This session aims to bring together studies that seek to quantify past, present, and future global and regional budgets, trends and variability of major GHGs, as well as studies that contribute to understanding the key drivers and processes controlling their variations. We welcome contributions using a variety of approaches, such as emissions inventories, field and remotely sensed observations, terrestrial and ocean biogeochemical modeling, earth system modeling, and atmospheric inverse modeling. We encourage contributions integrating different datasets and approaches at multiple spatial (regional to global) and temporal scales (from past over the present and to the future) that provide new insights on processes influencing GHG budgets and trends in the past and future.
Scenarios to keep global warming below 2°C include significant decreases in short lived atmospheric methane to allow time for the much longer-lived atmospheric CO2 to decrease more slowly. A methane decrease during the 2020s decade has been built into SSP scenarios and the need for this is reinforced by recent studies [Reisinger, 2024; Shindell et al., 2024]. In reality, the atmospheric methane burden has been growing very rapidly since 2006.
Atmospheric methane destruction is predominantly through oxidation by hydroxyl (OH). There is now evidence that since 1997, OH has been increasing in the Southern Hemisphere [Morgenstern et al., 2025]. This is based on 30 years of data for cosmic-ray produced 14C in atmospheric carbon monoxide (CO). Although most atmospheric chemistry models expect an increase in OH, the observed Southern Hemisphere increase of about +5% per decade is significantly greater than expected. Unfortunately, 14CO data in the Northern Hemisphere are insufficient to compare with models there.
The increase in methane removal rate inferred from the 14CO data means that methane sources are larger than prior estimates based on an almost-constant removal rate. If so, this new finding reduces a long standing discrepancy between “top-down” estimates of methane emissions from wetlands and consistently larger “bottom-up” estimates [Saunois et al., 2024].
While the increasing availability of satellite data is leading to better determination of methane’s source distribution, it is also necessary to differentiate between fossil fuel and biogenic sources. The positive trend of atmospheric δ13CCH4 for two centuries prior to 2006 reflected methane emissions from fossil fuel sources, but the strongly negative trend in δ13CCH4 since 2006 is primarily driven by biogenic sources such as wetlands and agriculture [Michel et al., 2024]. The magnitude of the source increase, particularly when the OH increase is taken into account, implies strong growth in wetland emissions, especially from northern tropical Africa.
More recent δ13CCH4 data for 2023 have shown flattening of its post-2006 trend at many Northern Hemisphere sites. While something similar was seen in 2012 this apparent shift in methane sources now appears more pronounced.
Given the urgency of reducing atmospheric methane to keep to the 2°C target, the recent changes in δ13CCH4 show atmospheric methane is in a very dynamic period of change. Future changes in the global methane budget may be less predictable than is currently assumed.
References:
Michel, S.E., Lan, X., Miller, J., et al, 2024: Rapid shift in methane carbon isotopes suggests microbial emissions drove record high atmospheric methane growth in 2020–2022. Proceedings of the National Academy of Sciences - PNAS, 121(44), e2411212121.
Morgenstern, O., Moss, R., Manning, M., et al, 2025: Radiocarbon monoxide indicates increasing atmospheric oxidizing capacity. Nature Communications, 16, 249.
Reisinger, A., 2024: Why addressing methane emissions is a non-negotiable part of effective climate policy. Frontiers in Science, 2, 5.
Saunois, M., et al., 2024: Global Methane Budget 2000-2020. Earth System Science Data, https://doi.org/10.5194/essd-2024-115 Discussion started: 6 June 2024, 147.
Shindell, D., Sadavarte, P., Aben, I., et al , 2024: The methane imperative. Frontiers in Science, 2, 1349770.
How to cite: Manning, M., Lan, X. (., Michel, S., and Nisbet, E.: New advances and new questions for atmospheric methane, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7918, https://doi.org/10.5194/egusphere-egu25-7918, 2025.
Indonesia is currently one of the three largest contributors of carbon emissions from land use and land cover change (LULCC) globally, together with Brazil and the Democratic Republic of the Congo. However, until recently, there was only limited reliable data available on LULCC across Indonesia, leading to a lack of agreement on drivers, magnitude, and trends in carbon emissions between different estimates. Accurate LULCC should improve robustness and reduce the uncertainties of carbon dioxide (CO2) emissions from Land Use Change (ELUC) estimation. Here, we assess several cropland datasets that are used to estimate ELUC in Dynamic Global Vegetation Models (DGVMs) and Bookkeeping models (BKMs). Available cropland datasets are generally categorized as either census-based such as the Food and Agricultural Organization (FAO) annual statistical dataset, or satellite-based such as the Mapbiomas dataset, which is derived from Landsat Satellite images. Our results show that census-based and satellite-based estimates have little agreement on temporal variability and cropland area changes. In some islands, they show spatial similarity, but differences appear in the main islands such as Kalimantan, Sumatra and Java. These differences lead to spatio-temporal uncertainty in carbon emissions. The different land cover forcings (census-based vs satellite-based) in a single model (JULES-ES) result in ELUC uncertainties of about 0.08 [0.06 to 0.11] PgC/yr. Furthermore, we found that uncertainties in ELUC estimates are also due to differences in the carbon cycle models in DGVMs, as DGVMs driven by the same land cover dataset show differences in ELUC estimates of 0.12 ± 0.02 PgC/yr with 95% confidence level and range [-0.04 to 0.35] PgC/yr. This is consistent with other product such as BKMs that estimates 0.14 [0.12 to 0.15] PgC/yr with both steady trend. We also compare emissions with those from the National Greenhouse Gas Inventory (NGHGI) product. The NGHGI estimates (based on BUR3; periodic official government report on Greenhouses Gas to UNFCCC) have much lower carbon emissions (0.06 ± 0.06 PgC/yr), though with an increasing trend. These numbers double when we include emissions from peat fire and peat drainage: the DGVM ensemble indicates emissions of 0.23 ± 0.05 PgC/yr and BKMs indicate emissions of 0.24 [0.22-0.25] PgC/yr. In contrast, emissions based on the Indonesian NGHGI remain much lower (BUR2: 0.18±0.07 PgC/yr BUR3: 0.13 ± 0.10 PgC/yr). Furthermore, emission peaks occur in year of moderate-to-strong El Nino events. Several improvements might reduce uncertainties in carbon emissions from LULCC in Indonesia, such as: combination of satellite-based dataset with census-based dataset, inclusion of peat-related emissions in DGVMs and potentially explicit inclusion of palm oil in the models as this is a major crop in Indonesia. Overall, the analysis shows that carbon emissions have no decreasing trend in Indonesia, Therefore, deforestation and forest fire prevention remain vital for Indonesia.
