegetation to climatic and catchment storage variables. A dominant driver approach is used to evaluate whether vegetation response is mainly controlled by meteorological or terrestrial variability. Furthermore, we analyzed the influence of key drought attributes, including severity, duration, development and recovery speeds, on vegetation elasticity with respect to climate and catchment variables. The results show a shift from precipitation-dominated vegetation control during mild drought conditions to storage-driven regulation under extreme droughts. These findings highlight the role of subsurface water storage in buffering vegetation against severe drought stress across India. Overall, this analysis offers valuable insights into the processes controlling vegetation resilience and susceptibility, allowing for a more refined understanding of vegetation-catchment-climate interactions across diverse drought conditions.

How to cite: Bilal, S. B. and Gupta, V.: Role of Water Balance Components in Regulating Vegetation Response to Drought , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18248, https://doi.org/10.5194/egusphere-egu26-18248, 2026.

Accurate estimation of gross primary productivity (GPP) in croplands is essential for quantifying terrestrial carbon uptake and understanding carbon–water coupling under increasing agricultural water stress. Conventional Light Use Efficiency (LUE) models typically rely on evaporative fraction (EF), derived from total evapotranspiration (ET), which does not distinguish between productive transpiration and non-productive evaporation. In contrast, transpiration-based framework explicitly represent the physiological coupling between carbon assimilation and water loss regulated by stomatal conductance. In this study, transpiration is estimated using a Leaf Area Index (LAI)-based approach driven by remotely sensed MODIS data and environmental variables within the underlying Water Use Efficiency (uWUE) framework.

We evaluate the transpiration-based uWUE model against an EF-based LUE model for GPP estimation using eddy covariance observations from 51 globally distributed cropland sites. The dataset includes 6 sites from India (Flux Tower and INCOMPASS networks), 3 sites from Japan (AsiaFlux), 9 sites from Europe, and 33 sites from the United States (FLUXNET), spanning a wide range of hydro-climatic and management conditions. Model performance was assessed using the coefficient of determination (R²), root mean square error (RMSE), and bias.

The transpiration-based uWUE model showed overall better agreement with observed GPP than the EF-based LUE model across the global set of crop sites. Improvements were evident in both the strength of the relationship with observations and the reduction of estimation errors. At the site level, uWUE more frequently achieved higher R² together with lower RMSE, demonstrating consistent performance across multiple evaluation metrics at a larger number of sites. Superior performance was observed at 28 sites, driven by the model’s ability to capture coupled carbon–water dynamics under varying crop types, canopy structures, and climatic conditions. In contrast, the EF-based LUE model showed advantages at a limited number of sites characterized by distinct water stress regimes or vegetation properties.

Overall, the results highlight the critical role of transpiration dynamics in GPP estimation, with higher GPP values associated with dense canopies and favorable environmental conditions. By explicitly isolating transpiration from total evapotranspiration, the uWUE framework provides a more physically meaningful representation of carbon–water interactions than ET-based approaches. These findings demonstrate that incorporating transpiration-based constraints improves GPP estimation in croplands and has important implications for large-scale agricultural carbon cycle assessments under future climate scenarios characterized by increased water stress and drought frequency.

How to cite: Harde, S. and Rajasekaran, E.: Improved Estimation of Gross Primary Productivity in Global Croplands Using a Transpiration-Based uWUE Model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18930, https://doi.org/10.5194/egusphere-egu26-18930, 2026.

Climate change and intensifying droughts represent a critical challenge to agricultural productivity and soil sustainability. This study evaluated the effect of two superabsorbent amendments with contrasting chemical compositions (polyacrylate-based polymer and a biodegradable polysaccharide nanocomposite) on carbon dynamics in common beans grown under drought conditions. The experimental design included analyses of morphological parameters, elemental composition, ¹³C allocation, and soil density fractionation. The results showed that drought drastically reduced biomass and nitrogen in leaves and roots, increased C:N ratios, and decreased root-derived carbon (RDC) incorporation, especially in stable soil fractions. The application of superabsorbents reversed these effects, increasing ¹³C translocation to roots and RDC in soil. NSN stood out for its ability to increase total RDC compared to the drought control parallelling the irrigated control in the heavy fraction associated with minerals, a key indicator of stable carbon sequestration. In contrast, Com mainly promoted flow to labile fractions, with less impact on stabilisation. These findings demonstrate that superabsorbents might be an effective tool for sustaining crop productivity and strengthening carbon sequestration in agroecosystems under conditions of increasing aridity.

How to cite: Guarda Reyes, M., Calabi Floody, M., Biron, P., Salvidar, M., Mora, M. D. L. L., and Rumpel, C.: Enhancing carbon sequestration in water stressed plant–soil systems through soil amendment with a Superabsorbent Nanocomposite derived from natural materials, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19408, https://doi.org/10.5194/egusphere-egu26-19408, 2026.

Continuous, spatially explicit estimates of environmental attributes are increasingly provided as gridded data. The accuracy of gridded data, including classifications derived from remotely-sensed data, is typically evaluated using measures based on confusion matrices with site-specific class allocations; however, these measures are defined for categorical variables and are therefore not applicable to ratio-scale attribute estimates representing quantities, such as canopy height or population abundance.

We present an approach that extends commonly used agreement measures, i.e. the Jaccard index, Precision, Recall, and F-score, to non-negative, continuous ratio-scale attributes. The extended measures (cJaccard, cPrecision, cRecall, and cF-score) are viable equivalents to their binary counterparts, invariant to data imbalance and suitable for evaluating the agreement of various types of data representing ratio-scale attribute estimates. The cJaccard measure has proven useful for a range of applications in the geospatial domain, illustrating the broader potential of these measures for evaluating large-scale environmental gridded data products and beyond.

The aim of this contribution is to showcase and discuss the practical application of these continuous agreement measures to real-world gridded datasets representing spatial-environmental variables. Through applied examples, we demonstrate how cPrecision and cRecall enable a directional interpretation of disagreement, disentangling commission and omission errors in the total proportion of misallocated magnitudes. We further illustrate how cJaccard provides a bounded, scale-independent measure of agreement that complements typically used error-based measures (such as Mean Absolute Error or Root Mean Square Error) in the data comparison process.

How to cite: Krasnodębska, K., Goch, W., Uhl, J. H., Verstegen, J. A., and Pesaresi, M.: Agreement measures for continuous, ratio-scale data: cJaccard, cPrecision, cRecall and cF-score, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20818, https://doi.org/10.5194/egusphere-egu26-20818, 2026.

Cropland abandonment is a key land-use change process within the human-environment system, shaped by diverse environmental and socio-economic determinants. However, many studies overlook the complex interrelationships among these determinants, which may result in the reconfiguration of agricultural landscapes. Here, we developed an analytic framework based on social-ecological system theory to map cropland abandonment archetypes in Sichuan Province, Southwest China, using a combination of biophysical conditions, proximity characteristics, socio-economic determinants, and the extent, cumulative proportion, and spatial configuration of abandoned croplands. We implemented self-organizing feature maps using a nested clustering approach, which resulted in 25 sub-archetypes and 6 meta-archetypes. We used random forest regressions to quantify the relative importance of explanatory determinants influencing archetype geographies. Our results revealed diverse cropland abandonment archetypes, with meta-archetype area shares ranging from 4.4 % to 48.4 %. The most widespread archetype was characterized by favorable terrain, low cropland per capita, and low cumulative proportions of abandonment. Determinants of meta-archetypes varied in their importance but consistently highlighted the role of environmental determinants (i.e., topography, temperature), as well as productivity-related and socio-economic determinants (i.e., employee wages, pension insurance, high-value crops) as the most important determinants. Our findings argue against one-size-fits-all solutions and are highly relevant to nuance existing regional land-use policies addressing cropland abandonment. They further allow targeting key determinants of cropland abandonment and considering regional and local socio-ecological contexts in decision-making processes.

How to cite: Hong, C.: Revealing nested archetypes of cropland abandonment based on social-ecological system theory, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21572, https://doi.org/10.5194/egusphere-egu26-21572, 2026.

Improving olive yield in Moroccan agro-ecosystems requires a better understanding of the interactions between water availability, soil properties, and management practices. The complexity and non-linear nature of these interactions limit the effectiveness of conventional analytical approaches. This study applies machine learning methods to predict olive yield and to assess how the importance of yield determinants varies under contrasting water regimes. A multi-site dataset from Moroccan olive groves, including more than 2,000 observations, was analyzed. Machine learning models showed high predictive accuracy across water regimes. Under rainfed conditions, CatBoost achieved the best performance (R² = 0.845), indicating that yield variability is mainly driven by soil properties and spatial context. Under irrigated conditions, XGBoost provided the highest accuracy (R² = 0.855), highlighting the increasing role of management practices such as planting density and nitrogen fertilization. Under intensive irrigation, fruit-related variables, particularly 100-fruit weight, became the dominant predictors, while the influence of edaphic constraints decreased.

Overall, the results demonstrate that irrigation does not simply increase olive yield but fundamentally alters the hierarchy of factors controlling production. These findings emphasize the need for data-driven, site-specific management strategies to enhance the sustainability and efficiency of olive production in Morocco.

How to cite: Azamz, R., Elyoussfi, H., Benzhair, F., El Mousadik, R., and Belaqziz, S.: Deciphering Olive Yield Determinants under Contrasting Water Regimes: A Multi-Site Machine Learning Approach in Morocco Agro-Ecosystems, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21818, https://doi.org/10.5194/egusphere-egu26-21818, 2026.

A new low-cost device based on Internet-of-Things (IoT) communication has been developed within the RemoTrees project to monitor climate-change effects in remote forest ecosystems. One of the key component of this device, referred to as the RemoTrees - beta, is a multispectral chipset composed of four sensors (three AS7265X and one AS7341), providing 26 spectral channels covering the range 410–940 nm. The chipset is equipped with a 1-inch diffuser designed to collect hemispherical solar radiation over incidence angles θ ∈ [−90°, +90°], with an angular response close to the cosine law. Here we present laboratory characterisation and calibration results obtained for 15 replicate RemoTrees - beta units. The spectral performance was highly consistent across devices, with central-wavelength variations below ~2 nm. Full width at half maximum (FWHM) values ranged from 19.17 to 47.93 nm, with standard deviations between 0.32 and 1.74 nm and a maximum relative expanded uncertainty of 0.90%. Because the devices will operate under highly variable illumination conditions (time of day, season, latitude, altitude, cloudiness, and canopy cover), optimisation of integration time (IT) and gain (G) is essential to avoid low digital-number (DN) values and insufficient use of the sensor dynamic range. As commonly applied in field spectrometry, automated IT/G optimisation and scan averaging are recommended to maximise signal-to-noise ratio (SNR) and minimise measurement uncertainty. When IT settings alone are insufficient to reach a satisfactory fraction of the dynamic range (≈65 000 DN; target ≥50%), summing of consecutive readings can be used to effectively increase the integration time while limiting saturation risks under rapidly changing sub-canopy light conditions. Radiometric sensitivity was evaluated by varying G and IT. Under optimised settings, SNR values up to ~5000 were achieved. For AS7265X sensors, gains G > 16 combined with IT optimisation increased SNR by up to ~4×, while for AS7341 gains G > 2 with IT optimisation yielded improvements up to ~5×. Detector nonlinearity contributes an expanded uncertainty of up to ±2.98% (k = 2) if uncorrected, which decreases to ≤±1.24% when nonlinearity correction is applied. The calibration coefficients derived from the tested devices showed moderate inter-device variability, with a maximum variation of approximately 10% for each spectral band. The RemoTrees - beta light sensor demonstrates stable spectral performance, high achievable SNR, and manageable inter-device variability, supporting its suitability for large-scale deployment in forest monitoring networks. Proper optimisation of integration time, gain, and signal averaging is essential to fully exploit the sensor dynamic range and minimise uncertainties under highly variable illumination conditions. Ongoing field deployment will further validate these strategies and refine operational protocols for long-term climate monitoring applications.

How to cite: Mihai, L., Toma, C., Mihalcea, R., Sakowska, K., Vescovo, L., Belelli Marchesini, L., Coppola, V., and Valentini, R.: Performance and optimisation strategy of a multispectral sensor as part of a newly developed low-cost IoT device for forest monitoring (RemoTrees - beta), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21910, https://doi.org/10.5194/egusphere-egu26-21910, 2026.

Bog peatlands in northwestern Germany release high amounts of greenhouse gas (GHG) emissions. Most of these bogs were drained, resulting in intensively used grasslands primarily for dairy production. While dairy production is economically highly important in the region drained bogs with intensive grassland use show high CO₂ emissions. To reduce GHG-emissions from intensively managed grasslands on bogs used for dairy production, the GreenMoor project investigates the effects of different water management approaches, such as such as subsurface irrigation and ditch blocking, as well as different usage practices including different fertilization intensities and pasture or cutting regimes. With a unique and expansive setup, we investigate the full GHG-balance of these different variants using manual chambers. We aim to present preliminary results from the first project phase including preliminary GHG-balances and an outlook on the potential success of different management approaches to reduce GHG-balances from drained intensively used bogs.

How to cite: Taube, R., Köhn, D., Gerken, H., Krause, A., and Jurasinski, G.: Impact of Water Management and Land Use Practices on Greenhouse Gas Emissions from an Intensively Farmed Bog Grassland in Northwest Germany, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-23185, https://doi.org/10.5194/egusphere-egu26-23185, 2026.

Urbanization, together with increasing global population pressure and climate variability, has introduced heat-related challenges across urban areas, severely impacting humans and the Earth. The rapid population growth has placed India at the top of the global population ranking. Demographic surges concentrate stress on existing urban systems, making Indian metropolises-both inland hubs and rapidly transforming coastal centers-critical laboratories for studying UHI dynamics.

The understanding of patterns and possible causes of the UHI effect due to urbanization-induced anthropogenic activities is a vital area in urban climate research. This study presents an overall multi-decadal day/night spatiotemporal seasonal analysis and trends in LST and UHI for six Indian cities: Ahmedabad, Mumbai, Panjim, Mangalore, Kochi, and Thiruvananthapuram, spanning the last three decades.

MODIS LST and AOD data are used to explain the possible reasons for the change in LST and UHI, focusing on the seasonal thermal behavior of cities under prevailing atmospheric, meteorological, and anthropogenic conditions. The Landsat series datasets are used to develop LULC maps and delineate high-resolution UHI zones, to explain shared trajectories and city-specific patterns that expose complex vulnerabilities within urban ecosystems in India. The findings, which integrate multi-decadal 30-year satellite-derived LST, LULC, and AOD data, demonstrate that greater increases in nighttime LST are associated with a decrease in the diurnal temperature range across all cities. Mumbai consistently showed lower mean LST values compared to Ahmedabad, which exhibited substantially higher values and extreme seasonal amplitudes ranging from 17.23 °C to 50.05 °C. Goa and Mangalore depicted a 1-4 °C increase in seasonal mean LST between 1993 and 2023. Corresponding to a rise in built-up area and a decline in vegetation, Kochi too exhibited a rise in LST. Thiruvananthapuram showed a strong warming, with a mean LST increase of about 3°C. AOD patterns also demonstrated similar spatial and temporal gradients across cities, helping to reinforce land-use change, urban expansion, and inland-coastal climatic contrasts as the significant causes of LST trends.

Collectively, these findings reveal how land-use transition, and climatic variability, significantly alters the thermal environment of Indian cities; making such studies important for climate-responsive planning and better urban management to enhance resilience and thermal comfort.

How to cite: Rai, R. and Murali R, M.: Utilising geospatial data to understand urban heat island and its effect on urban thermal comfort in selected Indian cities using Remote Sensing and GIS, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-488, https://doi.org/10.5194/egusphere-egu26-488, 2026.

Seagrass ecosystems in Indonesia provide a diverse array of services and societal benefits that helps to mitigate the impacts of climate change, yet they face complex threats and ongoing declines. Assessing their diverse values through pluralistic lenses can provide important baseline information to guide future conservation and restoration policies. Utilising the Seagrass Ecosystem Contributions to People (SCP) framework, a systematic review was conducted in representative seagrass ecosystem regions—west (Bintan), central (Selayar), and east (Ternate)—to examine the current state of research on their diverse values. Specifically, we identified the presence, perceived worldviews, characteristics, specific values, and their overlaps of SCP categories.

Publications were retrieved from Scopus, Web of Science, and the first ten pages of Google Scholar between February and April 2025. Then, following the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 Guideline, a thorough literature analysis was conducted using six established inclusion criteria. Present SCPs, perceived worldviews, specific values, and their overlaps were assessed in accordance with core meanings derived from McKenzie and Colleagues, the Intergovernmental Science-Policy Platform on Biodiversity and Ecosystem Services (IPBES) report on the diverse values of nature, and Himes and Colleagues’ publication, respectively.

Overall, 54 publications were included in this review, spanning the years 1989 to 2025 and identifying 25 SCPs across three regions, with a decreasing number of studies for each SCP from west to east. There were imbalances in the SCP perception, with bioindicator and scientific research being perceived in all regions and having twice the number of publications compared to other SCPs. These two prevalent SCPs generally studied the ecological status of seagrasses, their associated biota, and experimental results on their monitoring methods (e.g. remote sensing).  

Biocentric and anthropocentric worldviews were researched more and dominated interchangeably between SCPs, focusing on seagrass conservation values and societal perceptions of its services. Meanwhile, the pluricentric worldview had singular studies limited to several Material and Nonmaterial SCPs. Excluding the east region, all three specific values (intrinsic, instrumental, and relational) were present, with instrumental as the most frequent overlapping value. These value overlaps demonstrated fuzzy boundaries between material and nonmaterial groups, but not with the regulating SCPs, which were all studied with a singular specific value.

Regional differences in seagrass ecosystem management, benefit utilizations, and research focus might reflect the variability of the perceived SCPs, worldviews, and value overlaps. Although these perceptions are still biased towards tangible benefits for human ends. However, most of the reviewed publications were short-term studies and distinct from each other, demonstrating the need for local experts’ knowledge elicitation to further weave the information. Our study further developed the SCP framework by incorporating the concept of nature’s diverse values, which is highly relevant and applicable to the seagrass socio-ecological setting and management initiatives in Indonesia.

How to cite: Widanto, D. S., Sasmito, S. D., and Waltham, N.: A systematic review of the diverse values of Seagrass Contributions to People (SCP) in Indonesia: A pilot study, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-984, https://doi.org/10.5194/egusphere-egu26-984, 2026.

The EU Nature Restoration Regulation is the first continent-wide, comprehensive law of its kind and is a key component of the EU Biodiversity Strategy. This sets binding targets to restore degraded ecosystems, particularly those with the most potential to capture and store carbon and to prevent, and reduce, the impact of natural disasters. The EU Nature Restoration Regulation contains seven specific targets, including:

‘marine ecosystems – restoring marine habitats such as seagrass beds or sediment bottoms that deliver significant benefits, including for climate change mitigation…….’

The 800 hectares of seagrass meadows in South-West England are rightly regarded as important biodiversity ‘hot spots’, providing habitats for many species of juvenile fish, cuttlefish and sea horses. Many of the meadows in the region have been impacted by a ‘Seagrass Wasting Disease’ in the 1930s and the more recent damage caused by the anchoring of small boats (usually pleasure craft). This damage is being rectified by re-planting of seagrass, but many of those engaged in this work do not appreciate the full story behind the present distribution and development of the meadows.

The oldest seagrasses are known from the Maastrichtian of The Netherlands and are found in the Maastricht Chalk Formation (70 million years’ old). Between that time and the present day there are very few direct records of seagrass fossils, and this is because:

• Seagrass meadows from the tidal/inter-tidal boundary are not in an environment that is commonly preserved in the geological record; and
• In modern seagrass meadows, the plants are rarely – if ever – preserved and are rarely found in cores drilled into the meadows below ~30 cm.

In marine cores taken in Plymouth Sound and elsewhere in Southern England there are only low levels of carbon (spores, pollen, dinoflagellates, seeds, and organic debris) and not the high levels that would be required to suggest that sea grasses sequester high levels of ‘blue carbon’ for extended periods of time. The accumulation of low carbon levels can be explained by the enhanced sedimentation created by the seagrass, the so-called allochthonous carbon. The one element of carbon sequestration that is often ignored is that of foraminifera, ostracods and bryozoans, all of which are extremely abundant in meadow sediments. In many cases, the biodiversity of the foraminifera (>100 species) dwarfs the usual biodiversity counts of larger organisms. Such fixed calcium carbonate does have a long-term storage potential.

The other issue that can be ignored by those studying seagrasses is that the marine environment has undergone significant change throughout the 1 million years of the Pleistocene/Holocene and many of the seagrass meadows have only just re-established themselves following the Last Glacial Maximum, when sea levels were 120‒130 m below present-day levels. How seagrass migrated back into the present-day coastal areas is not yet fully understood, including the separation of the inter-tidal and sub-tidal taxa.

How to cite: Hart, M. and Fisher, J.: South-West England seagrasses: ecology, evolution and contribution to biodiversity and carbon sequestration , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4468, https://doi.org/10.5194/egusphere-egu26-4468, 2026.

To support resilient community planning and informed hazard mitigation decisions, having an effective flood risk evaluation is very important especially in coastal and flood prone areas. This presentation is focused on the development of an interactive web-based decision-making platform designed to analyze future flood risk and elevation ordinance impacts across five parishes in Louisiana, USA. The website allows users to explore long-term flood risk projections and ordinance related costs over multiple future decades from 2030 to 2100. The platform integrates various geospatial datasets including multi-return-period flood depth projections, decadal population forecasts, and building inventories. Flood depth raster datasets are converted from raster to point data using python and then assigned to building data obtained from Coastal Protection and Restoration Authority (CPRA) using spatial join. Then the obtained datasets are used to calculate Average Annual Loss (AAL) for different elevation ordinances. This framework incorporates a range of flood elevation ordinances, including ASCE 24-14, ASCE 24-24, and freeboard-based standards (BFE +1’, +2’, and +3’), with ordinance costs and risk outcomes by decade. ArcGIS Pro is used for spatial analysis and 3D geospatial visualization, while interactive webpages and different elevation ordinance scenario comparisons are implemented with react vita app. To improve accessibility for non-technical users, the website integrates AI-driven features that assist users in navigating the tool, interpreting results, and comparing ordinance scenarios. The platform supports hotspot analysis, side-by-side visualization of present and future flood risks, and iterative refinement through user feedback sessions. Overall, this tool provides planners, homeowners, and policymakers with a forward-looking environment to assess flood mitigation strategies, ordinance performance, and population-driven risk changes over time by combining advanced spatial analytics with interactive and user-centered design.

How to cite: Kunku, L. P., Friedland, C. J., and Mostafiz, R. B.: Assessing Long-Term Flood Risk and Elevation Ordinance Comparisons Using a Web-Based Geospatial Decision Tool, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4510, https://doi.org/10.5194/egusphere-egu26-4510, 2026.

The attenuation of atrazine in the saline water of the hypersaline Pétrola lake from a natural reserve (SE Spain) was studied to get more insight into the processes governing the fate of the contaminant in highly saline environments. In microcosms, the water column was spiked with 15.4 mg/L of atrazine for 24 days. Before atrazine amendment, the initial distribution of bacterial community was mostly composed of Proteobacteria (25.5 %), Cyanobacteria (25.2 %), Actinobacteriota (18.5 %), Verrucomicrobiota (11.5 %) and Bacteroidota (10.1 %). Within the mayor phyla, the most abundant families were identified as Cyanobiaceae (25 %), Rhodobacteraceae (10 %), Alcaligenaceae (9.9 %), Microbacteriaceae (7.3 %) and a poorly described PeM15 (6.2 %).

The reduction of atrazine concentration in the water column reaches 86.9 %, which means a reduction of dissolved atrazine mass of 98.1 %. Parallel to the decrease in atrazine, the amount of its intermediate degradation metabolite, desethylatrazine, increased. Desethylatrazine was the major short-term metabolite within the first 8-12 days, indicating the potential activity by atrazine-degrading bacteria. No deisopropylatrazine was detected in the saline water above detection limit. Microbiology results showed that atrazine can be removed from the saline lake environment. After atrazine amendment, the taxonomic bacterial composition at phylum level shifted to Proteobacteria (60.8 %), Patescibacteria (9.7 %), Bacteroidota (7.3 %), Campylobacterota (6.4 %) and Actinobacteriota (2.1 %). Atrazine supplementation suggested a selective pressure on bacterial structure morphology through the emergence of different dominant groups (i.e., Campylobacterota) or even the eradication of those phyla of bacteria capable of photosynthesis (i.e., Cyanobacteria). At family level, Rhodobacteraceae (16.7 %), Burkholderiaceae (11.7 %), Thiomicrospiraceae (7.9 %), Methylophagaceae (6.7 %), Sulfurimonadaceae (4.4 %) and Solimonadaceae (3.3 %) were the most abundant in the water column at the end of the experiment.

Related atrazine-degrading families established at the end of the experiment were Rhodobacteraceae, Solimonadaceae, Pseudomonadaceae, Rhizobiaceae, Chromatiaceae, Bacillaceae, Xanthomonadaceae, Caulobacteraceae, Moraxellaceae, Streptomycetaceae, Microbacteriaceae and Nannocystaceae. Related candidates such as Pseudomonas paralactis, Microbacterium sp., or Arthrobacter sp., among others, were isolated in water samples from previous studies. The bacterial candidates for atrazine degradation identified in the water column indicate that the herbicide acted as a selective pressure factor, altering the composition of the bacterial pattern. The water column would constitute a reactive environment which may govern the fate of pesticides in saline surface water bodies.

How to cite: Espín Montoro, Y., Martínez Couque, G., Fernández Pérez, J. A., Álvarez Ortí, M., and Gómez Alday, J. J.: Selective pressure of atrazine on bacterial pattern in a hypersaline lake environment , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5322, https://doi.org/10.5194/egusphere-egu26-5322, 2026.

Microorganisms in estuarine and coastal ecosystems are subject to changes in salinity and nutrient loads as well as threats from emerging contaminants, sea level rise, extreme weather patterns, and human encroachment. These ecosystems are of economic and ecological importance due to their biological diversity as well as their role in carbon sequestration, flood protection, and erosion prevention. However, the microbial community structure in the sediment of estuarine systems remains under researched despite the abundant ecosystem services they provide. In this study, we surveyed 25 sites within Econfina River State Park located in the eastern portion of the Northern Gulf of Mexico along a salinity gradient from freshwater upstream to coastal seagrass beds downstream. DNA extracted from the top 10 cm of sediment were 16S rRNA amplicon sequenced to determine microbial community structure. Results contribute to the understanding of microbial ecology of coastal ecosystems in the Northern Gulf of Mexico.

How to cite: Parker, S. G., Tryzbiak, B., Patel, A., Pereira, G., Chambers, L., and Beazley, M.: Spatial Variation in Sediment Bacterial Communities Along a Salinity Gradient in a Northern Gulf of Mexico Coastal Ecosystem, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6116, https://doi.org/10.5194/egusphere-egu26-6116, 2026.

Evidence suggests cetaceans utilise magnetoreception to navigate using magnetic fields. However, disturbances in the geomagnetic field from solar storms and anthropogenic activity can lead to beachings. Previous studies indicate fluctuations around 50 nT are large enough to influence strandings. Ísafjarðardjúp is home to a large humpback whale population in the summer, but marine activity, including fish farms, vessel traffic and coastal structures such as the Bolafjall radar station, makes the fjord prone to magnetic interference, potentially intefering with magnetoreception.  

How to cite: Rahman, A.: Magnetic Disturbances to Cetaceans in Isafjörðurdjup, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8273, https://doi.org/10.5194/egusphere-egu26-8273, 2026.

Plant responses to dry environments are shaped by diverse adaptive strategies linked to plant hydraulic traits, as reflected by the coexistence of deciduous and evergreen tree species in tropical seasonally dry forests. Empirical evidence suggests that leaf shedding is associated with declining leaf water potential, while leaf flushing depends on xylem rehydration. However, these physiological mechanisms are rarely incorporated into Dynamic Global Vegetation Models (DGVMs), which typically represent drought deciduous phenology using highly-simplified, threshold-based schemes with fixed rates of leaf phenological change. Here, we develop a stress–gradient based phenology scheme in which leaf shedding and leaf flushing are driven by the temporal gradients of leaf water potential and xylem water potential, respectively. This gradient–driven phenology mechanism was implemented in the LPJ-GUESS DGVM and validated with in-situ observations of phenological responses along hydraulic gradients. The new model has successfully reproduced phenological dynamics for the 7 selected locations and substantially improves model performance in simulating plant transpiration. We provide evidence that plant hydraulics are key controls for the phenological dynamics of tropical dry forests. The proposed stress-gradient phenological mechanism, linking phenology to plant hydraulic status, is an efficient approach to represent landscape phenology and improve simulations of water and carbon cycling over the tropical drylands. It may also help improve our understanding of forest response to drought stress, which remains largely unknown under warming climates.

How to cite: Zhu, Y., Pugh, T. A. M., and Wu, M.: Modelling Tropical Dry Forest Phenology from a Plant Hydraulic Perspective, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12529, https://doi.org/10.5194/egusphere-egu26-12529, 2026.

Canada’s terrestrial ecosystems play a critical role in the global carbon cycle and are being affected by unprecedented climate change and wildfire disturbance. However, we have an incomplete understanding of Canada’s historical carbon cycle. Existing assessments, conducted at varying spatial scales, use a wide range of data sources and methodologies, which lead to significant differences in the estimated strength of Canada’s land carbon sink over recent decades. Moreover, many approaches (e.g., inversions and data-driven estimates) have a limited ability to disentangle the relative contributions of different processes to the carbon sink over the recent past (1700 - 2022). We addressed this gap using a land surface model recently tailored to Canada and the most comprehensive information depicting wildfire disturbance and timber harvest available to make, to our knowledge, the first physically coherent wall-to-wall estimates of all major carbon pools and fluxes for Canada. We show that Canada’s terrestrial ecosystems have been a carbon sink since the mid-20th-century, due to the influence of wildfire and timber harvest before 1940. Since the early 2000s, wildfire disturbance has been driving Canadian forests towards becoming a carbon source. Based on our findings from a purely process-oriented perspective, projected increases in wildfire activity will further impact the strength and direction of Canada's terrestrial carbon sink.

How to cite: Curasi, S., Melton, J., Humphreys, E., Arora, V., Beaver, J., Cannon, A., Chen, J., Hermosilla, T., Lee, S.-C., and Wulder, M.: Canada’s forests shifting from a recovery-driven carbon sink to a disturbance-driven carbon source, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14857, https://doi.org/10.5194/egusphere-egu26-14857, 2026.

Sea level rise (SLR) is a key driver in altering spatial boundaries, species distribution, and functioning of coastal wetlands in the 21st century. Wetland adaptation to SLR depends on vertical accretion and landward migration; however, the magnitude and rate of these processes remain uncertain and are constrained by factors such as sediment supply and the availability of inland accommodation space. To enhance adaptive capacity, spatially explicit assessments are critical for identifying areas suitable for wetland migration. Nevertheless, much of the existing literature emphasises global-scale analyses with coarse spatial resolution and limited use of local SLR projections, which reduces their applicability for regional and local decision-making.

We conducted a scenario-based assessment of the potential extent of landward migration for mangroves and saltmarshes in Victoria, Australia, using high-resolution (10 m) regional spatial data under two socio-economic pathways (SSP2 and SSP5) for 2070 and 2090. The results indicate that, for both ecosystems, potential area gains from landward migration exceed losses from seaward inundation. For saltmarshes, ecosystem losses are driven more by mangrove encroachment (53%) than by inundation (47%). Land tenure emerges as a key factor shaping wetland migration capacity. Future accommodation space for mangroves is largely under public ownership (56%), primarily within protected areas and nature reserves (56.2%), providing a relatively secure buffer for inland migration. In contrast, most accommodation space for saltmarshes is privately owned (56.4%) and predominantly associated with primary production land use (45.4%). Without specific management actions, saltmarshes are likely to experience losses from both expanding mangroves and ongoing land-use pressures. Overall, these findings provide valuable insights to support stakeholders in scenario-based planning and the management of coastal and urban areas to enable wetland adaptation to rising sea levels.

How to cite: Perera, N., Wartman, M., Nuyt, S., Macreadie, P., and Duarte de Paula Costa, M.: Landward Migration of Coastal Wetlands under Land-Use Constraints in Australia, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15259, https://doi.org/10.5194/egusphere-egu26-15259, 2026.

         To address the intensifying urban heat island (UHI) effect driving by rapid urbanization, current research reveals a significant scale discontinuity between macro-level strategies, such as regional cooling network design, and micro-level studies that focus on localized cooling mechanisms of individual green patches. Macro-scale approaches often overlook small cooling islands embedded within dense urban fabrics, while micro-scale investigations lack systematic understanding of inter-patch connectivity. This study proposes a multi-scale cooling island ventilation network to synergistically mitigate UHI impacts across spatial hierarchies. Using the core area of Changsha City as a case study, the research introduces an innovative three-tier scale classification framework incorporating building density. By integrating relative land surface temperature and morphological spatial pattern analysis, the study identifies core cold island sources. Further, a cold island ventilation resistance surface is constructed using the CRITIC objective weighting method, enabling the identification of key nodes and corridors for establishing a comprehensive multi-scale ventilation network. Findings reveal that, amidst urban expansion and increasing building/road densities, landscape fragmentation has led to a “shrinking-in-size, growing-in-number” trend for both primary and secondary cold island sources. From 2009 to 2016, the total area of primary-scale cold sources declined sharply from 45 km² to 19.8 km², while their number rose from 130 to 151. The average patch size fell from 0.35 km² to 0.07 km², and the minimum temperature increased from 28.7 °C to 35.3 °C-signaling a depletion risk. Similarly, secondary cold sources shrank from 215.38 km² to 144.83 km², as their number increased from 123 to 169, with average patch size dropping from 1.75 km² to 0.86 km²-weakening their thermal buffering capacity. Despite this, ventilation corridors peaked in 2020, totaling 371 in number and 528.5 km in length, continuing to act as "relay stations" transmitting peripheral cooling effects to the urban core. Notably, tertiary cold sources rebounded after 2016 due to strengthened ecological conservation efforts, expanding by 237.5 km² by 2020. Their temperatures stabilized between 35–38 °C—significantly cooler than the urban core—demonstrating sustained cooling potential. Policy recommendations are proposed across three spatial scales: 1) primary scale, remove obstructions at cold source points to broaden cooling supply channels; 2) secondary scale: prioritize the protection of key corridors and junctions to preserve inter-patch connectivity and maintain dynamic cold air flow; 3) tertiary scale: safeguard and enhance core ecological areas to ensure stable and continuous cooling output. By identifying cold island sources and constructing a multi-scale ventilation network, this study offers a science-based framework for optimizing thermal environments in high-density urban areas.

Graphical Abstract

How to cite: Zhong, X., Wei, B., Liu, L., and Huang, Y.: Constructing a Multi-Scale Urban Cooling Island Ventilation Network to Mitigate the Urban Heat Island Effect: A Case Study of Changsha, China, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15541, https://doi.org/10.5194/egusphere-egu26-15541, 2026.

Mediterranean forest ecosystems are currently facing severe challenges due to the combined pressures of biotic and abiotic stressors. In particular, Holm oak (Quercus ilex L.) forests are experiencing a widespread decline driven by the effects of climate change-induced drought and the aggression of the soil pathogen Phytophthora cinnamomi. This decline threatens not only forest biodiversity but also the stability of essential ecosystem services. In response to this problem, the LIFE RECLOAK project aims to restore and improve the conservation status of these threatened habitats. The project adopts an approach involving the genetic selection of drought-tolerant and pathogen-resistant genotypes, their micropropagation, and subsequent planting in pilot sites across Italy, Spain, and Malta. Within this framework, Work Package 7 (WP7) is dedicated to the "Evaluation of ecosystem functioning and climate mitigation effects," validating the success of the reforestation efforts. Therefore, the primary objective of WP7 is to quantify the restoration of ecosystem processes and the enhancement of climate change mitigation potential provided by the selected resistant genotypes compared to traditional forest stock.

The activities of WP7 integrate field monitoring and modelling tasks. Firstly, the project will assess vegetation growth and biodiversity. In the pilot sites, key morphological parameters of Q. ilex (such as Basal Diameter (BD), Plant Height (PH), and Leaf Area Index (LAI)) will be measured annually to track biomass accumulation. Concurrently, biodiversity indexes (BI) will be calculated to monitor the recovery of understory vegetation. To evaluate the restoration of below-ground processes, soil quality will be assessed through measurements of soil respiration, Soil Organic Carbon (SOC), erosion rates, and Water Holding Capacity (WHC). Recognizing the slow growth rate of holm oaks, these monitoring activities are planned to continue for ten years after the project's conclusion, ensuring a long-term perspective on ecosystem recovery. Data collected from vegetation and soil monitoring will be used for the assessment of carbon sequestration, calculating the CO₂ absorbed by both the woody biomass and the soil compartment. WP7 will also develop a monitoring tool using the Biome-BGC Musso ecohydrological model. By integrating site-specific pedoclimatic data with the physiological traits of the resistant genotypes, this model will be calibrated to simulate carbon and water pathways (e.g., Water Use Efficiency) over the plantation's lifespan. This approach quantifies the added value of the resistant genotypes, demonstrating their superior resilience under changing environmental and management conditions.

Finally, under the coordination of the Democritus University of Thrace, WP7 will integrate these findings to analyze broader Ecosystem Services (ES), including provisioning, regulating, and supporting functions. Ultimately, by validating biological indicators and establishing a robust carbon monitoring protocol, WP7 will demonstrate the effectiveness of using improved genotypes, offering a replicable model for restoring Mediterranean areas affected by forest dieback.

How to cite: gori, A., beltrami, S., alderotti, F., ferrini, F., dibari, C., ferrise, R., paffetti, D., and brunetti, C.: Restoring Mediterranean holm oak forests: ecosystem functioning and climate mitigation in the LIFE RECLOAK project, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16743, https://doi.org/10.5194/egusphere-egu26-16743, 2026.

Magnetotactic bacteria (MTB) are an ancient microbial lineage that navigate geomagnetic field lines via intracellular magnetosomes, and their unique multi-disciplinary properties have long drawn research attention. This study focuses on MTB’s behavioral and metabolic adaptations under high magnetic fields—including extreme environments six orders of magnitude stronger than the geomagnetic field—and explores their application potential.Our recent progress is outlined as follows: 1) Using Magnetospirillum gryphiswaldense MSR-1 as the model strain, we analyzed how high magnetic fields reprogram MTB metabolism, modulate biomineralization dynamics, and impact MmaK scaffold assembly as well as magnetofossil genesis.2) We clarified the regulatory role of MTB-derived Mms6 protein in biomineralization, and synthesized magnetosome-mimetic nanocrystals in vitro that match natural magnetosomes in cuboctahedral morphology, soft ferromagnetic behavior, and high saturation magnetization. 3) We built a magnetic nanorobot-based navigation system to realize precise spatial control and trajectory planning of MTB, paving new ways for MTB-mediated nanodrug delivery and magnetic navigation.

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[3] Ma, Kun, et al. "Magnetosome-inspired synthesis of soft ferrimagnetic nanoparticles for magnetic tumor targeting." Proceedings of the National Academy of Sciences 119.45 (2022): e2211228119.

[4] TAO, Tongxiang, et al. A Precise BSA Protein Template Developed the C, N, S Co-Doped Fe3O4 Nanolayers as Anodes for Efficient Lithium-Ion Batteries. ACS Applied Energy Materials, 2022, 5.8: 10254-10263..

How to cite: Wang, J. and Ma, K.: Research progress on magnetotactic bacteria under high magnetic field, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17838, https://doi.org/10.5194/egusphere-egu26-17838, 2026.

Climate change is increasing the frequency and intensity of drought and heat events in Mediterranean regions, urging the need for resilient fruit crops that link stress tolerance to relevant fruit quality traits. My PhD project focuses on the strawberry tree (Arbutus unedo L.), an underutilised Mediterranean evergreen fruit species of considerable ecological relevance in Southern Europe, with a recognised capacity to cope with diverse abiotic and biotic constraints. The project objective is to characterise six Italian A. unedo populations in terms of physiological performance under water-limited conditions and fruit quality characteristics. The primary step is to select provenances with contrasting pedoclimatic characteristics and to use calculated climatic indices (e.g., Emberger’s Q2) across an aridity–temperature gradient. These provenances are then screened for constitutive traits under well-watered conditions combining measurements of xylem vulnerability to embolism formation (P50), water-use strategy (e.g., minimum epidermal conductance, g_min; specific leaf area, SLA), and cellular drought tolerance derived from pressure–volume analysis (turgor loss point, TLP; osmotic potential at full turgor, π₀; and modulus of elasticity, ε).  After that, inducible trait modifications are tested under water stress and recovery conditions, monitoring gas exchange, plant water relations, chlorophyll fluorescence parameters, hydraulic resistance, and growth. In parallel,  a core component of the work investigates fruit physiological performance across different ripening stages (identified by skin colour) and during post-harvest storage. Fruits, harvested at the yellow–orange stage, are analysed for respiratory activity using a custom fruit chamber coupled to a LI-COR 6800 system. Post-harvest dynamics are monitored under two storage treatments (ambient temperature vs. 4 °C) and related to quality attributes, including colour development, soluble solids (°Brix), firmness, weight loss, pectin content, sugar profile, and polyphenol-related traits. Within this post-harvest study, the project also considers the use of edible coatings as a practical tool to modulate storage techniques and help preserve the quality attributes of this perishable fruit. Therefore, integrating provenance screening with fruit respiration and post-harvest physiology provides a practical basis for selecting A. unedo genotypes with improved drought resilience and high fruit yield and quality, thereby fostering A. unedo cultivation in Mediterranean areas under a changing climate.

How to cite: Pascucci, G., Alderotti, F., Lo Piccolo, E., Beltrami, S., Detti, C., Baptista, A., Palchetti, V., Bini, L., Ferrini, F., Antunes, M. D., Giordani, E., Brunetti, C., and Gori, A.: Drought resilience and fruit performance in strawberry tree (Arbutus unedo L.) populations: ecophysiological screening and postharvest behaviour , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21475, https://doi.org/10.5194/egusphere-egu26-21475, 2026.

The role of wildfire as a controller in wildland ecosystems is well researched. However, much uncertainty is present with climate change. Will this morphing force turn into a game breaker in the longevity of terrestrial ecosystems? Or will it continue its role as the ultimate controller of vegetation composition, and for certain taxa, fecundity? This study aims to answer these questions for a study region situated in the northern segment of Eastern Mediterranean Basin – Anatolian Peninsula and its immediate surroundings. It considers the historical and potential future changes in biomass and fuel capacity in the region with respect to the changes in amplitudes of climate variability due to climate change in two distinct time periods (present and future). Changes in fire severity and fire return interval (FRI) are simulated using a dynamic vegetation model (LPJ-GUESS v.4.1) coupled with wildfire modules (SIMFIRE and BLAZE), and high-resolution climate datasets. For 1961-2025, the model is forced with ERA5-Land reanalysis data, and for 1961-2100, an ensemble of 5 CMIP6 datasets under the SSP 5-8.5 global warming scenario are used which are resized to 0.1°. While the historical trend analyses of the climate indices (such as SPEI) indicate strong drying for the region overall, simulation results signal an increase in burned area, the frequency of wildfire incidents, while highlighting important changes in vegetation composition and biomass under a changing climate, as wildfire turns into a response mechanism under increasing temperatures and changing rainfall patterns. 

How to cite: Ekberzade, B. and Görüm, T.: Control or destroy: Wildfire as a response mechanism, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-377, https://doi.org/10.5194/egusphere-egu26-377, 2026.

Fires ignited by human and lightning occur at distinct environments and thus diverge during their developing processes. A global characterization of fires by their ignition cause will inform fire forecast and prediction but is currently prohibited by a lack of ignition cause in global fire inventories. Here we develop a machine-learning classification system and ascribe the ignition cause of 65.17 million global, satellite-detected fire events during 2012-2024. According to this fire inventory, extratropical lightning fires exhibit longer duration, larger burned area and hotter flame, compared with human fires. Despite their contribution to only 2.4% of fire occurrence, lightning fires are responsible for 10.9% of extratropical burned area and 47.6% of that consumed by large fires over 100 km². This disproportionate abundance of lightning fires in the regime of most severe burning is attributable to synchronized seasonality of lightning ignition and burning conditions, as well as their scarcer accessibility to firefighting practices. Due to their closer linkage to the elongating fire-favorable weather, extratropical lightning fires has elongated by about 0.24 days decade^-1, outpacing human fires. With projected hotter, dryer, and stormier extratropical summers, our results provide a direct support for a future of severer lightning fires.

How to cite: Su, H., Qiu, K., Yu, Y., Tang, Y., Wang, S., Meng, X., and Guo, W.: Extratropical lightning fires burn increasingly more severe than human-ignited fires, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2363, https://doi.org/10.5194/egusphere-egu26-2363, 2026.

The 2023 Canadian fire season was record-breaking in terms of burned area and carbon emissions.  Yet, the climate impacts of these fires extend far beyond the immediate carbon emissions and can persist for decades. Post-fire changes in vegetation and surface properties prolong snow exposure during winter and spring, increasing surface albedo and producing long-lasting regional cooling impacts. Historically, the surface albedo-driven cooling has offset the warming influences of carbon emissions by boreal fires. However, with ongoing high-latitude warming, fire seasons are expected to become longer and more intense while spring snow cover declines. This combination may weaken the climate-cooling effect of post-fire surface-albedo changes and reduce the offset potential.

Here, we quantified and mapped the climate-cooling effects from post-fire surface albedo changes for the 2023 Canadian fire season under shared socioeconomic pathway SSP2-4.5 for a 70-year period. We estimate that the 2023 Canadian fires resulted in a time-integrated climate-cooling of –3.67 W m^-2 of burned area (95% CI: −4.83 to −2.51) over a 70-year period. Our analysis further shows that the climate-cooling impact of boreal fires has weakened by approximately 30% due to changes in snow cover and duration. This has significant implications for the ability of albedo-driven cooling to offset warming from fire emissions. As a result, we conclude that contemporary boreal fires are, on average, twice as likely to result in a net climate-warming effect relative to the 1960s.

