This session brings together studies that improve understanding and quantification of budgets, trends, variability and drivers of major GHGs (CO₂, CH₄ and N₂O) across land, ocean and atmosphere, while also advancing the inventory and Monitoring Reporting Verification (MRV) foundations needed for robust reporting, such as baseline definition, refinement of emission factors, uncertainty quantification, and scaling from site-level observations to national estimates.
Contributions across land, ocean and atmosphere are welcome, including land-use and forest-focused work where baselines and emission factors substantially influence national GHG accounts. We welcome diverse approaches, including (national) emissions inventories, field and remotely sensed observations, terrestrial and ocean biogeochemical modelling, Earth system modelling, atmospheric inverse modelling, and data-model integration. We encourage contributions integrating different datasets and approaches that provide new insights on processes influencing GHG budgets and trends across temporal scales, particularly where implications for reporting and policy are in focus.
Orals: Mon, 4 May, 08:30–12:30 | Room N1
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.
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.
The western South Atlantic Ocean is an important sink of anthropogenic carbon dioxide (Cant), whose deepest layers are influenced by Antarctic Bottom Water (AABW) formed at high latitudes, while also receives Cant transported by the Atlantic Meridional Overturning Circulation (AMOC) towards the Southern Ocean. The mismatch between observation and model-based estimations is a long-standing issue in the current global carbon budget but regional assessments of interior ocean Cant inventories are still limited. Recent analyses have shown that Global Ocean Biogeochemical Models (GOBMs) predictions underestimate the rates of increase of Cant in the western South Atlantic, especially in the Brazilian Basin. We contrast full-depth Cant inventories based on observations (Global Ocean Data Analysis Project, GLODAPv2.2023) against state-of-the-art GOBMs (RECCAP2) and Ocean Circulation Inverse model (OCIM) outputs. Here, we show that most the observation-based approaches, either methods that use transient tracers’ data (TRACE) or marine-carbonate-system data (Φ-method, eMLR(C*)), yield higher Cant inventories—by up to 50%—than the mean outputs from GOBMs and OCIM. The annual trend in the storage of Cant per unit area is higher in observation-based approaches (1.08 ± 0.12 mol m-2 year-1 for Φ-method, 1.18 ± 0.06 mol m-2 year-1 for eMLR(C*) and 0.66 ± 0.03 mol m-2 year-1 for TRACE) than the mean outputs from GOBMS and OCIM (0.55 ± 0.01 mol m-2 year-1). We identify the inaccurate characterization of AABW Cant concentration and extent as the main reason of disagreement. Furthermore, a limited advection of Cant from the North Atlantic to the South Atlantic by the AMOC also affects intermediate layers. This study confirms that GOBMs systematically underestimate Cant inventory in the western South Atlantic and reaffirm that high-quality deep ocean carbon observations are a requirement to avoid overlook the contribution of AABW to the global budget.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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 (ELUC), while enhancing land-based carbon sinks. In this context, realistic estimates of ELUC 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, ELUC 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 ELUC 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 ELUC is more than 30% smaller in Canada and ~10% smaller in Europe, China and Oceania. In contrast, net ELUC 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 ELUC are small. As tropical regions contribute most to global net ELUC, 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 ELUC estimates. However, as regional and even national carbon budgets gain importance, our improved approach provides a more realistic basis for estimating ELUC. 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.
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.
The Paris Agreement encourages member states to keep global warming below 2.0C, and more ambitiously, limit warming to 1.5C. Recent coupled Earth system model simulations adaptively adjusted emissions to reach these stabilization temperatures show that fossil fuel CO2 reductions cannot reach the goals of the Paris Agreement alone. Building upon this framework, we show how varying the relative contribution of cumulative sustained methane emissions reductions is independent of pathway and modifies the allowable emissions from fossil fuels to reach 1.5C, 2.0C, and 3.0C of warming. Our results show that methane emissions reductions can have a large impact on the allowable emissions budget, and with mitigation goals >75% methane emissions reductions combined with rapid decarbonization, may reach the Paris Agreement goals.
Despite much shorter atmospheric perturbation lifetimes of methane compared to CO2, we find a surprisingly linear relationship of the climate impacts of a one-time release of CO2 versus the cumulative impact of sustained reduction in methane emissions at 2663.1 kgCO2/kgCH4/yr. The 5000-year timescale of atmospheric CO2 removal by ocean sediments translates into a methane emission equivalency of 0.53x CO2, much smaller than the currently proposed emissions trading 1 system value of 25x and the Global Warming Potential approach 100-year horizon of 27.8x. Thus, methane emissions must be treated as a sustained reduction versus an instantaneous reduction like CO2, and should be part of the most urgent decarbonization towards the Paris goals, while the concept of a market exchange value between methane and fossil fuel CO2 must be viewed critically. While acknowledging the indefinite commitment of rapid methane emissions mitigation, this combined with rapid decarbonization may help to prevent an overshoot of Paris Agreement temperature goals.
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.
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.
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.
Since the industrial revolution, the ocean has absorbed nearly one third of anthropogenic carbon dioxide (Cant), playing a key role in climate regulation while marine systems simultaneously undergo substantial stress. The storage of Cant in the ocean is spatially heterogeneous, making its quantification both challenging and essential. Because Cant 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 Cant 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. Cant 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.
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.
Posters virtual: Tue, 5 May, 14:00–18:00 | vPoster spot 2
EGU26-3062 | ECS | Posters virtual | VPS5
Synthesis of greenhouse gas emission factors for forest organic soils in the Dfb zone of the Köppen–Geiger climate classificationTue, 05 May, 14:00–14:03 (CEST) vPoster spot 2
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.