How to cite: Brasika, I. B. M., Friedlingstein, P., Sitch, S., O'Sullivan, M., Duran-Rojas, M. C., Rosan, T. M., Goldewijk, K. K., Pongratz, J., Schwingshackl, C., Chini, L., and Hurtt, G.: Uncertainties in carbon emissions from land use and land cover change in Indonesia, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-267, https://doi.org/10.5194/egusphere-egu25-267, 2025.
Freeze-thaw periods contribute disproportionately to annual N₂O emissionsrepresenting a critical yet understudied component of its global budget. Understanding drivers of these hot moments and their sensitivity to climate change is essential, but their episodic nature and great spatiotemporal variability pose substantial challenges. Combining cross-ecoregion soil core incubations with in-situ automated measurements, we explored snow regime shift effects on N2O emissions. Our findings revealed ~50-day pulse emissions during freeze-thaw periods, accounting for over 50% of annual fluxes, increasing nonlinearly with snow depth. Emissions were regulated by water-filled pore space (WFPS) thresholds: below 43%, soil moisture dominated; at 43%–66%, moisture and microbial attributes jointly triggered emissions; above 66%, microbial attributes, particularly N enzyme kinetics, prevailed. Hotspots of freeze-thaw-induced emissions were linked to high root production and microbial activity in cold, humid grasslands. This hierarchical control of WFPS and microbial processes provides a framework for predicting the location and magnitude of freeze-thaw-induced N₂O pulses, improving N₂O accounting and informing mitigation strategies.
How to cite: Liu, L. and Luo, J.: Moisture-microbial interaction amplifies N2O emission hot moments under deepened snow in grasslands, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7905, https://doi.org/10.5194/egusphere-egu25-7905, 2025.
Methane (CH4) emissions from South America have been estimated to account for approximately 15% of global emissions over the past decade. While natural emissions are predominantly driven by wetlands, anthropogenic emissions include contributions from livestock and landfills. However, bottom-up estimates remain highly uncertain, particularly for wetland contributions. The top-down approach, based on atmospheric transport inverse modeling, offers a critical tool for enhancing the monitoring of regional CH4 emissions. Given the sparse network of in-situ measurements and limited aircraft campaigns in the region, satellite observations of total column methane mixing ratios (XCH4) provide a valuable source of observations for inverse modeling.
The TROPOspheric Monitoring Instrument (TROPOMI) aboard the Sentinel-5 Precursor (S5P) satellite, launched in 2017, provides XCH4 with global daily coverage and a relatively high (5.5×7 km²) horizontal resolution. Three different products are derived from the raw spectra measurements and are used in this study: the official product by SRON, the WFMD product by the University of Bremen and the BLENDED product by the University of Harvard. While widely used for detecting localized methane plumes linked to super-emitters, TROPOMI CH4 data also support regional and global flux inversions, enabling improved mapping of CH4 emissions. In 2019, TROPOMI provided over 4 million observations across South America, though with uneven spatial coverage, particularly limited over the tropical region due to cloud cover.
We assimilate the TROPOMI XCH4observations into regional atmospheric inversions of CH4 emissions over South America at a 0.2°×0.2° resolution, for 2019. The inversions are performed with the CHIMERE transport model coupled with the inverse modeling platform Community Inversion Framework (CIF). We first compare prior emission dataset, evaluating sector-specific uncertainties and spatial-temporal correlations within the background error covariance (B). The study then assesses system sensitivity to key input datasets and parametrization, including deep convection modeling, prior datasets and TROPOMI product selection, and optimization parameters. Additionally, the response of simulated XCH4 to sectoral contributions is analyzed. Particular focus is given over the tropical region and especially the Amazon basin, where extensive wetland emissions and low satellite observation coverage pose significant challenges. Finally, posterior CH4 emission budgets are presented at local, country, and regional scale, with detailed analysis of sectoral contributions from livestock, landfills, and wetlands, offering insights into the drivers of South America’s methane emissions.
How to cite: Sicsik-Paré, A., Pison, I., Fortems-Cheiney, A., Broquet, G., Potier, E., Martinez, A., Utreras-Diaz, F., and Berchet, A.: Tracking methane across South America: an inversion of TROPOMI satellite observations to quantify emissions and sectoral contributions, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11802, https://doi.org/10.5194/egusphere-egu25-11802, 2025.