How to cite: van Gerrevink, M. J., Gonsamo, A., Rogers, B. M., Potter, S., Zhong, Z., and Veraverbeke, S.: Climate-cooling impacts from post-fire snow-albedo for the 2023 Canadian fires season, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3494, https://doi.org/10.5194/egusphere-egu26-3494, 2026.

Biomass burning (BB) emissions in the Indo-China Peninsula (ICP) can be transported to southern China, perturbing the atmospheric environment and climate in southern China. However, the impact of these fire emissions transports on the terrestrial ecosystems in southern China remains unclear. Here we combine several state-of-the-art models and multiple measurement datasets to quantify the impacts of ICP fire-induced aerosol radiation and O₃ damage effect on gross primary productivity (GPP) in southern China during ICP fire seasons (March and April) in 2013-2019. Our results demonstrate that ICP fire-derived aerosols and O₃ collectively reduce annual mean GPP in southern China by 5.4% (13.86 TgC per burning season) under all-sky and 3.4% (12.87 TgC per burning season) under clear-sky conditions. In all-sky, fire aerosols decreased direct photosynthetically active radiation (PAR) by 2.68 W m⁻² while increased diffuse PAR marginally (+0.03 W m⁻²), driving a GPP reduction of 13.36 TgC per burning season across southern China. Concurrently, fire-induced O₃ reduces regional GPP by 0.54 TgC per burning season. In clear-sky, aerosols reduce direct PAR more sharply (−3.22 W m⁻²) but enhance diffuse PAR (+1.51 W m⁻²), resulting the GPP loss to 12.18 TgC, while O₃ damage effect is increased (−0.69 TgC). The fire aerosols contributed to 96.4% of the GPP reduction in all-sky and 94.6% in clear-sky, whereas ozone played a minor role (3.9% in all-sky and 5.4% in clear-sky). This study highlights ICP fire emissions as a significant driver of ecosystem productivity declines in downwind regions, influencing the regional land carbon cycle.

How to cite: Zhu, J.: Quantifying the multi-year impacts of Indo-China Peninsula biomass burning on vegetation gross primary productivity in southern China, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3711, https://doi.org/10.5194/egusphere-egu26-3711, 2026.

Fire is a global phenomenon and a key Earth system process. Extreme fire events have increased in recent years, and fire frequency and intensity are projected to rise across most regions and biomes, posing substantial challenges for ecosystems, the carbon cycle, and society. The Fire Model Intercomparison Project (FireMIP), launched in 2014, has contributed to advancing global fire modeling in Dynamic Global Vegetation Models (DGVMs) and improving understanding of fire's local drivers and local impacts on vegetation and land carbon budgets through land offline (i.e., uncoupled from the atmosphere) simulations. We now bring FireMIP into Coupled Model Intercomparison Project Phase 7 (CMIP7) to: (1) evaluate fire simulations in state-of-the-art fully coupled Earth system models (ESMs); (2) assess fire regime changes in the past, present, and future, and identify their primary natural and anthropogenic forcings and causal pathways within the Earth system, including the associated uncertainties; and (3) quantify the impacts of fires and fire changes on climate, ecosystems, and society across Earth system components, regions, and timescales, and elucidate the underlying mechanisms. FireMIP in CMIP7 will advance the fire and fire-related modeling in fully coupled ESMs, and provide a quantitative, detailed, and process-based understanding of fire's role in the Earth system by using models that incorporate critical climate feedbacks and multi-model, multi-initial-condition, and CMIP7 multi-scenario ensembles. Here, we presents the motivation, scientific questions, experimental design and its rationale, model inputs and outputs, and the analysis framework for FireMIP in CMIP7, providing guidance for Earth system modeling teams conducting simulations and informing communities studying fire, climate change, and climate solutions.

How to cite: Li, F. and the CMIP7 FireMIP group: The Fire Modeling Intercomparison Project (FireMIP) for CMIP7, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4207, https://doi.org/10.5194/egusphere-egu26-4207, 2026.

Although half of Earth’s population resides in the wildland-urban interface, human exposure to wildland fires remains unquantified. We show that the population directly exposed to wildland fires increased 40% globally from 2002 to 2021 despite a 26% decline in burned area. Increased exposure was mainly driven by enhanced colocation of wildland fires and human settlements, doubling the exposure per unit burned area. We show that population dynamics accounted for 25% of the 440 million human exposures to wildland fires. Although wildfire disasters in North America, Europe, and Oceania have garnered the most attention, 85% of global exposures occurred in Africa. The top 0.01% of fires by intensity accounted for 0.6 and 5% of global exposures and burned area, respectively, warranting enhanced efforts to increase fire resilience in disaster-prone regions.

How to cite: Sadegh, M., Seydi, S. T., Abatzoglou, J., Jones, M., and AghaKouchak, A.: Increasing global human exposure to wildland fires despite declining burned area, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4268, https://doi.org/10.5194/egusphere-egu26-4268, 2026.

Wildfires emit large quantities of brown carbon (BrC), a class of light-absorbing organic aerosols with poorly constrained climate effects. BrC exhibits highly variable absorptivity, from weakly absorbing chromophores in the near-ultraviolet to strongly absorbing "dark BrC" (d-BrC) extending into the visible spectrum, yet the optical properties, global prevalence, and radiative impact of d-BrC remain poorly understood.  Here we show that d-BrC is widespread in wildfire plumes globally, based on integrated analyses of aircraft, ground-based, and satellite observations. We found d-BrC mass absorption efficiencies of 0.5–1.5 m²/g at 500 nm, with absorption often comparable to or exceeding that of black carbon (BC). Implementing these observationally constrained optical properties in a global aerosol-climate model, we estimate a direct radiative effect (DRE) of +0.097 W/m² (range: +0.050 to +0.276 W/m²) from wildfire-derived BrC, with the upper bound surpassing BC and extending into mid- and high-latitude regions including the Arctic These findings position d-BrC as a critical but overlooked driver of wildfire radiative forcing, underscoring the need to account for its strong radiative effects on climate.

How to cite: Xu, L., Lin, G., and Liu, X.: Strong Shortwave Absorption by Wildfire Brown Carbon from Global Observations and Modeling, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4614, https://doi.org/10.5194/egusphere-egu26-4614, 2026.

The Fire INventory from NCAR (FINN) is a daily, high resolution (1 km) fire emissions inventory designed for use in atmospheric chemistry models. FINN uses a ‘bottom-up’ approach to estimate fire emissions. Satellite observations of active fires from MODIS (and VIIRS) are combined with land cover, emission factors and fuel loadings to predict fire emissions of key air pollutants. However, one of the key limitations of FINN is lack of peat fire emissions in the dataset, which only accounts above ground vegetation fires. Therefore, neglecting an important emissions source given the extensive abundance of peat in key tropical regions. Fires that occur on the surface of peatland can burn into the below-ground organic layers (up to 0.6 m). Peat fires can smoulder for weeks after the surface fire has extinguished, resulting in substantially greater emissions compared to surface vegetation fires. Therefore, it is essential to include peat fires in FINN.

Globally, peatlands cover >4 million km² (3 %) of the global land area. However, emissions from the combustion of tropical and Arctic-boreal peat alone account for a disproportionately large fraction of total global carbon emissions (13 %). This is driven by above ground fires burning into the carbon rich peat below.

We first focus on tropical peatlands in Indonesia since these have well documented impacts on air quality. Indonesia is home to a large proportion (36 %) of total tropical peatlands, and a large fraction of fires in Indonesia occur on peatlands. For example, in 2015 53 % of fires in Indonesia occurred on peatland, accounting for only 12 % of the land area. Peat fires contributed 71-95 % of the particulate matter (PM_2.5) fire emissions, though emissions are uncertain.

Our work builds upon previous work, which estimated Indonesian peat fire emissions for FINN.  Previously, satellite-derived soil moisture was used to determine a straightforward linear relationship with burn depth of fires that occurred on peatlands. We further develop this method adding additional complexity by using ground-based measurements of burn depth collocated with satellite soil moisture. We also consider canal density and fire frequency maps to account for changes in burn depth with drainage and fire history.

We plan to apply this method to other tropical peatland and boreal regions, so we welcome any discussions on our current work so far and/or future plans.

How to cite: Graham, A. M., Pope, R. J., and Chipperfield, M. P.: Accounting for peat fires in the Fire INventory from NCAR (FINN): Improved air pollutant emissions estimates for tropical peatlands using soil moisture, drainage density and fire history., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5608, https://doi.org/10.5194/egusphere-egu26-5608, 2026.

Pyrogenic airborne particle deposition downwind of active wildfires has traditionally been examined primarily as near-term hazards of fire spotting by firebrands or long-range transport of smoke particles (<10 µm). However, wildfires also emit substantial quantities of intermediate-sized airborne particles (10-2000 µm) that carry nutrients and contaminants affecting ecosystems downwind of the fire perimeter. The production, transport, and deposition of these intermediate-sized particles remain understudied. Here we develop a physics-based modeling framework for particle generation at fire lines, lofting by fire-driven convection, transport by prevailing winds, and subsequent ballistic settling. The framework enables characterization of this largely overlooked wildfire deposition footprint. Sensible heat flux from the fire feeds a convective plume capable of lofting particles to heights governed by fire intensity, particle size, shape, and density. Once aloft, particles are carried by ambient winds and ultimately ballistically deposited. The model performance was assessed using a unique dataset of particle deposition measured 3-40 km downwind of the fire front during the 2021 Caldor Fire. Supplemental observations of fire behavior, fuel properties, and meteorological conditions serve as inputs for model evaluation. The framework relies on various assumptions and constraints regarding unknown variables, including the mass fraction of emitted particles (5-7%), particle density (150-300 kg/m³), and drag coefficient formulation (fixed versus size-dependent), whose values were selected based on existing literature and physical plausibility. Over a 16-day sampling period, measured particle deposition ranged from 0.35 to 11.1 g/m². The largest deposition values (9.12-11.10 g/m²) occurred at collection sites closest to the fire (4-8 km), with progressively lower deposition (0.58-2.62 g/m²) observed at distant sites (10-40 km). When extrapolated to the landscape scale, a deposition rate of 10 g/m² over 1 km² corresponds to approximately 10 metric tons of pyrogenic material delivered to ecosystems for two weeks, an amount comparable to inputs from volcanic ashfall events. Within the modeling framework, simulations assuming a particle density of 300 kg/m³ and a pyrogenic emission fraction of 7% most closely matched field observations (RMSE < 1.8 g/m²; modest positive bias 0.8 g/m²; R > 0.90; p > 0.2). This configuration successfully reproduced both the magnitude and spatial gradients of observed pyrogenic mass deposition, demonstrating the framework’s potential to predict and quantify downwind delivery of wildfire-emitted particulate material to ecosystems.

How to cite: Scordo, F., Bavandpour, M., Or, D., Ebrahimian, H., Chandra, S., and Brahney, J.: Quantifying Downwind Deposition of Wildfire-Emitted Particles to Ecosystems, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5840, https://doi.org/10.5194/egusphere-egu26-5840, 2026.

Prescribed fire is the intentional use of fire under specific environmental conditions used to achieve specific land management objectives. Across the European Mediterranean basin, it is used for hazardous fuel reduction, pastoralism, habitat restoration, and silviculture. However, the ability to conduct prescribed burns is limited by meteorological conditions that facilitate the desired fire behavior to achieve the burns’ objectives, or the “burning window”. Under climate change, the continued availability of these conditions is highly uncertain as changes in the frequency and timing of these conditions are expected to occur. This presents a major challenge to future fire management planning. Here, we use projections of future climate based on scaling factors derived from the Coupled Model Intercomparison Project (CMIP6) and applied to ERA5 meteorology to quantify future changes in days suitable for prescribed burns (RxB days) across Mediterranean Europe. We find a 14% (-12 days) decrease in the number of RxB days across the region at a global warming level of 3.0°C, with losses most pronounced from April to October, particularly at the end of the spring burning window (May-June) and the beginning of the fall burning window (September-October). While some regions see an increase in winter burn days, these gains are outweighed by reduced burn days throughout the year. Future reductions in burn days were limited to 5% at 1.5°C, consistent with the commitments made in the Paris Agreement. Our results suggest that fire managers can expect a decline in opportunities to conduct prescribed burns, especially under higher warming scenarios. Thus, its continued use under these conditions will likely require significant investments and changes to current fire management policies to utilize and scale up remaining prescribed burning opportunities.

How to cite: Hsu, A., Abatzoglou, J., Fernandes, P., Ascoli, D., Clarke, H., Santin, C., Turco, M., Kolden, C., Patino, J. F., Rigolot, E., Carmenta, R., and Jones, M.: Prescribed Fire Opportunities in the European Mediterranean under Climate Change, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5864, https://doi.org/10.5194/egusphere-egu26-5864, 2026.

Fire is a dominant disturbance in tropical and subtropical dry forests and a major contributor to variability in carbon emissions, atmospheric composition, and land–atmosphere interactions. Despite their global extent and rapid transformation, the processes controlling fire size and extreme fire events in dry forest systems remain less understood than in savannas or humid tropical forests.

We investigated the controls on fire size using the South American Gran Chaco as a representative large-scale tropical dry forest system spanning strong climatic, ecological, and land-use gradients. We analyzed two decades (2001–2022) of satellite-derived fire patches from the FRY v2.0 burned-area database, combined with ERA5-Land meteorology and Fire Weather Index diagnostics, land-cover composition, landscape fragmentation metrics, topography, and anthropogenic pressure proxies. Our analysis focuses explicitly on fire size rather than fire occurrence, using statistical approaches and machine learning tools such as Random Forest models with SHAP-based interpretation to disentangle the relative and interacting roles of atmospheric forcing, landscape structure, and human-driven land transformation.

Our results show that fire size distributions are highly skewed across the region, with a small fraction of large and extreme events accounting for a disproportionately large share of total burned area. Wind and atmospheric dryness exert a strong influence on the final shape and size. At the same time, precipitation plays opposing roles by constraining fire spread through fuel moisture and enhancing fuel accumulation in fuel-limited environments. Landscape structure mediates the translation of meteorological extremes into large burned areas, with land-cover composition, fuel continuity, and fragmentation consistently ranking among the most influential predictors of burned area. Topography systematically emerges as the dominant predictor across subregions and seasons, acting not as a direct driver of fire spread but as an integrative proxy capturing hydrological gradients, vegetation structure, and human accessibility. Direct anthropogenic proxies show weaker importance at the event scale but exert strong indirect control through long-term land-use change and fuel reorganization, which in turn modulate fuel continuity and landscape configuration.

These results highlight tropical dry forests as a distinct fire domain where fire size emerges from coupled climate–biosphere–human interactions. By combining Earth observation fire products with explainable machine-learning approaches, this study advances understanding of fire–Earth system interactions and supports improved fire-risk assessment in rapidly transforming dry forest regions.

How to cite: San Martín, R., Ottlé, C., Sorenssön, A., Mouillot, F., and Vaittinada Ayar, P.: Atmospheric and landscape controls on fire size in tropical dry forests: insights from the South American Gran Chaco, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7609, https://doi.org/10.5194/egusphere-egu26-7609, 2026.

Fine fuel loads ignite easily because they dry rapidly and are therefore an important driver of wildfire occurrence and spread. Accurate modelling of fine fuel load dynamics is crucial not only for current and future wildfire prediction, but also carbon cycling. Current fire-enabled dynamic global vegetation models simulate fine fuel accumulation and decomposition, but using parameters that vary with plant functional types (PFTs). Observationally derived models from satellite products provide good estimates of fine fuel loads but cannot be used to predict how these will change in response to ongoing climate changes. We have combined an eco-evolutionary modelling approach to simulate litterfall with a simple empirical model of decomposition rate to predict fine litter loads. The litterfall model predicts the amount of leaf mass that is shed using leaf economics principles and predictions of optimal leaf area index to predict litterfall for evergreen and broadleaf trees and C₃ and C₄ grasses. The model of decomposition rate uses a generalised linear mixed model to fit a large available dataset of decomposition rate to three variables: C:N ratio representing the litter quality and growing degree days and dry days representing local climate. Both models were independently validated using field observations collated from the literature. We show that the combined model predicts the spatial and temporal variation in fine fuel loads reasonably well when compared to field observations and existing products. This new approach provides a robust framework to derive environmentally driven changes in fine fuel loads in the context of prognostic modelling of wildfires.

How to cite: Cain, S., Zhou, B., Prentice, I. C., and Harrison, S. P.: Annual Litter Fuel Load Estimation from Optimality-Derived Litterfall and Decomposition Dynamics, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8017, https://doi.org/10.5194/egusphere-egu26-8017, 2026.

The current methods to systematically validate Earth Observation (EO) products capturing transitory events such as fire activity rely mostly on the intercomparison between Near-real-time products without clearly identifying one as the reference dataset. In addition, due to the highly dynamic and ephemeral nature of such events, comparisons are restricted to near-simultaneous measurements which significantly limits the sample size of any intercomparison. In this study, we propose a new comparison framework that overcomes these limitations. This novel approach is based on a robust analysis of the frequency density (f-D) distributions of each product’s assessment of the event. We start by defining the concepts associated for distribution fitting and performance, temporal and spatial requirements, comparison metrics, and then provide an overview of the various sources of uncertainty contributing to the intercomparison exercise, and how and what uncertainties are propagated.

In this study we inter-compare eight operational remotely sensed active fire detections and fire radiative power (FRP) retrieval products: the polar-orbiter products derived from active fires detected using the Moderate Resolution Imaging Spectroradiometer data (MCD14ML), the Visible Infrared Imaging Radiometer Suite (VNP14IMGML), and the Sea and Land Surface Temperature Radiometer (SLSTR) Non-time critical product from European Space Agency (SLSTR-NTC), and the geostationary products derived from data collected by Meteosat’s Spinning Enhanced Visible and Infrared Imager (LSA-SAF FRP-PIXEL), and the three available products based on Advanced Baseline Imager (KCL/IPMA-GOES16, KCL/IPMA-GOES17, and KCL/IPMA-Himawari). We focus on annual detections and perform the analysis at 0.5° grid cell resolution, for the overlapping product’s time-series. The results are analysed for their temporal and spatial consistency, and inter-product differences are analysed in the context the product’s metadata.

The results show that an Inverse-gamma distribution can be used to characterize the fire ‘statistical signature’ and provide a reference baseline on to which all FRP products can be compared to, and their ‘representation uncertainty’ assessed. Individually, the fitting results show the degree of under representation of each sensor’s detections, namely the identification of minimum FRP detection limit, which typically precludes the detection of a proportion of the highly numerous but individually relatively small and/or low intensity fires. Furthermore, inter-comparison differences allowed for the identification, and assess the impact, of some of the key non-fire effects such as: pixel size, off-nadir pixel area growth, algorithm limitations, quality information, and the impacts of low temporal resolution of polar-orbiting sensors.

This proposed framework is a useful tool to compare EO-based FRP products and transferable to any product measuring transitory event properties that do not rely on simultaneous observations. It complements existent comparison exercises by identifying additional sources of uncertainty, the conditions under which these occur and how these translate into product inconsistencies. It is an essential tool, providing users with product-specific information on measurement limitations that, in principle, can be corrected and assimilated to higher level products and downstream applications such as GHG emission estimates from biomass burning, providing better quality information used for adaptation and mitigation policies.

How to cite: Mota, B.: Validation framework for EO measurements of transitory events based on robust statistics retrieved from non-simultaneous observations: A case study applied to Fire Radiative Power (FRP) products. , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8037, https://doi.org/10.5194/egusphere-egu26-8037, 2026.

Fire is a major ecosystem disturbance impacting the global carbon cycle, with its frequency and severity projected to increase. The time required for ecosystems to recover productivity after fire (recovery time) is an important metric for resilience, yet its global patterns remain poorly quantified. Here, we conduct a global analysis using Moderate Resolution Imaging Spectroradiometer (MODIS) observations from 2001 to 2024. We employ satellite-derived burned area data and the near-infrared reflectance of vegetation (NIRv) as a robust proxy for Gross Primary Production (GPP) to track recovery, which is defined as the duration to recover 90% of pre-fire productivity. Our analysis focuses on single-fire events, filtering out areas with recurrent disturbances, and defines recovery as the point when at least 90% of pre-fire productivity is regained.

Our results reveal that the global mean post-fire recovery time is 3.9 ± 0.3 years. This average is masked by strong geographical disparities: recovery follows a pronounced latitudinal gradient, with boreal ecosystems (≥50°N) requiring nearly twice as long to recover (5.6 ± 0.5 years) compared to tropical regions (3.0 ± 0.2 years). Evergreen needleleaf forests exhibit the longest recovery times (6.3 ± 0.9 years), while savannas and grasslands recover fastest. Statistical machine learning modeling identifies the magnitude of the immediate fire-induced GPP loss as the dominant factor controlling recovery duration, with burn severity and pre-fire productivity acting as important secondary drivers.

We show that CMIP6 Earth System Models (ESMs) significantly underestimate these recovery periods (simulating a global mean of 1.8 ± 0.1 years) and fail to capture the observed spatial heterogeneity, particularly in high-latitude regions. This suggests that current models may overestimate the carbon sink capacity of regenerating post-fire landscapes and underestimate positive fire-vegetation feedbacks. Our findings provide a new observational benchmark for improving the representation of post-disturbance dynamics in land surface models and refining global carbon budget assessments.

How to cite: Lin, Z., Chen, A., and Wang, X.: Global Patterns of Post-Fire Vegetation Productivity Recovery, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8718, https://doi.org/10.5194/egusphere-egu26-8718, 2026.

Variability in cloud droplet number concentrations (N_d) within the large subtropical stratocumulus decks can strongly impact outgoing shortwave radiation. The southeast Atlantic subtropical stratocumulus deck is particularly prone to elevated N_d, attributed to continental African fire emissions.  The highest stratocumulus N_d occur when Angolan agricultural fires coincide with weak surface warming during the austral winter months (June-early August). Dry convection fills a shallow continental boundary layer with smoke and a nighttime land breeze advects the aerosol into or slightly above the marine boundary layer. The offshore transport is strengthened by low-level easterlies from a continental high to the southeast of Angola that is stronger when the Angolan land is cooler. Simultaneously, the south Atlantic subtropical high (SASH) is weaker when Angolan land warming is more muted, allowing the biomass-burning aerosol to also disperse further south. The shortwave-absorbing aerosol can either reach the remote boundary layer by direct low-lying easterly transport, or through entrainment over longer time scales after being transported south. While the weak Angolan land heating in June-July correlates with higher offshore N_d, these coincide with lower cloud fractions and thinner clouds, primarily because the SASH is also weaker. This meteorological co-variation fully compensates for any aerosol brightening of the cloud deck. Marine cloud brightening by emissions from a southeast Atlantic shipping lane is more evident when Angolan land heating is stronger, coinciding with a stronger SASH, as the background N_d is less and the background cloud fraction is higher. Most of the year-to-year variability from 2003 to 2023 in the June-July marine shortwave cloud radiative effect can be constrained using the surface-level temperature over Angola (r2 = 0.4). While Angolan land has warmed slightly in June-July since 1980 in reanalysis, no trend is evident in synoptic variations of warmer versus cooler heating. Fire emissions have slightly increased since 2003. A continuing warming trend would deepen the continental boundary layer, and could place more of the transported smoke above the marine boundary layer, stabilizing the lower atmosphere through shortwave absorption.

How to cite: Zuidema, P. and Tatro, T.: Weak, low-level dry convection over Angola determines biomass-burning aerosol entry into the marine boundary layer, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8759, https://doi.org/10.5194/egusphere-egu26-8759, 2026.

Wildfires are unpredictable combustion events that significantly drive atmospheric emissions and modulate global cloud cover. An extreme example of such an event is the case of the 2023 Canadian wildfires, wherein nearly 5% of Canada’s forested area was burned between May and September 2023 [1]. This event produced the largest wildfire emissions ever recorded in Canada, with plumes extending across the Northern Hemisphere [2]. Aerosol intrusions and associated modifications absorbing and/or scattering can cause variability of solar irradiance [3], while reductions in photovoltaic power anywhere between 13% and 22% can take place because of aerosol optical depth (AOD) increases [4]. Consequently, the plumes resultant from the 2023 Canadian wildfires might have caused significant photovoltaic power losses over North America and Europe.

In this work, the global and local atmospheric impacts of this historic wildfire event are investigated using the EC‑Earth3 Earth system model in the interactive aerosols and atmospheric chemistry configuration (AerChem) [5]. BB emissions from the Copernicus Atmosphere Monitoring Service (CAMS) Global Fire Assimilation System (GFAS) were used through the model to produce two 10-member ensemble simulations, with and without the 2023 Canadian wildfire emissions respectively. The main parameter of interest is the modelled surface downwelling flux anomaly, which enables direct inference of modelled reductions in solar power output.

Model results have shown substantial radiative anomalies during May–September 2023 mainly in North America and Europe, with an average hemispheric shortwave radiation reduction of −4.18 W/m² leading to PV production deficits. Secondary analyses suggest that surface cooling, which amounted to an average hemispheric temperature anomaly of −0.91 °C and which impacts PV performance, compensated 8–21% of the PV losses, varying by region. The results indicate a total 5-monthly modelled PV generation loss of 6.38 TWh, and the emitted carbon burden equivalent to this reduction in energy production is estimated at 2083 tons of CO₂, with a total associated economic deficit of 1.33 billion euros. These findings emphasize the need for integrated transnational strategies in extreme event prediction and wildfire prevention to ensure the continued resilience of renewable energy production.

[1] Roșu, I. A., Mourgela, R. N., Kasoar, M., Boleti, E., Parrington, M., & Voulgarakis, A. (2025). Large-scale impacts of the 2023 Canadian wildfires on the Northern Hemisphere atmosphere. npj Clean Air, 1(1), 22.

[2] Byrne, B., Liu, J., Bowman, K. W., Pascolini-Campbell, M., Chatterjee, A., Pandey, S., ... & Sinha, S. (2024). Carbon emissions from the 2023 Canadian wildfires. Nature, 633(8031), 835-839.

[3] Wendisch, M., & Yang, P. (2012). Theory of atmospheric radiative transfer: a comprehensive introduction. John Wiley & Sons.

[4] Neher I., Buchmann T., Crewell S., Pospichal B. & Meilinger S. (2019). Impact of atmospheric aerosols on solar power. Meteorologische Zeitschrift, 4, 28.

[5] Van Noije, T., Bergman, T., Le Sager, P., O'Donnell, D., Makkonen, R., Gonçalves-Ageitos, M., ... & Yang, S. (2020). EC-Earth3-AerChem, a global climate model with interactive aerosols and atmospheric chemistry participating in CMIP6. Geoscientific Model Development Discussions, 1-46.

How to cite: Rosu, I.-A., Jones, M. W., Grillakis, M., Petrakis, M. P., Kasoar, M., Mourgela, R.-N., and Voulgarakis, A.: Impacts of 2023 Canadian wildfire emissions on solar power over North America and Europe, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9005, https://doi.org/10.5194/egusphere-egu26-9005, 2026.

Wildfires are mainly considered to be CO₂-releasing events, while their long-term impact on biogeochemical carbon sequestration remains a major source of uncertainty. We analysed five years of ecosystem-scale eddy covariance data in a South African Fynbos shrubland that experienced a wildfire in the middle of the measurement period and combined it with leaf-scale ecophysiological measurements to quantify the ecosystem-scale carbon feedbacks and energy flux shifts following wildfire.

Unexpectedly, wildfire doubled the annual net carbon sink from 5.36 to 10.55 t_C ha^-1 yr^-1. This increase was driven by a ca. 50% suppression of ecosystem respiration while ecosystem energy exchange remained stable. These findings reveal a significant missing carbon pool of ca. 110 t_C ha^-1 over the course of the fire return interval of 15-20 years. Likely explanations for this discrepancy are either a below-ground carbon pool protected from volatilization through fire or a potential sink into dissolved carbon, potentially leading to eventual long-term ocean storage.

To identify the biological drivers of this carbon sequestration, we measured gas exchange in the two main regeneration plant types of this fire-dominated ecosystem, i.e. obligate reseeders, whose seedlings must achieve reproduction before the next fire to persist, and resprouting species that invest into fire tolerance traits at the cost of slower growth. Stomatal conductance (g_sw) was the primary trait distinguishing the two strategies. Reseeders initiated photosynthesis earlier in spring and exhibited g_sw that was highly responsive to changes in ambient CO₂ and light, while resprouters exhibited stronger resilience to drought but no response to ambient CO₂ fluctuations. This difference in response to CO₂ suggests that current climate trends may preferentially boost reseeders, potentially partially offsetting the impacts of shortened fire return intervals. Conversely, resprouter resilience may prove crucial under a higher drought intensity and duration scenario.

Our unexpected findings for this Mediterranean-climate shrubland (typically considered to be a low carbon sink ecosystem) underscore the necessity for ground-based ecophysiological data to constrain Earth system models, and challenge biomass-centric climate policies, particularly in fire-prone, naturally tree-free ecosystems.

How to cite: Muller, J. D., Joubert, W., de Buys, A., Ramsay, E., Carkeek, R., and Midgley, G. F.: Fire as a Catalyst for Carbon Sequestration: Respiration Suppression and Regeneration Feedback in South African Fynbos Shrubland, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9056, https://doi.org/10.5194/egusphere-egu26-9056, 2026.

The late dry season of 2019 featured one of the most severe Indonesian wildfire events of the past decade, driven by persistent drought and extensive peatland burning. These extreme wildfires emitted large amounts of carbonaceous aerosols, substantially degrading air quality and posing risks to human health. However, the impacts of extreme wildfire events on black carbon (BC) across Southeast Asia remain poorly quantified. Here, we evaluate the influence of Indonesian wildfires during August–October 2019 using the GEOS-Chem chemical transport model at 0.25° × 0.3125° resolution. Sensitivity simulations with and without Indonesian fire emissions are conducted to isolate fire-driven contributions to BC. Results indicate dominant wildfire control over BC across Southeast Asia. Fire contributions reach about 91% over both Borneo and Sumatra during peak burning. Comparable fire influence extends to nearby seas, particularly the South China Sea, with contributions exceeding 90% over the southern South China Sea. Contributions remain near 70% over the Sulu and Celebes Seas and still reach about 50% over the Philippine Sea. In contrast, impacts over the East China Sea are episodic, occurring only during short-lived northeastward outflow events. These findings demonstrate the strong and spatially heterogeneous influence of Indonesian wildfires on regional BC across Southeast Asia, highlighting the role of extreme wildfire events in shaping air quality through fire-driven transboundary transport.

How to cite: Zheng, H.: Impacts of the 2019 extreme Indonesian wildfires on black carbon across Southeast Asia, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9088, https://doi.org/10.5194/egusphere-egu26-9088, 2026.

European wildfire response systems are increasingly challenged by the simultaneous demand for aerial and ground suppression assets. If major fire-prone regions burn asynchronously, Europe could benefit from risk-diversified deployment of shared suppression fleets and more efficient cross-border mutual-aid strategies. We test the hypothesis that fire activity in (1) the Iberian Peninsula (Portugal and Spain) and (2) Central–Eastern Mediterranean (Italy and Greece) exhibits identifiable and temporally stable dependence patterns modulated by large-scale climate variability.
Annual burned-area time series covering 1980–2023 are compiled from the European Forest Fire Information System (EFFIS). These are complemented by satellite-derived indicators of fire activity from MODIS, namely Fire Radiative Power (FRP), enabling joint assessment of burned area extent and fire intensity. Climate-fires’ dependence is quantified through correlations of annual and seasonal anomalies and joint-extreme metrics focused on tail co-exceedance probability. The relationship between fire activity (burned area, FRP, FRE) and large-scale climate variability is assessed following established teleconnection-based frameworks, combining seasonal aggregation, lagged cross-correlation analysis, and composite analysis of extreme fire years. Teleconnection indices considered include the North Atlantic Oscillation (NAO), East Atlantic pattern (EA), Mediterranean Oscillation Index (MOI), Arctic Oscillation (AO), and ENSO. Analyses explicitly account for the non-stationary and scale-dependent nature of teleconnection–fire relationships, and are conditioned on regional temperature and precipitation anomalies to isolate circulation-driven effects.

The analysis aims to identify: (i) the frequency and persistence of synchrony versus compensatory (negative) dependence in burned area and fire activity between the two macro-regions, (ii) the teleconnections most strongly associated with synchronous extreme fire seasons, and (iii) multi-decadal periods offering potential for suppression-fleet diversification. Owing to its direct control on Mediterranean-scale pressure gradients and precipitation contrasts, MOI provides the primary explanatory signal for synchronous versus compensatory fire activity between the two macro-regions.

Results are interpreted within an operational risk-pooling framework, where weak or negative dependence supports climate-informed scheduling of shared European suppression fleets and enhanced cross-border mutual aid, while strong positive dependence indicates heightened likelihood of concurrent continental-scale resource strain.

This work is partially supported by FCT, I.P./MCTES through national funds (PIDDAC): LA/P/0068/2020 – https://doi.org/10.54499/LA/P/0068/2020, UID/50019/2025 – https://doi.org/10.54499/UID/PRR/50019/2025, UID/PRR2/50019/2025 and Dhefeus (https://doi.org/10.54499/2022.09185.PTDC). AR, JMCP and JMNS also thank the FCT by supporting UIDB/00239/2020 (https://doi.org/10.54499/UIDB/00239/2020), UIDP/00239/2020 (https://doi.org/10.54499/UIDP/00239/2020), and through project references UIDB/00239/2020 (https://doi.org/10.54499/UIDB/00239/2020) and UIDP/00239/2020 (https://doi.org/10.54499/UIDP/00239/2020) and European Space Agency Climate Change Initiative (ESA-CCI9 Tipping Elements SIRENE project (Contract No. 4000146954/24/I-LR). 

How to cite: Russo, A., Gouveia, C., Bento, V., Silva, J. M. N., DaCamara, C., Trigo, R. M., and Pereira, J. M. C.: How asynchronous is fire burning in Iberia and the Central–Eastern Mediterranean? A dependence analysis of burned area, fire activity, and teleconnection forcing to inform shared European suppression fleets, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9452, https://doi.org/10.5194/egusphere-egu26-9452, 2026.

Wildfires are powerful forces of nature, shaping ecosystems, degrading air quality, and influencing the climate. Human activities intensify fires through land use change, accidental ignitions, and droughts driven by climate change. However, the complex interactions between climate change, vegetation shifts, and human behavior—and their consequences for wildfires—remain poorly understood. The Dutch innovations in atmospheric satellite sensors SPEXone, EarthCARE and TROPOMI now allow detailed studies of wildfires and their nearby and far-reaching consequences. The recently funded and started INFLAMES-project (Interdisciplinary Network for Fire research from Low Earth Orbit Atmospheric Measurements) aims to combine cutting-edge satellite data with state-of-the-art modeling techniques to unravel how wildfires alter air quality and climate, with a special focus on vegetation’s evolving role—both as a fuel source and a carbon sink in fire-affected regions. 

In this presentation, we demonstrate the scientific ambition of the INFLAMES-project. We then show the first scientific results from INFLAMES, including satellite-derived trace gas (NOx, VOCs) and aerosol emission estimates for severe fires in Les Landes, France (August 2022), based on TROPOMI and MODIS observations and evaluated against the GFED emission inventory. We further show the first coincident EarthCARE, PACE and TROPOMI observations of wildfire plume heating-rate profiles over the Pantanal, demonstrating the potential of combined active–passive satellite measurements to directly constrain aerosol radiative effects. Together, these results establish a pathway toward improved quantification of the Aerosol Direct Radiative Effect (ADRE), a major remaining uncertainty in present-day radiative forcing, which will be further addressed using aerosol microphysical constraints from SPEXone on PACE. We conclude by highlighting opportunities for broader community engagement through dedicated workshops and an international summer school.

How to cite: Boersma, K. F., de Graaf, M., Hasekamp, O., Penning de Vries, M., Vrieling, A., Schutgens, N., Koren, G., van Bodegom, P., Kollia, D., Geurts, M., and Chantry, A.: First results from INFLAMES - Interdisciplinary Network for Fire research from Low Earth Orbit Atmospheric Measurements, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10271, https://doi.org/10.5194/egusphere-egu26-10271, 2026.

Nuclear conflict can ignite widespread fires that inject massive quantities of smoke particles into the atmosphere. Using the chemistry–climate model CESM2-WACCM6, we simulate idealized nuclear war scenarios with varying emission magnitudes of black carbon (BC) and primary organic matter (POM) released at 150~300 hPa over a 7-day period. Model results show that absorption of solar radiation by BC and POM leads to stratospheric temperature increases exceeding 50 K. This intense heating enhances the vertical lofting of smoke particles, enabling their transport even into the lower mesosphere and significantly extending their atmospheric residence time to over 4 years, thus leading to long-term environmental and climatic impacts. Even a regional nuclear conflict between India and Pakistan, emitting 5 Tg of BC (IP-5B scenario), results in a global total column ozone reduction exceeding 400 Tg (~12%), comparable in magnitude to that simulated for a large-scale nuclear war between USA and Russia with 16 Tg of BC emissions (UR-16B scenario). The co-emission of POM further amplifying stratospheric ozone depletion, leading to increased ultraviolet (UV) radiation at the surface. This heightened UV exposure poses serious risks to ecosystems and human health.

How to cite: Zhuo, Z., Pausata, F. S. R., Paul, K. J., and Cheung, A. K. H.: Tropical Small-Scale Nuclear War Fire Emissions Cause Greater Ozone Depletion Than Extratropical Large-Scale Conflicts, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10325, https://doi.org/10.5194/egusphere-egu26-10325, 2026.

Climate change projections point to a sustained rise in emissions from biomass burning (BB), highlighting the need for a comprehensive evaluation of the environmental impacts of BB-derived aerosols (BBA). Of particular importance is the organic aerosol fraction (BBOA), which is chemically reactive and undergoes complex transformations during atmospheric ageing. These processes are especially critical in coastal regions, where strong coupling between atmospheric and marine systems can amplify environmental and ecological risks. In this study, we apply a multidisciplinary framework combining atmospheric chemistry, aerosol characterization, modeling, marine science, and toxicology to investigate the physicochemical properties of BBA, with emphasis on BBOA, and to assess how their atmospheric evolution affects air quality and marine ecosystems.

A comprehensive field campaign was conducted in the central Adriatic region, an area frequently impacted by intense wildfire events yet still poorly characterized in terms of BB influences. During controlled pinewood biomass burning experiments in April 2025, real-time measurements were conducted using state-of-the-art instrumentation, including a Scanning Mobility Particle Sizer (SMPS), an Optical Particle Counter (OPC), gas analyzers, and a CASS system combining an Aethalometer and a Total Carbon Analyzer. In parallel, fine particulate matter (PM_2.5), volatile organic compounds (VOCs), and size-resolved aerosols (0.010–32 µm) were collected for comprehensive offline analyses, including the determination of trace metals, major ions, anhydrosugars, polyols, organic carbon, and aerosol oxidative potential.

To link atmospheric processes with marine impacts, laboratory exposure experiments were performed to evaluate the effects of ambient BB aerosols and model black carbon materials on the growth of representative marine phytoplankton species (such as Emiliania huxleyi, Cylindrotheca closterium, Melosira nummuloides, Synechococcus sp.) under controlled conditions (18 °C; 16 h light/8 h dark). These experiments reveal species-specific physiological responses to BB aerosol exposure. Overall, the integrated dataset provides new insights into the properties and evolution of BB aerosols and their cascading impacts on coastal air quality and marine ecosystem health in the Adriatic region, with broader implications for other vulnerable coastal environments.

This work was supported by Croatian Science Foundation project IP-2024-05-6224 ADRIAirBURN.

How to cite: Frka, S., Depolo, A., Arapov, J., Skejić, S., Šantić, D., Cvitešić Kušan, A., Chaux, F., Vicente, E., Alves, C., and Bubola, L.: Linking Air Quality and Marine Ecosystem Responses to Biomass Burning Aerosols in the Adriatic Coastal Zone, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11040, https://doi.org/10.5194/egusphere-egu26-11040, 2026.

How to cite: Payette, T., Ashraf, S., Hayes, P., and Chen, J.: Integrating the Global Forest Fire Emissions Prediction System version 1.0 to GEOS-Chem , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11423, https://doi.org/10.5194/egusphere-egu26-11423, 2026.

Fire is a dominant terrestrial ecosystem disturbance and a major driver of atmospheric composition. Quantifying fire emissions and their variability remains a key challenge, particularly as fire frequency and intensity vary and increase under climate change. Inverse modeling provides a powerful framework to estimate fire emissions by constraining chemistry transport models (CTMs) with satellite observations, while simultaneously delivering three-dimensional information on the transport and distribution of fire-related pollutants.

In this study, we use the global CTM TM5 coupled with a four-dimensional variational data assimilation system (TM5-4DVar) to better constrain fire-related carbon monoxide (CO) emissions using satellite observations. We assimilate CO column super-observations from the Measurements of Pollution In The Troposphere (MOPITT) instrument aboard NASA’s Terra satellite (version 9) and, separately, higher spatiotemporal resolution CO observations from the TROPOspheric Monitoring Instrument (TROPOMI) aboard ESA’s Sentinel-5P. The assimilations are performed globally at 3° × 2° horizontal resolution over multiple years (2019–2024).

The posterior simulations provide insights into both regional fire emissions and the horizontal and vertical transport of CO, enabling assessment of downwind pollution impacts, evaluated against independent ground-based observations. Results show bias reductions with posterior simulated mixing ratios in comparison to prior simulations based on bottom-up emission inventories. We further investigate the influence of regional drought conditions on fire-related CO emissions and examine correlations with key environmental variables, including climate and vegetation indicators. Our results contribute to an improved understanding of interactions among fire emissions, climate, and atmospheric composition, and demonstrate the value of remote sensing data assimilation for reducing uncertainties and advancing fire emission monitoring.

How to cite: Peiro, H., van der Velde, I., van der Werf, G., Houweling, S., Rijsdijk, P., and Aben, I.: A global CO fire emissions assessment and its connection with drought events, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11440, https://doi.org/10.5194/egusphere-egu26-11440, 2026.

In May and June 2025, wildfires in Canada produced atmospheric effects extending beyond North America. Large quantities of gases and aerosols emitted by biomass combustion were transported across the Atlantic and reached Europe. Here, our aim is to investigate how these events affect the variability of climate-altering species in Italy using observations from permanent observatories.

Clear evidences of this long-range transport were observed from 8^th June 2025 at the GAW/WMO Global Station “O. Vittori” at Monte Cimone (2165 m a.s.l., northern Italy) and at the Potenza CIAO observatory (760 m a.s.l., southern Italy), two co-located sites for the Research Infrastructures ICOS and ACTRIS. It was also observed, albeit with weaker intensity, at the ACTRIS Environmental-Climate Observatory (ECO) in Lecce (37 m a.s.l., southern Italy). Atmospheric transport modelling (LAGRANTO and HYSPLIT back-trajectories) confirmed that the air masses affecting the sites originated in North America.

Average daily carbon monoxide (CO) values peaked to 207 ppb on 9^th June at CMN and to 247 ppb at ECO, nearly doubling the levels measured during the preceding 7 days. Also, black carbon (BC) showed marked increases, with values more than doubling the average of the preceding days at both sites.

Additional confirmation of the plume’s arrival and vertical evolution was provided by the ALICE-Net ceilometer at CMN: between 6^th and 8^th June, aerosol-rich layers were detected at high altitudes before gradually descending to the measurement site. At CIAO, the aerosol lidar observed smoke layers between 11 and 14 km from 5^th to 10^th June.

CO and ozone (O₃) remained high until 13^th June at CMN (average values: 188 ppb and 70 ppb), and at ECO (average CO value of 232 ppb, O₃ data not available). Subsequently, intermediate values have been observed from 14^th to 21^st June. At CIAO, CO increased between 8^th and 17^th June, reaching up to 250 ppb.

No corresponding increases in carbon dioxide (CO₂) have been observed during the wildfire plume event. During the days characterized by the peaks in CO and O₃ (8^th  – 13^th June), daily mean CO₂ values showed a – 6.4 ppm and – 3.4 ppm decrease with respect to the previous 7 days at CMN and ECO. The analysis of back-trajectories showed air masses travelling at pressure levels representative of the European PBL, where active ecosystems could take up CO₂, in the 24 hours before the arrival at CMN.

The analysis of the day-to-day variability of nighttime/daytime N₂O, CO₂ and δ¹³CO₂, pointed to a significant influence of air masses from the regional PBL to CMN during the daytime on 9^th – 14^th and 18^th – 19^th June. This suggests that emissions occurring at regional scale could contribute to the observed atmospheric composition variability. Together with the role of air mass mixing and in-plume chemical processes along transport, this implies that attributing the observed enhancements to wildfire emissions requires careful and critical evaluation.

Acknowledgments: Observations/analyses are supported by the ITINERIS (PE0000021, NRRP – NextGenerationEU) and PRO-ICOS MED (PON 2014–2020) projects, funded by the Italian Ministry of University and Research and the European Union.

How to cite: Cristofanelli, P., Barnaba, F., Bracci, A., Calidonna, C. R., Cesari, R., Contini, D., Diliberto, L., d'Amico, F., Decesari, S., Dinoi, A., Gori, L., Marinoni, A., Mona, L., Putero, D., Zaccardo, I., and Zanatta, M.: Impacts of wildfire plumes from Northern America on atmospheric composition as observed by permanent observatories in Italy during June 2025, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11975, https://doi.org/10.5194/egusphere-egu26-11975, 2026.