Methane emissions from the aquatic environment exhibit distinct characteristics: while oceans, covering 70% of Earth’s surface, emit 9 Tg of methane annually, freshwater wetlands, which occupy only 2% of Earth’s surface, emit 150-200 Tg per year. This significant contrast raises important questions about the underlying mechanisms and potential strategies to mitigate methane emissions in these water systems. In this work, we explore the challenges and opportunities of methane mitigation in both freshwater and marine environments.
For freshwater wetlands, existing projections of future methane emissions usually neglect feedbacks associated with global biogeochemical cycles. Here, we employ data-driven approaches to estimate both current and future wetland emissions, considering the effects of changing meteorology and biogeochemical feedbacks arising from atmospheric sulfate deposition and CO2 fertilization. We show that, under low-CO2 scenarios (1.5 and 2°C warming pathways), the suppressive effect of sulfate deposition on wetland methane emissions largely diminishes by 2100 due to clean air policies, resulting in an additional emission increase of 7 ± 2 Tg a-1. This increase account for 35% and 22% of total wetland emission changes under 1.5 and 2°C warming pathways, a factor not yet considered by current Integrated Assessment Models.
For marine waters, we assess the methane emissions from mariculture’s aquatic environment at 10-km resolution globally, using measurements from research cruises and satellite-observed net primary productivity. Mariculture’s aquatic emission intensity is estimated to be 1–6 gCH4 per kg of carcass weight (CW), >95% lower than freshwater systems, due to suppressed microbial production in marine waters and inefficient ventilation to the atmosphere. The life-cycle assessment shows that mariculture’s carbon footprints are ~40% lower than those of freshwater aquaculture, suggesting considerable climate benefits of mariculture expansion to meet future protein needs.
How to cite: Shen, L., Zhuang, M., Peng, S., Gauci, V., Wei, W., Wu, L., and MacLeod, M.: Challenges and opportunities in atmospheric methane mitigation from freshwater and marine environments, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14801, https://doi.org/10.5194/egusphere-egu25-14801, 2025.
Reaching the Paris Agreement temperature goals of no higher than +1.5°C or +2.0°C of global mean temperature change is quickly becoming difficult to reach by the end of the century. Not making the Paris Agreement temperature targets will impact all aspects of human society.
Around 1/3rd of global mean surface temperature changes, is estimated to be caused by methane making it the second most powerful greenhouse gas released anthropogenically. Anthropogenic sources emit 349 Tg of methane per year and are responsible for more than 50% of global methane emissions. The main emitters are the energy sector (>36% of emissions) and agriculture (40%). Fortunately, methane is a short-lived greenhouse gas, and removal of anthropogenic emissions sources may dramatically change the global concentrations on decadal timescales.
In response to the unlikelihood that methane emissions will be attenuated sufficiently in the coming decade by production reductions, methane emission mitigation technologies are under development. However, these technologies are yet to be rolled out on an industrial scale. New methane mitigation technologies can reduce a 50 ppm emissions source at ~60% efficiency and require an air volume rate of 4.36e13 m3/yr to remove 1 Tg CH4 per year. The volume of air required to process low concentrations to make a substantive impact on total emissions is major roadblock to their implementation. For example, for CO2 capture—a related carbon mitigation method—many test technologies are constructing large independent ventilation facilities. However, novel methane emission mitigation technologies are currently being tested and evaluated in several countries. These new technologies may capture CH4 and/or convert CH4 to molecules with less radiative forcing potential.
Here, we propose using dairy cow barns as a viable pathway for methane emission mitigation by utilizing existing infrastructure while targeting a major source of agricultural methane. Currently, there are ~264 M dairy cows worldwide. In Europe, there are 23 M dairy cows, and ~33% are housed in barns annually. For example, 70% of Denmark’s and 90% of Italy’s dairy cows are housed annually. For the health and welfare of the animals, barns are ventilated to maintain comfortable temperature and humidities, as well as ventilate abhorrent gases, such as methane. Standards for ventilation require 400 m3/hr/cow (high heat situations require 2500 m3/hr/cow), which is 3.5e6 m3/cow annually. A dairy cow emits between 55-100 kg CH4 per year. Which translates to 0.4-0.9 Tg CH4 per year for the ~7.59 M housed dairy cows in the European Union. The amount of air estimated to move through the EU dairy barns is 2.66e13 m3/yr and is within the estimated amount of air required to remove 1 Tg of CH4 from emerging technologies (4.36e13 m3/yr). Implementation of this type of methane mitigation is feasible and with additional air recycling, potentially capture methane emissions from dairy cow barns.
How to cite: Buzan, J., Terhaar, J., Joos, F., Iversen, N., and Roslev, P.: Mitigation and implications of methane emissions from dairy cow barns, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15780, https://doi.org/10.5194/egusphere-egu25-15780, 2025.