The 2019–2020 Australian Black Summer megafires burned over eight million hectares of vegetation and constituted an extreme perturbation to terrestrial carbon cycling, releasing an unprecedented quantity of greenhouse gases to the atmosphere. Quantifying fire-driven emissions remains a key challenge, as emission inventories typically fall into one of two categories; bottom-up approaches (such as with the Global Fire Emission Database, GFED) that rely on burned area, fuel load, and combustion completeness estimates, or top-down approaches, (such as the Global Fire Assimilation System, or GFAS) which scale Fire Radiative Power (FRP) observations to emissions using emission coefficients. Currently, the two most widely used inventories (GFED and GFAS) ultimately rely heavily on uncertain modelled estimates of broad scale biome-specific combustion completeness, which remains a major limitation in constraining carbon fluxes from fires. We apply the Fire Radiative Energy Emission (FREM) approach, a top-down framework that directly links observed Fire Radiative Energy (FRE) to trace gas emissions, thereby reducing reliance on poorly constrained fuel and combustion assumptions. FREM is derived from co-located observations of FRP from the geostationary Himawari satellite and carbon monoxide (CO) from TROPOMI aboard Sentinel-5P. A dataset of 580 cloud-free landscape fires and associated plumes across six major Australian biomes (low woodland savanna, grassland, shrubland, evergreen and deciduous broadleaf forests, and sparse vegetation) was assembled for 2019 to derive biome-specific emission coefficients relating FRE to excess CO. These coefficients, combined with a calculated small-fire correction factor and hourly FRE observations from Himawari, were used to estimate emissions from the Black Summer megafires and to compare FREM-derived fluxes with those from existing inventories (GFAS v1.2, GFED v4.1s, GFED v5.1, and the Fire Energetics and Emissions Research, or FEER). The FREM estimates exhibit coherent spatial and temporal patterns and fall within the spread of emissions reported by these inventories, indicating consistency at regional scales while retaining sensitivity to fire intensity and temporal variability. By utilizing the geostationary FRP observations from Himawari, the FREM approach provides high-temporal-resolution, near-real-time estimates of fire emissions across Australia that are directly linked to observed radiative energy release, and bypasses the need for fuel load and combustion completeness estimations.

How to cite: Maslanka, W., Xu, W., Wooster, M., and He, J.: Quantifying Greenhouse Gas emissions from the Australian Black Summer Megafires using the Fire Radiative Energy Emission (FREM) Approach, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12220, https://doi.org/10.5194/egusphere-egu26-12220, 2026.

Wildfires are increasingly shaping terrestrial ecosystems, with profound implications for land degradation processes across fire-prone regions.

This work advances the assessment of post-fire land degradation by jointly analysing fire occurrence, burn severity and vegetation recovery as key indicators of ecosystem vulnerability. By integrating multi-temporal fire records (2001-2019) the study captures both the frequency of disturbances and its immediate ecological impact, enabling another view on the evaluation of degradation trajectories globally (Vieira et al., 2026) .

Results indicate that recurrent fires, particularly when combined with high-severity events, substantially exacerbate vegetation loss, and erosion risk, thereby accelerating land degradation processes. Preliminary results indicate that areas experiencing short fire-return intervals show limited recovery capacity, leading to cumulative impacts on soil health, which on turn might be leading to alternate states (McGuire et al., 2024) . The analysis further highlights strong spatial variability, where land cover, and pre-fire conditions influence degradation response.

Overall, this work underscores the importance of moving beyond binary burned–unburned classifications and incorporating fire severity and recurrence into land degradation assessments. Such an approach provides critical insights for post-fire management, restoration prioritisation, and the development of adaptive strategies aimed at mitigating long-term degradation under a changing fire regime.

McGuire, L. A., Ebel, B. A., Rengers, F. K., Vieira, D. C. S., and Nyman, P.: Fire effects on geomorphic processes, Nat Rev Earth Environ, 1–18, https://doi.org/10.1038/s43017-024-00557-7, 2024.

Vieira, D. C. S., Borrelli, P., Scarpa, S., Liakos, L., Ballabio, C., and Panagos, P.: Global estimation of post-fire soil erosion, Nat. Geosci., 19, 59–67, https://doi.org/10.1038/s41561-025-01876-0, 2026.

How to cite: Vieira, D., Borrelli, P., and Panagos, P.: Feedback Loop between fire and land degradation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12251, https://doi.org/10.5194/egusphere-egu26-12251, 2026.

How to cite: Perkins, O., Kasoar, M., Haas, O., Smith, C., Teixeira, J., Voulgarakis, A., Mistry, J., and Millington, J.: Benefits and limits of Integrated Fire Management for climate change adaptation: a global quantitative assessment , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13135, https://doi.org/10.5194/egusphere-egu26-13135, 2026.

Global burned area (BA) products are commonly available at a Non-Time Critical (NTC) basis, several months or even several years from the present date; i.e. they are unavailable for Near-Real Time (NRT) applications. The Copernicus Land Monitoring Service (CLMS) delivers the only global BA product in NRT, since recently, at very high accuracy, comparable to the most accurate non-CLMS NTC product (FIRECCIS311). However, global BA products are generated from coarse >= 300 m reflectance observations. Despite the Sentinel-2 mission having been in operation since 2017, providing decadal resolution 10-50 m reflectance data every ~5 days, and despite the well-known benefits of using decadal resolution data to estimate BA, a global Sentinel-2 NRT BA algorithm does not exist. The purpose of this study is to adapt and apply the latest developments in NRT detection, as implemented in the CLMS, to Sentinel-2 L2A imagery. The mapping method uses a neural network (NN) with 2D convolutional layers, followed by a Long Short-Term Memory (LSTM) layer. The NN processes the time series of reflectance images on a per-pixel basis, with convolutional layers applied along the spectral and temporal dimensions. The time series of fractional BA maps, predicted by the NN, are combined with time series of spatio-temporal density of VIIRS active fire detections. Such a combination consists of a logistic model and allows the reduction of false positives (such as cloud shadows). The NN is trained on a sample dataset automatically generated from time series reflectance observations (Sentinel-2 data in this case), extracted over locations of VIIRS active fire detections across the Globe for the year 2020, and corresponding estimates of fractional BA, derived from physically-based radiative transfer modelling. The mapping method generates one BA map for each new Sentinel-2 image available (referred to as BAS2nrt0), which is updated with images from the following 5 days (referred to as BAS2nrt5) and the following 10 days (referred to as BAS2nrt10). The additional images available after the mapping day are expected to reduce false positives due to cloud shadows. The mapping method also generates an NTC BA map for each calendar month (referred to as BAS2ntc), with images available for a buffer of 45 days around the month. The algorithm results are validated against an independent global reference dataset for the year 2019, which includes long time series of Landsat-derived BA maps covering 105 sampling units distributed across the Globe. The analysis of the 2019 validation results shows that the accuracy of the proposed Sentinel-2 products is high regardless of estimation timeliness. As expected, (1) the accuracy of the NTC product, Dice coefficient (DC) of 87.2%, is higher than the NRT products, DC 82.7–85.4%, and (2) the accuracy of the NRT product is increased with each update. Such accuracy levels are remarkably high: the accuracy of NRT estimates is comparable to a precedent global non-CLMS NTC Sentinel-2 BA mapping (DC 81.8%).

How to cite: Padilla, M., Ramo, R., Gomez-Dans, J. L., Sierra, S., Mota, B., Lacaze, R., and Tansey, K.: Global near-real time burned area mapping with Sentinel-2 based on reflectance modelling and deep learning, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13146, https://doi.org/10.5194/egusphere-egu26-13146, 2026.

The rising frequency and intensity of wildfire-driven pyro-cumulonimbus (pyroCb) events constitute an important atmospheric perturbation, injecting massive amounts of smoke into the stratosphere. The Australian Black Summer wildfires of 2019–2020 released about a million tonnes of smoke and gases, causing the most significant stratospheric temperature perturbation since 1991 Pinatubo eruption. This study simulates the evolution of smoke plumes from the Australian wildfires using the UKESM1.1 model. The aerosol and greenhouse gas follow the CMIP6 SSP245 scenario, with 0.62 Tg of total smoke injected into the upper troposphere/lower stratosphere based on estimates from Global Fire Emissions Database (GFED). The simulated aerosol layer expands both vertically and horizontally, with significant lofting in the first month following injection, reaching altitudes of ~30 kms, consistent with CALIPSO observations. The modelled zonal-mean aerosol extinction agrees well with OMPS retrievals, with peak values of around 0.006 km⁻¹. However, the modelled stratospheric AOD is higher (up to ~2 times) than the observations showing the aerosols in the model are more optically efficient. Additional sensitivity tests are ongoing to examine whether a higher initial injection altitude in these simulations might be causing the aerosols to remain in the stratosphere longer and decay more slowly. These findings highlight the need for improved observational constraints and modelling strategies to better quantify the global impacts of wildfire-induced stratospheric smoke.

How to cite: Soni, M., Johnson, B., and Haywood, J.: Wildfire-driven Stratospheric Perturbations:Modelling Insights from the Australian Wildfires, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14942, https://doi.org/10.5194/egusphere-egu26-14942, 2026.

Fire is a major driver of forest change worldwide. In tropical regions, it is primarily used by local populations to clear forested land for human activities such as agriculture and infrastructure development. Here, we use three decades of Landsat-based observations to analyse fire-related forest loss over a broad temporal scale across a major tropical region in South America, spanning more than 2 million km² and encompassing a wide range of ecosystems. This long-term assessment provides a comprehensive view of post-fire forest cover dynamics, with strong potential to capture deforestation trends, forest fate, and the roles of protection status and landscape history. Over the study period, the newly generated medium-resolution dataset of burned area detected a cumulative total of approximately 345 million hectares burned, equivalent to an average annual burned fraction of 5.65%, with pronounced interannual variability and the period between 1999 and 2010 being the most extreme. During the same timeframe, more than 24.5 million hectares of forest were lost, representing nearly one-quarter of the 1990 forest extent, with fires accounting for 26% of this loss. Most of these losses have not recovered over time and were subsequently followed by deforestation, with 99% of affected areas converted to pastures and croplands, while recovery rates have remained negligible. Fragmentation and fire history legacy emerged as critical factors influencing the trajectory of forest loss.

How to cite: Khairoun, A. and Salinero, E.: Analysis of long-term fire-related deforestation and cover change dynamics in South American ecosystems, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15336, https://doi.org/10.5194/egusphere-egu26-15336, 2026.

Fires on Earth are changing in response to human activities, both through direct ecosystem management and indirect climate change-induced warming and associated shifts in regional rainfall patterns. While increased burning in forested systems often captures international media attention, the decline in burning in grassy systems––especially African savannas––receives less focus, despite their dominant contribution to total global burned area and fire emissions. Forecasting future fire activity and its impacts on local ecology and livelihoods, as well as global climate feedbacks, requires a robust mechanistic understanding of the complex interactions between climatic conditions, ecosystem functioning, human activities, and fire across a range of climate states not captured by modern satellite-based observations.

This study focuses on Africa, whose environments span a diversity of climates and ecologies, from some of the driest and most sparsely vegetated regions on Earth (such as the Sahara) to some of the wettest and most biologically productive (such as the Congo Rainforest). These two ends of the rainfall gradient experience non-existent to infrequent burning. However, the most expansive biomes in Africa are tropical savannas and grasslands where precipitation is intermediate and highly seasonal, supporting rapid vegetation growth during wet seasons and drying and abundant fires in the dry season. As a result, burning in Africa constitutes more than half of all global burned area each year. Robust histories of how fires have changed in Africa through time are therefore essential to understanding changes in biomass burning at a global scale. In addition to its broad scope of environments and outmatched contributions to total global burning, Africa also has the longest history of human fire use and land-use change, making it an ideal testing ground for interrogating the combined roles climate shifts and human behaviors play in shaping fire regimes through time.

Here, we present a new synthesis of African paleofire activity inferred from the accumulation of both physical and molecular proxies (e.g., charcoal and polycyclic aromatic hydrocarbons) within climate archives spanning multiple depositional contexts (e.g., lacustrine, marine, and peat sediments) which record biomass burning across a host of ecosystems. Our new reconstruction spans the last 24 thousand years, within which we focus on four key time periods: the Last Glacial Maximum and deglaciation, the mid-Holocene African Humid Period, the late-Holocene rise of metallurgy and agriculture, and the post-industrial era. We evaluate trends in biomass burning during these intervals, and, by comparison to paleoclimate and archeological datasets, we assess the extent to which these patterns are driven by climatic and/or human influences at continental, regional, and biome scales.

How to cite: O’Mara, N., Githumbi, E., Bartlein, P., Norwood, M., Teruel, O., Aleman, J., Staver, C., and Marlon, J.: Changes in biomass burning in Africa since the last glacial maximum: a new continental-scale paleo-synthesis and interrogation of the climatic and human drivers of shifting fire regimes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15696, https://doi.org/10.5194/egusphere-egu26-15696, 2026.

Wildfires are rapidly increasing in boreal forests and are extending to Arctic environments at an unforeseen scale. Above-ground biomass burning may be compensated by regrowth in the years following a wildfire, impacting atmospheric CO₂ levels only temporarily.  However, high-latitude wildfires characteristically combust deep into carbon-rich soils accumulated over centuries to millennia and thereby risk transforming these long-term carbon sinks into net sources into the atmosphere. Hitherto, research on Arctic-boreal fires has largely focused on their surface impacts, including the burned area, severity, and forest recovery, while many of their underground characteristics are poorly understood. For instance, observations of the age of carbon released in the fires remain scarce, resulting in incomplete understanding of the climate impact of high-latitude fires.

To determine the age of carbon released in recent Arctic-boreal fires, we collected charred organic material for radiocarbon dating from a tundra fire in Greenland, and two boreal forest and one tundra fire site in northwestern Canada. Our results indicate that, contrary to previous observations, up to centennial to millennial-aged carbon was released in these arctic and boreal wildfires. Moreover, laboratory combustion experiments of Arctic-boreal biomass collected from fire-susceptible surface layers (0-30 cm depth) from Svalbard, Russia, Norway and Finland, demonstrate that the combustion mode, and thus the phase of the emitted carbon, depend on the age of the combusted material. Above-ground modern vegetation combusts flamingly emitting mainly gases, while below-surface older and partly decomposed organic material smoulders, producing increasing carbonaceous particle/gas ratios with increasing age of the combusted material. Similar to the studied Greenland and Canadian wildfires, the laboratory combustion of the Arctic-boreal biomasses show up to millennia-aged carbon emissions.

Our results indicate that centennial to millennial-aged carbon is released in Arctic-boreal wildfires, thereby causing long-lasting feedback to the global climate system. Currently, climate models do not consider the potential release of ancient carbon from wildfires. Thus, our results indicate that increasing Arctic-boreal wildfires may exacerbate global warming more than previously estimated.  

How to cite: Ruppel, M., Granqvist, S., Diaz, L., Haghipour, N., Sippula, O., Smittenberg, R., Somero, M., Veraverbeke, S., and Väliranta, M.: Ancient carbon released in Arctic-boreal wildfires, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16499, https://doi.org/10.5194/egusphere-egu26-16499, 2026.

Fish Lake is located at 2700 m (a.s.l.) on the boundary of the Colorado Plateau and Great Basin geologic provinces in western North America. Climate forecast models suggest that this region will become warmer and drier during the 21st Century, which will likely intensify fire regimes and threaten biodiversity in this region, including the ancient Pando aspen clone located next to Fish Lake. Here we present a paleoenvironmental reconstruction from an 80-meter lake sediment core spanning the last 60,000 years. At the Last Glacial Maximum (LGM), the upland areas near Fish Lake (3200-3500 m asl) were heavily glaciated and plant communities were open and dominated mainly by herbs and conifers, such as grasses (Poaceae) and spruce (Picea spp.). During the LGM fire activity was low due to cold temperatures, low woody fuel abundance and connectivity, and the presence of megaherbivores (e.g., Mammuthus) as reconstructed from nearby fossil sites and the presence of coprophilous fungal spores (Sporormiella) in the Fish Lake sediments. In the Late Glacial Period, the demise of upland glaciers and megaherbivores was accompanied by a ‘release’ in woody vegetation, especially spruce and pine (Pinus spp.) and a rise in charcoal accumulation. During the Early Holocene, this rise in burning sustained and was likely enhanced by warming temperatures and the establishment of closed-canopy forests similar to modern composed of Engelmann spruce (Picea engelmannii), aspen (Populus tremuloides), and subalpine fir (Abies lasiocarpa). Fire activity in the Middle Holocene remained high, with a stepwise increase observed during the Late Holocene that occurred with increasing evidence of human activities and amplification of El Nino-Southern Oscillation (ENSO). Throughout the 60,000 record, aspen pollen is consistently present. While pollen alone does not provide direct evidence of the long-lived Pando aspen clone, this record does confer the presence of aspen growing near Fish Lake through contrasting climate periods and fire regimes. This long-term reconstruction offers new insights into the interactions of climate, vegetation, and herbivory in shaping wildfire in western North America to help support land management policies.

How to cite: Morris, J., Carter-Kraklow, V., Codding, B., Winward, N., Brunelle-Runberg, A., Vornlacher, J., Werne, J., Marchetti, D., Wilson, K., Anderson, L., Abbott, M., and Power, M.: Reconstructing the last 60,000 years climate-driven interactions of fire, vegetation, and megaherbivores at Fish Lake, Utah, USA, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16685, https://doi.org/10.5194/egusphere-egu26-16685, 2026.

Fire regimes show substantial variability among ecosystems, with a fundamental contrast between surface and crown fires. While surface fires predominantly consume understory vegetation, crown fires involve the combustion of canopy fuels. This distinction is therefore central to understanding fire-driven ecosystem dynamics and to designing effective wildfire risk management strategies.

Ongoing climate change is expected to further reshape fire regimes by altering temperature and moisture conditions and by driving shifts in species distributions. These processes may indirectly modify fire behaviour by changing fuel structure, continuity, and overall landscape flammability.

Within this context, plant functional traits provide a valuable lens through which to interpret fire–vegetation interactions. They not only respond to environmental filtering but also actively shape ecosystem functioning. Two traits in particular—branch shedding (the ability to shed dead lower branches) and serotiny (the retention of mature cones that open after exposure to high temperatures)—have been proposed as key adaptive strategies influencing fire regimes. However, there is limited understanding of whether environmental factors can effectively cancel the adaptive advantages conferred by these traits, which, if occurring frequently, might substantially alter ecosystem dynamics.

To explore these issues, we integrated forest information from the Spanish Forest Map with fire severity data from the European Forest Fire Information System (EFFIS). Our analysis focused on pine species dominating coniferous forests across the western Mediterranean region. We examined how branch shedding and serotiny relate to crown fire occurrence, and how these relationships are modulated by stand-level attributes such as successional stage, shrubs abundance, and the occurrence of extreme drought during the fire season.

Our results indicate that the effectiveness of these trait-based strategies is, at least in the western Mediterranean, strongly contingent on forest stand conditions and suggests that climate change might disrupt the current spatial consistency of these long-established  fire-traits relationships.

How to cite: Costa-Saura, J. M., Sirca, C., Spano, D., and Valor, T.: Environmental factors disrupting the adaptive advantage of fire-trait syndromes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17500, https://doi.org/10.5194/egusphere-egu26-17500, 2026.

South America (SA) has suffered a multitude of extreme, drought-induced fires in recent years, including 2024 which saw fire emissions across the continent 263 Tg C (84%) above average^[1]. Burned area and fire carbon emissions in SA are projected to increase over the coming decades due to higher temperatures and drier conditions associated with climate change^[2]. These effects are already being seen in the Amazon, where fire is driving the rainforest towards being a net carbon source^[3] and threatening existential climate tipping points. Meanwhile to the South, the ecologically diverse Pantanal wetlands have undergone a step-change in wildfire activity, with 2019–2021 experiencing a 408% increase in annual carbon monoxide (CO) emissions relative to the 2013–2018 average.

CO is a major trace gas released from fires. Its emissions can be used to quantify wildfire carbon impacts and investigate correlations between fire activity and global climate indices. Despite this, there remains considerable disagreement between fire inventory products, with mean annual CO emissions ranging from 284–625 Tg yr^-1 globally, and predictions diverging further at smaller spatial scales. These large uncertainties originate from the underlying assumptions of the inventory methodologies and the imperfect sensitivity of their satellite data inputs. Satellite observations of atmospheric total column CO, combined with inverse modelling techniques, provide a direct, top-down method to constrain these estimates, allowing more accurate CO emissions to be determined.

How to cite: Bradley, B., Wilson, C., Chipperfield, M., Reddington, C., Graham, A., and O'Connor, F.: Top-down carbon monoxide fire emissions over South America correlated with global climate indices, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18115, https://doi.org/10.5194/egusphere-egu26-18115, 2026.

Forest management at the landscape scale is increasingly regarded as a key instrument for maintaining and improving the supply of multiple forest ecosystem services. Contemporary policy agendas, including the EU Forest and Biodiversity Strategies for 2030, together with management paradigms such as sustainable forest management, closer-to-nature forestry and rewilding, promote markedly different pathways. Some approaches rely on targeted silvicultural interventions, while others emphasise non-intervention and natural dynamics. Despite their growing relevance, the spatial prevalence of these contrasting strategies and their implications for ecosystem service provision at regional scales remain insufficiently explored. In this study, we assessed how alternative forest management trajectories affect ecosystem services across the entire forested landscape of the Piedmont region (Italy). Drawing on information from regional forest management plans, we categorised planned management into two broad classes: active management, encompassing silvicultural interventions of varying intensity, and passive management, characterised by the absence of direct interventions. We quantified the spatial extent of each management type and analysed their relationships with three key ecosystem services—carbon storage, fire hazard reduction and tree-species diversity—using principal component analysis and generalised linear models. Additionally, we investigated the association between management strategies and Protected Areas, and whether protection status modulates ecosystem service outcomes. Our results indicate that approximately 60% of Piedmont’s forests are designated for active management, although actual implementation is increasingly constrained by widespread forest abandonment. Active management was consistently associated with higher levels of carbon stocks, reduced fire hazard and greater tree-species diversity. Protected Areas were more frequently linked to passive management, yet their contribution to enhancing ecosystem services appeared limited. Based on these findings, we highlight the importance of: (i) reactivating forest management in abandoned areas, (ii) prioritising active management strategies to strengthen ecosystem service delivery, and (iii) using currently unprotected, passively managed forests as strategic candidates for expanding the Protected Area network, in line with EU2030 policy objectives.

How to cite: Spadoni, G. L., V. Moris, J., Kirschner, J., de Miguel, S., Oliveras Menor, I., Passamani, C., Le Moguedec, G., Ascoli, D., and Motta, R.: How forest management, land abandonment, and protected areas affect wildfire occurrence, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18182, https://doi.org/10.5194/egusphere-egu26-18182, 2026.

Vegetation fires emit a wide variety of aerosol particles. Most originate from the combustion of carbonaceous material, however, fire-induced pyro-convective updrafts can modify the near-surface wind field in a way that mobilizes soil-dust particles from the ground and inject them into the atmosphere. Mineral dust particles are well known as efficient cloud condensation nuclei (CCN) and ice nucleating particles (INPs), thereby substantially altering cloud microphysics and influencing the Earth’s radiation budget through scattering and absorption of solar radiation. When emitted during wildfires, these dust particles are likely mixed with smoke aerosols, which modifies their physio-chemical properties and consequently their impacts on the atmosphere and climate. Therefore, a precise characterization of this emission pathway and robust knowledge of its global abundance are essential.

The fire-driven emission of soil-dust particles has already been incorporated into the global aerosol–climate model ICON-HAM through the development of a sophisticated parameterization that describes fire-induced dust emission fluxes as a function of fire intensity and some soil-surface properties, such as the soil type and the vegetation class at the fire location. Multi-year model simulations have indicated that fire-related dust emissions can account for a significant fraction of the global atmospheric dust load, exhibiting strong regional and seasonal variability driven by a varying fire activity and the local soil-surface conditions.

However, global fire activity has changed substantially over the recent decades due to both climatic and socioeconomic factors, resulting in significant shifts in the magnitude and regional distribution of fire-related dust emissions. Here, trends in fire-induced dust emissions over the past 20 years are analyzed and changes across different continental regions are contrasted. Furthermore, projections of fire activity under future climate scenarios can be used to assess the strength and regional distribution of fire-related dust emissions under changing climate conditions and mitigation strategies. This analysis can contribute to improved estimates of the future global aerosol burden, in particular with respect to the changing fire occurrence in a warmer world.

How to cite: Wagner, R. and Tegen, I.: Trends in fire activity and associated fire-induced soil-dust emissions over the last two decades, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18932, https://doi.org/10.5194/egusphere-egu26-18932, 2026.

The main objective of the Austria Fire Futures study is to develop a unique and innovative framework for fire risk assessment by producing high-resolution fire risk hotspot maps under multiple climate change scenarios. These maps integrate novel insights on local fuel types into forest and wildfire risk models, including mountain-specific variables such as topography, morphology, and recreational activities.

To generate fire risk information at the local scale, advanced fire hazard modeling is required to identify vulnerable forest types in combination with topographic effects. Recent wildfire events in the Austrian Alps have demonstrated that social factors—particularly hiking tourism—are currently underrepresented in fire risk assessments. In response, this study aims to advance fire risk hotspot mapping as a foundational element for forest and wildfire prevention. Such mapping is essential for integrated fire management, encompassing prevention, suppression, and post-fire measures, while contributing to climate change mitigation and minimizing impacts on ecosystems, ecosystem services, and human well-being.

We present modeling results from the Wildfire Climate Impacts and Adaptation Model (FLAM), a process-based fire risk model operating at a daily time step. FLAM employs machine learning techniques to calibrate extended suppression efficiency based on spatial segmentation of landscapes. Historical ground data on burned areas in Austria were used for model calibration and validation. The results include historical simulations (2001–2020) and future projections (2021–2100) of burned area across Austria at 1 km spatial resolution, based on an ensemble of downscaled climate change scenarios. In addition, FLAM was applied to Lower Austria at 250 m resolution, using the most recent high-resolution datasets on fuels, forest cover, human ignition probability, and response times.

The results improve our understanding of fire-vulnerable forest areas in the Alpine region and how these vulnerabilities may shift over time and space under changing climate and fuel conditions. This knowledge enables experts, practitioners, and the broader public to explore plausible future fire regimes and to derive robust short-, medium-, and long-term recommendations for fire-resilient and sustainable forest management, as well as for wildfire preparedness and emergency planning.

How to cite: Krasovskiy, A., Jo, H.-W., Vacik, H., Silva Andrade, M., Formayer, H., Laimighofer, J., Arnberger, A., Schadauer, T., Müller, M., Park, E., San-Pedro, J., and Kraxner, F.: Wildfire Hot Spot Mapping in the Alps - Austria Fire Futures, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19168, https://doi.org/10.5194/egusphere-egu26-19168, 2026.

Fire Radiative Power (FRP) is a quantitative measure of the instantaneous rate of radiant heat energy emitted by a fire during the combustion process. It is usually retrieved via satellite remote sensing and serves as a key indicator of fire intensity and the rate of fuel consumption. FRP is generally estimated by measuring the thermal radiation (radiances) emitted by wildfires, in the Middle Infrared (MIR) spectral range (3.9- 4.0) where the Planck function peaks for sources at 1000K and the contrast between the fire and the cooler background is most pronounced.

A number of satellite imaging systems, at LEO (i.e. MODIS-TERRA and AQUA, VIIRS-Suomi NPP, SLSTR-Sentinel 3A and 3B) and GEO (i.e. SEVIRI-MSG, ABI-GOES, ABI-HIMAWARI) orbits provide FRP retrievals. However, due to their coarse spatial resolution (1-2 km/px) and wide spectral bands, small fires detection and associated FRP retrieval is limited, representing a potential source of omission error.

While currently available high-resolution sensors lack coverage in the Mid-Infrared (MIR) spectral range, recent research has investigated the potential of Short-Wave Infrared (SWIR) sensors as an option. By analyzing airborne data from the AVIRIS, EMAS, and MASTER sensors, studies have established a robust correlation between MIR-derived and SWIR-derived FRP. Furthermore, the SWIR band on Sentinel-3 is already being effectively utilized to estimate FRP for gas flares monitoring.

In this study we retrieve FRP by using two similar hyperspectral sensors, Precursore IperSpettrale della Missione Applicativa (PRISMA) and Environmental Mapping and Analysis Program (EnMAP).  We compare the results with operational FRP products, namely the Sentinel-3 L2 NRT FRP and the CAMS-GOES-W FRP product and evaluate potentials and limitations for mapping the intensity of wildfires and gas flares.

How to cite: Amici, S. and Mota, B.: Critical analysis of Fire Radiaive Power derived by hyperspectral sensors from space, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19257, https://doi.org/10.5194/egusphere-egu26-19257, 2026.

Wildfires play a key role in the Earth system by shaping ecosystem dynamics and influencing the carbon cycle and atmospheric composition. Data-driven models have recently emerged as powerful tools for reproducing observed fire activity, particularly burned area, across a range of spatial and temporal scales. The first version of BuRNN (Burned area and emissions modelling through Recurrent Neural Networks) focused solely on burned area and outperformed all process-based fire-coupled DGVMs from ISIMIP over a wide range of spatial, temporal and spatio-temporal skill metrics. Here we present the 2^nd version of BuRNN, a data-driven model that now jointly represents burned area and fire-related emissions.

How to cite: Lampe, S., Gudmundsson, L., Kraft, B., Hantson, S., Chuvieco, E., and Thiery, W.: Modelling burned area and emissions with deep learning, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19404, https://doi.org/10.5194/egusphere-egu26-19404, 2026.

A new wildfire regime is emerging in Southern Europe, characterised by larger and more intense fires, and by a fire season that now extends beyond the traditional summer months. In this region, climate projections indicate that fire occurrence and severity will increase faster than the global average due to an increased risk of heatwaves and droughts, as well as the evolution of biodiversity towards more resilient and less fire-prone plant species. These changes in wildfire regimes reveal significant gaps in the tools and technologies needed for implementing comprehensive fire management approaches. The community still faces challenges in predicting which wildfires may escalate into extreme events, and the environmental, climate and health impacts of such events remain poorly understood.

The Southern Europe Biomass BURNing (EUBURN) programme emerged as a concerted response to the need to improve the prevention, monitoring and prediction of wildfire risks in southern Europe. EUBURN integrates a series of multi-year and multi-scale field campaigns, lab studies, satellite remote sensing, and advanced modeling to build the research foundations for understanding the complex interactions between wildfires and the atmosphere. Based on this fundamental research, the EUBURN programme aims to support fire responders, ecosystems and air quality management, while addressing specific climate research requirements by developing new or enhanced operational products, tools and services for monitoring and predicting wildfires and their atmospheric impacts.

The first field campaign SILEX (Smoke from European Wildfire Experiment) of the EUBURN programme took place in southern France from 15 July to 3 August 2025. It had three specific objectives: (i) characterising the interactions between fuel, fire, gases, aerosols, radiation and clouds; (ii) contributing to the development of numerical prediction tools for fire behaviour and atmospheric plume dynamics; and (iii) assessing the uncertainties, biases and limitations of fire and smoke products from ground-based and satellite remote sensing. Ten scientific flights were carried out with the ATR-42 research aircraft equipped with state-of-the-art remote-sensing and in situ instruments to characterise wildfires occurring in southern France, as well as their associated smoke plumes, from the onset of emissions to their regional transport. The main purpose of the presentation is to familiarize the broader scientific community with the EUBURN programme and the SILEX dataset it produced. New findings on fire characteristics, gas and aerosol emissions, physical and chemical aging and cloud condensation nuclei will be emphasized.

How to cite: Denjean, C., Paugam, R., Pelletier, S., Borbon, A., Chiapello, I., Costa, M. J., Senra Rivero, F., Rochoux, M., Salgado, R., Tulet, P., Marino, E., Roman, R., Luna, Y., Tong, G., Ceamanos, X., cambre, A., Di Giuseppe, F., Filippi, J. B., Petetin, H., and Ruffault, J. and the Cyrielle Denjean: A European Initiative on Wildfire Risk and Atmospheric Impacts, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19990, https://doi.org/10.5194/egusphere-egu26-19990, 2026.

An enduring heatwave over the Iberian Peninsula in July and August 2025 led to exceptionally extensive wildfires, resulting in the fifth-largest burned area in Spain since 2001 and the fourth-largest in Portugal. Hot and dry fire weather conditions are a key driver of large wildfires in the Mediterranean, and are intensifying rapidly under anthropogenic climate change. However, strong interannual variability of burned area and changes in multiple non-climatic drivers (e.g., land management) complicate the attribution of individual fire seasons.

Methods for attributing climate impacts to anthropogenic forcing are commonly divided into statistical and storyline approaches. Statistical methods quantify changes in the probability of exceeding predefined thresholds across climate states with different forcing levels, whereas storyline approaches examine how a specific historical event might have unfolded in the absence of anthropogenic climate change. Such counterfactual storylines can be generated with Earth system models (ESMs) constrained by observed historical conditions, enabling a process-based interpretation of climate impacts. However, this type of storyline method has not been applied to the attribution of complex ecosystem processes such as fires.

Here, we use the 2025 Iberian wildfire season as a case study to evaluate our nudged circulation storyline simulation with the Community Earth System Model 2 (CESM2) and compare it to statistical attribution. The ESM-based storyline enables a process-based quantification of thermodynamic influences on fire weather and of biological factors controlling fuel load. However, the approaches differ on the role of thermodynamic climate change in intensifying the 2025 fire season. Statistical attribution suggests a large thermodynamic contribution but indicates that events of comparable intensity are not exceptional under present-day climate. In contrast, the storyline approach identifies the 2025 circulation anomaly as unprecedented in magnitude. We show that this discrepancy arises from decadal Mediterranean circulation trends, which are implicitly absorbed into the thermodynamic response in the statistical attribution framework.

Our results demonstrate the utility of a storyline framework in the causal attribution of complex processes such as fires, and highlight the need for caution when applying attribution methods in regions characterized by strong dynamical trends.

How to cite: Dunkl, I., Mindlin, J., Turco, M., and Sippel, S.: Process-Based Attribution of the 2025 Iberian Wildfire Season Using a Storyline Framework, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20208, https://doi.org/10.5194/egusphere-egu26-20208, 2026.

Tropical montane forests have historically not been prone to large-scale forest fires as a result of their high humidity and rainfall. Yet, current increased frequencies and intensity of these fires are making them an increasingly pressing area of study, especially in the context of increasing climate variability and land use changes.  To understand present and future fire dynamics, it is, however, essential to look at the origins and factors behind trends in fire frequency and intensity. To explore this, long-term assessment of the dynamics of montane forest fire, and their relationships to anthropogenic and climate changes, are essential.

Such work has been largely lacking in montane ecosystems due to a paucity of available quantitative data, and a general perception that fire has played a minimal role in shaping biodiversity in these areas. Here we combine historical forest fire records and remote sensing to investigate the evolution and dynamics of montane forest fires in Kenya since the 1920s in response to changes in forest fire management, land use changes and climate variability.  We argue that historically, indigenous communities used their traditional knowledge and practices in managing local fires and limiting them to manageable intensities. However, the introduction of colonial rule shifted their role in forest management and ultimately their relationship in using fire within forest areas.

Our research and datasets highlight that changes in fire dynamics can be linked to extensive colonial prohibition of fire controls by traditional communities and the imposition of fines to deter their use. In addition, introduction of new fire sources through the development of the railway systems along forest areas, introduction of exotic tree species and largescale agricultural expansions exacerbated forest fire dynamics within the montane forests. Meanwhile, the colonial government introduced fire lines as a form of forest fire controls, which were meant as fire control measure and required sophisticated management plans, that were adopted in forest management.

We suggest that these changes have left legacies for contemporary fire issues as a loss of traditional fire management knowledge, smallholder relocation and land restrictions, and industrial pressures have accumulated to intensify fire risk in montane forest ecosystems. Looking into the future, we argue that, as with other regions of the latitudinal tropics, it is essential to understand traditional ecological knowledge and historical path dependencies in order to chart more effective and just conservation strategies including active use of fire and restoration of fire-resistant species. 

How to cite: Gitau, P., Kinyanjui, R., and Roberts, P.: Evolution of tropical montane forest fires in response to shifts in historical forest management, climate variability and land use changes., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20289, https://doi.org/10.5194/egusphere-egu26-20289, 2026.

High latitude wildfire regimes are changing, and boreal regions have seen unprecedented fire activity in recent years. Given the high climate sensitivity of the Arctic and boreal regions, it is important to explore the impacts of these changes. There are also region-specific impacts of biomass burning particular to high latitude regions, such as black carbon (BC) deposition on snow. While many sources of atmospheric pollution are being mitigated, fires are emerging as a growing contributor to poor air quality, both locally to the fire emissions source and across wider regions.

Here we investigate the climate and atmospheric effects of increased biomass burning emissions, including the sensitivity to emission region, focusing on aerosols. We perform idealized emission perturbation experiments in two Earth System Models (CESM2 and NorESM2), where we perturb first all boreal biomass burning emissions and then emissions in smaller regions of interest (boreal North America, East Siberia and West Siberia). These experiments use 2005-2014 as a baseline period, and use the sum of this period as the perturbation, giving an approximately x10 perturbation in the regions of interest, in both fixed SST (30 years) and coupled (200 years) simulations. The strength and location of the aerosol changes studied here (when comparing aerosol optical depth) are comparable to the recent trends in aerosols between 2015-2024 and 2005-2014.

We investigate subsequent effects on modelled atmospheric composition with a focus on the high latitudes, including air quality implications, and climate response, including effective radiative forcing (ERF) and fully-coupled climate response estimates. The preliminary analysis highlights the role of boreal forests in enhancing aerosol optical depth, over the source regions but also extending into the central Arctic, as well as local air pollution levels. Global and Arctic mean ERFs of 0.5 Wm-2 are estimated, with some distinct differences depending on the region of emission, at least for the Arctic average forcing.

How to cite: Lund, M. T., Staniszek, Z., Samset, B. H., Linke, O., and Ekman, A.: Regional to global impacts of boreal biomass burning emissions changes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20299, https://doi.org/10.5194/egusphere-egu26-20299, 2026.

Changing climatic conditions are amplifying the frequency and intensity of hydroclimatic extremes across Europe. Droughts, heatwaves, intense precipitation and floods increasingly co-occur and cascade, creating compound risks for ecosystems and societies. One of the most visible and severe consequences of these interconnected crises is the growing global threat of forest fires, which are more often facilitated by favorable weather conditions, as well as forest structure and fuel properties. However, the most important cause of fires is related to human pressure, resulting from intentional or unintentional activities that contribute to the outbreak of fires.

Forests are an assemblage of diverse habitats, each of which may differ markedly in fire risk and fire behaviour. Here, we examine how fire occurrence in Poland varies among forest habitat types, land-use patterns and management functions, and how these relationships are shaped by interannual meteorological variability and regional context. We compile (i) forest fire records for Poland for 2019-2024, (ii) a 2024 state forest administration database of forest divisions (i.e., basic forest management units) including habitat type, dominant tree species and main forest function, (iii) a database of socio-economic indicators for country's administrative units, and (iv) annual meteorological characteristics relevant to fire weather. This enables a spatially explicit analysis of fire frequency and (where available) burnt area across heterogeneous forest landscapes, while accounting for administrative-region differences and socio-economic factors that may reflect contrasting management practices, accessibility, and human ignition pressure.

We quantify fire occurrences in 2019-2024 for distinct forest area types (classified by habitat, dominant tree species and function) and evaluate their sensitivity to meteorological conditions across years. The analysis is designed to identify which combinations of forest habitat, tree species, forest function, and local socio-economic structure show consistently elevated fire incidence, whether observed changes between 2019 and 2024 are uniform or regionally differentiated across Poland, and to determine which meteorological characteristics best explain interannual variability in forest fire occurrence. By integrating ecological and forest management attributes with fire records and meteorological context, the study provides an empirical basis for stratified fire-risk assessment in Polish forests and supports targeted prevention and management measures. This research is conducted as part of the NCN project 2023/49/N/ST10/04035 "Fire, burnt area and charcoal - charcoal-data modeling of burnt area, cross-validation of fires and charcoal signal".

How to cite: Kowalczyk, P., Zin, E., Tyburski, Ł., Śleszyński, P., Słowińska, S., Kaszkiel, A., Czubak, D., Klisz, M., Pilch, K., Kaczmarowski, J., and Słowiński, M.: Dimensions of forest fires in Poland, 2019-2024, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22880, https://doi.org/10.5194/egusphere-egu26-22880, 2026.

Mountains create their own weather through topographic modification of the prevailing synoptic meteorology. As a result, wildfires in mountainous terrain may exhibit erratic and extreme behaviour as ridges and valleys modify the prevailing winds. Here we present a case study analysis of a wildfire that occurred in mountainous terrain in subtropical eastern Australia. The wildfire was observed to transition between a wind-driven and plume-driven wildfire on at least three occasions with a periodicity of around 60 minutes. The Weather Research and Forecasting (WRF) model was used to investigate the surface windfield and vertical thermodynamic properties of the atmosphere. Results from the WRF simulations aligned with observational data indicating that topographic lifting caused by only moderate changes in terrain may have contributed to the coupling of the wildfire plume to an elevated layer of humidity leading to rapid pyrocumulus (pyroCu) development. Strong horizontal wind shear caused the pyroCu to detach from the wildfire on at least three occasions with a subsequent return to wind-driven wildfire behaviour. Our results highlight the importance of understanding the influence of what may be perceived as only subtle to moderate changes in terrain on local meteorological conditions and wildfire behaviour.

How to cite: McGowan, H., Guyot, A., Sturman, A., Seifried, V., and Dale, T.: Wind to plume driven wildfire cycles caused by topographically forced wildfire – atmosphere coupling, Southeast Queensland, Australia., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-583, https://doi.org/10.5194/egusphere-egu26-583, 2026.

Wildfires are natural components of fire-prone settings. Yet, their severity, intensity, frequency and duration have escalated to damaging levels in recent decades, predominantly due to climate change. The rise of extreme fire weather conditions has amplified the impacts of wildfires, calling for prevention mechanisms to become more prominent and broadly implemented. In this context, Integrated Fire Management (IFM) emerges as a mitigation strategy worldwide, in which prescribed burning (PB) is a common activity. In Brazil, after the prevalence of fire exclusion policies, the Integrated Fire Management National Policy (PNMIF, in Portuguese) was approved in 2024, positioning IFM as a strategy to reduce the intensity and severity of wildfires, while encouraging a comprehensive understanding of the ecological, economic and sociocultural aspects of fire. In light of the recently approved National Policy, documentation of existing results is extremely important, as current IFM projects can inform the implementation of fire management activities at a national level. In this study, we assess over two decades (2001-2021) of remote sensing data to evaluate fire regime in protected areas in Brazil before and after the implementation of PB, through the analysis of burned area and fire intensity in the late dry season. We use MODIS MCD64A1 product to estimate burned area and Fire Radiative Power (FRP) derived from MCD14DL active fire product to estimate fire intensity. We evaluate 31 Protected Areas in Brazil, including Indigenous Lands, Conservation Units and Quilombola Territory, spread across Amazonia, Cerrado, Mata Atlantica and Pantanal biomes. We separate them into four groups, based on the year when PB started: 2015, 2016, 2017 or 2018. We compare the Kernel Probability Density Function for 11 different percentiles, from p50 to p99, of burned area and FRP for the periods before and after the implementation of PB of each group. We emphasize extreme events using the percentiles above p90 (p90, p95 and p99). Our results indicate that PB effectively reduces burned area and FRP, but its effectiveness decreases during extreme events, as shown by the prevalence of smaller reductions at higher percentiles. We hypothesize that extreme events are predominantly driven by climatic variables, which limits the effectiveness of PB in such conditions. This becomes increasingly relevant under a changing climate. Our results also indicate that PB does not yield immediate outcomes. For burned area, groups with the shortest PB history are ineffective at p99 in 2017 and from p85 onward in 2018, evidenced by higher values after PB implementation relative to the pre-implementation period. For FRP, 2018 is also dominated by the ineffectiveness of PB. This research is ongoing, and our preliminary results highlight the role of PB in managing burned area and fire intensity, as well as the influence of climatic factors in driving extreme fire events. Thus, the implementation of PNMIF and the management of wildfires require strategic planning and continuous monitoring, with adaptation and mitigation mechanisms as key components. 

How to cite: Veiga, R., Rodrigues, J., Sena, C., Peres, L., Moura, L., Boock, J., Gajardo, O., Silva, D., Schmidt, I., and Libonati, R.: Prescribed burning reduces wildfire impacts in Brazil, but extreme events are climate-driven, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-897, https://doi.org/10.5194/egusphere-egu26-897, 2026.

Anomalies in sea surface temperature of the tropical Pacific Ocean, are associated with changes in precipitation and humidity patterns in the Amazon region. Temperature increases (El Niño) causes abnormal dry seasons, making the forest more susceptible to wildfires. The decrease (La Niña) in ocean temperatures implies abnormal increases in rainfall, especially in the northern region of Amazon. Between 2019 and 2024, the municipality of Santarém (Pará, Brazil), eastern Amazon, was affected by an increase in forest fires, leading the local government to declare an environmental emergency state in 2024. The objective of this study was to characterize burned areas and changes in land cover in Santarém during the recent ENSO period (2019 to 2024). Annual data on Land Use and Land Cover (LULC) from MapBiomas (Collection 10), and monthly data of burned area from MapBiomas Fogo (Collection 4) were used. National Oceanic and Atmospheric Administration's (NOAAs) Weather Prediction Center data was used to define El Niño (EN), La Niña (LN) and “no anomalies” months (Regular - Rg). LULC was analyzed in small properties (SMp > 300 hectares (ha)), medium-sized (MS, 300 to 1125 ha), large properties (LP >1125 ha), and smallholdings (SMs < 300 ha), as well as indigenous lands (ILs), quilombola areas (Qa), and conservation units (Cs). These data were extracted from SICAR (National Rural Environmental Registry System). For EN periods, 19 months between 2019 and 2024 were analyzed, with 62,962.56 ha of burned areas. For LN (28 months), 15,799.59 ha were burned. During Rg (25 months), 60,109.20 ha of burned area were detected. During EN and Rg periods, Forest Formation (FF) was the most affected coverage, with 36,016.92 ha (EN, 57%) and 39,183.03 (Rg, 65%). For LN, the highest burned coverage was Pasture (Pt), with 8,537.94 ha burned. Mostly small properties (SMp) were affected, with 1,249.29 ha (EN) and 1,124.82 ha (Rg) of FF scorched (1.87%). Pt areas were also affected in SMp (2.07%), accounting for 4.84% of the total. For the protected areas, Cs had 5.63% of the total burned area, with 3,913.47 ha (EN), 2,574.09 ha (Rg) and 1,330.56 ha (LN), mostly in FF. ILs had 1.04% of the total, mostly during EN, with 1,287.27 ha. Other classes (MS, LP, SMs and Qa) accounted for only 1.06% of the burned area. Areas without SICAR classification had the largest burned area (87.43% of the total). These patterns raise concern, given that burning persists in forest areas that remain unprotected and unmonitored. The occurrence of climatic phenomena that induce drier vegetation and less precipitation in the Amazon enable increases in  burned area associated with anthropic activities. Implementing fire-prevention measures in vulnerable areas is crucial, and it is equally important to account for these climatic periods. Investment in public policies for environmental education and fire mitigation are essential for transforming these scenarios, in order to mitigate the effects of climate change.

How to cite: Freitas, S., Dutra, D., Haddad, I., Mataveli, G., Escada, M. I., and Aragão, L.: Fires during recent El Niño and La Niña periods in Eastern Amazon, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1269, https://doi.org/10.5194/egusphere-egu26-1269, 2026.

In recent years, California has experienced increasingly severe wildfire events, leading to substantial socio-economic losses and ecological degradation. Against this backdrop, this study aims to identify key indicators influencing forest fire occurrence, assess forest fire vulnerability, and examine vegetation cover changes in Butte County, California. First, we analyze and visualize 14 wildfire-relevant environmental and anthropogenic factors, capturing climatic, topographic, and land-use characteristics of the study area. To address multicollinearity among variables, the Variance Inflation Factor (VIF) is employed, resulting in the selection of 11 non-collinear indicators. Based on these selected variables, a Boosted Regression Tree (BRT) model is applied to evaluate spatial patterns of wildfire vulnerability in Butte County. Finally, we employ Vegetation Fractional Cover (VFC) to quantify post-fire vegetation cover changes, enabling an assessment of wildfire impacts on vegetation dynamics. The results indicate that rainfall, land use, and topographic conditions exert significant influences on wildfire vulnerability in Butte County. Moreover, VFC analysis reveals a notable decline in vegetation cover surrounding fire locations between July 2024 and September 2024, highlighting the short-term ecological impacts of recent wildfire events.

How to cite: Tong, C.: Wildfire Vulnerability Modeling and Vegetation Cover Change in Butte: An Analysis Based on Boosted Regression Tree, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4145, https://doi.org/10.5194/egusphere-egu26-4145, 2026.

In February 2024, the Las Tablas wildfire killed at least 135 people near the coastal city of Valparaíso, Chile, making it the deadliest wildfire disaster since the 2009 Black Saturday bushfires in Australia. Amid increased focus on global wildfire disasters, the economic impacts of wildfires often overshadow fatalities, presenting a gap in analysis and understanding of why some fires are more deadly than others. Here, we reconstruct the 2024 Las Tablas Fire and use a mixed methods approach to examine the factors contributing to the record fatalities. We further assess how this fire aligns with other recent global wildfire disasters that produced mass fatalities. The Las Tablas Fire occurred during a record heat wave and with an offshore wind, known locally as a puelche wind. Satellite data and burn severity patterns show it exhibited high rates of spread burning through highly flammable, non-native forests and complex topography in the wildland-urban interface. Most fatalities occurred in neighborhoods of informal, unregulated housing not connected to city services and home to some of the most vulnerable residents of the region. Both the biophysical and social factors present in the Las Tablas Fire are consistent with many recent fatal wildfire disasters globally, particularly in Mediterranean climates. These common denominators point to the potential for increasing frequency of fatal wildfire disasters with climate change, land use change, and social disparities. They also highlight the complexity of mitigating fatal wildfires.

How to cite: Kolden, C.: Why was the 2024 Las Tablas Fire in Chile so deadly? Common socioecological drivers of global wildfire disasters, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5690, https://doi.org/10.5194/egusphere-egu26-5690, 2026.

Extreme forest fires are escalating globally, causing extensive forest loss and prolonged recovery time, which raises the risk of forests transitioning from carbon sinks to sources. However, most studies define extreme fires solely by burned area, neglecting interactions among fire characteristics and potentially underestimating their impacts on post-fire recovery. Here we constructed a global multidimensional forest fire dataset (2001–2021) comprising >300,000 events with burned area, intensity, duration, spread rate, and severity. After around 2010, fire characteristics intensified, especially in extratropical forests, with burned area and duration often triggering cascading amplifications of intensity, spread rate, and severity. While extreme large‑area fires frequently coincided with fast spread and long duration, they seldom reached extremes in both intensity and severity. Notably, the 244 forest fires that were extreme across all five dimensions simultaneously increased significantly, yet 75% occurred after 2011. Forests affected by these synchronized extremes required 1.2 years longer to recover than the global mean and also 0.4–1.0 years longer than fires extreme in any single dimension. We further identified that the interaction between fire intensity and severity as the primary driver of prolonged recovery across nearly all biogeographic pyromes. These results demonstrate that conventionally defined extreme large-area fires do not necessarily represent the most ecologically damaging events. Despite increasing global fire-suppression investment, current strategies may primarily remove low-intensity, small fires while failing to mitigate the catastrophic consequences of climate-amplified extreme wildfires, escalating threat poses profound challenges to global forest recovery and carbon-cycle stability.

How to cite: Lv, Q. and Peng, J.: Synchronized Extremes in Forest Wildfires: Amplified Recovery Delays from Coupled Intensity and Severity, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6152, https://doi.org/10.5194/egusphere-egu26-6152, 2026.

Extreme wildfires are one of the most destructive natural phenomena in our world. Modeling of these fires is challenging due to large uncertainties in model parameters as well as initial and boundary conditions. High-resolution observations of fire behavior can be used to reduce modeling uncertainties. However, adequate observational systems and methods are scarce.

We will present airborne based mid-wave infrared (MWIR) and long-wave infrared (LWIR) imagery with high spatial and temporal resolution of extreme fires that occurred in California around September 2022. This data was captured using the SJSU Wildfire Imaging Suite during the California Fire Dynamics Experiment (CalFiDE) campaign together with meteorological data both from ground-based and airborne instruments.

We will show a comparison of our airborne observations with the infrared spectral imagery captured by the spaceborne MODIS and VIIRS instruments during the campaign. The cross-platform comparison will address the spatial extent of the fire as well as the differences in the registered radiance values. 

This rich dataset, including more than 400 overpasses over multiple days and multiple extreme fires, provides a unique detailed view of the active wildfire behavior during these fire events. 

Acknowledgements: This work was supported by the U.S. National Science Foundation under award number 2053619, the U.S. National Oceanic and Atmospheric Administration during the CalFiDE campaign, and the EU COST Action NERO (CA22164).

How to cite: Stockmans, T., Klofas, A., Clements, C. B., Giesige, C. C., Goldbeck-Dimon, E., Manoj Santhi, S., Olivera Prieto, P., and Valero, M. M.: Airborne infrared observations of extreme wildfires in California 2022, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6694, https://doi.org/10.5194/egusphere-egu26-6694, 2026.

Extreme wildfires present an increasing environmental and socio-economic concern across Europe. However, the absence of comprehensive observational datasets of fire behaviour restricts the capacity to analyse, model, and manage extreme wildfire events effectively. This work aims to develop a unified and standardized dataset of extreme wildfire events in Europe based on reliable official sources, thus contributing to a consistent reference for research and management applications.

Fire event information was gathered from European fire management agencies. The data has been filtered and organized to capture the most relevant variables for extreme fire behaviour analysis, such as the temporal evolution of the burned area and the fire perimeter. Data processing and validation was performed in QGIS and outputs were exported in GeoJSON format to ensure easy integration in any geographic information system. The produced dataset allows the temporal and spatial reconstruction of fire progression. The overarching goal is to develop a comprehensive dataset of extreme wildfire events across Europe to support research and modelling efforts through shared, high-quality and standardized data resources.

Acknowledgements: This research initiative is based upon work from COST Action NERO, CA22164, supported by COST (European Cooperation in Science and Technology).

How to cite: Olivera Prieto, P., Fernández Anez, N., Berčák, R., Stockmans, T., Manoj Santhi, S., Giannaros, T. M., and Valero, M. M.: Building a Unified Framework for Extreme Wildfire Data in Europe, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6760, https://doi.org/10.5194/egusphere-egu26-6760, 2026.

Extreme wildfires have become more frequent in many regions worldwide in recent years. Compared with moderate events, the most intense wildfires, especially those that generate pyrocumulonimbus (pyroCb) clouds, exert disproportionately large impacts on the Earth system and cause substantial socioeconomic losses. High‑fidelity modeling is a critical tool for studying wildfire behavior, identifying key drivers, and quantifying their impacts. Here, we improve the pyroCb representation in the global Energy Exascale Earth System Model (E3SM) by leveraging its kilometer-scale regionally refined model (RRM) capability, integrating satellite-based high-resolution (hourly, 500 m) fire emissions, and incorporating fire-related parameterizations. Compared with conventional global simulations at coarse resolution (approximately 100 km), the kilometer-scale grid spacing over the fire source region substantially improves the simulation by explicitly resolving more fire-related dynamic and thermodynamic processes. In the meanwhile, the RRM configuration enables seamless smoke transport and interactions between the fine and coarse meshes and allows efficient simulation of downstream fire aerosol spatiotemporal distributions in regions where high resolution is less critical. The simulations capture essential pyroCb features, e.g., cloud height, spatiotemporal evolution, and convective intensity, as observed by satellite and ground measurements for different cases occurred in California. Sensitivity experiments suggest that pyroCb formation in our simulations is not controlled by a single dominant factor, but instead emerges from the coupled interactions of multiple fire-atmosphere processes. Furthermore, we use the global RRM to investigate the mechanisms of stratospheric aerosol injection and examine implications for seasonal and longer predictability. Because these simulations include interactive chemistry and aerosol schemes, we also evaluate the impacts of wildfires on surface air quality.

How to cite: Tang, Q., Ke, Z., Zhang, J., Chen, Y., Ding, X., Randerson, J., Zhang, Y., and Chen, G.: Extreme wildfire simulations using kilometer-scale regionally refined E3SM, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8792, https://doi.org/10.5194/egusphere-egu26-8792, 2026.

Large wildfires are a major source of atmopsheric aerosol. The lifetime of the smoke aerosol in the atmosphere, and thus their impact on the climate, is strongly controlled by the altitude in which the smoke is injected into the atmopshere. While most fires release their smoke in the lower troposphere, so called pyrocumulunimbus (PyroCb) events have the potential to transport smoke aerosol upwards deep into the troposphere and even into the lower stratosphere, extending the lifetime of the smoke by several orders of magnitude. These PyroCbs are thunderstorms that are triggered by extreme heat release and occasionally form above particularly intense wildfires.

For example, during the extreme PyroCb event now often referred to as the “Australian New Year’s Eve Event” of 2019/2020, deep pyro-convective plumes generated by record-breaking wildfires injected vast quantities of smoke into the tropopause region that are comparable to those of a major volcanic eruption. It is therefore crucial to understand which fires produce deep PyroCbs and why. In this study, we investigate the critical heat emission threshold at which shallow wildfire smoke plumes transition into pyroCbs that penetrate deep into the tropopause region. We further examine the sensitivity of the pyroCbs to further changes in the total amount of heat released by the fire and analyze how changes in the sensible heat emissions and water vapor release impact plume dynamics. 

To do that, using case studies of extreme fires such as the Australian New Years Eve PyroCb event, we perform semi-idealized simulations with a regional high-resolution atmospheric model. Based on the so simulated plumes, we uncover a pronounced bimodal behavior of the fire-induced convection with an abrupt onset of pyroCb formation when the sensible heat flux emissions by the fire exceeds 50kW m^-2. We show, that whenever cloud formation is present within the plume, the plume top height is mainly controlled by the sum of the sensible and latent heat flux by the fire, while the ratio between the two plays a subordinate role. Increasing either heat flux will simultanously raise  both the plume water content and temperature anomaly within the cloud.  These results show the importance of accurate estimates of heat and moisture released by fires for predicting pyroCb development. Encouragingly, these results suggest that a reliable estimate of the total heat flux might be sufficient to characterize the behavior of pyroCbs, reducing the need for detailed partitioning of sensible and latent heat.

How to cite: Müller, J., Senf, F., and Tegen, I.: How Sensible Heat Release and Water Vapor Emissions from Fires Impact the Characteristics of Pyro-convective Plumes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10023, https://doi.org/10.5194/egusphere-egu26-10023, 2026.

Extreme fire weather conditions are becoming increasingly unprecedented worldwide, yet the full range of potentially high-impact extreme wildfires remains difficult to assess. Here we generate a large ensemble of wildfire simulations by forcing the process-based model LPJmL-SPITFIRE with a 40-member bias-adjusted and statistically downscaled climate model (ACCESS-ESM1-5). This enables robust sampling of extreme wildfire events and allows comparison against single realizations (using forcing from climate reanalysis GSWP3-W5E and from an individual climate model ensemble member, r1i1p1f1). We show that wildfire ensemble maxima typically exceed single realizations maxima, suggesting that using a single climate forcing misses a substantial portion of the plausible extreme wildfire events due to internal climate variability. Extreme fire impacts (carbon emissions and burned area) respond more strongly to internal climate variability than fire weather conditions, suggesting a strong vegetation-fire feedback sensitivity to the climate forcing. Additionally, the large ensemble simulations capture climate driver-fire relationships not captured by single realizations, where maximum impacts occur without maximum fire danger, and vice-versa, highlighting the critical role of other factors beyond weather conditions that contribute to whether fires become extreme. These findings demonstrate that modelling a large range of possible wildfire events using the full distribution of climate realizations can help identify the mechanisms leading to the most extreme events.

How to cite: Ribeiro, A., Thonicke, K., Billing, M., von Bloh, W., Wessel, J., Undorf, S., Forkel, M., and Zscheischler, J.: Sampling extreme wildfire events from LPJmL-SPITFIRE large ensemble simulations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10291, https://doi.org/10.5194/egusphere-egu26-10291, 2026.

Extreme wildfires and megafires in Mediterranean Europe generate disproportionate ecological, social, and economic impacts, yet the processes that govern transitions from large fires to the most extreme events remain insufficiently constrained. In particular, it is unclear whether the emergence of megafires is primarily controlled by short-term atmospheric fire-weather anomalies, antecedent drought-driven fuel preconditioning, or their compound interaction. Clarifying these mechanisms is critical for improving impact-oriented wildfire risk assessment and early warning.

Here, we analyse 11,403 summer wildfires (≥30 ha) that occurred across Mediterranean Europe between 2008 and 2022, including 44 megafires (≥10,000 ha). Fires are classified into four size categories (30–100 ha, 100–1,000 ha, 1,000–10,000 ha, and ≥10,000 ha) to explicitly examine transitions across wildfire size classes. Official fire perimeters from EFFIS are combined with the MESOGEOS environmental–fire datacube (daily, 1 km), integrating meteorological variables, drought indicators, and land-surface conditions.

Fast-reacting atmospheric drivers (air and land-surface temperature, relative humidity, precipitation, and wind speed) are characterized over a ±1-day window around the reported ignition date and aggregated as a 3-day mean to account for start-date uncertainty. Slow-reacting environmental controls are represented using multi-month antecedent drought indicators, including the Standardized Precipitation–Evapotranspiration Index (SPEI), capturing longer-term fuel moisture and stress conditions.

Across increasing fire-size classes, we observe a systematic intensification of hot, dry, and windy conditions near ignition, alongside progressively drier antecedent conditions. Drought indicators show marked stepwise deterioration from medium to very large fires, supporting a strong role of fuel preconditioning driven by prolonged moisture deficits. However, the transition from very large fires to megafires is distinguished less by further increases in drought severity and more by exceptional short-term fire-weather anomalies, particularly strong winds and anomalously high night-time land-surface temperatures.

Using Random Forest classification models with permutation-based feature importance and repeated cross-validation to address class imbalance, we identify a compact and interpretable set of predictors that consistently discriminate transitions toward extreme fire sizes. Night-time land-surface temperature and wind speed emerge as dominant drivers of megafire occurrence, while multi-month drought indicators play a secondary role at the uppermost tail. Complementary logistic regression analyses confirm coherent directions of effect and demonstrate meaningful predictive skill for rare extreme events.

Overall, our results support a compound but non-uniform mechanism: antecedent drought and fuel stress set the stage for very large fires, whereas megafires arise when this preconditioning coincides with extreme short-term fire-weather conditions, particularly persistent nocturnal heat and strong winds. These findings provide actionable insights for extreme-event-focused wildfire early warning and highlight the need to jointly address fuel management and short-term atmospheric extremes under a warming Mediterranean climate.

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Turco et al. (2017), Scientific Reports.

How to cite: Ghasemiazma, F., Tonini, M., Fiorucci, P., and Turco, M.: Why some wildfires become megafires: compound short-term fire weather and antecedent drought controls in Mediterranean Europe., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12505, https://doi.org/10.5194/egusphere-egu26-12505, 2026.

Fire plays an important role in the Earth system, affecting atmospheric composition and climate, vegetation, soil and societal resources. Extreme fires are particularly important, as they entail the most severe damages, both in terms of social and ecological values. According to the European Commission, within Europe “most damage caused by fires is due to extreme fire events, which only account for about 2% of the total number of fires”. Their occurrence and impacts are closely linked to climate change, and are related to a wide range of climatic and environmental state variables, such as soil and vegetation moisture content, biomass, temperature, etc. Fires have a powerful impact on the atmosphere and thus aerosol, greenhouse gases, and ozone concentrations, while the indirect effects of fire-related particles affect also water bodies and ice sheets.

Here we summarize progress on the XFires project, which aims to research and quantify all of the above interactions to gain a holistic understanding of extreme fires, including understanding drivers of extreme fire events, modelling their occurrence and their impact in the Earth system. A particular focus of this project lies in gaining an improved theoretical and quantitative understanding of what the medium-term net effects of fire are on global carbon and radiative forcing budgets.  This is important because at a global scale, little is known regarding how extreme fires impact vegetation and soil recovery timescales with respect to the time until the same system next experiences fire. Extreme fires are of particular interest because of how different biomes might hypothetically respond to, and recover from, different extreme fire characteristics, which have significant potential bearing on the global carbon cycle. To address these questions, we first use a cross-Essential Climate Variable (ECVs) approach to define and characterise extreme fires. Results show almost 20k extreme fire events over the period 2003 to 2022. We then explore trends in extreme fire events across biomes and associated greenhouse gas emissions. We will then develop and apply machine-learning approaches to model extreme fires and generate new emissions datasets to be used as input into an Earth System Model, to quantify impacts on atmospheric composition and climate. Finally, we will explore the wider impact of extreme fires on human health, lakes, and via black carbon affecting melt-rates on the Greenland ice-sheet.

How to cite: Sitch, S., Albergel, C., Ciais, P., Bowring, S., Chuvieco, E., Defourny, P., Dorigo, W., Eames, T., Ghent, D., Pettinari, M. L., Haywood, J., Hubert, D., Johnson, B., Kildegaard Rose, S., Lamarche, C., Langsdale, M. F., Segura García, C., Solano Romero, E. C., Vernooij, R., and van der Werf, G. and the XFires Team: Modelling multidimensional causes and impacts of extreme fires in the climate system through X-ECV analysis (XFires), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13422, https://doi.org/10.5194/egusphere-egu26-13422, 2026.

Fire weather waves (FWWs), episodes of persistent extreme fire weather akin to heat waves, sustaining favorable burning conditions over multiple consecutive days. Here, we examine the relationship between FWWs and fire activity, as well as the patterns and trends of FWWs across global terrestrial ecoregions. Accounting for only 4% of days during 2002–2024 in forested ecoregions, FWWs coincided with 26% of the area burned, and half of the top 1% of energetic fires ignited on FWW days. Compared with grassland and shrubland fires, forest fires exhibit a larger and more persistent increase in daily burned area in response to FWWs, particularly in Mediterranean forests. FWWs intensify fire activity by sustaining warmer, drier, and windier conditions compared to non-FWW periods – facilitating chronic periods of favorable fire weather that promote fire spread. FWWs have become, and are projected to become, more frequent, persistent, and severe, with a twofold increase in FWW days projected for 2076–2100 compared to 1979–2024. These findings underscore forecasted FWWs as an important component of early warning systems to strengthen preparedness for extreme forest fires.

How to cite: Abatzoglou, J., Yin, C., Jain, P., Sadegh, M., Flannigan, M., and Jones, M.: Fire weather waves drive extreme fires globally, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14889, https://doi.org/10.5194/egusphere-egu26-14889, 2026.

Extreme wildfires are occurring more frequently in many (although not all) flammable ecosystems. However, what exactly is meant by extreme depends on the context, as fires may be increasing in extent, size, intensity, rate of spread, severity, and/or infrastructural and economic damage, and these different meanings of extreme fire are often conflated. Here, we explore what is meant by extreme wildfire and discuss some of the analytical challenges to understanding extreme fire behaviors. We also examine some examples of analyses that have appropriately differentiated extreme fires from other wildfires to better understand the drivers of extreme wildfires in the context of climate and global change.

How to cite: Staver, C.: What makes a wildfire extreme?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15952, https://doi.org/10.5194/egusphere-egu26-15952, 2026.

As part of the ESA Climate Change Initiative (CCI), two projects – FireCCI and XFires – have developed during the past year several datasets that will significantly contribute to the understanding of the fire phenomenon and the analysis of extreme fires and their climatic consequences.

In FireCCI, we have developed the first global Sentinel-2 burned area (BA) dataset at 20-m spatial resolution (FireCCIS2.v1), achieving a level of detection of small fire patches not possible with coarse resolution sensors, and thus increasing the BA detection to more than 8 Mkm² for the year 2023. This means more than double the BA detected by other existing global products such as MCD64A1 and VNP64A1, and >60% more than the Sentinel-3 based dataset FireCCIS311. This new generation of medium resolution datasets is expected to significantly improve the calculation of fire emissions, and contribute to fire ecology, land use change, and other fire related research.  

Complementary, we have also produced a harmonised global burned area dataset that extends the ESA FireCCI record from 2003 to 2024 (to be extended to the future), with monthly temporal resolution on a 0.25° grid. The product, named FireCCI60, ensures continuity between the historical FireCCI51 product (based on MODIS) and the more recent FireCCIS311 product (based on Sentinel-3), addressing the challenge posed by the forthcoming end of the MODIS mission for long-term fire monitoring and its climate-related applications. This dataset harmonises de FireCCI51 BA detections to resemble as close as possible FireCCIS311, which has a better detection capability, in order to obtain a dataset that is consistent through the time series and can be directly used for time series analysis and extreme fire research. This harmonisation adds around of 1 Mkm² of BA per year to the FireCCI51 detection, with mean yearly BA values of ~5.6 Mkm².

Finally, as part of the XFires project, we have developed an extreme fire events (EFE) dataset, based on FireCCI51 BA and MODIS active fires products, and identified both extreme and non-extreme fire events over the past two decades on a 0.25° grid. The identification of EFEs is performed using a statistical approach on a per-region basis that aims to tackle the fact that different parts of the world present different typical patterns of fire – one of the main challenges to defining EFEs globally. This dataset is currently being updated to integrate the harmonised FireCCI60 one, to obtain a consistent EFE database spanning to the present that can be used to explore trends, causes and consquences of extreme fire occurrence during the past decades.

How to cite: Pettinari, M. L., Segura-García, C., Solano-Romero, E., Torres-Vázquez, M. Á., Khaïroun, A., Ramo-Sánchez, R., Storm, T., Boettcher, M., Neuschmidt, H., Brockmann, C., Albergel, C., Sitch, S., and Chuvieco, E.: CCI Fire advances: global Sentinel-2 burned area product, harmonised MODIS - Sentinel-3 dataset, and extreme fires events database, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16760, https://doi.org/10.5194/egusphere-egu26-16760, 2026.

Wildfires are becoming more frequent and severe in many fire-prone regions, with disproportionate impacts on carbon emissions, ecosystems, and society. However, existing fire and Earth system models still struggle to represent the highly localized and stochastic nature of extreme fire ignitions and to quantify their short-term impacts at fine spatial scales.

In this work, we develop a data-driven framework for next day active fire forecasting at sub-kilometre resolution by combining reanalysis meteorology with satellite fire observations. Our approach builds on recent advances in spatio-temporal deep learning from the AI community, in particular Earth system transformers and denoising diffusion probabilistic models. We use multi-year ERA5 meteorological fields together with static variables (topography, land cover, fuel proxies) as training data, and VIIRS active fire detections and pixel-level brightness/fire radiative power as targets.

The model consists of a deterministic spatio-temporal backbone that encodes the joint evolution of weather and surface conditions, coupled to a diffusion-based probabilistic head that predicts the distribution of future ignition locations and associated fire intensity. This design allows us to explicitly represent uncertainty in rare, extreme events while retaining high spatial resolution. We evaluate the system on multiple fire-prone regions and held-out seasons containing documented extreme fire episodes. Preliminary results show improved skill in localizing ignitions and capturing extreme-tail intensity compared to baseline statistical and convolutional models, particularly in top-k precision metrics relevant for operational targeting.

We plan to couple the predicted intensity fields with standard emission factors to estimate event-scale CO₂ emissions and explore the relative importance of meteorological and surface drivers using feature attribution techniques using causality discovery methods. Our findings illustrate the potential of modern probabilistic deep learning to bridge between high-resolution fire observations and Earth system applications, and to support the assessment and management of future extreme fires.

How to cite: Bai, Y., Athanasiou, G., Antonopoulos, D., Papoutsis, I., and Carvalhais, N.: Probabilistic forecasting of wildfire ignitions and intensity at sub-kilometre scale using diffusion models, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18849, https://doi.org/10.5194/egusphere-egu26-18849, 2026.

The 2025 European fire season was characterised by record-breaking burned area and multiple extreme wildfire events across the continent. Increasing wildfire extremes in Europe and globally has intensified interest in how climate and land-use changes are altering European fire regimes. Extreme event attribution of antecedent and concurrent fire weather conditions is used here to assess the changing likelihood and intensity of recent events both relative to preindustrial conditions and under projected climate change.

We analyse five regions that experienced extreme wildfire activity in 2025: northwestern Iberia, upland Britain, southwestern Mediterranean France, the eastern Adriatic/Ionian, and northern and western Türkiye. For each region, we attribute changes in the likelihood of short-term fire-weather extremes around peak wildfire activity, using 7-day maxima of vapour pressure deficit (VPD), surface wind speed, and a composite index of VPD and wind, in addition to spring and summer effective precipitation to characterise seasonal drought and fuel accumulation conditions. In addition to weather-related drivers, we assess trends in spring and summer vegetation cover using the leaf area index (LAI) and in land abandonment or reclamation using the changing fraction of managed and unmanaged land.

Climate change strongly increased vapour pressure deficit and the composite VPD/wind index for all southern European regions, with the likelihood of drought conditions at least as strong as 2025 also increasing by over a factor of three relative to in the preindustrial climate. Short-term fire weather or summer drought exhibited a weak positive and negative trend with warming respectively, though an increasing likelihood of spring drought conditions, a key driver of 2025’s wildfires, was identified. Spring vegetation significantly increased across Europe, implying higher fuel loads and a potential for more intense wildfires. Land management trends were mixed, with long-term land abandonment in southwestern France and northern and western Türkiye and a recent, rapid land abandonment signal in the eastern Adriatic/Ionian.

The record-breaking 2025 European fire season occurred in the context of a climate change driven intensification of the fire weather extremes and drought conditions associated with each of the five wildfire events examined. Combined with increasing growth-season vegetation cover and ongoing land abandonment, these factors suggest increases in European wildfire extremes will continue.

How to cite: Keeping, T., Zachariah, M., Barnes, C., Haas, O., Grillakis, E., Pinto, I., Clarke, B., Kimutai, J., Philip, S., Kew, S., and Otto, F.: How Climate and Land Cover Change Shaped Europe's Record Breaking 2025 Fire Season, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19805, https://doi.org/10.5194/egusphere-egu26-19805, 2026.

The 2024–2025 fire season saw extreme wildfires across the Americas, with events in the Amazon, Pantanal, and Los Angeles emerging from the tails of historical distributions and burning substantially larger areas than would have occurred without human-induced climate change. These amplified fire extents translated into severe impacts on carbon emissions, air quality, and communities. These are the key findings in the latest State of Wildfires report: an annual, community-led synthesis developed in response to the increasing prevalence of high-impact wildfire events worldwide.

Globally over this period, wildfires burned approximately 3.7 million km², exposed around 100 million people and over USD 200 billion of infrastructure, and generated more than eight billion tonnes of CO₂ emissions, which was around 10 % above the long-term average, driven largely by intense forest fires in South America and Canada. Impacts were particularly severe in the Amazon and Pantanal, where large-scale forest and wetland fires caused extreme smoke exposure and major economic losses, and in Los Angeles, where January 2025 fires resulted in mass evacuations and substantial damage.

In several regions, climate change substantially increased burned area, with fires approximately four times larger in Amazonia, 35 times larger in the Pantanal–Chiquitano, 25 times larger in Southern California, and nearly three times larger in the Congo Basin compared to a world without human-induced climate change. In these regions, we found anomalous weather created conditions for extreme fires, with prolonged drought dominating in tropical systems, and compound heat, wind, and fuel build-up shaping fires in California. Projections indicate that events of comparable scale will become markedly more frequent in tropical regions under continued warming, while strong mitigation can substantially limit, but not eliminate, the additional risk.

The State of Wildfires report (https://stateofwildfires.com/latest-report/) snapshot of globally extreme wildfire impacts and drivers, providing an evolving evidence base to support preparedness, mitigation, and adaptation as wildfire risk intensifies. Looking ahead, the 2025–2026 edition will expand coverage to emerging hotspots, and we welcome contributions that help capture the next generation of assessments of high-impact wildfire events.

How to cite: Kelley, D. I., Burton, C., Di Giuseppe, F., and Jones, M. and the State of Wildfires report 2024-2025 co authors: State of Wildfires 2024-2025, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19953, https://doi.org/10.5194/egusphere-egu26-19953, 2026.

Wildfires have become much more frequent in recent decades and are posing an increasing threat to human health and the surrounding environment. Beside generating aerosol particles predominantly in the accumulation mode, wildfires also emit giant aerosol particles (> 20 µm) and pyrometeors (> 2 mm), whose occurrence and transport in the atmosphere are not yet fully understood. This knowledge gap must be addressed in order to improve our understanding of the possible effects of these particles on the climate and to advance the early detection and tracking of wildfires using weather radar.

The NOAA/NASA joint aircraft field campaign FIREX-AQ of 2019 conducted systematic measurements of trace gases and aerosol particles in wildfire smoke plumes. During the project, we observed smoke particles up to a nominal diameter of 6.2 mm with state-of-the-art open-path instruments (Cloud, Aerosol, and Precipitation Spectrometer and Precipitation Imaging Probe; both manufactured by Droplet Measurement Technologies, Longmont, CO, USA) aboard the NASA DC-8 research aircraft at various distances from the wildfire. In total, 194 smoke plume encounters (“transects”) were investigated from nine different wildfires with some measured on multiple days. In this study we discuss the shape, occurrence, and transport of particles larger than 0.1 mm emitted by western US wildfires in the near- to mid-field from the source.

Giant aerosol particles and pyrometeors were found in the vast majority of the transects examined, with younger smoke containing more of the very massive particles than 4-hour old smoke. In only 4% of cases where the smoke age was less than 2 hours particles larger than 0.1 mm were absent. The largest particles, measuring up to over 4 mm, were observed during transects in which the Modified Combustion Efficiency (MCE) indicates flaming combustion conditions. All observed particles larger than 0.1 mm were analyzed based on their shape. The results show that the larger the particles are, the more elongated their shape is with median aspect ratios (ratio of major to minor axis length) of 5.2 for particles larger than 2.6 mm. Furthermore, a case study was considered in which we attempt to reconstruct the observed settling of pyrometeors with a size of about 3.5 mm with theoretical calculations.

How to cite: Schöberl, M., Tatsii, D., Dollner, M., Gattringer, A., Kupc, A., Schwarz, J. P., Holmes, C. D., Halliday, H. S., Hair, J. W., Fenn, M. A., Bui, P. T., Stohl, A., and Weinzierl, B.: Giant aerosol particles and pyrometeors emitted by western US wildfires: shape, occurrence, and transport, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21215, https://doi.org/10.5194/egusphere-egu26-21215, 2026.

As the frequency and intensity of megafires continue to increase, projecting and managing future wildfire occurrence is becoming increasingly important. Wildfires damage forests as major carbon sinks, thereby posing substantial uncertainties to carbon uptake. Furthermore, climate change is expected to intensify wildfire spread, leading to greater overall damage. Therefore, future wildfire management requires assessments that incorporate wildfire spread patterns under changing climate conditions. However, most existing studies have focused primarily on estimating wildfire ignition locations, with limited consideration of wildfire spread under climate change. In this study, we trained wildfire spread patterns within wildfire events using a combination of remote sensing data and field survey observations. Based on these patterns, we estimated future wildfire occurrence and subsequent spread using a dynamic Bayesian network framework. We further analyzed changes in forest carbon uptake resulting from wildfire occurrence and spread. Our results indicate that simulations accounting for both wildfire occurrence and spread result in greater total burned area by 2050 compared to simulations considering wildfire occurrence alone. In particular, repeated wildfire occurrences and their spatial propagation expanded the cumulative damaged areas. When wildfire spread was included, forest carbon uptake declined more sharply, with some regions projected to shift from net carbon sinks to net carbon sources. These findings demonstrate that excluding wildfire spread leads to an underestimation of wildfire damage and associated carbon sequestration.

How to cite: Kim, S. and Park, C.: Impact of future wildfire spread on forest carbon seqeustrartion: A case study of South Korea, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21274, https://doi.org/10.5194/egusphere-egu26-21274, 2026.

Methane (CH₄) is the second most important greenhouse gas after CO₂, contributing as much as 0.5°C of warming since pre-industrial times. Soil methane uptake (SMU) is thought to be the only biological sink of atmospheric CH₄, but global SMU estimates remain highly uncertain due to challenges in scaling local data. We develop a data-driven approach to refine this global estimate by incorporating local data of 79,800 flux measurements from 198 sites. This novel approach links the global SMU budget to local SMU fluxes by varying its parameters with soil properties. Our 2003-2018 global SMU estimate is ~39.0 Tg CH₄ yr^-1 —about 30% higher than existing bottom-up estimates and consistent with top-down assessments. The projected future global SMU is shaped by temperature and atmospheric methane, though local SMU is primarily influenced by changes in soil moisture. This study emphasizes the potential of soils in climate regulation and highlights the need to focus on key biomes for better understanding the soil-atmosphere methane feedback and optimizing methane management strategies.

How to cite: Jiang, J. and Yan, Z.: Global Soil Methane Uptake Estimated by Scaling up Local Measurements, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-93, https://doi.org/10.5194/egusphere-egu26-93, 2026.

Greenhouse gas emissions for North America show large disagreement between top down and bottom up methodologies. As part of the REgional Carbon Cycle Assessment and Processes study (RECCAP2) we evaluated these sources of disagreement using atmospheric inversions, process models, and national greenhouse gas inventories. We found that for the period 2010–2019, the national greenhouse gas inventories reported total net-GHG emissions of a source of 7,270 TgCO₂-eq yr⁻¹ compared to top down estimates of 6,132 ± 1,846 TgCO₂-eq yr⁻¹ and bottom up estimates of 9,060 ± 898 TgCO₂-eq yr⁻¹.  The differences between the estimates are from a combination of uncertainties in emissions and removals, but also due to definitions used to account for anthropogenic versus natural emissions or both, including the use of the managed land proxy, and the role of the land ocean aquatic continuum (LOAC). Reconciling net emissions between methodologies is partly achievable after accounting for these methodological and definition-based differences.

How to cite: Poulter, B., Murray-Tortorola, G., Hayes, D., Ciais, P., Bastos, A., and Canadell, P.: The North American Greenhouse Gas Budget: Emissions, Removals, and Integration for CO2, CH4, and N2O (2010–2019), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-178, https://doi.org/10.5194/egusphere-egu26-178, 2026.

Methane (CH₄) is the second most important greenhouse gas, with its atmospheric levels having more than doubled since pre-industrial times, and exhibiting highly variable growth rates in recent decades. Significant uncertainties remain in the global methane budget, despite ongoing efforts to quantify methane sources and sinks using bottom-up and top-down approaches. In particular, the relative contributions of natural and anthropogenic sources to the accelerated increase in recent years remain unclear. Wetlands are major natural sources of methane and are expected to respond to climate variability and the long-term increase in global temperature. Accurately capturing their temporal variability and long-term trend is a significant challenge to global methane budget assessments. In addition, atmospheric methane loss, which is primarily caused by the oxidation of hydroxyl radicals (OH), is a significant source of uncertainty in atmospheric inverse modelling. Uncertainties in the magnitude and temporal variability of OH directly impact the estimation of methane emissions. Therefore, improving estimates of methane emissions at global to regional scales advances our understanding of methane and its climate feedback.

In this context, we have applied the Jena CarboScope Global Inversion System to estimate global methane surface fluxes from 2000 to 2024. This analysis uses a Bayesian atmospheric inversion framework to optimize surface emissions by combining atmospheric transport modelling with long-term atmospheric methane observations.  Inversions were carried out at a horizontal resolution of approximately 3.8° latitude and 5° longitude. The prior emissions included wetland fluxes (ORCHIDEE model), anthropogenic emissions (EDGAR database), biomass burning emissions (GFEDv4s), as well as other minor source categories (termites, freshwater, geological and the ocean). To evaluate the sensitivity of emission estimates to assumptions about atmospheric loss, we conducted inversions varying the OH fields, such as a climatological OH distribution and an interannually varying OH field.

We present the temporal evolution of global methane emissions over the last two decades, analyze their spatial distribution and regional emission patterns, and evaluate the consistency of the inversion results using independent observational datasets across different regions. Using two representations of atmospheric methane loss, we found that differences exist not only in whether interannual variability is included, but also in mean magnitude and spatial distribution. These differences lead to variations in inferred emission strengths. The largest variations in flux magnitude occur in  North America temperate, South America temperate, and Eurasia temperate regions. Overall, global posterior fluxes tend to be larger than prior fluxes, with model adjustments that are spatially heterogeneous. While there are differences in absolute flux estimates, posterior global methane emissions derived from various inversion setups show consistent interannual variability, with minor differences in variability during the latter part of the period. Overall, this work provides a multi-decadal, top-down perspective on global methane emissions, emphasizing the importance of accounting for uncertainties in atmospheric loss when interpreting methane budgets. 

How to cite: Basso, L., Rödenbeck, C., and Gerbig, C.: Global methane emissions and their variability over two decades: insights from atmospheric inversion modelling, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3861, https://doi.org/10.5194/egusphere-egu26-3861, 2026.

High mountain sites offer strategic spots for long-term monitoring of greenhouse gases, thanks to their altitude and distance from local anthropogenic emissions that enable measurements of well-mixed troposphere. At the atmospheric monitoring station at Plateau Rosa carbon dioxide (CO₂) and methane (CH₄) mole fractions are measured continuously with a cavity ring-down spectrometer. The station is situated in in the north-western Italian Alps near Mt. Cervino at 3480 meters AMSL and is part of the ICOS (Integrated Carbon Observation System) framework and WMO/GAW program (World Meteorological Organisation/Global Atmospheric Watch, Identification Code: PRS).

In this study we show the CO₂ and CH₄ record measured at the station since 2018 in comparison with NOAA's global trends, demonstrating the PRS representativeness of global mole fractions, and we select pollution events at regional scale that led to significant CO₂ and CH₄ mole fraction enhancements at the station. Analysis of these events using the FLEXPART-COSMO modelling framework for tracing back air masses draws attention to specific hotspot areas in Europe. We identified five pollution events during the 2021-2024 period, lasting more than six hours, associated with air masses coming mainly from the Po Valley, in Italy, and European countries such as France, Germany, Belgium, the Netherlands and the UK.

We finally demonstrate how observations of CO₂ and CH₄ at Plateau Rosa provide a continuous and accurate record of the two major greenhouse gases, which can be used, together with atmospheric transport modelling, to address specific source regions in Europe for targeted reduction efforts.

How to cite: Zazzeri, G., Apadula, F., Henne, S., and Lanza, A.: The continuous record of carbon dioxide and methane at the atmospheric station at Plateau Rosa: analysis of global trends and identification of source regions in Europe , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3981, https://doi.org/10.5194/egusphere-egu26-3981, 2026.

Direct emissions from agricultural soils represented approximately 35% (3.28 kt or 1,269 CO2 equivalent kt) of Switzerland’s total nitrous oxide (N₂O) emissions in 2022, according to the annual Swiss National Greenhous Gas (GHG) Inventory submitted to the United Nations Framework Convention on Climate Change (UNFCCC). While concerning, estimating N₂O emissions over large geographical scales is challenging because of high spatial and temporal variability caused by factors such as climaate, soil properties, and land management. 

This study aims to first improve the Swiss National GHG Inventory by estimating N₂O emissions from agricultural soils using the DayCent model in lieu of emission factors. Process-based models have the advantage that they consider the effects of both management and environmental factors on N₂O emissions, while emission factors only account for management effects. Second, we compare the resulting, national-scale emissions against estimates based on atmospheric inverse modelling of N₂O emissions. 

For the first part of our study we used newly available, high resolution land use maps to simulate N₂O in different land use types (croplands, meadows, and pastures). Simulations were performed based on pedo-climatic conditions that were defined by land use type, regional weather conditions, soil texture, and soil depth. For the second part of the study N₂O emissions from this bottom-up approach were compared for a three year period to top-down estimates that were derived from atmospheric observations and transport simulations using inversion techniques. 

For the years 2021-2023 the bottom-up analysis showed high spatial variability in N₂O emissions that could be attributed to both differences in management (e.g. crop types or fertilization intensity) and soil properties. The results of the bottom-up and the top-down approaches were comparable in terms of seasonality. As expected monthly emissions from the top-down approach were generally greater than those of the bottom-up approach as they include other sources of N₂O that are not accounted for in the DayCent model (e.g. emissions from manure management and indirect N₂O emissions). Similarly, the average percent change in annual N₂O emissions from the bottom-up apparoach was 29% lower than the Swiss National GHG Inventory. 

Our preliminary results show that atmospheric inversions are very useful to evaluate N₂O emission variability at the national scale. The model-based bottom-up approach we set up will allow others to evaluate the effect of different cropping systems under different environmental conditions in future studies and can help stakeholders implement targeted regional measures to reduce emissions.

How to cite: Rainford, S., Henne, S., and Keel, S.: National-scale simulations of N2O emissions from agricultural soils in Switzerland, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4846, https://doi.org/10.5194/egusphere-egu26-4846, 2026.

Atmospheric methane, a key greenhouse gas, has continued to grow in recent years, jeopardizing the Paris Agreement's climate goals. Atmospheric methane growth rate (MGR) shows pronounced inter-annual variability (IAV), which provides a "natural laboratory" to unravel climatic controls on methane dynamics, thereby improving future projections critical to climate mitigation. While multiple processes are known to influence methane sources and sinks, the drivers remain actively debate and their interplay is unquantified systematically. Here, we integrate state-of-the-art emission inventories, observation constraints, and model simulations to resolve and evaluate systematacially these contributions. Challenging the prevailing wetland-centric consensus, we demonstrate that wildfires dominate the IAV in MGR through near-equivalent dual mechanisms: direct methane emissions and indirect atmospheric sink, followed with wetland emissions and lightning-induced sink effects. These drivers are orchestrated by the El Niño-Southern Oscillation (ENSO) through distinct phase-specific contrasts: during El Niño, disproportionately escalating wildfire impacts are partially offset by suppressed wetland emissions and enhanced lightning sink, whereas La Niña amplifies wetland emissions and inhibits lightning-induced sink. This framework largely explains observed MGR variability. Our study implies that under future warming, the nonlinear intensification of fire-climate feedbacks may accelerate atmospheric methane growth, posing a greater threat than previously anticipated.

How to cite: Wang, X. and Zhang, Y.: Wildfires dominate inter-annual variability in atmospheric methane growth, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5202, https://doi.org/10.5194/egusphere-egu26-5202, 2026.

The global carbon budget is a critical system to understand with respect to global temperature change. An accurate carbon budget correctly allocates carbon among Earth's four key reservoirs: fossil fuel reserves, the atmosphere, the ocean, and terrestrial ecosystems. Such budgets allow for the monitoring of the health of the natural global carbon sinks. Both the ocean and land sinks have demonstrated high levels of resilience in the face of increasing anthropogenic carbon emissions and subsequent growth of carbon dioxide (CO₂) in the atmosphere. However, there are signals that these two critical carbon sinks' abilities to sequester carbon are declining.

Observations of CO₂ and oxygen (O₂; in the form of δ(O₂/N₂)) from both in situ analysers and flask sampling activities from the Jungfraujoch high-alpine observatory (3572 m above sea level) in the Swiss Alps will be used to constrain the carbon budget using the O₂-CO₂ partitioning method to illuminate the behaviour of the ocean and land sinks between 2005 and 2025. High-precision measurements of CO₂ and O₂ are useful for partitioning because these two species are intrinsically linked through photosynthesis, respiration, and combustion processes. However, the dissolution of CO₂ into the ocean does not involve O₂, thus allowing for the separation of the ocean and land sinks. The O₂-CO₂ partitioning, along with other observational-based analyses such as the exploration of seasonal amplitudes and potentially isotopic measurements, will be used to shed light on the behaviour of the ocean and land sinks over the past decade purely from observational records, thus offering a validation and verification process for other, generally modelling-based estimates. The possible downstream climate impacts will be discussed.