Tropical South America plays a critical role in the global carbon cycle. On one hand, the Amazon stores large stocks of carbon (150-200 PgC), representing 50% of the tropical rainforest biomass. On the other hand, the semiarid biomes of the neighbouring Cerrado and the Caatinga contribute largely to the inter-annual variability of the global land carbon sink. Both biomes are experiencing large threats due to deforestation, forest degradation, agricultural expansion and climate variability. While these threats in the Amazon have been largely studied, vegetation loss and associated carbon emissions from the Cerrado and Caatinga biomes have been somewhat overlooked. As a result, the mean and long-term trend in net carbon exchange in both biomes remains largely unknown. In this talk, I will give an overview of recent estimates in net carbon exchange and their uncertainty range for the Amazon and the Cerrado and Caatinga biomes. I will particularly focus on the development of the 2023/2024 drought and the carbon cycle response in the region. For this we leverage multiple data streams, from bottom-up models and top-down inversion systems, to remotely-sensed vegetation dynamics and in-situ flux and atmospheric measurements. I finalize highlighting the spatial heterogeneity of carbon fluxes across the region and emphasize on the remaining challenges to reduce the uncertainty in carbon cycle estimates and the need for enhanced atmospheric monitoring networks to improve our understanding of biome-specific drivers of net carbon exchange.
How to cite: Botía, S. and the Amazon drought 2023 team: Net carbon exchange in the Amazon, Cerrado, and Caatinga: Challenges and Insights from the 2023/2024 Drought, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14074, https://doi.org/10.5194/egusphere-egu25-14074, 2025.
Vegetation acts as an essential land-based carbon sink, which can be affected by military conflicts and wars through landscape fires that can cover large territories and will lead to additional greenhouse gas (GHG) emissions into the atmosphere. To investigate this impact, we spatially analyzed the effect of the ongoing Russo–Ukrainian War on the GHG emissions from landscape fires and determined the change to the carbon sequestration capacity of the forests. Using remotely sensed data from 2022–2023, we first identified the fire perimeters in the territory of Ukraine. We then classified the burned areas into coniferous and deciduous forests, croplands, and other landscapes, and evaluated the distribution of the fires according to their intensity based on the differenced normalized burn ratio. We used several fire weather condition indices and calculated the attribution factor to identify the share of fires that were war related and were thus not caused by natural factors or human activity that would be typical in times of peace. We estimated the war-related biomass losses during the first two years of the war, considering the landcover type, the species and the age structure of the forest stands, the fire intensity, and the biomass content. The corresponding GHG emissions in the immediate term were estimated to be 9.08 Mt carbon dioxide equivalent (CO2e), with a relative uncertainty of ±46% (95% confidence interval). The estimated future (long-term) biomass losses due to current forest fires and their corresponding GHG emissions were calculated to be 16.86 Mt CO2e (±21%). Finally, losses in the carbon sequestration capacity of the burned forests during the first five years following the landscape fires were estimated to be 2.9 Mt CO2e.
How to cite: Vasylyshyn, R., Bun, R., Myroniuk, V., de Klerk, L., Soshenskyi, O., Zibtsev, S., Krakovska, S., See, L., Shlapak, M., Blyshchyk, V., Kryshtop, L., Romanchuk, Z., Yashchun, O., Kalchuk, E., and Rymarenko, Y.: Quantifying greenhouse gas emissions from landscape fires due to the Russo–Ukrainian War and the impact on the carbon sequestration capacity of forests, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9043, https://doi.org/10.5194/egusphere-egu25-9043, 2025.
Monitoring ecosystem carbon dioxide (CO2) exchange is crucial for assessing the impacts of climate extremes and constructing carbon budgets to inform land management and enforce international climate treaties. To this end, we present here gridded hourly ecosystem CO2 fluxes upscaled from eddy covariance observations at 0.1° × 0.1° resolution and updated at low latency. Sentinel-2 indices are used to drive a modified Vegetation Photosynthesis Respiration Model (VPRM) following Bazzi et al. (2024) with a restructured Ecosystem Respiration equation and explicit soil moisture stress functions. VPRM parameters are optimized to half-hourly eddy covariance Net Ecosystem Exchange (NEE) and Gross Primary Production (GPP) datasets for each of 36 FLUXNET sites. Additionally we modify the temperature dependence of GPP by optimizing minimum and maximum temperatures as parameters and estimating optimum temperatures from mean annual temperature. We find these temperature modifications reduce RMSE for NEE and GPP respectively by 11% and 12% overall, 16% and 18% at evergreen needleleaf forests, 14% and 12% at grasslands, and 12% and 16% at mixed forests. Using site data on meteorology and vegetation, we train a random forest to produce mapped VPRM parameters representing the spatial heterogeneity in ecosystem characteristics. Gridded VPRM NEE estimates are presented based on both modeled parameter maps and multi-site optimizations by plant functional type, and upscaled products can be produced within hours of satellite data availability.
[1] Bazzi, H. et al. "Assimilating Sentinel-2 data in a modified vegetation photosynthesis and respiration model (VPRM) to improve the simulation of croplands CO2 fluxes in Europe." International Journal of Applied Earth Observation and Geoinformation 127 (2024): 103666.
How to cite: Briner, O., Bazzi, H., Ciais, P., and Santaren, D.: Upscaling near-real-time biospheric CO2 fluxes over Europe with a modified Vegetation Photosynthesis Respiration Model (VPRM), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6908, https://doi.org/10.5194/egusphere-egu25-6908, 2025.
The global methane pledge (GMP) aims to cut methane (CH4) emissions across all sectors by at least 30 percent below 2020 levels by 2030, which can thereby provide benefits in air quality and health, as well as in climate, relative to not cutting the emissions. We have used a fully coupled Earth system model (ESM) with interactive CH4 sources and sinks to study the future levels and trends of global atmospheric CH4 concentrations under different emission scenarios. Fully coupled simulations have been performed from 1995 to 2050, using multispecies emissions from the ECLIPSE V6b emissions database supplemented by new anthropogenic methane emissions estimates for Current Legislation (CLE), Maximum Feasible Reduction (MFR) and Global Methane Pledge (GMP) from IIASA/GAINS to simulate the future evolution of CH4 levels. In the baseline CLE scenario, global anthropogenic CH4 emissions increase from 298 Tg in year 2000 to 335 Tg in 2015, then continues to increase to 430 Tg in 2050 under CLE. Under MFR, anthropogenic CH4emissions first drop to 240 Tg in 2030, then slightly decrease to 220 Tg in 2050, while under the GMP scenario, they first drop to 300 Tg in 2030, then slightly increase to 320 Tg in 2050.
Preliminary results show that the interactive simulation slightly underestimates the observations on average by 2% between 1995-2022. All scenarios show an increase in the global CH4 concentrations, from 1.8 ppm in the present-day CH4 to 1.9 ppm (6%) in 2050 in the MFR scenario, 2.2 ppm (22%) in the CLE scenario, and 2.1 ppm (17%) in the GMP scenario. In addition, while anthropogenic CH4 emissions decrease, all simulations predict increasing wetland CH4emissions, by up to 10% in 2050 compared to 2020. Corresponding atmospheric CH4 lifetimes also increase in all simulations from 8.4 years in 2020 to lowest 8.5 years in CLE, 9.2 years in MFR, and 9.4 years in GMP. The increasing CH4 lifetime and concentrations in all scenarios despite reductions in emissions highlights that the response of concentrations are not necessarily linear with the changes in emissions as the chemistry is non-linear, and dependent on the oxidative capacity of the atmosphere due to other species such as CO and VOCs. In addition, missing sinks in ESMs such as halogens chlorine can lead to less chemical removal and longer lifetime compared to the box model.
We will further present the impact of these scenarios on the global surface temperatures and evaluate if the GMP will achieve its goal by 2050. However, preliminary results, compared with the recent 2021 AMAP SLCF assessment, suggest that despite the reduction in emissions, the atmospheric global CH4 levels simulated in the present study may not fulfil the larger goals of the GMP such as decreasing global CH4 concentrations and avoiding a 0.2°C warming by 2050 relative to 2020. However, reductions in emissions can still be achieved, which can lead to benefits in air quality and health. This work was accomplished through the Reduc(h4)e project funded by the Nordic Council of Ministers-and contributes to ongoing AMAP assessment work.
How to cite: Im, U., Tsigaridis, K., Bauer, S., Shindell, D., Olivié, D., Wilson, S., Sørensen, L. L., Langen, P., Eckhardt, S., Isaksson, L. H., Klimont, Z., and Bruhwiler, L.: Evolution of atmospheric methane under the global methane pledge: insights from an Earth system model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8281, https://doi.org/10.5194/egusphere-egu25-8281, 2025.
Atmospheric oxygen (O2) allows to separate the natural and anthropogenic components in the atmospheric CO2 signal, thereby providing additional constraints on these processes in the global carbon cycle. This is enabled through the ratio of O2 and CO2 in carbon cycle processes: the Exchange Ratio (ER). This ER signal has distinct values for combustion of different fossil fuel types, as well as between photosynthesis and respiration processes. Using these ER signals, we aim to further explore the potential of using atmospheric O2 observations in CO2 emission verification. For that, we are developing a global scale data assimilation system that can, next to CO2, assimilate O2 observations. This is our new multi-tracer implementation, specifically aimed at decadal and annual timescales: the CarbonTracker Europe Long Window system. Additionally, we implemented O2 and the O2/CO2 exchange ratios into the Simple Biosphere model (SiB4) to further understand the influence of biosphere exchange on using Atmospheric Potential Oxygen (APO) as a tracer for fossil fuel emissions. We will present the results from this biosphere O2 and CO2 modelling to get a first theoretical assessment of the variability of the biosphere O2 and CO2 ER signals, both over space (related to the plant functional types) and time (related to seasonal patterns). These biosphere model results, are subsequently used in our first attempt of atmospheric inverse estimates of CO2 fluxes using O2 as a tracer. Finally, we will show our progress towards understanding the implications of the variability in the ERs for photosynthesis and respiration on APO calculations, as well as their influence on fossil fuel estimates using atmospheric O2.
How to cite: Faassen, K., Hooghiem, J., van der Woude, A., van den Berg, A.-W., Hilman, B., Hulsman, L., Kaushik, A., de Kok, R., van de Sande, M., Peters, W., and Luijkx, I.: Using atmospheric O2 to disentangle the natural and anthropogenic CO2 signals , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16559, https://doi.org/10.5194/egusphere-egu25-16559, 2025.
As the oceans warm and acidify, the calcification of coral reefs declines, with net calcium carbonate dissolution projected even under moderate emissions scenarios. The impact of this on the global carbon cycle is however yet to be accounted for. We use a synthesis of the sensitivity of coral reef calcification to climate change, alongside reef distribution products to estimate alkalinity and dissolved inorganic carbon fluxes resulting from reductions in reef calcification. Using the global ocean biogeochemical model NEMO-PISCES, we simulate the impact of these fluxes on ocean carbon uptake under different emissions scenarios, accounting for uncertainty in present-day calcification rates.