How to cite: Grange, S., Nyfeler, P., Mandrakis, V., Zürcher, F., and Harris, E.: Exploring the ocean and land carbon sinks from Jungfraujoch's carbon dioxide and oxygen observational record, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7090, https://doi.org/10.5194/egusphere-egu26-7090, 2026.

Wildfires release large amounts of greenhouse gases into the atmosphere, exacerbating climate change and causing severe impacts on air quality and human health. In this study, based on a bottom-up approach and using satellite data, combined with emission factor and aboveground biomass data for different vegetation cover types (forest, shrub, grassland, and cropland), the dynamic changes in CO₂ emissions from wildfires in China from 2001 to 2022 were analyzed. The results showed that between 2001 and 2022, the total CO₂ emissions from wildfires in China were 937.7 Tg (522.6–1516.0 Tg, 1 Tg = 10¹² g), with an annual average of 42.6 Tg (23.8–68.9 Tg). The CO₂ emissions from cropland and forest fires were relatively high, accounting for 45 % and 46 % of the total, respectively. The yearly variation in CO₂ emissions from forest and shrub fires showed a significant downward trend, while emissions from grassland fires remained relatively stable. In contrast, the CO₂ emissions from cropland fires showed an upward trend, primarily in Northeast China. Hot spot analysis and geographically and temporally weighted regression (GTWR) models revealed significant spatial heterogeneity in emissions across vegetation types. Persistent hot spots of shrub and forest fires were located in Southwest and South China, while Northeast China experienced sporadic but extreme fire events. The GTWR model for shrub fire CO₂ emissions exhibited the highest predictive performance (R² = 0.87), and climatic factors (particularly temperature and humidity) were the main influencing factors. Notably, the recent rise in cropland fire CO₂ emissions in Northeast China is closely linked to region-specific straw-burning policies. The research results provide valuable references for atmospheric transport models, regional fire management, and national carbon accounting frameworks in the context of climate change.

How to cite: Gong, X. and Han, Y.: Spatiotemporal patterns and drivers of wildfire CO2  emissions in China from 2001 to 2022, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7525, https://doi.org/10.5194/egusphere-egu26-7525, 2026.

Since the 1950s, the rapidly rising atmospheric greenhouse gas (GHG) concentrations have driven anthropogenic climate change, with terrestrial ecosystems acting as both sources and sinks of carbon. While global syntheses provide crucial benchmarks, regional assessments are essential to understand the fine-scale interactions between land-use, climate variability, and carbon fluxes. Motivated by this need, the Regional Carbon Cycle Assessment and Processes- Phase 2 (RECCAP2) initiative aims to deliver updated GHG budgets across (sub-) continental scales. Here, we focus on South America, a continent of critical importance to the global carbon cycle due to its extensive tropical forests, particularly the Amazon Forest. This is also important to the methane cycle due to the large wetland areas in the region.

Quantifying the regional carbon budget is challenging because it emerges from the net balance of large opposing fluxes: high productivity and long carbon residence times in old-growth forests act as a sink, while deforestation, degradation, and human-induced fires contribute to a source. Climate variability, including the El Niño-Southern Oscillation and Atlantic-Pacific sea surface temperature anomalies, modulates interannual and decadal fluxes, influencing droughts, fire risk, and forest stability. The interactions of land-use change, climate extremes, and fire introduce substantial uncertainty in current budget estimates.

Using a combination of dynamic global vegetation models, atmospheric inversions, and regional observational datasets, we quantify the terrestrial carbon balance of South America at continental, national, and Amazon basin scales, for the period 2010-2019, and assess recent trends (i.e., 2020–2024) in key components, including land-use and land-cover change (LULUCF) and fire emissions. Preliminary results reveal spatially heterogeneous contributions to the continental carbon sink and highlight regions where disturbances and climate extremes are driving shifts in the net flux towards a carbon source. To provide a more comprehensive overview of the dynamics in this region, we also examine methane fluxes during this period and investigate potential recent trends. Our findings will provide a benchmark for regional greenhouse gas budgets, improve attribution to processes, and inform climate mitigation strategies in South America.

How to cite: Rosan, Dr. T. and the RECCAP2 South America team: Decadal Carbon Budget and Recent Trends in South America: Insights from RECCAP2, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7668, https://doi.org/10.5194/egusphere-egu26-7668, 2026.

Global atmospheric CO2 inversion results have been providing key estimates of net carbon flux variations between atmosphere, land, and ocean. These results seem robust at large spatial scales but are uncertain locally due to spatially compensating errors arising from atmospheric transport uncertainty, observation density and other factors. Inversions using satellite-based CO2 benefit from much larger observation density relative to in situ CO2 data and promise improved capabilities in localizing carbon fluxes. However, it remains unclear which regions and at which spatial granularity atmospheric inversion results are robust and useful for policy relevant budgeting, process interpretation, or as data constraint for global ecosystem model evaluation or calibration.

To address this question we developed a pattern recognition methodology to delineate regions with optimal robustness based on the ensemble of atmospheric inversions of the OCO2-MIP project. The employed optimization procedure balances systematic differences of carbon flux patterns between regions and uncertainties within regions. The algorithm delivers a hierarchical tree-like structure of nested regions that are beneficial for interpretation and analysis. Due to the factorial design of OCO-2-MIP we can address the following key questions: 1) How do these regions compare to the traditionally used TRANSCOM regions? 2) For which regions does the inclusion of satellite based CO2 data lead to large changes in net carbon flux estimates and its ensemble spread? 3) For which regions do we find the largest differences between prior and posterior flux estimates?

How to cite: Jung, M., Gans, F., and Byrne, B.: Discovering regions of robust CO2 fluxes based on an atmospheric inversion ensemble, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9187, https://doi.org/10.5194/egusphere-egu26-9187, 2026.

Carbon Accounting in Forest Ecosystems Under Alternative Management Regimes: Distributional Implications for Baselines and Emission Factors

Juliet Isnino Eisimsidele, Cathal O’Donoghue, Patrick McGetrick

University of Galway

Abstract

Robust carbon accounting in forest ecosystems depends critically on baseline selection, emission factors, and temporal boundaries, yet these elements are highly sensitive to forest management decisions across the forest life cycle. Building directly on existing work on life-cycle economic and social returns to afforestation, this study examines how alternative management regimes, specifically thinned versus unthinned systems, shape carbon accounting outcomes from pre-planting baselines through harvest and post-harvest use, with particular attention to the timing and distribution of carbon benefits.

An integrated life-cycle carbon accounting framework is applied, combining forest growth modelling with carbon stock and flow analysis across full rotation cycles. The approach incorporates management-specific baselines, rotation length, thinning interventions, and the allocation of harvested timber to long-lived construction products, reflecting assumptions consistent with national greenhouse gas inventory practice. The analysis captures both in-forest carbon stocks and post-harvest carbon storage over time by linking forest growth dynamics with harvested wood product pathways. Sensitivity analyses are used to assess uncertainty related to baseline definition, temporal scaling, and key accounting parameters.

Preliminary results indicate systematic differences in both the magnitude and timing of carbon sequestration across management regimes. Unthinned systems concentrate carbon stocks earlier in the rotation. In contrast, thinned systems redistribute a greater share of carbon benefits to later stages through harvested wood products and extended storage beyond the forest stand. These variations affect the representation of mitigation performance within standard reporting periods used in national greenhouse gas inventories and influence implied emission factors.

This research provides empirical evidence relevant to ongoing debates on baseline definition, emission factor design, and Measurement, Reporting and Verification (MRV) by explicitly linking forest management decisions, life-cycle dynamics, and distributional carbon outcomes. The findings support the development of decision support tools and accounting frameworks that better reflect the long-term dynamics of afforestation systems, thereby improving the policy relevance of forest-based climate mitigation strategies within EU and international contexts.

How to cite: Eisimsidele, J.: Carbon Accounting in Forest Ecosystems Under Alternative Management Regimes: Distributional Implications for Baselines and Emission Factors, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9259, https://doi.org/10.5194/egusphere-egu26-9259, 2026.

Since the industrial revolution, the ocean has absorbed nearly one third of anthropogenic carbon dioxide (C_ant), playing a key role in climate regulation while marine systems simultaneously undergo substantial stress. The storage of C_ant in the ocean is spatially heterogeneous, making its quantification both challenging and essential. Because C_ant cannot be measured directly, its estimation relies on indirect approaches that can be broadly classified into model-based and observation-based methods. Observation-based approaches are particularly valuable, as they commonly serve as benchmarks for evaluating model performance. These methods include those based on transient tracer data such as CFCs (e.g., Transit Time Distributions, TTD) as well as approaches relying on marine carbonate system observations, including back-calculation techniques or repeated measurements used to infer decadal carbon changes. In this study, we estimate C_ant concentrations using carbon and CFC data from the GO-SHIP A25-OVIDE and A05-RAPID sections in the North Atlantic and the GO-SHIP A17-FICARAM section in the South Atlantic. C_ant is derived using several observation-based methodologies, including the φ-method, Cant-TMI, TrOCA, TRACE, and a TTD-based approach. This intercomparison provides an up-to-date assessment of widely used observation-based techniques and offers a detailed analysis of their underlying assumptions, methodological differences, areas of convergence, and inherent limitations.

How to cite: López-Mozos, M., Marigómez-Roldán, B., Velo, A., Steinfeldt, R., and F. Pérez, F.: Intercomparison of observation-based anthropogenic carbon estimates across the Atlantic Ocean using hydrographic cruise data, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10468, https://doi.org/10.5194/egusphere-egu26-10468, 2026.

How to cite: Marigómez-Roldán, B., Fontela, M., A. Padín, X., Velo, A., and F.Pérez, F.: Underestimation of the anthropogenic carbon inventory of the Western South Atlantic Ocean linked to Antarctic Bottom Water characterization, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10681, https://doi.org/10.5194/egusphere-egu26-10681, 2026.

Wetland methane (CH₄) emission seasonality is a major yet uncertain component of the global CH₄ seasonal cycle, limited by challenges in accurately characterizing wetland dynamics and CH₄ emissions. Advances in satellite observations, methodology and computing capabilities enable the production of tropical basin-scale wetland-CH₄ seasonality at a finer scale. Here, we quantify monthly CH₄ emissions in the Lake Chad Basin, Africa—a region with pronounced hydroclimatic variability—using an advanced divergence method and TROPOspheric Monitoring Instrument (TROPOMI) satellite observations. We distinguish open water and inundated vegetation and quantify their monthly area dynamics using high-resolution Sentinel-2 data (10 m). Our results reveal a strong seasonal amplitude (4.75 Tg a⁻¹) and significant seasonal hysteresis between CH₄ emissions and wetland inundation (i.e., greater CH₄ emissions during the reduction period of inundation, +1.68 Tg a⁻¹). The cascading link of precipitation–wetland inundation–vegetation succession–CH₄ emissions is proven to drive emission seasonality, comprising a three-month lag for wetland inundation and a subsequent four-month lag for CH₄ emissions. These findings provide new constraints for tropical CH₄ flux estimates, which are the dominant sources of uncertainty between the bottom-up models (± 44—65%), and differences from satellite observations. It is also crucial to improve our understanding of the driver(s) of tropical wetland CH₄ emissions to better assess the impact of future climate changes on these wetland emissions and potential positive feedback.

How to cite: Liu, R., Zhang, G., Liu, M., van der A, R., van Weele, M., Schneising, O., Yang, J., Peng, S., Huijnen, V., Buchwitz, M., Zuo, X., and Dong, J.: Unveiling Cascading Lag Effects of Wetland Methane Emissions: Evidence from Lake Chad in Africa, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10696, https://doi.org/10.5194/egusphere-egu26-10696, 2026.

Monitoring global food security and climate change necessitates a precise understanding of rice production dynamics, given that rice cultivation constitutes a major source of methane emissions worldwide. However, understanding the complex trade-off between rice productivity and methane emissions has been impeded by the high spatial variability of agronomic practices and a scarcity of consistent field data to discern regional trends. Therefore, researchers and policymakers have assessed these trade-offs by focusing on broader variables like area and water regimes, which fail to account for the agronomic variability. To address these gaps, this study employed a physics-aware self-supervised digital twin to map rice areas and yields (a product of agronomic practices) at 500 m resolution across India from 2004 to 2021. As a key global rice producer and methane emitter, Indian rice cultivation has significantly increased in its area (17%) and yield (52%), with specific regions showing a clear pattern of intensification (22.7%), discontinuation (24.4%), and expansion (37.5%). By integrating these detailed rice yield maps with top-down methane emissions, the analysis uncovered nine distinct yield emission decoupling scenarios where rice cultivation did not necessarily increase methane emissions. In the most favourable scenario, approximately 27% of cultivated areas achieved higher yields with concurrently reduced emissions, providing evidence of sustainable decoupling. However, a concerning scenario in 6% of the cultivated areas involved regions with reduced yields and increasing emissions, suggesting inefficient cultivation practices and poor resource management.  Such decoupling scenarios in cultivation offer insights to enhance global food security strategies effectively, while also indicating a need to rethink existing emission estimation methods.

How to cite: Ilampooranan, I., Narayanan, M., and Sharma, A.: Does Rice Cultivation Decouple from Methane Emissions?, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10785, https://doi.org/10.5194/egusphere-egu26-10785, 2026.

Tropical peatlands constitute the largest and most uncertain natural source of methane. Methane is a highly potent greenhouse gas, with a 100-year global warming potential approximately 30 times that of carbon dioxide, and accounting for around one quarter of total anthropogenic radiative forcing.

Natural wetlands contribute roughly one-third of global methane emissions, while tropical wetlands dominate this flux due to their high productivity, warm temperatures, and persistently waterlogged conditions. However, significant uncertainties remain in estimating current methane budgets and in understanding how environmental drivers, such as temperature, hydrology, and soil carbon availability, interact to regulate tropical wetland methane emissions.

Robust digital twins of tropical methane regions are being developed with The Joint UK Land Environment Simulator (JULES) to address these gaps. A first step towards achieving this understanding is the evaluation of JULES wetland methane emissions across different model configurations, exploring dependencies related to forcing data, temperature sensitivity and wetland extent. The model will be tightly coupled with Earth observation data to develop a near–real-time framework that enhances process-level understanding of methane dynamics while reducing uncertainty in emission estimates. The resulting improved model representations will inform projections of future methane emission rates under a range of ISIMIP climate scenarios.

These analyses will together deliver policy-relevant insights into the magnitude, variability, sensitivities, and temporal evolution of methane emissions across near- and long-term horizons, supporting climate assessments and informing mitigation and adaptation strategies.

How to cite: Emmett, J., Parker, R., and Gedney, N.: JULES Modelling of Tropical Wetland Methane, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11689, https://doi.org/10.5194/egusphere-egu26-11689, 2026.

The conversion of abandoned coppice forests into high forests is promoted in Europe as a sustainable forest management strategy and as a potential carbon farming intervention under the EU Carbon Removal Certification Framework (CRCF, European Union, 2024), replacing low-input, low-output systems with practices aligned to long-term carbon sequestration goals. While the expected increase in aboveground biomass (AGB) carbon stock is supported by prior research, the effect of this transition on soil organic carbon (SOC) remains insufficiently quantified (Chiti et al., 2026). This study evaluates carbon stock variations across five ecosystem pools, AGB, belowground biomass (BGB), litter, deadwood, and SOC, in two broadleaved forest types, beech and mixed broadleaves, in central Italy. For each forest type, three abandoned coppice stands and three coppices converted to high forest were selected. Conversion occurred 5 years prior in mixed broadleaved forests and 18 years prior in beech stands. Biomass was measured using forest inventory protocols and species-specific allometric equations, while SOC was quantified across the 0–30 cm mineral soil layer by dry combustion (CHN) following carbonate removal.

In beech forests, AGB carbon stock increased from 59.00 Mg C ha⁻¹ (control) to 77.88 Mg C ha⁻¹ in the converted sites, with statistically significant differences (p = 0.001). In mixed broadleaved stands, no statistically significant differences were observed five years after conversion (46.47 vs. 49.70 Mg C ha⁻¹, p = 0.8147).

SOC stocks across the 0–30 cm profile decreased in both forest types following conversion. In mixed broadleaves, total SOC declined from 59.44 Mg C ha⁻¹ to 43.08 Mg C ha⁻¹, in beech, from 89.83 to 78.47 Mg C ha⁻¹. While no significant differences were observed at individual depth layers (0–5, 5–15, and 15–30 cm), total SOC over the 0–30 cm profile was significantly reduced following coppice conversion.

Litter carbon stocks increased significantly in mixed broadleaved forests (from 1.54×10³ to 2.92×10³ kg C ha⁻¹, p = 0.0022), while a non-significant decrease was observed in beech stands. Deadwood carbon stocks remained stable in mixed broadleaves and showed slight reductions in beech.

The results demonstrate that conversion to high forest enhances carbon storage in aboveground biomass, particularly in older stands, while SOC exhibits early-phase declines that may persist in the short to medium term. This highlights the importance of pool-specific and time-sensitive assessment frameworks when evaluating the climate mitigation potential of forest management practices. The inclusion of coppice-to-high forest transitions in CRCF-aligned carbon farming schemes is supported, provided that monitoring protocols capture dynamics across all major carbon pools.

- Chiti, T., Rey, A., Abildtrup, J., et al. (2026). A review of forest management practices potentially suitable for carbon farming in European forests. Journal of Environmental Management, 398, 128391. https://doi.org/10.1016/j.jenvman.2025.128391

- European Union. Regulation (EU) 2024/3012 of the European Parliament and of the Council of 27 November 2024 establishing a Union certification framework for permanent carbon removals, carbon farming and carbon storage in products (Regulation 2024/3012) https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=OJ:L_202403012

How to cite: Antoniella, G., Fantoni, G., Marinari, S., Brunori, A., Mariano, E., Marabottini, R., and Chiti, T.: Impact of coppice conversion to high forest as a carbon farming practice: a case study from broadleaved forests in central Italy, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11713, https://doi.org/10.5194/egusphere-egu26-11713, 2026.

Maritime transport underpins nearly 90% of global trade and constitutes a persistent and growing source of anthropogenic greenhouse gas (GHG) emissions, contributing approximately 3–4% of global CO₂ emissions and around 14% of transport-related emissions within the European Union. As global warming alters atmospheric composition and feedback processes in marine and coastal systems, improved monitoring of maritime emissions is increasingly important for constraining warming-induced greenhouse gas emissions (WIE).

Funded by the European Space Agency, the EO4SEM project assesses the capability of Earth Observation (EO) technologies to provide independent, spatially explicit information on maritime GHG emissions and to complement bottom-up, activity-based inventories. EO4SEM develops a multi-scale Representative Dataset that integrates satellite observations from TROPOMI, PRISMA, EnMAP, and GHGSat with high-resolution emissions simulated using the Ship Traffic Emission Assessment Model (STEAM v4). Modelled emissions are derived from Automatic Identification System (AIS) data and ship technical characteristics, providing hourly, gridded and ship-level estimates of CO₂, NOₓ, and CH₄ emissions across European maritime regions. Satellite data are analysed using a combination of regional to local atmospheric inversion techniques and plume-based methods adapted for moving point sources, enabling emission estimates at regional, shipping-lane, and individual vessel scales. Regional inversions assimilate TROPOMI NO₂ and CH₄ products into atmospheric transport models to derive monthly emission budgets over major European sea regions; estimates for shipping lanes rely on the analysis of the divergence of mass fluxes in satellite images, while ship-level approaches exploit plume divergence and cross-sectional flux methods to quantify instantaneous emissions from isolated vessels. Hyperspectral data from PRISMA and EnMAP are further explored to evaluate methane detection capabilities in port and coastal environments, and GHGSat glint-mode observations are used to investigate methane emissions associated with liquefied natural gas (LNG) ship-to-shore transfers. Together, these approaches demonstrate the potential of EO to identify emission hotspots, characterise spatial emission patterns, and support independent verification relevant to regulatory frameworks such as the EU Emissions Trading System and Monitoring, Reporting, and Verification requirements. However, EO4SEM also highlights substantial scientific and technical challenges. These include low signal-to-noise ratios and strong background interference in coastal and industrial regions, difficulties in separating ship plumes from land-based sources, and the limited spatial and temporal coverage of hyperspectral sensors. Validation remains a challenge due to scarce in-situ measurements over marine environments and uncertainties associated with incomplete or missing AIS data.

The EO4SEM project aims to showcase the transformative potential of EO-based monitoring systems in supporting regulatory compliance, informing policy decisions, and advancing scientific understanding of maritime emissions. Its findings will contribute to paving the way for future Copernicus Sentinel Expansion missions, such as CO2M and CHIME. To support transparency, reproducibility, and policy uptake, all EO4SEM-derived datasets including satellite products, inversion outputs, and model-based emission inventories are being made available through the ESA APEx and geospatial explorer platforms.

How to cite: Brandão, F., Vitorino, J., Sengupta, D., Gini, R., Broquet, G., Chevalier, F., Diouf, M., Vignesoult, H., Fortems-Cheiney, A., Jalkanen, J.-P., Maragkidou, A., Debart, C., Magnall, N., Foucher, P.-Y., and Delavois, A.: Leveraging Earth Observation for Maritime Emission Monitoring: Insights from the EO4SEM Project, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11807, https://doi.org/10.5194/egusphere-egu26-11807, 2026.

The rapidly shrinking carbon budget to stay within the Paris Agreement targets raises the importance of reducing CO₂ emissions from land use (E_LUC), while enhancing land-based carbon sinks. In this context, realistic estimates of E_LUC and land-based carbon dioxide removal require an accurate representation of the fate of harvested wood, including how much carbon remains on site as slash versus being removed for harvested wood products, and how long this carbon is stored.

For regional and global carbon budgets, like the Global Carbon Project’s annual Global Carbon Budget, E_LUC estimates are typically derived from bookkeeping models, which track carbon pools and their responses to land use change and land management. These models, however, currently represent the fate of harvested wood in highly simplified ways: They heavily rely on expert judgement and outdated data to determine slash and wood product pool fractions, typically only using a few generic wood product pools with lifetimes following an exponential decay, which poorly captures the dynamics of long-lived wood products. Here, we implement an improved representation of the fate of harvested wood in the bookkeeping model, BLUE, one of the three bookkeeping models used in the Global Carbon Budget. It is informed by the best available literature, FAO and IPCC data, and the LUH2 land use forcing. Our approach includes spatially explicit, partially time-varying fractions of harvested carbon allocated to slash and six wood product pools with different lifetimes, which capture specific product groups, and a computationally efficient two-step scheme that approximates more realistic gamma-function-like decay.   

Compared to the default implementation of harvested wood products, net E_LUC in our improved scheme differs substantially in regions where harvested carbon is stored for much longer periods, predominantly in the Global North: Over the last 20 years, net E_LUC is more than 30% smaller in Canada and ~10% smaller in Europe, China and Oceania. In contrast, net E_LUC is more than 40% larger in Russia, highlighting that longer storage of harvested carbon can also result in temporary emission increases, since carbon from past harvest or clearing events remains in the system for longer. In tropical regions, where soil turnover times are short and most wood products are short-lived, differences in net E_LUC are small. As tropical regions contribute most to global net E_LUC, this translates into a reduction of only ~3% at the global scale over the last 20 years and even less over longer time scales. 

Our results suggest that the simplified representation of the fate of harvested wood in current bookkeeping models is adequate for global E_LUC estimates. However, as regional and even national carbon budgets gain importance, our improved approach provides a more realistic basis for estimating E_LUC. Our approach is also transferable to land surface and Earth system models, which currently exhibit similar limitations in their treatment of harvested wood. 

How to cite: Nützel, T., Nabel, J. E. M. S., Holube, K. M., Metzler, H., and Pongratz, J.: Improving the representation of the fate of harvested wood in global and regional carbon budgets, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11944, https://doi.org/10.5194/egusphere-egu26-11944, 2026.

In the context of the project "Integrated greenhouse gas monitoring system for Germany", a central objective is to facilitate the availability of marine cruise-based greenhouse gas data for the land-based or atmospheric end-user community.

During annual ship cruises in the southern German Bight since 2019, the concentrations of dissolved methane were continuously determined. Based on wind speed and atmospheric methane concentration, the diffusive methane flux was calculated. Since the configuration of cruise tracks is generally limited to single lines between different ports, spatial extrapolation to wider areas is needed for regional flux estimates.

Therefore, we utilised water body categories provided by the Federal Environment Agency, which included euhaline, polyhaline tidal flats, and coastal waters, to extrapolate methane emissions to the entire region. Six regional categories were defined based on salinity, tidal flat exposure, tidal range, current velocity and other factors. For the years 2019-2023 the six categories had significantly different methane fluxes. The combined fluxes ranged from 3.2 g CH₄ / m² in 2019 to 20.3 g/m² in 2023. By combining the methane recorded during cruise track with the shape files of the different water body categories, we can provide methane emissions estimates and variability from the whole southern North Sea which are suited for use by local authorities and stakeholders.

How to cite: Bussmann, I., Dahal, S., Dähnke, K., Rewrie, L., Sanders, T., Voynova, Y., and Imhof, H.: Methane emissions in the southern North Sea: From single cruise tracks to an aerial German Bight extrapolation, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12295, https://doi.org/10.5194/egusphere-egu26-12295, 2026.

Greenhouse gases (GHGs) play a key role in the Earth's climate due to their connection with the planet's energy balance. A scientific understanding of contemporary GHG fluxes and their drivers is essential for any climate change mitigation policies being implemented or considered. Furthermore, regular, scientifically accurate information on recent GHG emissions supports the implementation of existing policies by allowing to identify - and act on – potential deviations.

Atmospheric inversion systems, such as CarboScope Regional and ITMS-Demonstrator, are used to support climate policies (e.g. Paris Agreement) within the German ITMS (Integrated Greenhouse Gas Monitoring System). They provide independent estimates of anthropogenic and natural greenhouse gas emissions (currently targeting CO₂ and CH₄) on regional scales, with a particular focus on national anthropogenic fluxes. One of the main sources of uncertainty in fluxes retrieved by inversion systems is the misrepresentation of the height of atmospheric boundary layer’s height (ABLH). At the regional scale, inaccuracies in the ABLH can lead to biases in the estimated GHG fluxes that are challenging to identify and quantify, as they can vary in both space and time.

In this study, we evaluate the performance of the STILT (the transport model in the CSR system) and ICON (playing the same role for the ITMS-Demonstrator) in representing the ABLH across Europe. We compare the model performance with high-resolution radiosonde data collected over Europe between 2021 and 2023. We present the spatial and seasonal patterns of bias, and furthermore, we evaluate the models' performance against ceilometer data collected in Germany by the German Weather Service (DWD) ceilometer network. Finally, we show preliminary results on the application of Kriging with External Drift (KED) applied to the European and German domains, exploring the potential of using spatially resolved, data-driven fields as input for ABLH corrections in the inverse model.

How to cite: Galkowski, M., Mouji, N., Förstner, J., Schlemmer, L., Xu, Y., and Gerbig, C.: Towards improving regional and national budgets from regional inversion system CSR by using ABLH measurements, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12601, https://doi.org/10.5194/egusphere-egu26-12601, 2026.

In 2019, more than 26 million natural Christmas trees were purchased in the United States, with nearly twice that number sold across Europe. Each year, the majority of these trees are either landfilled or incinerated, leading to substantial methane and carbon dioxide emissions. This study explores alternatives to natural Christmas trees and evaluates climate-smart end-of-life strategies to reduce the overall carbon footprint associated with Christmas tree consumption. We first employ Google Trends data to approximate global production, consumer demand, and predominant disposal practices for both natural and artificial Christmas trees. Using these data, we construct a global map of Christmas tree-related eCO₂ emissions under different disposal scenarios, including landfilling, burning, and mulching. We introduce a “Christmas Tree Carbon Exchange Index” to quantify the disparity between carbon emissions generated during production and those occurring in consumer regions. For instance, exporting countries such as China exhibit negative index values due to their role as producers of artificial trees for international markets.
Our analysis reveals pronounced regional imbalances in carbon exchange, with major importing regions such as the European Union and the United States bearing a disproportionate net carbon burden. Life-cycle assessment results indicate that the environmental performance of a Christmas tree type is highly dependent on end-of-life management. Natural trees disposed of in landfills emit methane that, over a 10-year horizon, can exceed the cumulative emissions of an artificial tree. In contrast, mulching or chipping natural trees provides a net carbon benefit by returning biomass to the soil. We estimate that the carbon “break-even” point for an artificial tree is approximately 12 years of reuse when compared with a landfilled natural tree, but this threshold increases substantially when natural trees are mulched. Overall, achieving a genuinely greener Christmas requires shifts in both policy and consumer behavior, emphasizing the diversion of natural trees from landfills, support for local production, and long-term reuse of artificial trees.

How to cite: Zhao, L. and Yang, Q.: Towards a Greener Christmas: Reducing the Carbon Footprint of Christmas Trees, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13263, https://doi.org/10.5194/egusphere-egu26-13263, 2026.

Satellite and surface observations of the annual growth rate of atmospheric methane (MGR) often show notable differences, which are typically interpreted as inter-platform discrepancies. The surface network is conventionally considered the more accurate benchmark. Using a chemical transport model (GEOS-Chem) with precisely known methane budget terms, we demonstrate that these differing MGR estimates can be inherently consistent and do not necessarily reflect observational error. By sampling the model to create pseudo-observations, we show that satellite-derived MGR aligns more closely with the model's "true" global growth rate than the surface-network-derived MGR at monthly-to-annual scales. This superior performance stems from the satellite's more comprehensive spatial coverage. Perturbation experiments reveal that the sparse and uneven distribution of surface sites systematically biases global burden estimates in response to short-term, regional emission changes—underestimating signals from poorly sampled regions (e.g., tropical Africa) and overestimating those from well-sampled regions (e.g., East Asia). In contrast, satellite observations provide a more robust estimate of such perturbations, although gaps in coverage can still introduce bias. We conclude that for monitoring the global methane growth rate, satellite observations offer greater representativeness and accuracy than the surface network, reconciling apparent discrepancies and redefining the hierarchy of observational constraints for global-scale methane variability.

How to cite: Zhang, Y.: Reconciling differences in observed annual methane growth rates, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13433, https://doi.org/10.5194/egusphere-egu26-13433, 2026.

The decreasing global trend in δ¹³C–CH₄ suggests that rising biogenic sources are a plausible explanation for the accelerated atmospheric mole fraction observed over the last decade. Tropical wetlands play a critical role in this context and represent one of the largest sources of uncertainty in the global methane budget. The Amazon lowland region, where up to 20–30% of the area can be seasonally flooded, is among the largest natural methane sources in the tropics. However, limitations in both isotopic observations and the representation of wetland diversity and sparse ground base flux measurements continue to limit our ability to attribute emissions to specific ecosystem types and to understand their temporal variability.

In this study, we combine new methane isotopic source signature information from different wetland and aquatic environments in central Amazonia with a refined wetland flux map for the lowland Amazon basin. The combined isotopic and bottom-up flux information is used in atmospheric transport simulations to interpret methane mole fractions and δ¹³C–CH₄ time series at the Amazon Tall Tower Observatory (ATTO). Using a tagged-tracer approach we explore the ability of habitat-specific methane source signatures to distinguish wetland contributions to atmospheric δ¹³C–CH₄ measurements compared to anthropogenic and fire sources. Our results contribute to improving measurement-based source attribution and to reducing uncertainties in regional methane budgets for tropical wetlands.

How to cite: Botía, S., Santos Fleischmann, A., Melack, J., S. Basso, L., Wagh, S., Al Bitar, A., van Asperen, H., Jones, S., Komiya, S., Lavric, J., Sierra, C., Jordan, A., Rothe, M., Moossen, H., Röckmann, T., and Trumbore, S.: Integrating methane isotopic source signatures with high-resolution wetland fluxes to interpret atmospheric δ13C–CH4 measurements in the central Amazon, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13545, https://doi.org/10.5194/egusphere-egu26-13545, 2026.

CO₂ atmospheric inversions are typically used to derive Net Ecosystem Exchange (NEE) estimates from atmospheric observations, while prescribing the anthropogenic component or resolving for CO₂ emissions using proper proxy data. Year-to-year variability of the biosphere sink is primarily caused by climate variations such as drought events, heat waves, and seasonal changes. However, the response of biospheric sink to climate conditions varies spatially across lands depending on vegetation type. In this study, we modified our CSR experiment by augmenting the state space of a standard CO₂ inversion enabling the separate optimization of seven vegetation types within CSR, which increases the state space by a factor seven. The diagnostic biosphere model VPRM is used to provide a priori fluxes of CO₂ for the targeted vegetation classes, which are derived from the remote sensing data. Posterior flux estimates demonstrate the contributions of CO₂ estimates from evergreen, deciduous, mixed forests, as well as shrublands, savanna, croplands, and grasslands. The results indicate that the largest flux adjustments are associated with croplands over Europe, suggesting a shift from being largest sink in the prior model to the largest source of CO₂. A similar analysis at the national scale over Germany shows substantial flux adjustments in croplands, which also exhibit the dominant interannual variability. Although the inversion suggests smaller corrections for mixed, evergreen, and deciduous forests, these vegetation types contribute substantially to total fluxes over Germany and display lower interannual variability than croplands. Additionally, we assess the sensitivity of the system to choices of the prior uncertainty settings.

How to cite: Munassar, S., Rödenbeck, C., Koch, F.-T., and Gerbig, C.: Estimating biogenic CO2 fluxes for different vegetation types using CarboScope-Regional inversion (CSR) over Europe, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13862, https://doi.org/10.5194/egusphere-egu26-13862, 2026.

Atmospheric methane concentrations experience an ongoing increase following a brief stabilization in the early 2000s. Evidence suggests that recent increases are driven by different mechanisms than during the pre-2000 period, with enhanced natural emissions from tropical regions as a leading hypothesis. However, the processes responsible for increasing methane emissions from tropical wetlands remain poorly understood. Improving our understanding of the magnitude, variability, and drivers of methane emissions from tropical wetlands is therefore essential. As large parts of these systems are subject to some form of land management, an often-overlooked factor is how such management practices might influence methane emissions. Land management practices such as prescribed burning and cattle grazing can strongly affect biomass accumulation and, consequently, the availability of carbon substrates for methanogenesis. We therefore hypothesized that treatments leading to a reduced biomass accumulation would also result in lower methane emissions. Here, we present results from a field experiment designed to assess the effects of cattle grazing and prescribed burning on the structure and functioning of an inundated savanna in the Orinoco Plains, Colombia. We conducted chamber measurements of CO₂ and CH₄ fluxes under four treatments: no fire and no grazing, fire and no grazing, no fire and grazing, and fire and grazing. In total, 571 chamber measurements were collected between January 2024 and October 2025. We found that the inundated tropical savanna acted as a substantial source of methane during the wet season (mean 27 mg CH4 m⁻² d^-1) and as a small sink during the dry season (mean -1.5 mg CH4 m⁻² d^-1). Although treatments significantly altered biomass accumulation (range 128–685 g m⁻²), differences in methane emissions among treatments were not significant, indicating that grazing and prescribed burning do not exert a strong control on methane emissions in this tropical wetland ecosystem.

How to cite: Hantson, S., Sánchez, A., Benavides, J. C., Ceballos, J. J., González, M., Roa, Y., Gutierrez Rincon, A., Botía, S., and Fernandes Amaral, J. H.: Limited impact of fire and grazing on methane emission in a tropical inundated savanna, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14756, https://doi.org/10.5194/egusphere-egu26-14756, 2026.

Vegetation greening is commonly viewed as a proxy of increasing land carbon sink since the 1980s. Here we show a weakening or reversal of the coupling between vegetation greening and land sink trends over the recent decade by integrating regional carbon sink estimated by atmospheric measurements with satellite-based greening signals from optical vegetation index. While vegetation greening continued during the recent decade in the northern lands, carbon sinks decreased, implying a carbon sink deficit of 0.37 PgC yr^-1 compared to the cases when the coupling remained constant. In addition to changes in annual and seasonal climate, recent increases in hot extremes and forest disturbances explain 37% and 22% of the carbon sink deficit. This study underscores the imperative to improve the representation of the impacts of climate extremes and disturbances in predictive models of the land sinks, and to bolster forest management practices to maintain ecosystem functioning when facing climate extremes and disturbances.

How to cite: Wang, K., Ciais, P., Xu, Y., Wang, X., Ryu, Y., Zhu, D., Anniwaer, N., Li, X., Tang, S., Yang, H., Piao, S., and Wang, Y.: Weakening and reversal of greenness-carbon sink coupling across northern lands, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-15770, https://doi.org/10.5194/egusphere-egu26-15770, 2026.

An alarming decline has been observed in the European carbon sink in recent years, thought to be a combination of increased harvest, severe droughts, bark beetle infestations, tree mortality and slow-down in tree growth causing reduced CO₂ uptake. These developments are challenging European forests in their capacity to remain carbon sinks. Meanwhile the European Union’s climate policy is counting on this large natural carbon sink to meet their agreed climate targets.

Although Europe is an extensively studied region, several knowledge gaps remain in the European greenhouse gas (GHG) budgets, importantly a lack of assessments of carbon losses from recent forest disturbances. Due to the highly fragmented European landscapes, data at very high resolution of tree cover and biomass are needed to capture disturbance and heterogeneity at small scales. Large uncertainties also remain in the contribution of land-cover and land-use change and fires.

Here we investigate the recent changes in the European carbon sink by combining new high-resolution Earth Observation-based estimates of forest biomass, forest disturbance and recovery, atmospheric CO₂ inversions, and national GHG inventory (NGHGI) approaches to ask (i) which European regions have already turned into carbon sources, (ii) in how far this is due to decreased carbon uptake or increased carbon release, and (iii) how these changes relate to natural and anthropogenic disturbances. We highlight regional differences across the continent and discuss advantages and challenges of the complementary data streams. 

How to cite: Linscheid, N., Mayer, L., Ciais, P., Sitch, S., Brandt, M., Juillard, M., Kowalski, K., Liu, S., Senf, C., Viana-Soto, A., Xu, Y., and Bastos, A.: The European Carbon Budget - declining forest sinks and regional carbon sources, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16287, https://doi.org/10.5194/egusphere-egu26-16287, 2026.

How to cite: Buzan, J., Terhaar, J., Joos, F., Iversen, N., and Roslev, P.: Rapid Methane Emission Reductions within Stabilized Climate Scenarios, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16307, https://doi.org/10.5194/egusphere-egu26-16307, 2026.

Methane (CH₄) is the second most important anthropogenic greenhouse gas, yet the drivers of recent increases in its atmospheric concentration remain insufficiently constrained, particularly regarding the relative contributions of different source sectors and sinks. Improving methane source attribution is therefore essential to support effective climate change mitigation strategies.

Atmospheric methane isotopic measurements (δ¹³C–CH₄) provide valuable information to distangle between methane sources, but have so far relied primarily on sparse surface observations. Recent advances in satellite remote sensing, notably with the TROPOspheric Monitoring Instrument (TROPOMI) onboard Sentinel-5P, now offer near-global coverage of column-averaged methane mole fractions (XCH₄), opening new opportunities for integrated source attribution approaches.

Within the ESA-funded SMART-CH4 project (2024–2026), we investigate how combining satellite methane observations with surface isotopic signature measurements can improve constraints on the global methane budget. We assimilate TROPOMI XCH₄ observations (2018–2024) together with updated δ¹³C–CH₄ datasets using inversion techniques implemented in the Community Inversion Framework (CIF), coupled to the LMDZ-SACS chemistry transport model.

We explore the sensitivity of inferred methane emissions to the choice of observational data streams and inversion configurations, and assess the potential added value of isotopic information for separating methane source categories at the global scale. This work aims to contribute to improved estimates of the global methane budget and its uncertainties by integrating satellite and isotopic constraints, with implications for emission monitoring.

How to cite: Tapin, E., Berchet, A., Martinez, A., Montenegro, N., Menoud, M., Thanwerdas, J., Lan, X., Malina, E., Gasbarra, D., Michel, S., and Saunois, M.: Satellite and isotopic constraints on global methane source attribution, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16589, https://doi.org/10.5194/egusphere-egu26-16589, 2026.

In this study, we provide an update on the methodology and data to compare the national greenhouse gas inventories (NGHGIs) and atmospheric inversion model ensembles contributed by international research teams coordinated by the Global Carbon Project. The comparison framework uses transparent processing of the net ecosystem exchange fluxes of carbon dioxide (CO₂) from inversions to provide estimates of terrestrial carbon stock changes over managed land that can be used to evaluate NGHGIs. For methane (CH₄), and nitrous oxide (N₂O), we separate anthropogenic emissions from natural sources based directly on the inversion results to make them compatible with NGHGIs. Our global harmonized NGHGI database was updated with inventory data by compiling data from the first biennial transparency reports (BTRs) under the Paris Agreement, providing the first annual time-series official reported values in most non-Annex I countries. For the inversion data, we used an ensemble of 30 global inversions produced for the most recent assessments of the global CO₂ and CH₄ budgets coordinated by the Global Carbon Project with ancillary data, and 6 inversion results of CH₄ budgets from Ciais et al, 2026. The inversion ensemble in this study goes through 2024, building on our previous report from 1990 to 2021. The methodology proposed here to compare inversion results with NGHGIs can be applied regularly for monitoring the effectiveness of mitigation policy and progress by countries to meet the objectives of their pledges.

How to cite: Deng, Z., Ciais, P., Hu, L., Gong, P., and Chevallier, F.: National greenhouse gas budgets reconciliation 2025, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17182, https://doi.org/10.5194/egusphere-egu26-17182, 2026.

The ocean has absorbed approximately 30% of global carbon dioxide emissions since the pre-industrial era, thereby mitigating climate change. The uptake of atmospheric carbon depends on coupled changes in ocean circulation, atmospheric CO₂ forcing, and ocean biogeochemical processes, and exhibits pronounced variability on interannual to decadal timescales. However, the scarcity of in situ observations makes it difficult to robustly quantify the magnitude, temporal variability, and drivers of oceanic carbon uptake over the period of 1960-2020.

Using multiple observation-based data products together with numerical experiments based on the Community Earth System Model version 2 (CESM2), we examine the variability of air-sea carbon fluxes on interannual to decadal timescales. Consistent with previous studies, we find that externally forced variability driven by anthropogenic emissions, along with natural variability associated with climate modes such as the El Niño–Southern Oscillation (ENSO) and the Interdecadal Pacific Oscillation (IPO), are key contributors to carbon-flux variability over the past decades. Earth System Models including the CESM2 tend to underestimate the magnitude of this variability because they struggle to capture complex physical and biogeochemical processes as well as inter-decadal climate variability. Assimilating realistic anomalies in observed surface winds improves the representation of variability in the equatorial ocean, enhancing the model’s ability to reproduce observed changes in ocean carbon uptake since the 1960s. Additional assimilation of observed ocean temperature and salinity anomalies further improves extra-tropical variability, although model performance degrades in the equatorial regions.

Based on these assimilated simulations, we demonstrate how a large-scale climate mode in the Pacific led to a redistribution of both natural and anthropogenic dissolved inorganic carbon in the global ocean, accompanied by a slowdown of ocean carbon sink during the 1990s (the so-called carbon-sink hiatus). Finally, we discuss the inferred decadal variability of the land carbon sink, estimated by incorporating the newly constrained ocean carbon sink into the global carbon budget.

How to cite: Sharif, J., Kwon, E.-Y., Kim, Y.-Y., Chikamoto, Y., Bethke, I., Lee, S.-S., and Lee, J.-Y.: Decadal climate modes and ocean carbon sink variability from 1960 to 2020, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17508, https://doi.org/10.5194/egusphere-egu26-17508, 2026.

Inverse modelling is employed to reconcile greenhouse gas (GHG) emission inventories, based on bottom-up methods, with the observed atmospheric GHG concentrations. The Community Inversion Framework (CIF) was created to unify inverse-model developments and simplify the generation of inversions. It makes atmospheric transport models and inversion algorithms easily interchangeable and facilitates the comparison of inversion results obtained using such diverse components.

After several years of development and the coupling of CIF with a wide range of transport models used by the inversion community, we present the first intercomparison study conducted with CIF. This exercise focuses on Europe and aims to refine CO₂ natural emissions for the year 2019, following a strict protocol. It involves five transport models (CHIMERE, ICON-ART, LMDz, STILT, and WRF-CHEM) and two inversion algorithms (variational and ensemble-based). Two additional transport models, TM5 and FLEXPART, will be incorporated in the near future.

The results show a good agreement, both across transport models, and inversion algorithms. It paves the way towards using CIF as an operational tool for intercomparison studies. It also highlights its strong potential to support the systematic derivation of GHG budgets with multiple transport models, enable a proper and easy quantification of the modelling uncertainty, and improve the robustness of emission estimates, for any relevant atmospheric species, at any scale.

How to cite: Thanwerdas, J., Berchet, A., Pison, I., Reum, F., Elias, E., Broquet, G., Chevallier, F., Thompson, R. L., Fortems-Cheiney, A., Tsuruta, A., Mengistu, A., Peylin, P., Bastrikov, V., Potier, E., Saunois, M., Martinez, A., Emmenegger, L., and Brunner, D.: The Community Inversion Framework as an operational tool for inverse modelling: towards robust, streamlined, and automatized intercomparisons of top-down estimates, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18213, https://doi.org/10.5194/egusphere-egu26-18213, 2026.

Accurately mapping the sea surface partial pressure of carbon dioxide (pCO₂) remains a major constraint for quantifying global air-sea CO₂ fluxes. New autonomous platforms, including biogeochemical(BGC)-Argo floats, now provide unprecedented temporal coverage across the global ocean, enabling the derivation of pCO₂ from measured parameters such as oxygen and pH. However, recent studies have highlighted biases in these parameters, raising questions about their impact on derived parameters and flux estimates. Float oxygen offsets and carbonate system thermodynamics are among the reasons behind float derived pCO₂ biases. By correcting the sources of bias in pCO₂, we aim to improve global air-sea CO₂ fluxes and provide guidance for refining observational strategies to constrain the ocean carbon sink. We also examine how sensor characterization of uncertainties and recalibration in BGC-Argo data propagate through pCO₂ derivation and ultimately affect regional and global CO₂ flux quantification.