Reductions in global coral reef carbonate production could enhance the ocean anthropogenic carbon sink by 0.34 PgC yr-1by mid-century (0.13 PgC yr-1 median estimate) with cumulative ocean carbon uptake up to 110 PgC greater by 2300 (46 PgC median estimate). Under medium to high emissions scenarios, two critical aspects emerge: (i) the full potential for coral reef degradation to affect carbon fluxes is reached within decades, and (ii) air-sea carbon fluxes remain substantial for centuries, due to the imbalance between carbon and alkalinity sinks/sources for the global ocean.
Accounting for the coral reef feedback into Earth system models could revise upward remaining carbon budget estimates, increasing the likelihood of achieving net-zero emissions without relying on negative emissions. The coral reef feedback could have a 21st-century impact comparable in magnitude to boreal forest dieback, though opposite in sign. This underscores a critical paradox: conserving calcifying organisms, such as coral reefs, may counteract a natural mechanism for mitigating climate change, but at the cost of protecting vital biodiversity. This challenges the "all-carbon" framework often used to address environmental issues, highlighting the complex trade-offs between carbon cycle regulation and biodiversity conservation.
How to cite: Planchat, A., Kwiatkowski, L., Pyolle, M., Laufkötter, C., and Bopp, L.: Declining coral calcification to enhance twenty-first century ocean carbon uptake by gigatons, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10326, https://doi.org/10.5194/egusphere-egu25-10326, 2025.
The global ocean uptake of anthropogenic CO2 is sensitive to the uptake in the Southern Ocean, which accounts for 40-50% of the total uptake. At the same time, the Southern Ocean is the windiest region on the planet and experiences storms all year round. These storms, in turn, play an important role for the CO2 uptake in the Southern Ocean, because they can trigger outgassing of CO2 to the atmosphere. Storms induce outgassing by stirring the mixed layer via wind forcing, which leads to entrainment of waters rich in dissolved inorganic carbon into the mixed layer and elevates ocean pCO2 at the air-sea interface. However, since storms occur on synoptic time scales, such outgassing events are highly localised and short lived. Recent work based on in-situ measurements suggests that the magnitude of storm-induced outgassing and its contribution to the total Southern Ocean CO2 air-sea flux may have been severely underestimated by previous modelling studies, which do not sufficiently resolve storms and outgassing events. In this study, we take advantage of a cutting-edge simulation conducted with a fully-coupled, global, atmosphere-ocean model (ICON) with ocean biogeochemistry. Running on the assumption that the smaller grid spacing of 5 km better resolves storms and variability in wind forcing, we analyse the simulated contribution of storm-induced outgassing to the Southern Ocean uptake of CO2.
How to cite: Kumar, A., Nielsen, D., Serra, N., Chegini, F., Jungclaus, J., and Ilyina, T.: The contribution of storm-induced outgassing to the CO2 air-sea flux in the Southern Ocean in a high-resolution, atmosphere-ocean simulation with ICON, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15314, https://doi.org/10.5194/egusphere-egu25-15314, 2025.
Global ocean biogeochemistry models are a key tool for estimating the global ocean carbon uptake. These models are designed to represent the most important processes of the ocean carbon cycle, but the idealized process representation, uncertainties in the initialization of model variables and in the atmospheric forcing lead to errors in their estimates. To improve the agreement with observations, we use ensemble-based data assimilation into the ocean biogeochemistry model FESOM2.1-REcoM3. In addition to the recently implemented assimilation of temperature and salinity observations, which improves the physical model state and indirectly influences biogeochemical variables, we extend the set-up further. Here, we explicitly include the assimilation of biogeochemical observations. Specifically, in-situ sea surface pCO2 measurements, remotely sensed chlorophyll-a, and in-situ measurements of dissolved inorganic carbon, alkalinity, oxygen, and nitrate, are assimilated to reduce the uncertainty stemming from the ecosystem model. This directly affects the modelled air-sea CO2 flux. Here, we present an updated estimate of the ocean carbon uptake for the period 2010–2020 and compare it to prior estimates.
How to cite: Bunsen, F., Nerger, L., and Hauck, J.: Assessing the recent ocean carbon sink with data assimilation into a global ocean biogeochemistry model, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-19322, https://doi.org/10.5194/egusphere-egu25-19322, 2025.
In 2023, sea-surface temperatures (SST) reached record highs. Historically, the years with highest global mean SST anomalies were associated with a slight increase in oceanic CO₂ uptake, primarily due to reduced CO2 outgassing from the tropics during El Niño. In contrast, our observation-based estimates reveal that the global non-polar ocean absorbed about 10% less carbon in 2023 than expected (+0.16±0.28 PgC yr-1).
This weakening of the ocean carbon sink occurred although the CO2 outgassing in the tropics was indeed as low as expected. Instead, the decline in CO2 uptake was concentrated entirely in the extratropics, driven largely by elevated SSTs in the Northern Hemisphere. While thermally induced reductions in CO2 uptake are well-documented in the extratropics, our analysis using two ocean biogeochemical models highlights a mitigating process in the subtropical North Atlantic: the depletion of dissolved inorganic carbon in the surface mixed layer. Such negative feedbacks caused an overall muted response of the ocean carbon sink to the record high SSTs, but this resilience may not persist under long-term warming or more severe SST extremes.
By the time of this presentation, we anticipate confirming – or refining – our expectation that the ocean carbon sink in 2024 remained unusually weak, because the CO2 outgassing from the tropics revived, whereas remaining high SSTs in the extratropics continued to suppress the CO2 uptake.
How to cite: Müller, J. D., Gruber, N., Schneuwly, A., Bakker, D. C. E., Gehlen, M., Gregor, L., Hauck, J., Landschützer, P., and McKinley, G. A.: The ocean carbon sink under record-high sea surfacetemperatures in 2023/24, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-21437, https://doi.org/10.5194/egusphere-egu25-21437, 2025.
The ocean is an important sink for anthropogenic carbon dioxide (CO2), but recent data from the Global Carbon Budget (GCB) highlight discrepancies in ocean carbon uptake estimates. Since the early 2000s, reconstructions of in-water CO2 fugacity (fCO2) using advanced interpolation techniques (data-products) have shown a growing divergence from estimates derived from global hindcast model simulations. This offsets in the mean flux amounts to approximately 0.49 GtC per year in the decade 2014-2023. The reasons for this discrepancy are not fully understood but may stem from a combination of factors including insufficient data coverage, uncertainties in scaling measurement-based estimates, and errors in model simulations. Previous studies suggests that biases in the fCO2 data-products from the under-sampled Southern Hemisphere, may contribute significantly to this gap.
To address these concerns, the Surface Ocean CO2 Mapping project has launched its second phase (SOCOMv2). This initiative aims to identify and quantify the accuracy and uncertainties related to data availability, changing observational networks, and input data. SOCOMv2 includes four key experiments: 1) a comprehensive geospatial uncertainty analysis, and three subsampling studies employing: 2) GCB hindcast simulations to capture true climate variability, 3) large ensemble simulations representing multiple climate states, and 4) idealized carbon uptake scenarios without climate variation. These efforts aim to provide a clearer understanding of the underlying factors contributing to the observed discrepancies in ocean carbon uptake estimates.
Results from the GCB subsampling hindcast simulation experiments reveal that individual fCO2 data-product reconstructions can significantly overestimate or underestimate both the annual mean and the trend of the ocean carbon sink relative to the models ‘truth’. Nonetheless, the ensemble mean of the fCO2 data-products tends to exhibit only a small overestimation of the model ‘truth’ ocean carbon sink. These discrepancies highlight the impact of limited data coverage and the inherent challenges of extrapolating from sparse measurements but cannot fully explain the observed divergence between models and fCO2 reconstructions in the GCB.
SOCOMv2 aims to improve the accuracy and precision of ocean carbon flux estimates, contributing to improved observational approaches and guiding policy development for climate mitigation. SOCOMv2 efforts have been driven by the community, with supporting funding within a larger European Space Agency ocean carbon study (Ocean Carbon for Climate).
How to cite: Roobaert, A., Ford, D. J., Rödenbeck, C., Gruber, N., Hauck, J., Fay, A. R., Heimdal, T. H., Behncke, J., Shaum, A., Luke, G., Watson, A., Djeutchouang, L. M., Mohanan, S., Gehlen, M., Jersild, A., Zeng, J., Iida, Y., Chevallier, F., McKinley, G. A., and Shutler, J. D. and the SOCOMv2 team: SOCOMv2: On the strengths and limits of pCO2 interpolations products to estimate the ocean carbon sink, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15370, https://doi.org/10.5194/egusphere-egu25-15370, 2025.
Sailboats expand the observational network of sea surface partial pressure of CO2 (pCO2), particularly in the undersampled Southern Ocean through regularly repeating circumnavigations, however, their added value to the fCO2-product based ocean sink estimate (Socean) has thus far not been quantified. Here, we show through an observing system simulation study with different sampling schemes how integrating sailboat data from different race tracks improves air-sea CO2 flux estimates.
We find that neural network reconstruction of the air-sea CO2 flux used within the Global Carbon Budget, when reconstructing a model that mimics present-day real-world sampling, underestimates the ocean carbon sink. This is consistent with recent studies on the interior accumulation of carbon. Increased and continuous sampling by sailboats reveals a stronger carbon sink and improves present-day estimates from 0.06 to -0.02 mol C m⁻² yr⁻¹ (0.99 μatm to -0.32 μatm for the fCO2 estimate), particularly in the Southern Ocean between 40°S and 60°S. The improvement in reconstructions persists even when data from three circumnavigation tracks contain artificial measurement biases. However, the additional data remains insufficient to correct the overestimated air-sea CO2 flux trend. While sailboat data has the potential to improve air-sea CO2 flux reconstructions, expanding the observational network and maintaining long-term time series is crucial to minimize discrepancies between fCO2-products and Global Ocean Biogeochemical Models.
How to cite: Behncke, J., Landschützer, P., Chegini, F., and Ilyina, T.: Improved air-sea CO2 flux estimates by adding sailboat measurements , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6427, https://doi.org/10.5194/egusphere-egu25-6427, 2025.
Ocean fronts are dynamic features that play a critical role in regulating marine ecosystems and influencing global carbon cycles. These regions, characterized by strong horizontal gradients in temperature, salinity, and other properties, enhance vertical mixing and advection, driving increased nutrient supply that supports elevated primary production. Despite their importance, the impacts of changing ocean fronts on the budget and trends of ocean CO2 uptake remain insufficiently understood. In this study, we perform a comprehensive global analysis of ocean fronts using 20 years of satellite observations (2003–2023), identifying key regions of intense frontal activity and areas undergoing rapid changes in frontal dynamics. Our results show that nearly 50% of global ocean CO2 uptake occurs in these key frontal areas, underscoring their disproportionate role in the ocean’s carbon sink. Furthermore, we observe that trends in sea surface chlorophyll concentration—a proxy for primary production—and ocean CO2 uptake are strongly correlated with local changes in frontal activity. Our findings provide critical insights into the role of ocean fronts as modulators of global biogeochemical processes and air-sea CO2 exchanges. By linking ocean fronts to changes in primary production and air-sea CO2 exchange, this study contributes to a more detailed understanding of how changing ocean dynamics may influence carbon cycles under future climate scenarios.