How to cite: Bajon, R., Bushinsky, S., Guo, H., Landschützer, P., Olivelli, A., Burt, D., Rödenbeck, C., and Johnson, K.: Global air-sea CO2 flux estimates leveraging both ship and corrected BGC Argo observations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18294, https://doi.org/10.5194/egusphere-egu26-18294, 2026.

Mitigating global climate change requires massive greenhouse gas emission reductions and carbon removal efforts. Although terrestrial ecosystems store large amounts of carbon, land-use change has substantially diminished these stocks in many regions. However, a consistent, high-resolution approach to quantify the differences between actual and potential carbon stocks in vegetation and soils – the terrestrial carbon deficit – remains elusive, limiting the evaluation of global climate models. In particular the high spatial heterogeneity of vegetation and soil organic carbon stocks at the ecosystem level introduces major uncertainty into common methods for estimating land-use change carbon fluxes, propagating uncertainties into national, regional and global carbon budgets.

Here, we generate spatially explicit maps of vegetation and soil carbon stocks for ten ecosystem types by combining a machine-learning algorithm with semi-empirical observations and simulations of global dynamic vegetation models (DGVMs). Our results show that commonly used default carbon values substantially underestimate the heterogeneity of carbon within ecosystems. By integrating our spatially explicit carbon data into the bookkeeping of land-use emissions model BLUE – one of the models underlying the net land-use change flux estimates of the annual Global Carbon Budget of the Global Carbon Project –, we find that global estimates of the net land-use change flux for 1960–2023 are 3–14% lower than estimates relying on default values from the literature. The estimates further reveal in several regions pronounced differences of more than 20%, highlighting the value of spatially explicit carbon data for accurate national and sub-national net land-use change flux assessments. Improving this accuracy reduces the uncertainty in net land-use change flux estimates and in land-based carbon mitigation potential calculations, which both are fundamental for informing political decision-making to achieve carbon neutrality and global climate targets.

Across ecosystems, we quantify the terrestrial carbon deficit to be 344 (251–393) PgC, equivalent to a 24% depletion, predominantly driven by pasture expansion (30%), cropland expansion (24%), and forest management (23%). We reveal that dynamic global vegetation models (DGVMs) underestimate the terrestrial carbon deficit by 37% on average (range: 2%–58%), highlighting critical limitations. Our findings support assessments of anthropogenic impacts on ecosystems and help constrain global climate models to better evaluate nature-based solutions and climate mitigation policies.

How to cite: Ganzenmüller, R., Obermeier, W. A., Bultan, S., Spawn-Lee, S. A., Zabel, F., and Pongratz, J.: High-resolution estimates of vegetation and soil carbon densities for regional and global carbon budgets, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18522, https://doi.org/10.5194/egusphere-egu26-18522, 2026.

Atmospheric inversions are used by the global greenhouse gas (GHG) monitoring community for the estimation of GHG emission budgets both at global and regional scales. The Community Inversion Framework (CIF) brings novel inversion capabilities for emission monitoring, especially based on satellite data. The system is designed to enable easily deployable inversions using a large variety of inputs, with one of the key aspects of interest being the smooth integration of satellite data (from existing platforms such as S5P TROPOMI, or new ones as GOSAT-GW and S5) and their comparison to transport model simulations. To cover the needs of the inversion community, CIF is compatible with multiple inversion algorithms (variational and ensemble-based) and chemistry and transport models. These integrated features in a single system facilitate inter-comparison analyses and transparent and reliable policy-relevant reporting, consistent with WMO-promoted guidelines for inversion use in the UNFCCC context. 

In the present study, we showcase a satellite-based inversion system over tropical regions using the CIF-CHIMERE inversion setup. Domains of interest include Africa, India and Southeast Asia, and South America, which contribute approximately 14%, 23%, and 16%, respectively, to the total annual CH₄ emissions worldwide, according to the Global Methane Budget (Saunois et al., 2025). Thus, our system covers more than 50% of methane emissions worldwide. Still, CH₄ emission estimates over these regions remain largely uncertain due to the scarcity of observational data, as well as the complexity and diversity of emission processes. We use satellite CH₄ total column mixing ratios observation from TROPOMI that provides extensive spatial coverage over the Tropics to better constrain emissions in these regions. 

Inversion results are highly dependent on transport patterns, observational coverage, uncertainties, and reliable prior information. In this study, we assess the system capabilities in monitoring fluxes using a low-cost Monte-Carlo approach. We highlight potential and remaining gaps for future systematic application for emission monitoring.

How to cite: Elias, E., Sicsik-Paré, A., Kamoun, I., Saunois, M., Martinez, A., Pison, I., Broquet, G., Fortems-Cheiney, A., Potier, É., and Berchet, A.: Satellite-based CH4 emission monitoring based on the Community Inversion Framework (CIF): application to the Tropics, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19053, https://doi.org/10.5194/egusphere-egu26-19053, 2026.

Peatlands are among the most carbon‑rich terrestrial ecosystems and play a key role in the global carbon cycle. However, managed peatlands for agriculture and silviculture emits significant carbon. Southeast Asia hosts approximately one third of tropical peatlands with around half of it are managed for agriculture and silviculture to support economic and population growth.

Substantial uncertainties remain in existing estimates with a large range. Partially, such uncertainties can be attributed to both limited field measurements from major land uses and also lack of direct measurements of carbon loss when using short‑term chamber and subsidence approaches. Despite strong interests from scientific community and policy makers, current Intergovernmental Panel on Climate Change (IPCC) Tier 1 emission factors (EFs) for tropical peatlands are derived from short‑term chamber and subsidence measurements, which may not fully capture total ecosystem carbon dynamics and introduce potential uncertainty into emission estimates.

Using continuous 30-minutes eddy covariance measurements, we quantified comprehensive greenhouse gas (GHG) balance of an Acacia crassicarpa plantation on tropical peatland in Sumatra, Indonesia. Net ecosystem carbon dioxide (CO₂), methane (CH₄), and soil nitrous oxide (N₂O) exchange to estimate the GHG exchange.

Considering carbon export from harvested wood over a complete plantation rotation as emissions, the Acacia plantation exhibited net CO₂ emissions of 30.0 ± 4.6 tCO₂-eq ha⁻¹ yr⁻¹, approximately 50% lower than IPCC Tier 1 EFs. Emissions were also ~20% lower than degraded peatlands in the same landscape, and the partial use of harvested biomass for bioenergy potentially further reduces the plantation’s overall climate impact.

These findings indicate that current emission factors by IPCC may not fully represent GHG dynamics in existing Acacia plantations on tropical peatlands. Incorporating ecosystem-scale observations and full plantation rotation assessment into Tier 3 EFs estimation improved the accuracy in GHG emissions from managed tropical peatland ecosystems.

How to cite: Susanto, A. P., Deshmukh, C. S., Nardi, N., Nurholis, N., Kurnianto, S., Gunawan, S., Ramadhanti, S., Kusumawardhani, S. D., Samosir, A. G. A., Wenadi, R., Desai, A. R., Page, S. E., Cobb, A. R., Hirano, T., Guérin, F., Serça, D., Agus, F., Sabiham, S., and Evans, C.: Ecosystem-Scale Carbon Balance to Improve the Emission Factors for Acacia Plantations on Tropical Peatlands , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19061, https://doi.org/10.5194/egusphere-egu26-19061, 2026.

We have estimated that for Quebec, a province of eastern Canada, an ambitious climate change mitigation portfolio of actions mobilizing the forest lands of the province and the wood processing industries could generate annual greenhouse gas reductions varying from 0.5 to 6.7 Mt CO₂ eq/year by 2030. Implementing these actions requires detailed knowledge of the territory and dynamics of forest ecosystems and the links between forests and societal needs for materials and energy. In this context, our simulation results suggest partial-cut harvesting, when used as an alternative to clear-cut harvesting in the boreal forests of Quebec, can be a promising way of supplying high-quality wood products to markets and maintaining carbon stocks in ecosystems, although field data do not always support this promising view about partial cut. Conversely, afforestation measures such as tree planting on abandoned agricultural lands do not appear to provide benefits in the context of Quebec. Most of these lands supported forest ecosystems before their clearing for agriculture, and field data suggest that they can revert relatively quickly to natural succession leading to a forest cover and sequestering large quantities of carbon without the need for artificial plantation. Moreover, the change in surface albedo and associated radiative forcing incurred by the establishment of a coniferous plantation on a previously non-forested land can be substantial due to the high latitude and long snow-covered winter season of Quebec; the deciduous-dominated natural succession can lower this effect. Nevertheless, our research demonstrates that improving the management of the end-of-life of wood products by preventing their landfilling (which is still very common in Quebec) through increased wood cascading use or increasing the recovery and use of landfill methane would yield significantly higher climate benefits than any forest management action.

How to cite: Thiffault, É.: Forestry and climate change mitigation in Quebec (Canada), EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19933, https://doi.org/10.5194/egusphere-egu26-19933, 2026.

Observing atmospheric CO₂ concentrations is akin to taking the pulse of the global carbon cycle. Long-term observations at sampling stations in the Northern Hemisphere reveal a pronounced seasonal cycle, reflecting the annual course of terrestrial photosynthetic carbon uptake and respiratory release. This cycle has changed over the last decades: The amplitude has increased due to increased respiration during winter and greater carbon uptake during the growing season. At the same time, the phase defined as the timing of the zero-downward crossing of the seasonal cycle has shifted to earlier in the season. However, the drivers of the increase in amplitude, and particularly of the phase shift, are still uncertain.

Here, we analyse this phase shift and its drivers over the last six decades using observational data, process-based models and statistical learning. Our analysis reveals a statistically significant phase shift towards earlier dates of 1.5 – 2.0 days per decade at multiple stations in the Northern Hemisphere and even at the South Pole (2 ± 1 days per decade). In contrast to the increase in amplitude and phenological changes, the phase shift does not increase with latitude and is rather consistent across the latitudinal gradient.

To understand what is behind the observed phase changes, we next analyse simulations from different experiments using Earth system models and land surface model outputs from the TRENDY protocol. The carbon fluxes from the TRENDY models are transported using an atmospheric transport model. Additionally, we train statistical learning models to predict phase changes based on various potential drivers, such as observed temperature and pressure fields and evaluate their performance and feature importance.

By combining long-term atmospheric CO₂ observations, process-based model simulations and statistical learning, this study will shed light on the driving forces of seasonal CO₂ phase shifts and provide key insights into the changing land carbon dynamics.

How to cite: Hafezi Rachti, D., Reimers, C., Sippel, S., and Winkler, A. J.: Widespread Shift in the Seasonal Phase of Long-Term and Multi-Site Atmospheric CO2 Observations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19942, https://doi.org/10.5194/egusphere-egu26-19942, 2026.

In boreal and subarctic regions, dwarf shrubs may dominate the ground cover in forests as well as open habitats. Therefore, their contribution to the carbon capture in these areas is important to quantify. The length of the growing season impacts greatly on the carbon capture and is also very variable depending on duration of the snow cover as well as daylenghts and temperatures. In a project studying many ecological aspects of dwarf shrubs in four sites in Norway, we compare a coastal and an inland site in the south and the north of the country. The coastal sites typically have less snow than the inland sites, whereas the southern sites have higher mean air temperatures than the northern sites. The extremes of these four sites are then the southern coastal site where the snowless season with favourable temperatures can come in April, versus the northern continental site where snowmelt and favourable temperatures may come in June when there is midnight sun. If the plants from varying locations are differently adapted to start photosynthesising and producing new leaves, it will impact on the seasonal carbon capture. To compare these abilities between sites, we collected plants from each site and grew them in controlled conditions giving them the same winter and spring startup conditions. The dwarf shrubs Calluna vulgaris and Empetrum nigrum are among the species we studied. Repeated measurements of photosynthesis rate, respiration rate and branch lengths were done to investigate the phenology. This presentation will show how the species differed between sites of origin and the results will be discussed with respect to the normal climate at each site.

How to cite: Vollsnes, A., Geange, S. R., and Vandvik, V.: Boreal and subarctic dwarf shrub contribution to carbon capture early in the growing season , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20380, https://doi.org/10.5194/egusphere-egu26-20380, 2026.

Process-based models are widely used to estimate forest carbon exchange, however, their outcomes depend strongly, among other factors, on the choice of climate forcing data. This study assesses the sensitivity of modeled carbon exchange in German forests to differences between the E-OBS and ERA5-Land climate datasets using the ecosystem LandscapeDNDC model for the period 2011–2023. Simulations were conducted on a spatially explicit 10 × 10 km grid across Germany for the four dominant tree species groups (beech, oak, spruce, and pine). Within each grid cell, 15 representative sampling points per species were selected and used to extract the vegetation and soil properties. Forest structure was initialized using biomass and canopy height derived from Planet products, soil properties from SoilGrids, and climate forcing was provided alternatively by E-OBS and ERA5-Land. Preliminary results indicate that on average, ERA5-driven simulations produce higher gross primary production (GPP) due to higher precipitation amounts, but also higher total ecosystem respiration (TER) associated mainly with increased minimum temperatures, reflecting warmer nighttime conditions and enhanced ecosystem respiration. As the relative increase in TER exceeds that of GPP, net ecosystem exchange (NEE) is reduced under ERA5-Land forcing compared to E-OBS. Despite this general reduction, NEE exhibits considerable spatial variability across Germany, including both positive and negative deviations. Overall, both climate datasets reproduce the large-scale spatial patterns of GPP, TER, NEE, with consistent regional gradients across Germany. These findings demonstrate that climate forcing choice can significantly influence modeled forest carbon balances at national scale, with important implications for greenhouse gas inventories and forest carbon accounting.

How to cite: Moutahir, H., Grote, R., Kraus, D., Haas, E., and Kiese, R.: Sensitivity of modeled forest carbon exchange in Germany to climate forcing differences between E-OBS and ERA5-Land, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21963, https://doi.org/10.5194/egusphere-egu26-21963, 2026.

Approximately 54% of woodlands in the UK are undermanaged meaning they have not had a Woodland Management Plan, grant or felling licence in the last 15 years. There is policy interest in restoring management to these woodlands to enhance biodiversity, ecosystem function and ecosystem resilience, however it is well known that management can influence forest carbon stocks by both removing carbon in harvested material and by shifting carbon into the deadwood pool where it decomposes. Therefore, there are expected to be trade-offs between managing forests for biodiversity and carbon objectives.

This paper outlines research showing that the carbon losses from woodland restoration could be long lasting on both a regional and national scale when applied to the GHG inventory.

We examined this from a top-down and bottom-up approach. The top-down approach applies a restoration target to the UK National Greenhouse Gas inventory by transitioning areas reported as unmanaged areas to low intensity silvicultural management. The transition takes place over a 10-year period to either achieve a target of 65% or 75% of total UK woodland into active management. The GHG Inventory and inventory projections applied the CARBINE-R forest sector carbon accounting model to model carbon sequestration in trees, transfers to and between deadwood, litter, soil, and the atmosphere due to turnover, mortality, harvesting, and decay, and allocation of harvested timber to the raw wood products of bark, roundwood, and sawlogs. This was used to project the change in national carbon stocks over the next 100 years, which showed a modest decline that increased with the area of forest restored.

The GHG Inventory assumes growth without disturbance in the baseline, and the restoration is applied agnostically to all unmanaged woodland types, therefore a bottom-up method stand-level assessment was performed for a number of unmanaged woodland case studies that ranged in species composition, management history, and targeted management interventions for either biodiversity or commercial objectives. This approach allowed us to consider the impact of different stocking levels, species mixes, as well as comparing the impacts of different levels of management. Also, a business-as-usual scenario was developed that considered disturbance from common tree diseases (ash dieback, acute oak decline, Dothistroma needle blight), that could affect the baseline.

The results show that in most of the unmanaged woodland types modelled, introducing management leads to large carbon stock losses which do not recover by 2150, except areas of woodland that are young and have failed to establish, resulting in understocked or overly browsed woodland. These consistently gained land carbon due to introducing management. For other woodland types, the carbon losses can be reduced if there is considerable mortality due to natural disturbance in the baseline, suggesting that targeting restoration to areas at high risk of disturbance would mitigate the carbon losses. We can use these results to refine the GHG inventory projections by focusing on suitable tree species mixes and ages of stands and to identify the potential impact of a more targeted management restoration policy.

How to cite: Whittaker, C., Hubbert, E., Henshall, P., Hogan, G., Clark, C., and Matthews, R.: The impact of restoring management to undermanaged forests in the UK: Comparing stand level assessments to the impact at a National Greenhouse gas inventory scale. , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22007, https://doi.org/10.5194/egusphere-egu26-22007, 2026.

The mixing ratio of nitrous oxide (N₂O), an important greenhouse gas and ozone-depleting substance, in the troposphere has increased by 25% (~336 ppb) since the preindustrial period, with increased emissions in the last few years showing that effective mitigation policies are urgently required.  N₂O is emitted from a range of anthropogenic sources, particularly fertilised agricultural soils. N₂O sources and sinks can be constrained using measurements of four isotopocules: ¹⁴N¹⁵N¹⁶O (α), ¹⁵N¹⁴N¹⁶O (β), ¹⁴N¹⁴N¹⁶O, and ¹⁴N¹⁴N¹⁸O, and the site-specific relative isotope ratio differences (δ¹⁵N^α and δ¹⁵N^β); however, N₂O’s long tropospheric lifetime requires high precision (<0.1 ‰) to distinguish source signals from background variability. Existing preconcentration-laser spectrometry (TREX-QCLAS) systems lack the sufficient precision required for detailed tropospheric N₂O budget studies, for example, resolving trends in site preference or the interhemispheric gradient in isotopic composition. In this project, we build upon preconcentration system development with key innovations: (1) a simplified single 6-port VICI valve design; (2) a system-wide reduction of dead volumes to minimise memory effects; (3) a smaller trap enabling faster heating/cooling without linear actuators; and (4) integration with MIRO Analytical's first commercial N₂O isotope spectrometer featuring a temperature/pressure-controlled measurement cell. This system will measure N₂O isotopic composition in flask samples from Jungfraujoch High-Altitude Research Station and other background sites, establishing global isotope scale compatibility through multi-site measurements and inter-laboratory comparisons. These advances will improve constraints on regional and temporal variability in the global N₂O budget to support effective mitigation strategies.

How to cite: Agredazywczuk, P., Meier, R., Hlubucek, J., Bruckuisen, J., Espic, C., Wolf, B., Mohn, J., Aseev, O., and Harris, E.: Developing an enhanced preconcentration system (RAPTOR) for high-precision tropospheric nitrous oxide isotope measurements by laser spectroscopy , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-523, https://doi.org/10.5194/egusphere-egu26-523, 2026.

Maize and wheat are two major staple foods that collectively contribute two-thirds of the world’s grain supply. The extensive use of nitrogen (N) fertilizers during the cultivation of both crops leads to significant losses of reactive nitrogen (Nr) into the environment. Here, using machine learning algorithms, we generate high-resolution maps of crop-specific soil Nr losses based on global field measurements. We estimate that global annual soil Nr losses from the use of synthetic N fertilizer in 2020, including direct emissions of nitrous oxide (N2O), nitric oxide (NO), ammonia (NH3), N leaching and run-off, amount to 0.18, 1.62, 0.09, 1.47 and 1.10 million tonnes N for maize, and 0.12, 1.33, 0.07, 1.21 and 0.95 million tonnes N for wheat, respectively. The annual indirect N2O emissions induced by synthetic N fertilizer use from these soil Nr losses are estimated to be 45,000 and 37,000 tonnes for maize and wheat, respectively, with hydrologic pathways playing a predominant role. Enhancing N use efficiency up to 60% for regions below this value can achieve a total soil Nr loss mitigation potential of 4.00 million tonnes per year for the two crops, thereby reducing indirect N2O emissions by 49%. Our results contribute to constrain global N budgets from the use of fertilizer in agriculture, which then can help to improve projections of nitrogen cycle–climate feedbacks using modelling approaches.

How to cite: Liu, S.: Reducing soil nitrogen losses from fertilizeruse in global maize and wheat production, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1654, https://doi.org/10.5194/egusphere-egu26-1654, 2026.

Peatlands cover a small portion of the Earth's land area, but their impact on the carbon (C) and nitrogen (N) cycles at both regional and global scales is significant. The water regime of peatlands (as an indicator of oxygen content) and temperature are the main factors in peatland greenhouse gas (GHG) fluxes. Under high water tables, as well as very dry conditions, emissions of both carbon dioxide (CO₂) and nitrous oxide (N₂O) are low, but excess moisture and anoxic conditions increase methane (CH₄) emissions. At moderate soil moisture and fluctuating water table, CO₂ and N₂O emissions are high. Peatland N₂O emissions also depend significantly on availability of total mineral nitrogen (TIN). Permanently wet (i.e., natural) peatlands act as CO₂ sinks, accumulating organic C in the soil. In drained peatlands, both gaseous and dissolved C losses are high. Artificial drainage and climatic drying induce approximately 70% of all N₂O emissions from organic soils.

Tropical regions are some of the most important terrestrial sources of N₂O. In drained tropical peatlands, N₂O emissions are the second most important contributor to the GHG budget after CO₂. Forests dominate tropical peatlands. These are more complex ecosystems than open peatlands, as the canopy (phyllosphere) may significantly influence GHG fluxes, especially during wet periods. Our studies show that large N₂O fluxes from the soil can be absorbed by the canopy, although the underlying mechanisms remain unclear.

In our empirical process-based PeatN2O model, which simulates monthly N₂O fluxes in peatlands, we integrate the following parameters: peat ammonium (NH₄⁺) and nitrate (NO₃^–) content, C/N ratio, soil moisture level, rate of change in soil moisture, N and C cycle microbiome ratios, source (NH₄⁺ and/or NO₃^–) partitioning based on N₂O isotopologue signatures, a plant traits factor, and a canopy factor. The results of this model can be used to refine the global N₂O estimates based on a combination of N₂O emission estimates from the Global Peatlands Initiative map (2022) and the Major Land Cover Units map (MODIS, 2022). The sources are from our working group's global studies, IPCC emission factors, and other published studies. The main challenge in scaling future GHG fluxes to global change scenarios is predicting the spatial and temporal variability in environmental conditions that create hot spots and hot moments of fluxes.

How to cite: Mander, Ü., Pärn, J., Espenberg, M., Thayamkottu, S., Masta, M., Kazmi, F. A., Sagris, V., and Soosaar, K.: Modelling N2O Fluxes in Peatlands: From Process to Global Mapping, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-2377, https://doi.org/10.5194/egusphere-egu26-2377, 2026.

Terrestrial nitrogen cycling plays a vital role in the Earth system, influencing climate change and a myriad of dimensions of human well-being, yet remains poorly constrained in Earth system models (ESMs). In particular, terrestrial biological nitrogen fixation (BNF) is the dominant natural nitrogen source to the terrestrial biosphere and can alleviate nitrogen limitation of CO₂ fertilization but is a key source of uncertainty in ESMs. When comparing terrestrial BNF from a CMIP6 ensemble of ESMs to a new global synthesis of observations across natural and agricultural biomes, ESMs are found to underestimate agricultural BNF but overestimate natural BNF by over 50% in the present day. Natural BNF is overestimated in the most productive ecosystems that contribute most to the terrestrial carbon sink (forests and grasslands). There is a positive correlation between modeled present-day natural BNF and the CO₂ fertilization effect across ESMs, suggesting that overestimated natural BNF translates to an exaggerated CO₂ fertilization effect of approximately 11%. Additionally, while the focus of terrestrial nitrogen cycling in ESMs has primarily been nitrogen limitation of CO₂ fertilization, nitrogen losses from the terrestrial biosphere to the atmosphere and hydrosphere has been neglected. These include key flows of nitrogen, such as reactive nitrogen gas emissions from soils and wildfires as well as its transport along the land to ocean aquatic continuum, that are strongly influenced by human activities. ESMs with fully interactive nitrogen cycling could both improve climate change projections and be used to project nitrogen pollution and its impacts to inform planetary stewardship over the 21st century.

How to cite: Kou-Giesbrecht, S., Reis Ely, C., Perakis, S., Cleveland, C., Menge, D., and Reed, S. and the Terrestrial Biological Nitrogen Fixation USGS John Wesley Powell Center for Analysis and Synthesis Group: Terrestrial nitrogen cycling in Earth System Models: from biological nitrogen fixation to projecting pollution for planetary stewardship, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3617, https://doi.org/10.5194/egusphere-egu26-3617, 2026.

Human activities have profoundly altered the global nitrogen (N) cycle, with far-reaching consequences for the environment and human well-being. By integrating data from multiple sources and employing advanced modeling techniques, here we present an up-to-date comprehensive assessment of the global nitrogen budget from 1980 to 2022, quantifying the major flows and redistributions of reactive nitrogen (N_r) among the atmosphere, terrestrial ecosystems, and aquatic systems. Our analysis reveals a 49% increase in anthropogenic Nr release over the past four decades, largely driven by agricultural intensification and industrial expansion. Emissions to the atmosphere (NH₃, NOₓ, N₂O) rose by 37%, while nitrogen losses to water bodies surged by 72%, intensifying air pollution, eutrophication and climate change. Regarding the terrestrial fate of Nr, we estimate that terrestrial ecosystems eliminate approximately 100 Tg N yr⁻¹ via denitrification to N₂, while net accumulation in soils, biomass and industrial products accounts for 130-150 Tg N yr⁻¹. Hotspots of nitrogen accumulation and deficiency emerging in different regions, exacerbating regional and global inequalities. These findings underscore the urgency of coordinated global policies and region-specific strategies to mitigate nitrogen pollution and advance sustainable nitrogen management.

How to cite: Zhang, X., Xu, X., Winiwarter, W., and Gu, B.: Global Nitrogen budget 1980-2022, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-3763, https://doi.org/10.5194/egusphere-egu26-3763, 2026.

Imbalanced synthetic nitrogen fertilizer use remains a critical obstacle to global sustainable development. Excessive nitrogen application leads to environmental pollution in many world regions, whereas insufficient nitrogen input elsewhere constrains yields and exacerbates food insecurity. Resolving this spatial imbalance requires a comprehensive understanding of how nitrogen use can be more effectively redistributed, together with the associated economic costs and societal benefits to the achievement of Sustainable Development Goals (SDGs). We present a global analysis of synthetic nitrogen fertilizer redistribution among countries and its potential to contribute to multiple SDGs, particularly enhancing food security while mitigating nitrogen emissions to air and aquatic systems. The redistribution based on optimal regional nitrogen use efficiencies could increase global crop production by 14% while reducing global nitrogen fertilizer use by 11 million tonnes. This reduction would lower reactive nitrogen losses, decreasing emissions to the atmosphere and aquatic systems by 22% and 21%, respectively. The estimated implementation cost is US$21 billion, far below the projected social benefit of US$535 billion. Redistribution would improve 1-16% of multiple SDG performance, especially the SDG 2 (Zero Hunger). These findings offer a practical and cost-effective pathway to reconcile crop production with environmental sustainability, providing an evidence base for more equitable and efficient global nitrogen management.

How to cite: Qiu, Z. and Gu, B.: Redistributing 14% of global nitrogen fertilizer use advances multiple Sustainable Development Goals, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-4749, https://doi.org/10.5194/egusphere-egu26-4749, 2026.

Nitrogen (N) addition from anthropogenic atmospheric deposition and fertilizer application is widely recognized to enhance terrestrial carbon (C) storage by alleviating ecosystem nutrient limitation. However, long-term N addition can also acidify soils and impair ecosystem functioning, an effect that is often overlooked in global assessments of terrestrial C cycling. Here, we performed a global meta-analysis to systematically quantify both the impacts of long-term N addition on soil pH and the responses of vegetation root growth and soil microbial respiration to soil pH changes. This data-driven understanding was then used to develop a parameterization for soil acidification and its impacts on vegetation and soil microbe within the C-N-coupled terrestrial biosphere model QUINCY. Model simulations show that present-day global N fertilization effects on terrestrial net ecosystem productivity (NEP) are around 240 Tg C yr^-1, which are approximately 20% lower than the estimate when neglecting the long-term N-induced soil acidification. In the meanwhile, inclusion of soil pH effects increases the simulated soil carbon storage, consistent with patterns emerging from the meta-analysis. By explicitly incorporating soil acidification into terrestrial C–N interactions, our results reveal critical gaps in current representations of long-term ecosystem responses to N enrichment, with important implications for future sustainable N management and climate change mitigation.

How to cite: Gong, C. and Zaehle, S.: Overestimated nitrogen fertilization effects on global terrestrial carbon sinks due to neglect of long-term soil acidification, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5298, https://doi.org/10.5194/egusphere-egu26-5298, 2026.

Nitrous oxide (N₂O) production in the biosphere is traditionally attributed to microbial nitrification and denitrification. Recent studies suggest that N₂O can be produced via chemodenitrification, i.e., the reduction of nitrite to N₂O, which remains a major uncertainty in global N₂O budget. By conducting ¹⁵N-tracer incubations, samples from a land–ocean continuum demonstrated that the significance of N₂O production via chemodenitrification may be overlooked, particularly at metal-rich, acidic and anoxic conditions. Transition metals beyond iron, specifically manganese and zinc, drive abiotic N₂O formation in both oxic and anoxic environments. And the rates are significantly enhanced under lower oxygen concentration. In natural estuarine waters, abiotic N₂O production is modest but consistent (0.0001–0.0013 nmol N L^-1 d^-1). In contrast, acidic metal-rich mine wastewater stimulated abiotic N₂O production up to 138 nmol N L^-1 d^-1. Furthermore, at the interface where mine drainage contaminating soils, N₂O efflux reached 446 μmol N m^-2 d^-1, rivaling or exceeding emissions from many intensively managed croplands. In these hotspots, abiotic and biotic processes act in concert to sustain elevated N₂O production, with microbial activity potentially modulating substrate availability for abiotic production. These findings highlight the necessity to integrate chemodenitrification into regional and global nitrogen assessments to improve the accuracy of N₂O budget.

How to cite: Zheng, X. and Ji, Q.: Abiotic N2O Formation Across the Land–Ocean Continuum: An Overlooked Source of Nitrous Oxide via Abiotic Formation Across the Land–Ocean Continuum, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6235, https://doi.org/10.5194/egusphere-egu26-6235, 2026.

Sustainable intensification of rice systems requires strategies that synergize productivity, environmental, and economic goals. This study presents a comprehensive, multi-dimensional evaluation of eight rice-based cropping systems (including straw-return and diversified green manure rotations) in the Yangtze River region, China. We uniquely integrated field measurements of greenhouse gases and reactive nitrogen (N_r) species (CH₄, N₂O, NH₃, HONO) with agronomic and soil health indicators. The climate impacts were assessed using multi-temporal metrics (GTP₂₀, GTP₁₀₀). A Comprehensive Evaluation Index (CEI) quantified system-level synergies and trade-offs. The medium rate straw-return system (NPKS2) achieved the highest CEI score (0.63), representing the optimal balance among evaluated systems. A fundamental trade-off was identified: economic benefits and crop yield showed strong positive correlations with net GHG (r = 0.6 & 0.61, P ≤ 0.001) and N_r gas emissions (r = 0.54, P ≤ 0.001and r = 0.45, P ≤ 0.05, respectively), but were negatively linked to soil organic carbon (SOC) sequestration and biodiversity. This reveals an inherent conflict between short-term productivity and environmental sustainability. Critically, by including short-lived N_r species, our assessment shows that the climate impact is highly time-dependent. For instance, NH₃-induced aerosol cooling offset 8–70% of N₂O -induced warming over 20 years, but less than 0.1% over a century. We conclude that moving beyond single-gas or single-timescale assessments is essential to reveal the true costs and benefits of management practices, thereby informing strategies that are genuinely climate-smart and sustainable.

How to cite: Huang, J., Yue, L., Ding, Y., Wu, D., and Sha, Z.: Using half-straw return to tackle trade-offs among Grain Yield, Multiple Soil Gas Emissions, and Soil Health in Rice-Based Rotations, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6898, https://doi.org/10.5194/egusphere-egu26-6898, 2026.

To estimate N₂O fluxes from groundwater due to N leaching from agricultural soils, an empirical parameter had been determined from the ratio of dissolved N₂O-N to NO₃^--N (EF5(1), leading to a first estimate of IPCC-EF5g of 0.015 in 1998. While the data-set of dissolved N₂O was steadily growing, the IPCC-EF5g was first lowered to 0.0025 in the 2006 guidelines, but raised back to 0.006 in the IPCC2019 guidelines based on a more recent review (Tian et al 2019). But it had previously been shown that the concept of EF5(1) must overestimate indirect N₂O fluxes because it related N₂O measured at a certain sampling point in groundwater to the NO₃^- concentration at that point (Well and Weymann, 2005). This neglects the fact that some of the NO₃^- leached to the groundwater surface is typically consumed by denitrification. Studies measuring N₂O together with excess-N₂ from denitrification and residual NO₃^- have shown that this overestimation can be highly relevant (Weymann et al., 2008). An alternative emission factor EF5(2) was thus proposed as the ratio between dissolved N₂O-N and initial NO₃^--N, where the latter was calculated from the sum of excess N₂ and residual NO₃^--N. Neglecting NO₃^- reduction in the EF5g concept had been justified by the wide lack of excess-N₂ data in groundwater (Tian et al, 2019). But NO₃^- consumption in groundwater can also be estimated from the difference between NO₃^--N in leachate calculated from N budgets and the residual NO₃^--N in groundwater monitoring wells. For Germany, these data are widely available and could be used to correct current estimates of indirect N₂O fluxes.

Here we present recalculations of indirect N₂O fluxes using the EF5(2) concept. For the dataset of Tian 2019, we select data from regions where we can assume typical ranges of N fertilization together with the default IPCC factor for N leaching and typical ranges of seepage rates to estimate initial NO₃^--N at the groundwater surface. For Germany, we use respective data from inventories and spatial models. For both cases, indirect N₂O fluxes based on EF5(1) and EF5(2) are compared. For Germany, we also estimate the lowering of currently reported indirect N₂O fluxes with those based on EF5(2). We conclude that there is need for new research on indirect N₂O fluxes from groundwater globally to avoid overestimation of this source.

References:

IPCC, 2019: 2019 Refinement to the 2006 IPCC Guidelines for National Greenhouse Gas Inventories, edited by E. Calvo Buendia, K. Tanabe, A. Kranjc, J. Baasansuren, M. Fukuda, S. Ngarize, A. Osako, Y. Pyrozhenko, P. Shermanau, and S. Federici, IPCC, Switzerland. 

Tian, L., Y. Cai and H. Akiyama (2019), Environmental Pollution 245: 300-306.

Well, R. and D. Weymann (2005), 4th International Symposium on non-CO2/ greenhouse gases (NCGG-4), science, control, policy and implementation, Utrecht, Netherlands, 4-6 July 2005: 129-136.

Weymann, D., R. Well, H. Flessa, C. von der Heide, M. Deurer, K. Meyer, C. Konrad and W. Walther (2008). Biogeosciences 5(5): 1215-1226.

How to cite: Well, R., Fuß, R., Wolters, T., and Zinnbauer, M.: Overestimation of indirect agricultural N2O fluxes from the groundwater due to neglect of nitrate attenuation , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7363, https://doi.org/10.5194/egusphere-egu26-7363, 2026.

Nitrogen (N) is an essential element for life and a fundamental regulator of terrestrial ecosystem productivity, carbon sequestration, and climate feedbacks, yet it remains one of the most weakly constrained and uncertain components of Earth system models. Despite major advances in terrestrial biosphere modeling, large discrepancies persist in how models represent nitrogen inputs, internal cycling, losses, and their coupling to the carbon and water cycles. Here we present the first comprehensive, process-resolved benchmark of the global terrestrial nitrogen cycle based on coordinated simulations from the Nitrogen Model Intercomparison Project Phase 3 (NMIP3) combined with multiple independent observational constraints.

We trace the full nitrogen cascade across land ecosystems—from natural and anthropogenic inputs (biological nitrogen fixation, atmospheric deposition, and fertilizer and manure application), through plant uptake and soil–microbial transformations, to hydrological export to inland waters and gaseous losses to the atmosphere (N₂O, NH₃, NO, and N₂). This integrated framework allows us to evaluate not only individual fluxes and pools, but also the internal consistency of regional and global nitrogen budgets and their emergent coupling with carbon cycling.

Across models, we find broad agreement in the magnitude of total nitrogen inputs and in first-order global spatial patterns. However, models diverge strongly in how nitrogen is partitioned among vegetation, soils, and loss pathways. The largest spreads occur in biological nitrogen fixation, soil nitrogen turnover, nitrate leaching, and gaseous emissions, producing substantial inconsistencies in regional budget closure and large uncertainty in carbon–nitrogen feedback strength. These discrepancies are especially pronounced in intensively managed agricultural regions and climate-sensitive ecosystems, including the tropics and high latitudes, and they propagate directly into uncertainty in the magnitude and spatial distribution of the terrestrial carbon sink.

By systematically comparing model structures and process representations, we diagnose the dominant sources of these divergences and show that a small number of key processes control most of the uncertainty. Our analysis demonstrates that improving the representation and observational constraint of biological nitrogen fixation, soil organic matter turnover, and coupled nitrification–denitrification pathways can substantially reduce uncertainties in nitrogen budgets, N₂O and NH₃ emissions, and land carbon sink estimates.

More broadly, this work establishes a community framework for nitrogen cycle benchmarking that moves the field from qualitative model intercomparison toward quantitative, process-level accountability. Our results show that coordinated benchmarking can transform nitrogen–carbon–climate projections into more robust and policy-relevant tools, with direct implications for climate mitigation, air and water quality management, and integrated carbon–nitrogen stewardship.

How to cite: Tian, H. and the NMIP3 Participants: Where Does the Nitrogen Go? Model Intercomparison and Benchmarking of the Global Terrestrial Nitrogen Cycle and Carbon–Nitrogen Interactions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7379, https://doi.org/10.5194/egusphere-egu26-7379, 2026.

Anthropogenic nitrogen (N) losses from croplands have risen alongside global food production and are a major driver of transgressed planetary boundaries. Price-based policy instruments are widely proposed to curb agricultural nitrogen pollution, yet their effectiveness and distributional consequences under market feedbacks remain insufficiently understood. Here we assess the global impacts of nitrogen pricing on cropland N losses, food security and economic outcomes. We extend the global land-use model GLOBIOM by endogenizing crop- and country-specific nitrogen balances and explicitly representing multiple N-loss pathways. Field-level mitigation technologies are incorporated, with adoption governed by marginal abatement costs, yield effects and economic affordability, allowing nitrogen taxation and subsidies to interact with production decisions, land allocation and international trade. Without additional intervention, global cropland N losses increase by 28% by 2050 relative to 2020. Nitrogen taxation reverses this trend, reducing N losses by 22% (12–29%) compared with business as usual, but at the cost of higher food insecurity. Field-level mitigation technologies provide a critical buffer, delivering additional abatement and offsetting nearly one-third of the food-security losses induced by taxation. In contrast, mitigation subsidies implemented alone yield limited net mitigation, as technology-driven reductions are partly offset by subsidy-induced cropland expansion. Combining taxation, subsidies and technologies yields the most balanced outcome, reducing global N losses by 23 Tg N by 2050 while moderating food-security impacts. Responses to nitrogen pricing vary strongly across regions. Under the combined policy scenario, South Asia, East Asia and Europe together account for about 58% of global mitigation, but through distinct pathways. Economically resilient regions mainly achieve mitigation through higher adoption of field-level technologies and declines in N-loss intensity, with mitigation shares exceeding their emission shares. Less affluent regions rely more on trade adjustments, shifting part of the mitigation burden to exporting regions through virtual N flows. These contrasts translate into marked distributional effects: technologies and subsidies offset more than half of taxation-induced farmer revenue losses in high-income regions, whereas buffering effects remain limited in some low-income regions, with mitigation costs increasingly borne by consumers and governments. Overall, price-based nitrogen mitigation can halt the long-term rise in global N pollution, but its effectiveness and equity critically depend on technology deployment and policy design and must be aligned with broader food-system transformations.

How to cite: Huang, W., Chang, J., Frank, S., Leclere, D., Kozicka, M., Havlík, P., and Zhou, F.: Price-based nitrogen mitigation from global croplands with uneven regional responses, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7384, https://doi.org/10.5194/egusphere-egu26-7384, 2026.

In recent years, emission factors published by the Intergovernmental Panel on Climate Change (IPCC) are widely used by national inventory compilers as a Tier 1 methodology for estimating N₂O emissions at national levels. Whilst emission factors are straightforward to implement and offer several practical advantages, conventional emission factors tend not to account for the impacts of interannual climatic variability or spatial heterogeneity.

To investigate the added value of using spatially and temporally explicit processes included in land surface models, we assess the spatial and temporal variability of N₂O emissions associated with land management and extreme weather events over Italy for the 2010-2021 period. We compare N₂O emissions and N₂O emission factors estimated from two process-based land surface models, LPJ-GUESS and ORCHIDEE, against those estimated using national inventory data and published emission factors from IPCC guidelines.

Inventory-derived emissions do not show a trend over the study period and have limited interannual variation. In contrast, both models show a positive trend in emissions over the study period with interannual variability that extends well beyond the variability suggested by the inventory. We investigate the variability in emissions simulated by both models and assess whether this is indicative of a sensitivity to climate that is largely muted in IPCC based emission factors.

Both models show higher emissions from croplands than grasslands (total and per square meter) but higher emission factors from grasslands than croplands, indicating that the addition of (organic) fertilisers to pastures is more likely to be emitted as N₂O emissions than the same fertiliser added to croplands. We discuss key structural difference in how the models treat grasslands and pastures and how these discrepancies underscore the simplifications present in land surface model representations of these systems, especially regarding grazing, harvests, and manure management.

The substantial interannual variability in emission factors produced by both models exceed those estimated by inventory estimates and indicated by IPCC emission factors. These temporal patterns highlight the potential relevance of considering climate anomalies when using emission-factor methodologies, particularly with the increasing occurrence of extreme climate events.

How to cite: Lippmann, T. J. R., Lagergren, F., Naudts, K., Jönsson, A. M., and Fiore, A.: Large differences in variability between land surface models (LPJ-GUESS and ORCHIDEE) and inventory estimates: N₂O emissions and emission factors in Italy, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8421, https://doi.org/10.5194/egusphere-egu26-8421, 2026.

The environmental problems caused by the overuse of nitrogen (N) fertilizer is well recognized. However, the complexity of the N cycle and its multiple pollution pathways have hindered the quantification of a safe operating space for N fertilizer use in China. We used a modeling approach and environmental thresholds for N deposition, N concentrations in surface water and groundwater, as well as for ammonia (NH₃) volatilization and nitrous oxide (N₂O) emissions to assess spatial patterns and quantify N use mitigation goals for different regions in China.

At the national scale, the results indicate that the safe operating space for N use can be achieved if total N deposition is reduced to 5.2 Tg N yr^-1, total loading of N to surface water and groundwater are reduced to 5.4 and 13.9 Tg N yr^-1, respectively, and total NH₃ volatilization and N₂O emissions are below 5.3 and 0.6 Tg N yr^-1, respectively. Meeting these thresholds would require reductions of approx. 22%, 44%, 11%, 48%, and 30%, respectively. In total, this amounts to a reduction of 12.5 Tg N yr^-1, or a 29% decrease from current levels of N inputs to the environment. Specifically, central China and southern China require higher emission reductions to meet the thresholds, particularly in provinces such as Henan, Shandong, and Sichuan. This study is the first to integrate multiple N indicators to determine a national reduction target for China. This approach provides a scientific basis for improving N management, mitigating its environmental impacts and identifying regional “low-hanging fruits” where targeted reductions could yield the greatest environmental benefits.

How to cite: Huang, J., Ti, C., Serra, J., Yan, X., and Butterbach-Bahl, K.: Integrated environmental thresholds for nitrogen in China, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10815, https://doi.org/10.5194/egusphere-egu26-10815, 2026.

Earth system models (ESMs) need to include nutrient limitation to predict realistic land carbon (C) uptake. In particular, Nitrogen (N) is a critical nutrient, that controls photosynthesis and decomposition processes. We have implemented an explicit N cycle in the land component of the CNRM-ESM model. Here we present an evaluation of the model using data from the Free-Air CO2 Enrichment (FACE) experiments conducted over 10 years in North America. We compare the reference version of the model without the N cycle (C) to the new version in which it is included (CN). We investigate the response of the Net Primary Prodcution (NPP) to elevated CO2 and confront our results to a multi-model analysis carried out on these two sites. Our results fall in the inter model range. We show that the CN version of the model performs better than the C version because NPP is reduced by N limitation. In the literature, diverging strategies are observed to overcome N limitation. We analyse the simulated N dynamics and show that the model reproduces well the main features but fails to represent some sites characteristics.

How to cite: Decayeux, J., Delire, C., and Decharme, B.: Evaluation of the Nitrogen Cycle in the Land Surface Model of CNRM, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-11153, https://doi.org/10.5194/egusphere-egu26-11153, 2026.

Nitrous oxide (N₂O) is a major GHG and ozone-depleting substance which is produced by microbial processes in soils, with mineral nitrogen availability, carbon availability, soil moisture, soil temperature, oxygen availability and pH being important controlling factors. Emissions of N₂O are notorious for being short-lived with the magnitude of emissions being difficult to predict due to the interplay of the aforementioned controlling factors. In Europe, the major share of anthropogenic N₂O emissions result from fertilizer application to agricultural land. National reporting typically relies on so-called Tier 1 or 2 approaches which relate activity data (N inputs) to an emission factor to estimate a national total. However, this method does not consider the full set of spatially and temporally varying controlling factors, so that the latter approaches may be biased. For this reason, reconciliation with an independent, top-down method has large potential to improve national GHG budgets and to review mitigation strategies.

Here we present results from the Horizon Europe project Process Attribution of Regional emISsions (PARIS), where we calculate bottom-up and top-down N₂O emission inventories for Germany, the UK and Switzerland at monthly time resolution for the timeframe 2018 – 2024. Bottom-up estimates are obtained using the biogeochemical model LandscapeDNDC and state-of-the-art European datasets. Top-down estimates are averaged results from three different inverse modeling systems: InTEM (UK MetOffice), RHIME (University of Bristol), ELRIS (EMPA) and two different atmospheric transport models: NAME-UM and FLEXPART-ECMWF.

We find the emission estimates from both top-down and bottom-up methods to be consistently higher than the corresponding national inventories, but bottom-up approaches are within the uncertainty of the top-down estimate. In terms of seasonality, bottom-up and top-down methods indicate a seasonal cycle, although its magnitude is country dependent. Across all countries, the discrepancy between bottom-up and top-down estimates is greatest in autumn, where LandscapeDNDC predicts an emission peak following planting of winter crops. Discrepancies regarding magnitude and seasonality of top-down and bottom-up approaches will be discussed considering controlling factors for N₂O emissions simulated using LandscapeDNDC.

How to cite: Weber, C., Wolf, B., Chojnacki, L., Scheer, C., Kiese, R., Kraus, D., Haas, E., Smerald, A., Brito Melo, D., Henne, S., Manning, A., Redington, A., Ramsden, A., Andrews, P., Lugato, E., De Longueville, H., Danjou, A., Murphy, B., and Ganesan, A.: Reconciling bottom-up and top-down N2O emission inventories for Germany, Switzerland and the UK , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-14527, https://doi.org/10.5194/egusphere-egu26-14527, 2026.

Nitrous oxide (N₂O) emissions from agricultural soils vary greatly in time and space, rendering detailed quantification challenging. Process models that have been used for that purpose are challenged by high computing resources and duration of model runs while providing modest improvement over data-driven approaches. In addition to the well-confirmed dependence on nitrogen input that also provides the basis for the IPCC emission factor to be applied to agricultural soils, multiple studies denoted a non-linear effect, such that excess fertilization provides over-proportionally high emissions. Directed towards effect-based consideration of sources and in order to better reflect mitigation measures, we have revised the N₂O emissions calculation methodology for IIASA’s GAINS model to cover such non-linearities, which requires spatially explicit accounting of inputs and emissions. In a first step, emission sources (mineral N fertilizer application and manure N application taken from GAINS) were distributed on a 5’ grid globally using harvested areas from the M3 crop map and the gridded livestock of the world dataset, both updated using annual EUROSTAT data on NUTS2 level (for Europe) and FAOSTAT data for the rest of the world. In a second step, a data-driven approach was chosen reflecting enhanced emissions based on excessive nitrogen application to calculate N₂O emissions. The spatially explicit representation of emissions allows to discern sub-regional hot spots of particularly high impact of this non-linearity such as the Indo-Gangetic plain in South Asia, Egypt’s Nile delta, the Yangtse river delta in China, with Northern France or also the Brazilian North-East tip to follow. Automatizing the calculations facilitates the development of a time series as well as the analysis of individual sources of nitrogen and different scenarios. Scenario analysis identifies the value of efficient N abating measures even before applying specific N₂O reduction technology. These improvements in depicting N₂O emissions in GAINS enhance the analysis of sub-regional emission patterns. Furthermore, they offer to cost-effectively address emission hotspots in more focused emission reduction policies and provide the foundation for fully assessing the impact of N₂O abatement policies, both retroactively and in emission projections.

How to cite: Kaltenegger, K. and Winiwarter, W.: Global analysis of N2O emissions from agricultural soil surfaces considering non-linearity effects for the GAINS model, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17628, https://doi.org/10.5194/egusphere-egu26-17628, 2026.

Atmospheric nitrogen deposition has long been recognized as an important external driver of terrestrial carbon uptake by alleviating ecosystem nitrogen limitation. However, it also enhances terrestrial nitrous oxide (N₂O) emissions, leading to a potential climate trade-off under future mitigation pathways. Despite extensive research, the relative roles of anthropogenic emissions and climate change in regulating nitrogen deposition and their impacts on the terrestrial carbon sink and N₂O emissions remain poorly constrained at the global scale. Here, we quantify the impacts of past and future nitrogen deposition pathways on terrestrial carbon cycling and N₂O emissions from 1850 to 2100 by generating historical and future nitrogen deposition scenarios with the GEOS-Chem atmospheric chemistry transport model under the SSP1-2.6 and SSP3-7.0 pathways. We use these data and climate forcing from ISIMIP to drive a global carbon-nitrogen cycle model (ICON-Land in QUINCY configuration) in a factorial design to isolate climate and emission effects, while keeping the land cover fixed at 2014 land use conditions.

We find that increasing nitrogen deposition during the historical period (1850–2014) substantially enhanced terrestrial carbon uptake – contributing approximately 0.15 Pg C yr^-1 to the global land carbon sink – but also accounted for about 0.82 Tg N yr^-1 of terrestrial N₂O emissions. In the future period (2015-2100), declining nitrogen deposition under strong mitigation (SSP1-2.6) leads to a decline of the terrestrial carbon sink and a reduction of terrestrial N₂O emissions, whereas elevated nitrogen deposition under weak mitigation (SSP3-7.0) enhances both terrestrial carbon sequestration and N₂O emissions. Climate change further modulates these responses by altering nitrogen deposition patterns, amplifying both positive and negative feedbacks. These results highlight a fundamental trade-off within the nitrogen–carbon–climate system and underscore the importance of explicitly representing nitrogen processes in earth system carbon budget assessments and mitigation strategies.

How to cite: Deng, J., Gong, C., Engel, J., Nabel, J., Slominska-Durdasiak, K., Nerobelov, G., Ninomiya, H., Zhang, L., and Zaehle, S.: Impact of Past and Future Nitrogen Deposition Pathways on the Terrestrial Carbon Sink and N2O emissions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18329, https://doi.org/10.5194/egusphere-egu26-18329, 2026.

Nitrogen oxides (NOₓ ≡ NO + NO₂) play a central role in atmospheric chemistry, with direct impacts on human health through respiratory stress and indirect effects on climate via tropospheric ozone production, methane lifetime, and secondary aerosol formation. To study the impacts of NOₓ emissions on the atmospheric chemistry and the climate, we developed a version of the LMDZORINCA Chemistry-Transport model in which soil NOₓ emissions are computed by the ORCHIDEE land surface model, in complement of anthropogenic emissions provided by inventory data.

Current estimates place global total NOx emissions at about 45–50 Tg N yr⁻¹, dominated by fossil fuel combustion. Soils are a substantial source of NOₓ, with global emissions estimated at ~10–15 Tg N yr⁻¹, of which ~3 Tg N yr⁻¹ are attributable to fertilizer and manure inputs, the remainder arising from natural processes. Due to air-quality and climate policies reducing NOₓ emissions from transport and industrial sectors, the relative importance of soil NOₓ emissions is expected to further increase in the future. Currently, most atmospheric chemistry models take into account agricultural soil NOₓ emissions, using inventory-based approaches. These inventories rely on fixed emission factors or highly simplified parameterizations to calculate NOₓ emissions from nitrogen inputs, thereby neglecting, or overly simplifying, the strong non-linear dependence of emissions on climate, soil biogeochemistry, and vegetation type. Furthermore, natural soil NOₓ emissions are often neglected or calculated using simplified parametrizations.

In this work, we use soil NOₓ emissions estimated by the ORCHIDEE terrestrial biosphere model as an input to the LMDZINCA atmospheric chemistry model. ORCHIDEE simulates the carbon-nitrogen cycle as well as soil microbial nitrification and denitrification processes, thus offering a mechanistic and ecologically grounded description of soil NOₓ emissions. We first evaluate ORCHIDEE soil NOX emissions against three different datasets : CAMS-GLOB-SOIL product, which is based on empirical parametrizations, the inventory-derived dataset for anthropogenic NOₓ emissions CEDS, and the DESCO dataset using top-down constraints from satellite-based NO2. In the current configuration of LMDZINCA, soil NOₓ emissions are based on the CEDS anthropogenic emission inventory, therefore not taking into account NOₓ emissions from natural soils. Replacing these current CEDS soil NOₓ emissions with ORCHIDEE soil NOₓ emission includes the very substantial natural soil NOₓ component which has previously not been accounted for in LMDZINCA. The resulting changes on atmospheric NO2 in recent years are then analysed and compared with satellite derived NO2 columns from OMI and TROPOMI. These differences of soil NOX emissions and resulting tropospheric NO2 changes are studied over the last two decades.

The offline implementation of ORCHIDEE soil NOₓ in LMDZINCA represents a first step toward a fully coupled nitrogen cycle within the IPSL framework, enabling future assessments of feedbacks between terrestrial and atmospheric nitrogen reservoirs.

How to cite: Hanig, N., Lathiere, J., vuichard, N., Simpson, D., Cozic, A., and Hauglustaine, D.: Improving the representation of NOx emissions from soils in the LMDZORINCA model for global chemistry and climate purposes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18454, https://doi.org/10.5194/egusphere-egu26-18454, 2026.

Anthropogenic transformations to river systems are profoundly altering basin-scale nitrogen cycling globally, leading to long-term nitrogen accumulation that poses persistent and episodic threats to downstream water quality. Net nitrogen input (NNI) is a key integrative indicator that quantifies the cumulative influence of human activities on nitrogen budgets. This study constructed a comprehensive spatiotemporal NNI dataset for the Yangtze River Basin (YRB) between 1980-2020 and systematically examined its temporal dynamics, source composition, and landscape-driven controls. Results show that basin-wide NNI in the YRB followed a distinct three-stage trajectory during 1980–2020, characterized by a rapid increase, a high-level plateau, and a subsequent partial decline. Average NNI intensity typically increased along an upstream-downstream gradient, primarily governed by intense nitrogen fertilizer use and dense population pressures. Trend analyses revealed strong spatial asynchrony in NNI evolution, whereby: the downstream basin exhibited the earliest plateauing effect (c. 1994); the midstream basin experienced the longest period of sustained accumulation (1995–2010); and the upstream basin, despite possessing the lowest average NNI overall, displayed the fastest growth rate that highlights emerging nitrogen management challenges in upstream regions. Machine learning analyses demonstrated that these trends were primarily driven by agricultural land cover, whereas urban land and water bodies also exerted strong but nonlinear controls on long-term NNI evolution. This study thus provides novel and unique insights into long-term, large-scale nitrogen fluxes operating across one of the world’s mega-basins. By characterizing anthropogenic pressures governing these trends, this research could help underpin effective nutrient management efforts in the Yangtze River Basin and beyond.

How to cite: Wen, W., White, J., Xia, B., Zhuang, Y., Shen, W., Hannah, D., and Zhang, L.: Long-term trends in Net Nitrogen Inputs across the Yangtze River Basin and large-scale management implications, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20535, https://doi.org/10.5194/egusphere-egu26-20535, 2026.

Quantifying lateral nitrogen (N) transfers and riverine N₂O emissions is essential for closing the global N budget. We present ORCHIDEE3-N_lat, which couples lateral N routing with ORCHIDEE3 to simulate NH₄⁺, NO₃^-, and DON fluxes through the land ocean aquatic continuum, from canopy to ocean. Aquatic transformations, including nitrification, denitrification and DON decomposition, occur within the routing framework, and riverine N₂O emission is estimated to using an emission-factor scheme tied to nitrification and denitrification rates. Evaluation against global observation-based datasets shows that the model reproduces the global magnitudes and broad spatial patterns of DIN and DON concentrations and fluxes, as well as N₂O emission rates across major river systems spread across the world. The model was then applied to reconstruct the historical evolution (1901–2020) of global N lateral transfers from land to rivers, and ultimately to the ocean, together with associated N₂O emissions. Globally, DIN inflow to rivers and export to oceans increased by ~245% and ~151% from 1901–1920 to 2001–2020, whereas DON increased more modestly (~38% and ~32%), implying a century-scale shift towards inorganic N cycling. Riverine N₂O emissions increased substantially, with a strong acceleration after the mid-1960s, with contemporary hotspots in intensively managed subtropical regions. Attribution analysis indicates that DIN trends were dominated by atmospheric deposition and sewage injection before the 1960s, while fertilizer inputs dominated the increase after the 1960s. The analysis also revealed that due to the fertilization effect on vegetation, increasing atmospheric CO₂ decreased the DIN exports to the global river network. In contrast, DON variability and trends were governed primarily by manure application and hydroclimate, showing weaker sensitivity to anthropogenic N inputs than for DIN. Together, these results provide a comprehensive picture of how human activities have reshaped riverine N composition, downstream N export, and the spatial distribution of N₂O emissions over the twentieth century, offering a robust baseline for global N-cycle assessments and mitigation planning.

How to cite: Ma, M., Vuichard, N., Zhang, H., Huang, T., and Regnier, P.: Anthropogenic Perturbations of Nitrogen Cycling and Budgets Across the Land–Inland Water Continuum: Insights from ORCHIDEE3_Nlat , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-22032, https://doi.org/10.5194/egusphere-egu26-22032, 2026.

Oxides of Nitrogen (NO_x) are key precursors of tropospheric ozone and particulate nitrate (NO₃^-), both of which contribute to air quality degradation and climate forcing. NO_x is oxidized to nitric acid (HNO₃), which partitions into particulate NO₃^-, an important component of PM_2.5. The formation of HNO₃ and ultimately NO₃^- occurs through multiple chemical pathways and is influenced by atmospheric chemistry as well as meteorological parameters like temperature, relative humidity, and boundary layer dynamics. India has been recognised a global hotspot for NO_x emission, owing to rapid urbanization and population growth. Major sources of NO_x include emissions from traffic, agriculture, biomass burning, and combustion. Despite being a major contributor of NO_x, large uncertainties exist in regional emission inventories due to limited observational constraints. Stable isotopic signature of particulate NO₃^- serves as an excellent tool to understand its formation pathways and sources of its precursor.  Here, we have applied a dual-isotope (δ¹⁵N and δ¹⁸O) approach to understand seasonal and diurnal variations in NO₃^- formation pathways and NO_x sources over Ahmedabad, an urban megacity in western India, during winter and summer. In winter, overall particulate NO₃^- formation was driven mainly by the OH oxidation pathway (P₁, 61.9 ± 7%) and N₂O₅ hydrolysis (P₂, 24.6 ± 6%), with smaller contributions from VOC-derived (P₃, 7.6 ± 4%) and ClNO₂ pathways (P₄, 5.9 ± 3%). However, strong diurnal contrasts were evident, with P₁ accounting for 69.4 ± 5% during the day and P₂ increasing to 32.8 ± 7% at night, reflecting enhanced photochemical activity during day and nocturnal buildup of N₂O₅ under cooler, low-light conditions at night. In summer, NO_3^- formation was dominated by the OH pathway throughout the day and night (67.5 ± 7%), with no significant diurnal variability. This seasonal shift was attributed to elevated boundary layer height and enhanced atmospheric mixing, which stabilized particulate NO₃^-, which was particularly associated with stable non-volatile cations. Source apportionment of NO_x using the Bayesian model (MixSIAR) revealed no significant diurnal differences within either season; however, a distinct seasonal pattern in NO_x sources was observed. In winter, traffic was the largest contributor (46.7 ± 19%), followed by soil emissions (24.4 ± 12%), biomass burning (18.0 ± 9%), and coal-fired power plants (10.9 ± 8%). In summer, soil-related emissions increased to 38.4 ± 12% due to temperature-enhanced microbial activity and volatilization from urban waste, livestock areas, and fertilized land, while traffic remained a dominant source (40.1 ± 17%). Biomass burning and power plant contributions remained lower but persistent across both seasons. Together, these results provided the first dual-isotope-based evidence from western India showing how meteorology and emission processes jointly influence NO₃^- formation and NOx source, thus offering critical observational insight needed to improve regional nitrogen budgets and air quality mitigation strategies.

How to cite: Shaw, C., Rastogi, N., Mandal, R., and Sanyal, P.: Sources and formation pathways of particulate nitrate over the western India: Insights through δ15N and δ18O isotopes, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-128, https://doi.org/10.5194/egusphere-egu26-128, 2026.

Excessive reactive nitrogen (Nr) is a growing challenge for sensitive terrestrial habitats like forests. Nepal is experiencing threats of nitrogen (N) pollution largely transported from the Indo-Gangetic Plain (IGP) – a global nitrogen pollution hotspot – which affects biodiversity, ecosystem functioning and human health. This urges the quantification of the impacts of those pollutants in the Himalayan region. Our analysis, based on the atmospheric chemistry transport model (European Monitoring and Evaluation Programme-Weather Research and Forecasting 2010 emission with 2018 chemistry and meteorology) with land use land cover and digital elevation model, shows that 95-99% of Nepal’s forests have already exceeded the United Nations Economic Commission for Europe (UNECE)-recommended ammonia (NH₃) critical levels and N critical loads. Overall, ammonia (NH₃) (0.54-13.13 μg m^–3) and nitrogen oxides (NO_x; 0.05-13.64 μg m^–3) concentrations are higher at low elevation forests, but a contrasting pattern of bulk N deposition (4.52-38.56 kg N ha^–1 yr^–1) is observed in forests along the elevation gradients and forest types. Wet deposition of N is exceptionally high in forested areas receiving high precipitation, but dry deposition is heterogeneously distributed over different parts of the country. The forests in the lowland Tarai and Mid-hills that are near IGP are exposed to high concentrations of NH₃ and NO_x – thus are at a higher risk of biodiversity loss. Contributing only small shares, deciduous and needleleaf forests are vulnerable to N pollution as they cover the subtropical to subalpine region of the Mid-hills and host most of the sensitive species like lichens. This demonstrates a serious concern of N pollution on biodiversity and ecosystem services in the region. The empirical testing of N impacts on Nepal’s forested ecosystems is now crucial to establish the field-based toxicity threshold of N-based pollutants for biodiversity conservation and policy negotiation.

How to cite: Pradhan, S. P., Ellis, C. J., Deshpande, A. G., Wang, Y., Vieno, M., Jones, M. R., Rai, S. K., Raut, N., Weerakoon, G., Stevenson, D. S., and Sutton, M. A.: Nitrogen air pollution concerns for Nepal’s forested ecosystems and lichen bioindicators , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-914, https://doi.org/10.5194/egusphere-egu26-914, 2026.

Sub-Saharan Africa (SSA) faces a critical dilemma: how to close yield gaps and ensure food security while minimizing agriculture's climate footprint. While nitrogen (N) fertilisation is essential for boosting crop productivity, it can also lead to increased nitrous oxide (N₂O) emissions, thereby further fueling climate change. SSA is highly vulnerable to changes in climate. Yield-scaled N₂O emissions offer a framework to evaluate agricultural climate efficiency, but regional estimates require robust modeling approaches that are calibrated to local conditions. Here, we calibrated LandscapeDNDC, a process-based biogeochemical model, using the most comprehensive dataset on N2O emissions and yields as obtained from 25 field experiments conducted across 12 locations in SSA. These experiments focused on the dominant food crops of maize, sorghum, millet, and rice, and legumes (soybeans and beans). Site-specific parameterization was achieved through Latin hypercube sampling via SPOTPY-LDNDC, followed by validation against an independent dataset of 256 treatment-years across 44 sites representing SSA's major agroecological zones. We assessed the model’s performance in terms of absolute N₂O emissions, yields, and yield-scaled emissions (YSE). We then applied sensitivity analysis to identify the primary drivers of emission variability. Our results show that LandscapeDNDC effectively captures the variability in N₂O and YSE across various cropping systems, highlighting its potential as a tool for national and regional GHG inventories. This could be an efficient way to improve greenhouse gas inventories, enabling better-targeted mitigation and sustainable intensification strategies.

How to cite: Barbacias, M. G., Butterbach-Bahl, K., and Rahimi, J.: Site-Calibrated LandscapeDNDC Modeling of Yield-Scaled N₂O Emissions from Smallholder Cropping Systems in Sub-Saharan Africa, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1215, https://doi.org/10.5194/egusphere-egu26-1215, 2026.

Deep meromictic lakes are anoxic below the chemocline and accumulate chemically reduced solutes in bottom waters. In the 120 m deep meromictic Lake Idro (Italy), nitrate is almost completely consumed at the chemocline depth, yet measurable concentrations (≈ 3 μM NO₃⁻) are consistently found in the sulphide-rich bottom water and surficial sediment. Under strongly reducing conditions, nitrate is expected to be rapidly consumed as evidenced by measured denitrification rates, and its presence suggests the existence of a hidden source.

Two potential nitrate sources were hypothesized: (i) the oxidation of NH₄⁺ to NO₃⁻ via manganese oxides (MnOx) as the lake sediment is rich in Mn; and (ii) allochthonous inputs, supported by nitrate-rich sinking particles.

To test the first hypothesis, potential nitrification was measured in sediment slurry incubations amended with ¹⁵NH₄⁺ and MnOx. These experiments showed no clear evidence of NH₄⁺ oxidation, indicating that Mn-driven nitrification is unlikely to sustain the observed nitrate pool. The analyses of intracellular nitrate storage revealed nitrate concentrations an order of magnitude higher than the dissolved fraction, suggesting that sinking diatoms are potential nitrate sources for the benthic system.

Diatoms are well known for their ability to accumulate nitrate in vacuoles and to respire it under unfavourable or anoxic conditions. Lake Idro experiences frequent diatom blooms, and the sediment is enriched in diatom frustules, primarily from the genus Aulacoseira, which is capable of surviving in anoxic sediments for extended periods. These observations support the hypothesis that sinking diatoms may act as carriers of nitrate to the deep sediments of Lake Idro, fuelling benthic nitrogen transformations.

The application of the ¹⁵N isotope-pairing technique on intact sediment cores confirmed active ¹⁴N-NO₃^- denitrification in the monimolimnion sediment, with measured rates of 5.9 ±1.5 µmol ¹⁴N-NO₃^- m^-2 h^-1, accounting approximately for 25 % of total benthic denitrification in the entire lake. Dissimilative nitrate reduction to ammonium (DNRA) rates were also detected but were five times lower than denitrification. These findings demonstrate that diatom-mediated delivery of intracellular nitrate may represent a quantitatively significant and previously overlooked nitrate source to sediments in stratified lakes. Consequently, this mechanism represents an important sink for nitrate and must be considered in future nitrogen-cycle models of meromictic and stratified lakes.

How to cite: Morini, L., Sudo, M. L., Arroyave-Gomez, D. M., Magri, M., Benelli, S., Marzocchi, U., Castaldelli, G., and Bartoli, M.: Hidden source of nitrate fuel benthic denitrification in the anoxic monimolimnion of a deep meromictic lake., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1371, https://doi.org/10.5194/egusphere-egu26-1371, 2026.

How to cite: Mohinuddin, S., Huang, J.-C., and Chen, Y. Y.: Uneven decline and role of long-range atmospheric transport of global wet nitrogen deposition , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-1717, https://doi.org/10.5194/egusphere-egu26-1717, 2026.

The transition towards circular nutrient management requires fertilizers that enhance nitrogen (N) use efficiency while minimizing environmental losses. Struvite, a recovered magnesium ammonium phosphate, is increasingly proposed as an alternative to conventional mineral fertilizers such as monoammonium phosphate (MAP). However, the extent to which fertilizer chemistry interacts with soil properties to regulate microbial functioning and N cycling processes remains insufficiently understood.

In this study, we investigated short-term N transformations, microbial activity, and greenhouse gas emissions in two agricultural soils differing in pH (acidic and alkaline) following fertilization with struvite and MAP. Soils were incubated under controlled conditions, and temporal changes in mineral N forms, soil chemical properties, and CO₂ and N₂O emissions were monitored. Microbial respiration and growth were quantified to assess microbial carbon use efficiency (CUE) and biomass turnover. To resolve underlying process rates beyond net fluxes, stable isotope techniques were applied to quantify gross ammonium and nitrate production and consumption, allowing the calculation of microbial nitrogen use efficiency (M-NUE).

Fertilizer effects were strongly regulated by soil pH. In acidic soil, struvite promoted a more gradual and microbially efficient N turnover compared to MAP, characterized by distinct ammonium and nitrate transformation pathways and higher M-NUE. In alkaline soil, N cycling was dominated by rapid nitrification, which reduced functional differences between fertilizer types. Across both soils, fertilizer-specific shifts in microbial growth, CUE, and biomass turnover revealed changes in microbial resource allocation and N processing pathways.

By integrating gas flux measurements, microbial efficiency indicators, and stable isotope–derived gross N transformation rates, this study highlights how soil chemical context governs the biogeochemical performance of recovered fertilizers. Our findings emphasize the need to account for soil pH and microbial functioning when optimizing the use of struvite and other circular fertilizers in sustainable agricultural systems.

How to cite: Alberghini, M., Friedl, J., Rosinger, C., Weinrich, F., Hood-Nowotny, R., Ferretti, G., Keiblinger, K., and Coltorti, M.: From fertilizer form to microbial function: soil pH controls nitrogen cycling pathways under conventional and recovered phosphorus fertilization, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5550, https://doi.org/10.5194/egusphere-egu26-5550, 2026.

Degrading topsoil, declining habitat and biodiversity, climate change and social and political unrest alongside a growing population and demand for food are calling for a sustainable alternative to the current industrialised agricultural systems. Permaculture and agroecology are two potential alternative sustainable food systems that are currently lacking scientific evidence base. This study compared the two alternative management approaches against a conventionally practiced control in terms of their soil fertility, microbial abundance and diversity (via PLFA analysis) and greenhouse gas mitigation potential. The permaculture site comprised of a no-dig, organically amended market garden for vegetable production, while the agroecology site was minimally tilled and organically amended, whereas the control was tilled & fertilised with a legacy of herbicide and pesticide use. Monthly soil sampling and greenhouse gas emission monitoring via closed chambers over a 12-month period assessed the soils biogeochemistry, microbial abundance and greenhouse gas fluxes. Permaculture soils supported the most abundant microbial community, with an annual mean total microbial biomass of 89.92 ± 20.84 µg g^-1 (23.23 ± 30.7 µg g^-1 and 28.69 ± 30.7 µg g^-1, more than the minimally tilled and conventionally managed soil, respectively). The same soils also exhibited more than double soil organic matter content (annual mean 16.87%) relative to the conventional management, alongside a significantly lower proportion of soil organic carbon (SOC) loss as CO₂ (1.98%, compared to 7% under conventional management). Surprisingly, nitrous oxide (N₂O) fluxes at the conventional site were limited, despite the build-up of the soil nitrate pool during summer, which was attributed to the exceptionally dry soil conditions that prevailed during the year of study, suppressing microbial N₂O production. However, the denitrification product ratio (N₂O/N₂+N₂O) was consistently lower under permaculture soils compared with agroecology and conventional soils, an indication of a strong potential for N₂O emission mitigation. Seasonal warming during spring further stimulated microbial activity, accelerating nutrient acquisition and carbon turnover, with permaculture no-dig soils maintaining three times greater total soil carbon (0.67 ± 0.02 %, annual mean), suggesting a more stable carbon pool. Overall, this study demonstrates permaculture and agroecology practices, particularly no dig management combined with organic amendments, enhances soil fertility, microbial activity, and carbon retention, indicative of a more balanced food system. Multi-year assessments across contrasting climatic conditions are warranted to reduce the uncertainty of temporal variability in GHG flux dynamics and assess long-term carbon stability under these managements.

How to cite: Sgouridis, F., Williamson, R., Reay, M., and Williamson, C.: The effect of sustainable agricultural land managements (agroecology & permaculture) on soil nitrogen and carbon cycling, microbial diversity and greenhouse gas emissions, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5670, https://doi.org/10.5194/egusphere-egu26-5670, 2026.

Soil nitrogen (N) supply and plant N acquisition strategies are central to species coexistence and ecosystem functioning, but how topography regulates plant N acquisition strategies remains poorly understood. Here, we used ¹⁵N natural abundance approach to quantify plant N uptake proportions along a valley to slope gradient in Southwest China. We further measured leaf and root functional traits with soil N transformation rates to explore topography controls of plant N acquisition strategies.

The results showed that soil nitrate (NO₃^–), decreased significantly from valley to slope, whereas soil ammonium (NH₄⁺) and extractable organic N (EON) increased significantly. These differences were attributed to distinct soil N transformation pathways, with markedly higher soil N mineralization and nitrification rates in valley soils. Consistent with the shifts of soil N availability, plants predominantly utilized NO₃^– (83.1%) in the valley, but markedly increased the uptake proportions of organic N and NH₄⁺ at slope. In addition, leaf functional traits shifted from an acquisitive strategy in valley plants, characterized by high leaf N concentrations, to a conservative strategy in slope plants with higher leaf carbon (C) to N ratios and increased leaf thickness. In contrast, root functional traits changed from “amount” strategies in the valley, indicated by high specific root length, to “efficiency” strategies reflected by high root N uptake rates at slope. Our structural modeling indicated that topography-driven shifts in plant biomass, leaf and root C: N, soil physicochemical properties, and soil enzyme activity constrain soil N mineralization and nitrification rates on slopes, thereby increasing the relative contribution of EON and NH₄⁺ in soils and driving a corresponding shift in plant N acquisition strategies.

Together, these findings highlight that plants adapt to topography-driven variations in soil N supply by coordinating above and belowground functional traits. Our results provide a scientific basis for future forest restoration and species selection across topographic gradients.

How to cite: Yang, S. and Zhu, T.: Topography-driven divergence of plant nitrogen acquisition strategies in forests, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5881, https://doi.org/10.5194/egusphere-egu26-5881, 2026.

Quantifying the response of cropland N₂O emissions to future warming is critical for predicting the feedback between nitrogen cycling and climate change. A central uncertainty is whether soil N₂O emissions thermally adapts, an assumption often invoked in carbon-cycle theory. If present, both the magnitude and mechanistic basis of this adaptation remain unresolved. Here, using a global compilation of N₂O flux measurements from temperature-controlled incubations of cropland soils, we identify mean annual temperature (MAT) as the dominant predictor of N₂O fluxes and their temperature sensitivity (Q₁₀). Along the MAT gradient, N₂O fluxes at a reference temperature (25 ℃) declined by 12.2 ± 2.6% (mean ± SE) per °C, and Q₁₀ decreased by 0.05 ± 0.01 per °C. To probe mechanisms, we conducted two complementary experiments using soil samples spanning climate gradients: a short-term temperature-response assay and a 90-day warming incubation, both under controlled moisture and with ¹⁵N-labelled substrate additions. Across both datasets, warmer thermal regimes (higher MAT and experimental warming) reconfigured temperature response curves toward lower Q₁₀ and higher T_opt (temperature optima) for both nitrification and denitrification. Mechanistically, this pattern is aligning with the compensatory theory, microbial N₂O production rates normalized to mean nitrifier and denitrifier RNA abundances were reduced under warmer thermal regimes. Together, these findings highlighted that soil N₂O production adapts to local thermal regimes across space and to sustained warming through time, implying that future warming may amplify cropland N₂O emissions, but less than commonly predicted.

How to cite: Zhang, W., Nie, M., and Zhou, F.: Quantifying thermal adaptation of cropland N2O emissions and its compensatory microbial basis, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6968, https://doi.org/10.5194/egusphere-egu26-6968, 2026.

Peatlands are globally significant sinks for carbon and nitrogen. The carbon and nitrogen cycles in peatlands are highly sensitive to changes in water table, temperature, and soil moisture. Long-term rewetting has been suggested as a potential restoration strategy for peatland restoration; however, if done improperly, it can create transitional oxic and hypoxic zones, which can act as major hotspots for N₂O emissions. In this study, we investigated the effect of transitioning from oxic to hypoxic conditions in a drained peat soil prepared in mesocosms, which were installed in a climate chamber to simulate day and night conditions. The humidity in the climate chamber was maintained above 90% to study the interaction of the produced N₂O with artificial fog, generated using foggers. We prepared 12 mesocosms, out of which 4 received a ¹⁵N-NO₃^- tracer, 4 received a ¹⁵N-NH₄⁺ tracer, and the remaining 4 were kept as controls. One birch plant sapling was also planted in each mesocosm before the start of the experiment. Soil oxygen levels were reduced from 9 mg/L to 1.5 mg/L over the course of ten days, and the effects of this change from oxic to hypoxic conditions were studied.

Our results indicate that due to a decrease in soil oxygen over time, N₂O emissions increased and peaked on the final day (162 ± 22.80 μg N m^-2 h^-1) of the experiment. During this transition (oxic to hypoxic), we observed a significant increase in the abundance of nirK-type denitrifiers. Our ¹⁵N tracers indicate that on the initial days, the produced N₂O was dominated by ^{the 15}N-NH₄⁺ tracer, but on the final days, the ¹⁵N-NO₃^- showed a significant contribution to the N₂O flux. The birch sapling showed a major uptake of ¹⁵N-NO₃^- in its roots and leaves. This indicates a preference for birch saplings towards the soil nitrate pool compared to the soil ammonium. We also applied the 3D Frame isotope model to the natural isotopomers of soil-produced N₂O and observed a change in the N₂O production processes over the course of the experiment. The initial days were dominated by nitrifiers’ denitrification and nitrification; however, by the end of the experiment, isotopic mapping revealed the dominance of nitrification, coupled with bacterial and nitrifier denitrification. We also found evidence of the solubility of tracer-produced N₂O in the fog water.

Our study demonstrated that the improper restoration of peatlands through rewetting can create transitional oxic-hypoxic zones, which can serve as hotspots for N₂O emissions. Moreover, soil-produced N₂O can be dissolved in fog during colder seasons, which can be further coupled by tree leaves as they also possess potential for N-cycle processes.

How to cite: Masta, M., Ali Kazmi, F., Espenberg, M., Visnapuu, T., Sennett, L. B., Eving, L., Lewicka-Szczebak, D., Deb, S., Khanongnuch, R., Kuusemets, L., Kupper, P., Butterbach-Bahl, K., and Mander, Ü.: Transitional hypoxia during peatland rewetting drives high N2O fluxes via coupled microbial pathways with evidence of N2O sink potential by fog and tree leaves., EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7079, https://doi.org/10.5194/egusphere-egu26-7079, 2026.

Nitrous acid (HONO) is a key precursor to hydroxyl radicals (OH) and a reservoir of reactive nitrogen, yet the processes sustaining elevated daytime HONO in marine and coastal environments remain poorly understood. We combine coastal field observations with irradiation chamber experiments and atmospheric modeling to identify abiotic photodecomposition of marine algae as a previously unrecognized HONO source. During Ulva prolifera green tides, daytime HONO levels in the coastal atmosphere closely followed tidal cycles and peaked at low tide, in contrast to typical inland nocturnal peaks. Chamber experiments confirm that common algae (Ulva prolifera, Bryopsis plumosa, Chaetomorpha spiralis Okam., Sargassum, and Silvetia siliquosa) directly emit HONO under irradiation, with fluxes increasing with light intensity and algal surface area. Measured HONO fluxes of 1.08 × 10^–7 to 2.31 × 10^–6 mol m^–2 h^–1are comparable to reported soil HONO emissions and exceed marine NO fluxes by 2 to 3 orders of magnitude. Incorporating this source into an atmospheric model increases HONO concentrations, enhancing OH and ozone production and accelerating the oxidative loss of dimethyl sulfide and methane. As eutrophication and warming intensify algal blooms worldwide, algal photodecomposition is likely to become an increasingly important driver of coastal reactive nitrogen emissions and oxidation capacity.

How to cite: zhong, X., shen, H., and xue, L.: HONO Emission from Marine Algae, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8551, https://doi.org/10.5194/egusphere-egu26-8551, 2026.

Temperature sensitivities (Q₁₀) of nitric oxide (NO) and nitrous oxide (N₂O) emissions are the core parameters to project future trajectories of soil nitrogen (N) cycling and climate feedback. However, spatial variations in Q₁₀ and their underlying microbial processes are unknown, hindering accurate projection. We sampled 21 upland soils across a 4000-km transect in China and conducted incubations at 5 to 40°C with ¹⁵N tracer to quantify Q₁₀ of NO and N₂O emissions, alongside process-specific emissions from nitrification, denitrification and co-denitrification. Optimal temperatures (T_opt) for these processes exceeded  30°C and increased with mean annual site temperature. Q₁₀ ranged widely from 1.3 to 5.7 (averaged 3.3) and 1.0 to 5.9 (averaged 3.5) for NO and N₂O emissions, respectively, showing higher values observed in lower mid-latitudes and high-pH croplands. The Q₁₀ values were governed by shifts in the ratios between nitrifier and denitrifier functional genes, which are in turn regulated by edaphic and climatic factors. Our observed Q₁₀ values are significantly higher than the default of 2 set in Earth System Models (ESMs). Integrating the experiment-derived Q₁₀ values into model projections reveals that current ESMs underestimate future NO and N₂O emissions by 17.5–26.6% across the Shared Socioeconomic Pathways (SSP3-7.0 and SSP5-8.5) by 2100. This suggests a substantial underestimation of future gaseous N losses from global croplands under warming.

How to cite: Ba, W., Yu, H., Yu, L., Dörsch, P., Nie, M., Han, P., Hobbie, E., Fang, Y., and Zhou, F.: Substantial underestimation of soil nitrogen gaseous losses from global croplands under warming, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-8694, https://doi.org/10.5194/egusphere-egu26-8694, 2026.

Enhanced ‘woody growth’ (dry matter increments, specifically), averaging 10%, has been sustained in patches of long-established (180+ years old) oak forest through 9 years of treatment with elevated CO₂ (eCO₂; 150 ppm above ambient). Root exudation of carbon (C) into the rhizosphere increased by 63%, which primed the microbes for nutrient acquisition to meet enhanced tree N demands. A ‘faster-tighter’ nitrogen cycle accelerates the return of nitrogen via ammonification to plant-available forms and suppresses processes such as nitrification. This ecosystem-scale N conservation strategy supports increased net productivity by maintaining the nutritional balance of the trees in the C-rich atmosphere. The faster-tighter N-cycle makes an additional 25 kg N ha^-1 yr^-1 available to the trees under eCO₂. That is, the forest’s N-cycle adjusts to the increased C supply, but whether this capacity to adjust endures may be constrained by soil organic N stocks and anthropogenic N deposition. Further, when considering broader aspects of the forest under eCO₂, we find nutritional deficiencies producing a cascade of nascent ecosystem fragility in pollen, seeds, seedlings, and food webs. The clear policy implications are: (i) that enhanced net primary productivity does not, in itself, guarantee forest resilience; (ii) that both C and N emission pathways must be accounted for when forecasting 21^st-century C uptake into temperate forests; and (iii) that, when proposing forests as natural climate solutions, understanding C-nutrient interactions is of primary concern.

How to cite: MacKenzie, R., Rumeau, M., Reay, M., Handy, G., Mayoral, C., Gardner, A., Norby, R., Smith, A., Hartley, I. P., Hamilton, R. L., and Ullah, S.: They say “carbon!”, we say “…and nutrients!”: N-cycle biogeochemistry sustaining net productivity in a long-established temperate broadleaf forest under elevated CO2, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12836, https://doi.org/10.5194/egusphere-egu26-12836, 2026.

Soil nitrogen (N) availability and plant N uptake strategies are central to species adaptation and community assembly, yet how lithology shapes soil N supply and plant N uptake remains poorly understood. Here, we used ¹⁵N labeling to compare soil N supply and plant N uptake preferences in forests on soils developed from limestone and clastic rocks, respectively. Our results revealed significant contrasts in inorganic N pools: nitrate (NO₃^–) dominated in limestone soils, while ammonium (NH₄⁺) was more abundant in red soils developed from clastic rocks. We attributed these differences to different soil N transformation pathways. Increased nitrification rates in limestone soils increased NO₃^– content, whereas red soils exhibited high mineralization but lower nitrification rates, leading to NH₄⁺ dominating inorganic N. Forest plants in both limestone and red soils preferentially utilized NH₄⁺ as their primary N source. However, plant in limestone soils took up significantly higher proportions of NO₃^– and glycine. Moreover, total N uptake rates by plants were significantly larger in limestone than red soils, suggesting a more efficient N acquisition strategy. Structural equation modeling indicated that lithology significantly affected soil N mineralization and nitrification by regulating soil pH and total N, thereby driving differences in soil inorganic N pools and ultimately plant N uptake. Our results provide evidence that lithology-driven variations in soil N supply can strongly affect plant N acquisition strategies.

How to cite: Dörsch, P., Yang, S., and Zhu, T.: Lithology controls of soil N availability and plant N acquisition strategies in subtropic forests, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-13347, https://doi.org/10.5194/egusphere-egu26-13347, 2026.

Freeze–thaw cycles (FTCs) are recognized as important regulators of nitrous oxide (N₂O) emissions in temperate and boreal soils, yet the underlying drivers and processes during FTC remain poorly understood. 

We set up two controlled incubation experiments to investigate the effect of freezing and thawing on N₂O emissions, emission drivers and N₂O forming processes. Soil samples were collected during spring freeze-thaw period from a biodiversity cover crop plot trial in Helsinki, southern Finland. In experiment 1, we studied the effects of soil depth and cover crops (CC) on N₂O emissions, soluble nutrients (N, P, C) and active N cycling genes (RNA) during consecutive freezing and thawing phases over a 3-week period. In experiment 2, we studied N₂O emissions and their isotopologue ratios in a dynamic automated FTC experiment with alternating freezing (–4 °C) and thawing (+4 °C) cycles. To support the controlled experiments, we conducted twice weekly N₂O flux measurements in the field during the spring freezing-thawing period.

Throughout the experiment 1, we found significantly greater N₂O production at the surface (0 – 2 cm) compared to the subsurface (9 – 11 cm) soil depth. To support this, soil nitrate, ammonium, total dissolved N, dissolved organic C and soluble reactive P concentrations where higher in the topsoil compared to the subsurface. In experiment 2, N₂O emissions occurred during thawing periods but were stimulated by freezing. Based on isotopologue ratios, the N₂O originated predominantly from denitrification. Field N₂O flux data support the laboratory results showing higher N₂O emissions during freeze-thaw, and smaller during warm periods, and that cover crop treatments potentially lead to higher N₂O emissions during soil freeze-thaw. Overall, the findings demonstrate the episodic nature of freeze-thaw related N₂O emissions governed by substrate dynamics in soil that support conditions suitable for “hot moments”.

How to cite: Pihlatie, M., Virta, O., Aaltonen, H., Teikari, J., Turunen, P., Kohl, L., Znamínko, M., Palacin Lizarbe, C., Nykänen, H., Biasi, C., and Koskinen, M.: Cover crops, soil depth and nutrient dynamics drive N2O emissions and N2O forming processes during soil freezing and thawing, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16855, https://doi.org/10.5194/egusphere-egu26-16855, 2026.

Nordic agricultural production faces multiple challenges in a warming climate. Although predictions indicate an overall increase in annual mean precipitation in northern Europe, increasing temperatures may lead to earlier snowmelt and drying of soil during springtime, as well as longer growing season and higher evapotranspiration increasing the risk of summer droughts. 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 climate extremes such as drought, and how the combined effects of cover crops, their diversity and drought affect greenhouse gas (GHG) emissions from soil remain largely unknown. We studied the effect of cover crop diversity and drought on soil and crop C and N dynamics and GHG (CO₂, N₂O) emissions in a biodiversity cropland experiment with or without shelters that remove 50% of incoming precipitation for two years. GHG emissions were measured with the manual dark chamber method twice a week during growing season and once a week during off-season. Soil temperature and water content were measured continuously, and the soil was sampled for mineral N and total C and N analysis seasonally.

The preliminary results showed that reduced rainfall did not affect N₂O emissions significantly during the growing season in either year. During off-season, reduced rainfall led to elevated N₂O emissions irrespective of cover crop diversity treatments. However, the effect was absent in the second year, indicating that factors other than drought were driving the N₂O production. Contrary to N₂O, drought did not affect CO₂ emissions during off-season in either year. Overall, during both years off-season N₂O emissions dominated the annual N₂O balance in all diversity treatments, highlighting the importance of including off-season measurements to the annual N₂O balance estimation.

How to cite: Turunen, P., Simojoki, A., Koskinen, M., Heinonsalo, J., and Pihlatie, M.: Seasonal patterns of N2O and CO2 emissions from Finnish agricultural soil under oat with and without cover crops as affected by reduced rainfall, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-16945, https://doi.org/10.5194/egusphere-egu26-16945, 2026.

As peat extraction for energy has declined in Europe, extensive areas released from peat production require sustainable after-use. This land use change provides opportunities to mitigate climate change, halt biodiversity loss and support socially fair and rewarding solutions for communities. Here we present the first results from PaluWise project’s large 50 ha peat extraction area converted into demonstration site of paludiculture i.e., the productive land use of rewetted peatlands that preserves the peat soil and thereby reduces carbon dioxide (CO₂)  and nitrous oxide (N₂O) emissions and subsidence. The risks related to paludiculture include increased methane (CH₄) emissions, high nutrient losses and wetting the surrounding fields. We also reviewed evidence from climate change mitigation potential of common after-use options in agriculture and forestry for peat extraction areas in Northern Europe (ALFAwetlands project). Our data synthesis of annual greenhouse gas (GHG) fluxes revealed that boreal paludiculture showed a net loss of carbon (C) based on the net ecosystem C balance at least in the short term after rewetting cultivated peat soil. A woody crop, short rotation coppice of willow had more favourable greenhouse gas balance than forage and set-aside treatments during 4 years after transition. Options enhancing C input to the soil without rewetting may stop net annual C losses from a former peat extraction site just in one year: Afforestation on Scots pine with fertilization turned the site fast into a CO₂ sink, as measured by eddy covariance technique. We hypothesize that woody crops having low nutrient requirements and potential for added value products may offer a win-win after-use solution for rewetted peat extraction areas. We examined biomass and CO₂, CH₄ and N₂O fluxes from stands of downy birch and colonizing wild vegetation at our demonstration site. We found that the first Sphagnum mosses co-occur with downy birch, indicating favourable conditions for enhanced C sequestration. We expect that land use decisions may optimize many targets: climate, biodiversity, water quality, and economy simultaneously. Confounding factors, e.g. time perspective may affect landowner’s preferences. Long-term changes in peat carbon stock under any after-use option require further study.

How to cite: Larmola, T., Sarkkola, S., Juutinen, S., Rautakoski, H., Linkosalmi, M., Jauhiainen, J., Aurela, M., Ukonmaanaho, L., and Merilä, P.: Woody paludiculture as an after-use option for peat extraction fields , EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17046, https://doi.org/10.5194/egusphere-egu26-17046, 2026.

Arctic permafrost-affected soils serve as one of Earth’s most significant terrestrial reservoirs of nitrogen (N), storing an estimated 55 Pg of total N within the first three meters of the soil. Ongoing anthropogenic climate change is causing permafrost soils to thaw at greater depths each summer, rendering part of vast pools of N stored in the permafrost accessible to plant uptake and microbial processing. However, little is known of the magnitudes and consequences of the potential increase of N availability due to permafrost thaw, as the mobilisation and mineralisation of this N has the potential to alter ecosystem productivity, as well as increase emissions of reactive nitrogen gases, such as nitrous oxide (N₂O). This research aims to quantify nitrogen dynamics across the Arctic following permafrost thaw from the historical period to the end of the twenty-first century.

In our study, we first estimate the total amount of soil N that will be mobilized through thawing. To do this, we combine a vertically-resolved high spatial resolution soil C and N dataset with future projections of pan-Arctic active layer depth changes derived from five CMIP6 models across four climate change scenarios. Vertical mean soil N profiles were thereby determined for different land cover types of the tundra, taiga, wetlands and barren biomes. Secondly, we estimated the amount of permafrost organic soil N that is rapidly mineralized to bioavailable forms, was determined from a temperature-dependent mineralisation flux estimation. Finally, we perform a first-order estimation of the impact of the additional bioavailable N for Arctic vegetation NPP and N₂O emissions. 

Across the CMIP6 models, the pan-Arctic mean maximum active layer depth is projected to increase by an additional 1 - 2.65 m by 2100 (SSP 1-2.6 to 5-8.5), relative to present-day conditions. This increase corresponds to a potential cumulative release of 20 - 44 Pg total N by the end of the century, of which 4.4 - 5.5 % may be mineralised rapidly under projected soil warming. Putting these estimates into context with our novel budget of present-day pan-Arctic N fluxes, we show that the addition of reactive nitrogen from the permafrost will consist of an important part of N sources to the Arctic in the future (40-50 %).  

Based on our synthesis of N fertilisation effects on Arctic vegetation net primary productivity (boreal ANPP: 14.1 (+/- 3.55) g C / g N, BNPP: 2.82 g C / g N; tundra ANPP: 2.66 (+/- 2.22) C / N, BNPP: 2.29 (+/- 4.41) g C / g N), we furthermore quantify that the release of N from the permafrost could increase  NPP by 150 – 400 Tg C yr-1 until year 2100. In a similar approach based on soil manipulation experiments, we also estimate a potential additional 0.12 – 0.8 Tg N yr-1 in N₂O emissions by the year 2100.

Our results show that permafrost thawing will significantly alter the Arctic N budget, having very likely substantial impacts for both terrestrial NPP and as N₂O emissions. 

How to cite: Oxley, L. R., Stocker, B. D., Zähle, S., Zhu, Y., and Lacroix, F.: Petagrams of Nitrogen released from the Permafrost affect Arctic Ecosystem Fluxes under any Climate Scenario, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17105, https://doi.org/10.5194/egusphere-egu26-17105, 2026.

The Arctic is warming four times faster than the global average, triggering the widespread degradation of permafrost and enhancing mobilization of vast, previously frozen soil nitrogen (N) and carbon (C) stocks. While C release associated with permafrost thaw is better documented, the liberation of permafrost N, a potential precursor to the strong greenhouse gas (GHG) nitrous oxide (N₂O), remains a critical knowledge gap. This is particularly relevant for ice-rich Yedoma deposits, which are highly vulnerable to abrupt thaw and the formation of disturbance features, such as retrogressive thaw slumps (RTSs), thermokarst lakes, and drained thermokarst lake basins (DTLBs). While RTSs are known hotspots for N₂O, recently formed DTLBs underlain by ice-rich Yedoma deposits with a high content of buried, poorly decomposed organic matter, remain largely understudied, although they are widespread across Yedoma landscapes. Importantly, there are no studies reporting N₂O fluxes from DTLBs, despite the high N mineralization expected after drainage, which might support high emissions.

Here, we report N₂O fluxes and N turnover processes from RTS and DLB on the Baldwin Peninsula, Western Alaska, underlain by ice-rich late Pleistocene Yedoma deposits. In situ fluxes were measured during the summer of 2024, alongside aerial surveys for high-resolution elevation and vegetation mapping with lidar and optical cameras. We conducted laboratory incubations for GHG production, including denitrification and ¹⁵N labeling to quantify gross rates of mineralization, nitrification, and dissimilatory nitrate reduction to ammonium (DNRA) using the ¹⁵N tracer method.

Our study reveals high N₂O emissions at both disturbance sites, demonstrating that DTLBs are emerging as significant sources of N₂O (up to 7.7 mg N m^-2 d^-1) emissions, comparable to known high emissions from thaw slumps. supported by high nitrate concentrations, reaching up to 205.1 µg N gDW^-1. We identified the role of environmental factors in driving the spatial variability in N₂O fluxes as well as N cycling. These findings suggest that as thermokarst lake drainage events increase across the Arctic, DTLBs in Yedoma uplands represent a major, expanding source of permafrost-driven N emissions that must be integrated into global climate feedback models. By tracking how N moves through the soil and how different environmental conditions, like moisture and thaw, trigger specific microbial processes, we can better understand the overall behavior of the N cycle and its growing role in these disturbance landforms.

How to cite: Hashmi, W., Martinez-Risco Martinez, P., Sanders, T., Veremeeva, A., Nitze, I., Gil, J., Rütting, T., Paul, D., Strauss, J., C. Treat, C., and E. Marushchak, M.: When Yedoma permafrost thaws: disturbances from lake drainage to thaw slump, and their impact on nitrogen cycling, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17133, https://doi.org/10.5194/egusphere-egu26-17133, 2026.

The input of reactive nitrogen sourced from anthropogenic activities such as smallholder farming as well as changes in its transport and fate in the environment may alter the nitrogen balance of a catchment and the nitrogen use efficiency for crop production. Both have the potential of causing detrimental effects on agricultural productivity and the environment such as water bodies. Insufficient nitrogen addition for crop production could lead to soil nitrogen depletion, while too high input rates could lead to excess nitrogen polluting water bodies. In the Mau Forest Complex (MFC) in Kenya, fertilizers and livestock management have been assumed to be associated with the increase in annual riverine export of reactive nitrogen. Twice the annual export of nitrogen from a catchment dominated by smallholder agriculture was reported compared to that from the native forest. To assess the role of smallholder agriculture in nitrogen losses, this study aims at determining the nitrogen balance and nitrogen use efficiency of a 27 km² headwater catchment characterized by smallholder farming in the MFC. Anthropogenic inputs and outputs were estimated from a household survey (n=185), field measurements involving precipitation collectors in 10 different locations as well as literature review. The nitrogen flows in the native forest were obtained from the literature.

Results show that at farm scale, about one third of investigated farms have negative nitrogen balances, while at the catchment scale the aggregate nitrogen balance is −10.9 kg N ha⁻¹ yr⁻¹. This is in contrast to the positive nitrogen balance of the native forest of 26.5 kg N ha⁻¹ yr⁻¹. With respect to the nitrogen use efficiency only 20% and 18% of the maize fields as well as 7% and 12% of the potato fields, recorded nutrient use efficiency between 50% and 90% in 2018 and 2019, respectively.

The study shows that inorganic fertilisers, atmospheric deposition and biological fixation are the most important sources of reactive nitrogen, while crop harvest, denitrification and leaching were identified as major loss pathways. The wide range of nitrogen surplus and deficits among farms and the subsequent potential for eutrophication and soil mining highlight the need to better educate farmers on the optimal use and timing of fertiliser application to close the deficit gap and prevent pollution.

How to cite: Kasebele, M., Jacobs, S., and Breuer, L.: Nitrogen balance and nitrogen use efficiency in an East African tropical montane catchment characterised by smallholder farming, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17418, https://doi.org/10.5194/egusphere-egu26-17418, 2026.

Tropical wetlands are among the most important regulators of the global carbon (C) and nitrogen (N) cycles, largely through microbially mediated processes that control greenhouse gas (GHG) production and consumption. Tropical peat forests play a key role in these biogeochemical cycles by storing large amounts of organic matter and regulating gas exchanges between soils and the atmosphere, with their functioning strongly influenced by vegetation composition and seasonal shifts between dry and rainy periods. Amazonian peatlands are emerging as potentially significant sources and sinks of nitrous oxide (N₂O) and methane (CH₄), depending on climatic conditions and climate change, including more frequent droughts and increasing irregularity between rainy and dry seasons. Despite their importance for climate regulation, the links between peat forest structure, microbial C and N cycling, and ecosystem-scale GHG fluxes remain poorly quantified. In addition to vascular plants, cryptogams such as mosses and lichens may exert important yet understudied controls on microbial activity, thereby potentially affecting N₂O and CH₄ emissions in aboveground compartments.

This study aims to assess how cryptogam-associated microbial processes affect N₂O and CH₄ fluxes in the Quistococha peat swamp forest and Zungarococha secondary peat swamp forest of Peruvian Amazon, and to evaluate how these processes  differ between forest types.

A total of 25 cryptogam samples were collected from two sites in the Loreto Region of northern Peru. Quistococha is an intact peat swamp forest dominated by Mauritia, Tabebuya, and Caspi, whereas Zungarococha is a secondary peat swamp forest dominated by Cashapona, Mauritia, Hebea, Caspi, M_Beuna, Symphonia, and Cumala. Samples were collected from the stems of trees and palms during two campaigns, in rainy and dry seasons. Metagenomic sequencing of cryptogams was performed to investigate microbial functional potential related to C and N cycling and its relationship with forest type.

Our results show that: (1) Cashapona, Caspi, Cumala, and Hebea exhibited similar functional gene abundance patterns across different seasons and sites, suggesting relatively stable microbial functional characteristics; (2) genes associated with N fixation, dissimilatory nitrate reduction to ammonium (DNRA), and nitrification–processes regulating N availability and potential N₂O production–were more abundant in Zungarococha, especially during the rainy season; (3) genes related to methanogenesis (CH₄ production) and methanotrophy (CH₄ oxidation) were present at relatively low abundances at both sites, with no significant seasonal differences; (4) most functional genes related to C and N cycling were more abundant in Zungarococha than in Quistococha, with peak abundances during the rainy season , whereas in Quistococha, genes related to methanotrophy, N fixation, nitrification, and denitrification (also influencing N₂O consumption) were more abundant during the dry season; (5) Burkholderiaceae and Methanobacteria were more abundant in Zungarococha, Methylococcales and Opitutae were more abundant during the dry season, and Oscillatoriales were more abundant in the rainy season, which are affecting C and N cycling.

How to cite: Chen, S., Mander, Ü., Khanongnuch, R., Kazmi, F. A., Masta, M., Soosaar, K., Fachin-Malaverri, L., and Espenberg, M.: Cryptogam-associated microbial processes shaping N2O and CH4 cycling in Amazonian peat swamp forests, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-17679, https://doi.org/10.5194/egusphere-egu26-17679, 2026.

Iron exists abundantly in soil in multiple oxidation states and mineral forms, and is the dominant redox-active metal. Recent evidence suggests iron chemistry plays a central role in producing volatile reactive nitrogen oxides (NO_y = NO + NO₂ + HONO + other N-oxides), which are key air pollutants contributing to tropospheric ozone formation, acid deposition, and respiratory health risks. Current atmospheric models do not accurately represent soil NO_y fluxes, particularly HONO and NO₂, because biogenic production mechanisms remain poorly characterised. In moist soils, HONO is primarily produced by bacterial and archaeal ammonia oxidisers. However, as soils dry, nitrite and nitrate can accumulate and pH often decreases, potentially favouring abiotic nitrate reduction as a critical HONO source.

To investigate how soil iron mineralogy, concentration, and speciation influence NO_y emissions during drying, HONO and NO₂ fluxes are measured over 24 hours using an ICAD-HONO/NO₂-210L system (Airyx GmbH) from soil microcosms amended with three iron oxides (ferrihydrite, goethite, magnetite) at two concentrations (3.5% and 4.5% total iron). Microbial community responses will also be assessed via quantitative PCR targeting nitrogen cycling genes. We hypothesise that: 1) soil drying will increase nitrate accumulation and lower pH, leading to HONO fluxes that peak at intermediate moisture when thin water films enable reactions but allow gas diffusion; 2) ferrihydrite-amended soils will exhibit the highest NO_y emissions due to its Fe³⁺ reduction potential, transition metal adsorption, and reactive oxygen species generation; and 3) NO_y emissions will increase with iron oxide concentration, although high concentrations may suppress microbial activity via metal toxicity.

Preliminary results show substantial HONO emissions from all iron amendments in neutral soils (~pH 7), followed by a steep decline as soils dry. A late NO₂ peak was observed, possibly due to physical release during drying or shifts in microbial pathways. Increasing goethite concentrations correlated with higher HONO emissions, whereas ferrihydrite showed a negative correlation. Future work will examine the pH modulation of the relationship between iron and NO_y fluxes by repeating flux measurements in acidic soils (~pH 5.5), where we expect enhanced nitrite protonation, and altered iron solubility and redox activity.

How to cite: Purchase, M. L., Waez, C., Thorpe, A. J., and Mushinski, R. M.: Influence of Iron Mineralogy on Reactive Nitrogen Gas Emissions from Soil, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-18666, https://doi.org/10.5194/egusphere-egu26-18666, 2026.

Salinization is an increasing threat to global food security. Sea-level rise and storm surges drive coastal salinization, while inland salinization is driven by intensive fertilization and low-quality irrigation. High salt levels cause osmotic stress, which impairs plant growth and microbial activity, ultimately degrading soil health and food production. Both the EU and UN recognize soil salinization as a major global challenge requiring urgent action. 

This study is part of the EJP SOIL project SoilSalAdapt, with Norwegian partners funded by the Research Council of Norway. The project explores adaptation strategies to soil salinization in a temperate climate. Experiments indicate that controlled saline irrigation can promote salt tolerance in soil microbes, suggesting that saline irrigation may serve as a proactive climate adaptation measure. This sub-study examines the legacy effect of previous salt exposure on soil biogeochemical turnover of carbon and nitrogen in response to a new shock salinization event.

Specifically, this study investigates 1) oxic microbial respiration and carbon use efficiency, 2) anoxic respiration and denitrification end-product stoichiometry, and 3) nitrification potential rates and the relative contributions of ammonia-oxidizing bacteria and archaea.

Denitrification completeness was strongly impacted by the salt treatment, particularly in the low-fertilization scenario, were salt seems to reduce nitrous oxide production per total denitrification. Nitrification rates responded differently to historical salinity in clay and sand soils, but the saline shock converged rates across soil types at a lower overall level.

At the EGU conference, I will present our findings and discuss how soil-based adaptation strategies can support resilient food production under ongoing and future climate pressures.

How to cite: Kyllingstad, R., Dörsch, P., and Almås, Å.: Adapting soils to salt: Effects of saline irrigation on soil C and N turnover, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-19174, https://doi.org/10.5194/egusphere-egu26-19174, 2026.

Human activities have increased atmospheric reactive nitrogen (N) deposition, with important consequences for ecosystem biogeochemical cycles. In forest ecosystems, tree canopies act as active filters that intercept, transform and redistribute atmospheric N before it reaches to the soil. These canopy-level processes determine the chemical forms of N that become available for biological uptake or are transferred to the soil. Despite their importance, the temporal variability of these processes remains poorly understood, particularly in Mediterranean ecosystems with pronounced seasonal contrasts.

In this study, we investigated the seasonal dynamics of atmospheric N transformations within the canopy of a Mediterranean Holm oak forest (Quercus ilex / Q. rotundifolia) in Spain. We focused on canopy-scale nitrification processes and the abundance of N-fixing and nitrifying microorganisms associated with the phyllosphere and precipitation. Canopy N fluxes were quantified, nitrate sources were identified using Δ¹⁷O isotopic signatures, and microbial abundances were quantified by qPCR, to explore seasonal dynamics and their environmental drivers.

Our results show that the canopy acted as a net sink for atmospheric N throughout the year, indicating that N inputs did not exceed ecosystem demand and suggesting potential N limitation. The nitrate measured in throughfall samples indicated a predominantly atmospheric origin during most of the year (76–92%). In contrast, during summer up to 76% of the nitrate was derived from in situ biological processes at canopy level. These enhanced biological transformations were correlated with weather conditions, particularly the higher temperatures and dry conditions typical of summer, which may favour nitrification and promote the accumulation of N compounds on leaf surfaces. Reduced plant activity and lower N uptake during summer further prolong N residence time within the canopy, increasing the likelihood of microbial transformations. Both archaeal and bacterial nitrifiers, as well as N-fixing microorganisms, were detected year-round in the phyllosphere and precipitation. Archaeal nitrifiers consistently outnumbered bacterial ones, and showed a marked increase during summer, driven by higher radiation, temperature and lower humidity. This pattern suggests that archaea may play a significant important role in nitrification, coinciding with the highest nitrification rates observed in summer. These findings highlight the crucial function of canopy processes in regulating N fluxes in Mediterranean forests, particularly during summer. The seasonal dynamics of biological transformations and microbial communities emphasise the influence of environmental conditions on N cycling.

How to cite: Ruiz-Checa, R., Elustondo, D., Ávila, A., Guerrieri, R., Walter, W., Mattana, S., and Alonso, R.: Biological nitrogen transformations within the tree canopy: seasonal variations and microbial contributions to nitrogen fluxes in a Mediterranean Holm oak forest, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20602, https://doi.org/10.5194/egusphere-egu26-20602, 2026.

Nitrogen dioxide (NO₂) is a critical atmospheric pollutant and ozone precursor, yet biogenic soil sources remain poorly constrained. Current models assume soil NO₂ flux is exclusively depositional. Here we demonstrate that soils can produce NO₂ through microbial superoxide (O₂^–) production. Using manipulative slurry experiments, native microbial communities produced 6-10 times more NO₂ than sterile controls following NO exposure. Stimulating superoxide production with NADH increased NO₂ formation 15-fold, while inhibiting NADH oxidase reduced production to near-sterile levels. Superoxide dismutase decreased NO₂ production by 50-75%, and superoxide concentration explained 60% of variation in NO₂ production rates. Addition of peroxynitrite to soil increased headspace NO₂, confirming this intermediate as the mechanistic link. These findings reveal a novel pathway linking carbon and nitrogen cycling where heterotrophic decomposers facilitate biogenic NO to NO₂ via superoxide chemistry, potentially explaining discrepancies between satellite observations and modelled soil NOx emissions.

How to cite: Mushinski, R., Purchase, M., Raff, J., and Wang, D.: Microbial superoxide production influences biogenic nitrogen dioxide formation in soils, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20705, https://doi.org/10.5194/egusphere-egu26-20705, 2026.

Nutrient loss from land use is a major cause of water-quality problems worldwide. High inputs of nitrogen (N) and phosphorus (P) to rivers, lakes, and coastal waters drive eutrophication, reduce aquatic biodiversity, and damage ecosystem services. In many regions, policy frameworks such as the European Union Water Framework Directive require reliable estimates of nutrient pressures to support effective water-quality management. However, measured load data are often limited or inconsistent, particularly at large spatial scales. As a result, export-coefficient (EC) approaches are widely used to estimate nutrient losses from land use. A continuing challenge is ensuring that the coefficients applied are relevant to the environmental context and selected in a consistent and transparent way, especially when values are transferred from international studies.

This study develops a harmonised framework for selecting and applying nutrient export coefficients based on international literature. A structured decision-tree approach is used to systematically assess whether published export coefficients are suitable for application under different climatic and environmental conditions. Each coefficient is screened against six practical criteria: compatibility with local land-use systems, similarity of soil types, relevance of climatic setting, comparability of dominant hydrological pathways, suitability of reporting format for load calculation, and study reliability—evaluated based on the quality of methods, length of monitoring, and peer-review status.

The framework is demonstrated using Ireland as a case study, and the analysis also compares how different land-cover datasets influence national nutrient export estimates. Three datasets are used to explore the effect of spatial representation: the Irish National Land Cover Map 2018 and the CORINE 2012 and 2018 Land Cover maps. National nutrient exports are calculated by multiplying harmonised export coefficients by mapped land-use areas and compared with a national benchmark study, the Source Load Apportionment Model (SLAM).

Across the different land-cover datasets, nutrient export coefficients derived from the framework show strong agreement with SLAM in estimating national nitrogen loads. This suggests that the decision-tree framework supports the selection of export coefficients for dominant agricultural systems, which are the main drivers of nitrogen loss. In contrast, larger differences between SLAM and framework-based estimates are observed for phosphorus, particularly in peatlands, wetlands, and forestry areas. This reflects both the higher sensitivity of phosphorus to coefficient choice and the influence of land-cover representation. Differences between land-cover datasets lead to significant changes in the mapped extent of organic soils and semi-natural land uses, resulting in notable variation in national phosphorus estimates. These findings show that even when identical export coefficients are applied, national nutrient totals can vary substantially depending on the structure and resolution of the underlying spatial data.

Overall, this study demonstrates that combining harmonised export coefficients with high-resolution land-cover data provides a robust and adaptable basis for national-scale nutrient modelling. The close agreement with SLAM for nitrogen supports the validity of the approach for dominant agricultural pressures, while the divergence observed for phosphorus highlights the need for improved representation of peatlands, wetlands, and forestry in national frameworks. 

How to cite: Alighanbari, S.: Developing a harmonised framework to model nutrient emissions from land uses: a case study from Ireland, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-20909, https://doi.org/10.5194/egusphere-egu26-20909, 2026.

Nitrogen is a fundamental plant nutrient and important fertilizer in modern agriculture, while nitrate-based nitrogen losses from agroecosystems become an increasing problem in ground- and surface waters. To reduce the emission of nitrate from agricultural soil, substantial efforts were made in regulation and assessment of plant specific fertilizer needs to reduce fertilization excess. Unfortunately, those efforts have not yet led to a considerable reduction of nitrate loadings in ground and seepage water under agricultural land use. This lag of response is often explained with residence and transport times in groundwater and a potential contribution of nitrogen legacies accumulated in soils.

Since 1980 the water and solute balances of different soils under agricultural land use are investigated at the lysimeter station Brandis (Saxony, Germany). Additionally, historic marking experiments with ¹⁵N enriched fertilizers were performed on some of the investigated soils. The combination of the long-term nitrogen balances together with an ¹⁵N isotope measurement campaign clearly show, that in a broad range of soils:

• a substantial amount of the historic fertilizer excess has accumulated in the soils
• historic fertilizations with ¹⁵N enriched fertilizer are still visible in the top soils after 40 years of agricultural landuse
• nitrogen residence times are independent of water transport times
• nitrate loss from soil organic matter pools is a major source of nitrate lost by seepage water

Our results clearly show, that substantial nitrogen legacies from fertilization excess can accumulate in a broad range of soil types. It becomes evident that considering and understanding the dynamics of this biochemical nitrogen legacy in agricultural soils is key to explain the lag of response in water quality observations in ground- and surface waters.

How to cite: Werisch, S. and Alexandra, T.: Nitrogen legacies in agricultural soils? Evidence from long-term lysimeter balances and isotope analyses, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21159, https://doi.org/10.5194/egusphere-egu26-21159, 2026.

Excessive emissions of greenhouse gases (GHGs), are driving uncontrolled planetary heating. This is already causing devastating consequences for our climate and to avoid the worst consequences of climate change, we mustn’t let global heating exceed 1.5°C.

Nitrous oxide (N₂O) is 265 times as powerful a GHG as CO₂ and persists in the atmosphere for 120 years, meaning today’s N₂O emissions will still be affecting the climate in five generations’ time. Given the ongoing trajectory of global GHG emissions, we already require negative emissions technology to limit global heating to 1.5ºC

Current understanding is that the only process that consumes N₂O in soils is complete denitrification, which occurs under extremely wet conditions when a proportion of N₂O produced is converted to nitrogen gas and returned to the atmosphere. New technologies, however, have provided data which suggest that there may be a previously unknown biological process which consumes N₂O in soils, under dry aerated conditions.

We will present initial data describing soils which have this capacity and discuss approaches to answer the following key questions: how N₂O uptake occurs in soils; who is responsible; why these organisms take up N₂O; where within the soil N₂O uptake occurs; when it occurs and under what conditions and; how much N₂O is drawn down.

How to cite: Keane, J. B., Ineson, P., Moir, J., and Hodson, M.: Investigating biological uptake of nitrous oxide (N2O)in soils, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-21533, https://doi.org/10.5194/egusphere-egu26-21533, 2026.

The pedogenic minerals in volcanic soils are predominantly composed of short-range order (SRO) aluminosilicates (e.g. allophane, imogolite) and Fe-hydr(oxides) (e.g. ferrihydrite), which influence the geochemical cycling of phosphorus (P). SRO minerals are metastable and can transform into more stable crystalline phases, a process influenced by environmental conditions like temperature and soil moisture. The present study aimed to analyze the variation in Fe and Al contents associated with SRO and their reactivity toward P across two soil toposequences with different soil moisture conditions on the Irazú Volcano, Costa Rica. Soil samples were collected from various horizons along an East-South (ES) toposequence (1734–2853 m.a.s.l.) with a consistently humid udic regime, and a West-South (WS) toposequence (1724–3178 m.a.s.l.) that transitions from a udic to a drier ustic regime when altitude decreases. Pedogenic forms of Fe, Al, and Si were operationally defined using ammonium oxalate (AO), dithionite-citrate (DC) and sodium pyrophosphate (Py) extractions. Phosphorus pools (P-Olsen, AO-extractable P (P_ox), total P) were also quantified. Phosphorus adsorption was evaluated using batch experiments, and data were interpreted using the Langmuir equation and the mechanistic Charge Distribution (CD) model to estimate P adsorption capacity (Q_max) and reactive surface area (RSA) of the soils. In the humid ES toposequence, AO-extractable Al (Al_ox) and (Fe_ox), Q_max and RSA, increased as altitude decreased. Those trends were attributed to the stable moisture along the altitudinal gradient and the increasing temperatures with decreasing altitude, favoring the formation and persistence of SRO minerals. In contrast, the WS toposequence showed no consistent trend with altitude, probably because the transition to ustic regime at lower altitudes promoted the transformation of SRO minerals into more crystalline phases. The P-Olsen/P_ox ratio was low (<10%) across all samples and significantly lower in the ES toposequence, suggesting that the persistence of SRO minerals under humid conditions severely constrains P availability. An independent dataset of samples (n = 88) from the same study region corroborated the above findings. The udic soils showed a strong negative correlation between altitude and Al_ox (r = -0.80), Fe_ox (r = -0.77), P_ox (r = -0.53), and total C (r = -0.64). In ustic soils, the relationships were not evident and only Fe_ox correlated with altitude (r = -0.63). The results show that soil moisture regime is a key factor regulating the persistence of highly reactive SRO minerals along altitudinal gradients. Thus, in humid regimes, persistent SRO minerals increase the capacity of soils to retain P and stabilize organic C, resulting in direct implications for P availability and cycling in these tropical volcanic landscapes.

How to cite: Mendez, J. C., Solano-Solano, C., Camacho-Umaña, M. E., Solano-Arguedas, A. F., and Kaune, A.: Moisture-driven controls on the stability of short-range order minerals and phosphorus cycling in tropical volcanic soils, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-204, https://doi.org/10.5194/egusphere-egu26-204, 2026.

Phosphorus (P) bioavailability is crucial for the productivity of natural and agricultural ecosystems, and soil P speciation plays a major role therein. Better understanding of P forms present in soil is thus essential to predict bioavailability. However, P speciation studies are only as powerful as the reference spectra used to interpret them, and most studies rely on a limited set of reference spectra. Most studies on soil P forms differentiate between Ca-bound P (e.g. apatite), organic P, Fe-bound P, and Al-bound P. In our analysis of a Ca, Al, and P rich soil from the Kohala region of Hawaii, we identified the mineral crandallite, CaAl₃(PO₄)₂(OH)₅∙H₂O, a mineral previously not considered to play a significant role in soils. Crandallite was first identified with powder X-ray diffraction. Subsequently reference spectra were collected, and the presence of crandallite was confirmed using micro-focused P K-edge X-ray absorption near edge structure (XANES) spectroscopy, micro-infrared spectroscopy, and solid-state ³¹P nuclear magnetic resonance (NMR) spectroscopy. Crandallite XANES spectra were distinct from other common XANES spectra due to the presence of features in the post-edge region of the spectrum. Linear combination fitting of bulk P K-edge XANES spectra allowed the determination of the proportion of crandallite to the total P content, indicating that crandallite comprises up to half, possibly even more of the soil P in the samples. Crandallite is therefore an important and potentially overlooked component of soil P, which pedogenically forms in soils with high P, Al, and Ca contents, where it could play an important role in P bioavailability.

How to cite: Vogel, C., Helfenstein, J., Massay, M., Kretzschmar, R., Schade, U., Verel, R., Chadwick, O., and Frossard, E.: Spectroscopic analysis shows crandallite can be a major component of soil phosphorus, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-5410, https://doi.org/10.5194/egusphere-egu26-5410, 2026.

Long-term phosphorus (P) fertilization has resulted in substantial P accumulation in Taiwanese rice paddy soils, with concentrations reaching several thousand mg kg⁻¹. To assess the phytoavailability of this legacy P to rice, soil P speciation was characterized using X-ray absorption near-edge structure (XANES) spectroscopy and a sequential extraction procedure, and quantified P accumulation in rice as soil-to-plant translocation. Despite lower total and extractable P, acidic soils showed greater soil-to-root P translocation, whereas alkaline soils contained larger soil P pools but exhibited more constrained P translocation. Sequential extraction and XANES consistently indicated the coexistence of Ca-bound P (Ca–P) and Fe-bound P (Fe–P) across the pH range, including species not predicted to dominate from thermodynamic considerations. In acidic soils, the persistence of Ca–P suggests a potentially available pool that may supply P through gradual dissolution. In alkaline soils, abundant Fe–P implies retention within mineral phases that could remain chemically labile over long timescales. Overall, these findings highlight the need to account for soil P speciation when evaluating legacy P use and guiding fertilizer management, and the information is essential for developing strategies to sustain rice growth while reducing or eliminating P inputs.

How to cite: Huang, Z.-L. and Wang, S.-L.: Decoupling Phosphorus Pools and Plant Uptake: Chemical Speciation and Phytoavailability of Legacy P in Taiwanese Rice Paddies, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6111, https://doi.org/10.5194/egusphere-egu26-6111, 2026.

Phosphorus (P) is essential for marine life, but fungal roles in the marine P cycle remain unclear despite the increasing recognition on marine fungal biomass. Using size-fractionated (0.8-5, 5-20, 20-180, 180-2000 µm) metagenomes and metatranscriptomes from the global epipelagic ocean, we reveal size-dependent fungal P metabolism dominated by Ascomycota . Pyrimidine metabolism dominates in the 20–180 µm fraction, whereas functions diversify in other sizes. Fungi on the largest particles (180-2000 µm) exhibit pronounced P uptake via transporters but limited extracellular alkaline phosphatase expression relative to smaller fractions. Signal peptide analysis indicates alkaline phosphotase (APase) as the main extracellular APase on large particles, yet overall AP expression remains modest and size-dependent. Linking P metabolism with carbohydrate and protein pathways shows coupling of P metabolism and carbohydrate/protein metabolism, suggesting acquisition of bioavailable P during particle degradation. Considering the notable biomass of marine fungi, these patterns imply an overlooked P sink and a particle-associated transfer route for P to fungal cells.

How to cite: Guo, K. and Zhao, Z.: Ubiquitos and dynamic phosphorus cycle mediated by marine fungi, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6497, https://doi.org/10.5194/egusphere-egu26-6497, 2026.

Forests play a fundamental role in supporting global biodiversity, supplying key resources such as timber, paper, and energy, and acting as one of the largest terrestrial carbon sinks. Forest productivity, however, is constrained by several environmental factors, including the availability of carbon dioxide (CO2) and essential nutrients such as nitrogen (N), phosphorus (P), and potassium (K). Over the past decades, an increasing number of terrestrial ecosystem models (TEMs) have incorporated representations of nutrient cycles, most frequently considering N (Zaehle et al. 2009, Vuichard et al. 2019) more rarely P (Goll et al. 2012, 2017, Jiang et al. 2024) and K (CASTANEA model, see Cornut et al. 2022a, b).

Our study contributes to that effort by focusing on to the quantification and modelling of phosphorus (P) cycles, based on data and model simulations from Eucalyptus plantations in Brazil. As a starting point, we studied the fluxes of P between the soil (i.e., soil organic and inorganic P stocks) and the trees (i.e., aboveground biomass and P stocks). To do so, we used data from a P fertilization experiment conducted at the Itatinga experimental station (University of Sao Paulo) with various forms of P fertilizers. Using allometric relations and concentration measurements, we quantified the mass of phosphorus in each compartment of the trees (leaves, branches, trunk wood, bark and roots) during the entire rotation and compared it to the variation of P stock in the soil, measured in different chemical forms.

Results showed that, compared to control conditions (no fertilizer added), phosphorus fertilization increased the tree biomass production, the amount of P accumulated in plant tissues, as well as increasing the soil P stocks. However, the magnitude of these effects depended on the type of fertilizer used. Complexed humic phosphate, designed to enhance phosphorus bioavailability, produced the highest tree biomass and phosphorus mineralomass. In contrast, rock phosphate was most effective at increasing total soil phosphorus stocks. This outcome aligns with previous findings, as rock phosphate is less readily absorbed by plants than more soluble forms. Accounting for the spatial heterogeneity in soil P concentrations proved essential when computing the ecosystem P. In 5 out of 6 treatments we observed apparent P losses (i.e. unclosed P balance), which may reflect underestimation of deep root biomass and P pools in deeper soil layers. By contrast, in rock phosphate treatment, apparent P gains probably stemmed from overestimations of soil P related to uncertainties in the estimation of soil P spatial variability.

Given limitations in the data, we are currently considering incorporating a simplified representation of soil P in the CASTANEA model, representing only a small number of phosphorus compartments (organic vs. mineral form and availability to trees).

How to cite: Dubertrand, P., le Maire, G., da Cruz Rodrigues, A., de Moraes Gonçalves, J. L., Cornut, I., and Delpierre, N.: Analysis of phosphorus stock variation in soil and biomass during an Eucalyptus rotation: a step towards modelling the phosphorus cycle, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-6796, https://doi.org/10.5194/egusphere-egu26-6796, 2026.

Soil organic phosphorus (SOP) can represent a large fraction of the total soil phosphorus pool, and its mineralization plays a key role in plant P supply. Phosphorylated organic compounds generally exhibit stronger adsorption to soil minerals than non-phosphorylated organic carbon, suggesting that SOP may cycle more slowly than bulk soil organic carbon (SOC). However, direct comparisons of SOP and SOC turnover times remain largely unknown due to methodological limitations.

Here, we investigated SOP turnover using soils from a 56-year chronosequence documenting the conversion of C₄ pasture to C₃ oil palm, thereby exploiting the natural δ¹³C contrast between vegetation types as an in situ tracer of carbon turnover. To specifically assess SOP dynamics, we applied a recently developed method to isolate SOP compounds from other soil organic compounds and quantified the δ¹³C signature of this SOP pool (Tian and Spohn, 2025). Turnover times of isolated SOP were then compared with those of bulk SOC across the chronosequence.

This study provides empirical data on SOP dynamics that are currently poorly represented in soil biogeochemical assessments and offers a transferable approach for disentangling phosphorus and carbon turnover in soils across ecosystems.

Reference

Tian, Y., & Spohn, M. (2025). A method to isolate soil organic phosphorus from other soil organic matter to determine its carbon isotope ratio. Soil Biology and Biochemistry, 210, 109911.

Acknowledgement

This research was funded by the European Research Council (ERC) (grant number 101043387).

How to cite: Tian, Y., Quezada, J. C., and Spohn, M.: Comparing turnover of soil organic phosphorus and bulk soil organic carbon in a 56-year oil palm chronosequence, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7061, https://doi.org/10.5194/egusphere-egu26-7061, 2026.

Soil organic matter (SOM) dynamics involve interactions between carbon (C) and phosphorus (P) cycling; while organic phosphorus (OP) constitutes only a small fraction of total SOM, its long-term turnover remains poorly constrained and may strongly influence nutrient availability and long-term biogeochemical cycling. While organic carbon (OC) turnover has been extensively studied using radiocarbon (¹⁴C), OP dynamics are commonly assumed to mirror those of OC, despite evidence that phosphorylated compounds interact more strongly with soil minerals and may persist longer than non-phosphorylated compounds. Here, we use bomb-derived ¹⁴C as a tracer to investigate multi-decadal OP turnover in agricultural soils based on a technique that allows us to isolate soil OP to measure its isotopic signature [1].

We analysed archived topsoil samples (0–20 cm) collected between 1957 and 2019 from a long-term field experiment, replicated at three sites in southern Sweden. This time series spans the period of atmospheric bomb ¹⁴C enrichment caused by thermonuclear weapons testing in the late 1950s, and subsequent decline, enabling thus direct comparison of C incorporation into OC and OP pools over more than five decades. Using a recently developed extraction–precipitation approach [1], we isolated soil organic phosphorus (TPOP) and measured its Δ¹⁴C signature alongside the Δ¹⁴C signature of soil total OC.

At the beginning of the observation period, the Δ¹⁴C values of bulk soil organic carbon (TOC) were consistently lower than those of the total precipitated organic phosphorus (TPOP) fraction across all sites. Over time, Δ¹⁴C of bulk TOC increased, reflecting incorporation of bomb-derived radiocarbon, and subsequently declined following the decrease in atmospheric Δ¹⁴C. In contrast, Δ¹⁴C values of TPOP showed a slower, attenuated response compared to bulk TOC across the study period. This pattern indicates a slower incorporation of recently fixed carbon into the OP-associated pool relative to bulk soil organic carbon.

The attenuated Δ¹⁴C response of TPOP therefore suggests that OP-associated organic matter is preferentially stabilized within mineral-associated pools [2,3], leading to longer persistance compared to bulk soil organic carbon. Although TPOP accounted for only a small proportion of soil TOC (≤ 14%), its older radiocarbon signature indicates a distinct contribution to long-term SOM persistence.

Our results provide the first long-term, radiocarbon-based evidence that soil OP turns over more slowly than TOC, likely due to stronger mineral associations and reduced microbial accessibility. These findings support the view that carbon and phosphorus cycling in soils are partially decoupled at multi-decadal timescales, with OP turnover constrained not by pool size but by stabilization mechanisms.

References:

[1] Tian, Y., & Spohn, M. (2025). A method to isolate soil organic phosphorus from other soil organic matter to determine its carbon isotope ratio. Soil Biology and Biochemistry, 210, 109911.

[2] Kögel‐Knabner, I., Guggenberger, G., Kleber, M., Kandeler, E., Kalbitz, K., Scheu, S., Eusterhues, K., & Leinweber, P. (2008). Organo‐mineral associations in temperate soils: Integrating biology, mineralogy, and organic matter chemistry. Journal of Plant Nutrition and Soil Science, 171(1), 61-82.

[3] Spohn, M. (2020). Phosphorus and carbon in soil particle size fractions: A synthesis. Biogeochemistry, 147(3), 225-242.

Acknowledgement:

This research was funded by the European Research Council (ERC) (grant number 101043387).

How to cite: San Emeterio, L. M., Sierra, C. A., and Spohn, M.: Long-term soil organic phosphorus dynamics: evidence from 14C time series, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-7661, https://doi.org/10.5194/egusphere-egu26-7661, 2026.

Phosphorus (P) is essential for plant growth, but excessive accumulation in soils can pose environmental risks, particularly through losses into water bodies. However, despite large spatial variability in P concentration and availability, no nationwide map of soil P exists for Switzerland. Moreover, knowledge of the relative importance of management-related factors compared to soil chemical and pedoclimatic drivers on the distribution of total and available P remains limited.

This study aims to predict and explain the distribution of total and available P pools in Swiss topsoils. For this purpose, we combined machine-learning approaches (ML) using Random Forests with model interpretation based on Shapley values to identify the main drivers controlling the P distribution. As model input, we used total P data measured at 960 sites of the Geochemical Soil Atlas of Switzerland in combination with predictor variables representing land use, soil properties, as well as environmental and geological conditions. To further investigate P dynamics in agricultural soils, we integrated a dataset from the Swiss Proof of Ecological Performance (PEP) subsidy scheme, which comprises 14 years of soil analyses since 2010. Available P pools were operationally defined using CO₂ saturated water extraction as a proxy for immediately plant available P, and ammonium acetate - EDTA extraction (AAE10) representing a larger pool of exchangeable soil P. This dataset includes approximately 150’000 observations, allowing differentiation between arable land and grassland.

As expected, total P concentrations are significantly higher in arable land and in pastures/grasslands compared with forests and alpine areas. Accordingly, interpretable ML measures, including Shapley values, indicate that land use is the most important predictor, followed by the presence of nutrients such as nitrogen (N), potassium (K), and sulfur (S). In contrast, soil chemical properties (e.g. pH, soil organic carbon) and proxies for pedoclimatic conditions, such as temperature or lithology, are less important for the prediction on a national scale.

Across Switzerland, the lowest available P concentrations are observed in north-western and southern regions, whereas the highest concentrations were measured along the Swiss Plateau and in central and north-eastern Switzerland. While P concentrations extracted with CO₂ saturated water are similar between arable crops and grassland, arable soils exhibit systematically higher AAE10 extractable P. Further work will focus on identifying the main drivers of available P pools and their temporal changes across Switzerland, including data from remote sensing and other monitoring programmes.

By combining spatially resolved geochemical data, interpretable machine learning approaches, and long-term agricultural monitoring data, this study provides a framework for identifying key drivers of the distribution of P pools in Swiss soils, thereby supporting targeted and sustainable nutrient management strategies.

How to cite: Reusser, J. E., Gilgen, A., Schneuwly, J., Baumgartner, S., Aasen, H., Bürge, D., and Hirte, J.: Disentangling the drivers of total and available phosphorus distributions in Swiss soils, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-9236, https://doi.org/10.5194/egusphere-egu26-9236, 2026.

Organic phosphorus (Po) plays a critical role in soil phosphorus (P) cycling, yet the behavior and fate of specific Po species remain poorly understood. In this study, ion chromatography coupled with inductively coupled plasma mass spectrometry (IC-ICP-MS) was employed to characterize NaOH-extractable Po species in two soil types, with a focus on their temporal dynamics and responses to soil degradation. Nine distinct phosphorus peaks were identified in soil extracts, of which four remain unidentified. Based on their occurrence patterns and sensitivity to environmental change, these Po species were classified into three groups: unstable species, detected only in fresh plant or algal materials; stable species, consistently present across all samples with minimal variation; and indicator species, exhibiting moderate sensitivity to environmental conditions. Notably, the indicator species α-glycerophosphate (α-gly) and an unidentified compound (P150) showed pronounced declines during degradation. Along a grassland degradation gradient, P150 concentrations decreased by 66% in highly degraded soils compared with non-degraded soils, while α-gly declined by 27%. In addition, IC-ICP-MS revealed a tenfold discrepancy between conventional colorimetric and direct Po measurements, indicating the dominance of recalcitrant macromolecular Po fractions in soils. These results provide new insights into the molecular-level dynamics of soil Po and highlight the importance of small-molecular Po species in sustaining soil fertility and ecosystem resilience.

How to cite: Wang, Y. and Chen, Z.: Characterization and Dynamics of NaOH-Extractable Organic Phosphorus Species in Soils, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-10267, https://doi.org/10.5194/egusphere-egu26-10267, 2026.

Phosphorus (P) availability has regulated terrestrial productivity over geological time, leaving a persistent imprint on ecosystem structure, biodiversity, and function. In tropical forests, strong soil P gradients are overcome by fine-tuned P use and acquisition strategies, enabling forests to maintain high productivity despite large differences in soil P supply. Rising atmospheric CO₂ increases biological P demand, making P constraints a central factor for tropical forest carbon sink capacity and a major source of uncertainty in future model projections. Climate change and human disturbances further disrupt plant–soil–microbial interactions and reconfigure P losses and recycling, raising questions about forest functioning and vulnerability.

I synthesize current understanding of tropical forest functioning across soil P gradients, focusing on the co-evolution of soil P pools, vegetation P acquisition strategies, and consequences for the forest carbon (C) cycle. Evidence on P acquisition spans “foraging” strategies in relatively P-rich systems to “mining” of less accessible P forms in highly weathered soils.

Building on this framework, I present model results showing that internal recycling of organic P pools plays a critical role in shaping carbon sink capacity and vulnerability under rising CO₂. Simulations with a terrestrial biosphere model across the Amazon reveal that CO₂ fertilization effects depend not only on background soil P, but also on the capacity of forest ecosystems to enhance enzyme-driven acquisition of rapidly recycled organic P, intensifying internal P recycling. This strategy occupies an intermediate position between foraging and mining, relying on carbon investment to increase turnover of actively cycling P. Such recycling may support short-term forest functioning while increasing sensitivity to P disruption and loss under global change.

Finally, I highlight how an upcoming CO₂ enrichment experiment in the Amazon will provide a unique opportunity to directly test these mechanisms and provide empirical constraints on how internal phosphorus recycling shapes tropical forest carbon sink capacity and vulnerability under global change.

How to cite: Fleischer, K.: Tropical Forests on a Phosphorus Loop: Internal Recycling Regulates Carbon Sink Capacity and Vulnerability under Global Change, EGU General Assembly 2026, Vienna, Austria, 3–8 May 2026, EGU26-12109, https://doi.org/10.5194/egusphere-egu26-12109, 2026.