How to cite: Yang, K., Meyer, A., Strutton, P. G., and Fischer, A. M.: Global trends in ocean fronts: impacts on air-sea CO2 flux and chlorophyll concentrations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2215, https://doi.org/10.5194/egusphere-egu25-2215, 2025.
Tropical wetlands account for ∼20% of the global total methane (CH4) emissions, but uncertainties remain in emission estimation due to the inaccurate representation of wetland spatiotemporal variations. Based on the latest satellite observational inundation data, we constructed a model to map the long-term time series of wetland extents over the Sudd floodplain, which has recently been identified as an important source of wetland CH4 emissions. Our analysis reveals an annual, total wetland extent of 5.73 ± 2.05 × 104 km2 for 2003–2022, with a notable accelerated expansion rate of 1.19 × 104 km2 yr−1 during 2019–2022 driven by anomalous upstream precipitation patterns. We found that current wetland products generally report smaller wetland areas, resulting in a systematic underestimation of wetland CH4 emissions from the Sudd wetland. Our study highlights the pivotal role of comprehensively characterizing the seasonal and interannual dynamics of wetland extent to accurately estimate CH4 emissions from tropical floodplains.
How to cite: Dong, B., Peng, S., Liu, G., Pu, T., Gerlein‐Safdi, C., Prigent, C., and Lin, X.: Underestimation of Methane Emissions From the Sudd Wetland: Unraveling the Impact of Wetland Extent Dynamics, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2466, https://doi.org/10.5194/egusphere-egu25-2466, 2025.
The atmospheric carbon dioxide (CO2) concentration has been increasing rapidly since the Industrial Revolution, which has led to unequivocal global warming and crucial environmental change. It is extremely important to investigate the interactions among atmospheric CO2, the physical climate system, and the carbon cycle of the underlying surface for a better understanding of the Earth system. Earth system models are widely used to investigate these interactions via coupled carbon–climate simulations. The Chinese Academy of Sciences Earth System Model version 2 (CAS-ESM2.0) has successfully fixed a two-way coupling of atmospheric CO2 with the climate and carbon cycle on land and in the ocean. Using CAS-ESM2.0, we conducted a coupled carbon–climate simulation by following the CMIP6 proposal of a historical emissions-driven experiment. This paper examines the modeled CO2 by comparison with observed CO2 at the sites of Mauna Loa and Barrow, and the Greenhouse Gases Observing Satellite (GOSAT) CO2 product. The results showed that CAS-ESM2.0 agrees very well with observations in reproducing the increasing trend of annual CO2 during the period 1850–2014, and in capturing the seasonal cycle of CO2 at the two baseline sites, as well as over northern high latitudes. These agreements illustrate a good ability of CAS-ESM2.0 in simulating carbon–climate interactions, even though uncertainties remain in the processes involved. This paper reports an important stage of the development of CAS-ESM with the coupling of carbon and climate, which will provide significant scientific support for climate research and China’s goal of carbon neutrality.
How to cite: Zhu, J., He, J., Ji, D., Li, Y., Zhang, H., Zhang, M., Zeng, X., Fei, K., and Jin, J.: Coupled Simultion of Atmospheric CO2 in CAS-ESM, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7573, https://doi.org/10.5194/egusphere-egu25-7573, 2025.
Lakes, as a fundamental component of the Earth's surface system, play a crucial role in the carbon cycle, closely linked to climate change. However, understanding carbon flux in Qinghai-Tibet Plateau (QTP) lakes is restricted by environmental factors and limited observations, hindering insights into regional and global climate change. Continuous annual carbon dioxide (CO2) flux, encompassing ice-covered periods, has been monitored in the largest freshwater lake on the QTP. Utilizing continuous eddy system data, the characteristics and mechanisms influencing carbon flux at various temporal scales in this lake were investigated. Findings revealed Ngoring Lake as predominantly a carbon sink year-round, with two CO2 absorption peaks in spring and autumn, respectively. These peaks were associated with mixing state triggered by cooling processes. In spring, as temperatures rose above the lake water's maximum density temperature (3.98 ℃ for freshwater lake), subsequent rapid cooling and mixing occurred upon ice melt. In autumn, cooling and mixing were induced by decreasing air and water temperatures alongside strong winds. These cooling processes facilitated significant CO2 absorption. As the lake transitioned from stratification to mixing, lake mixing played a dominant role. Biochemical reactions driven by water temperature play a dominant role during stable stratification and complete mixing phases.
How to cite: Wang, M., Wen, L., Li, Z., Meng, X., and Su, D.: Characteristics of carbon sink and the influence factors in Ngoring Lake, Qinghai-Tibet Plateau, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7650, https://doi.org/10.5194/egusphere-egu25-7650, 2025.
The Terrestrial Ecosystem Research Network (TERN) OzFlux group operates a network of eddy covariance stations that collect long-term atmospheric and soil measurements for monitoring and understanding changes in climate and the environment. Ideally, all data collected would be gap-free, however, all real data has gaps where instruments have not recorded measurements or data has been discarded due to low turbulence. To allow this data to be used as a continuous time-series in further analysis, the missing data is gap-filled using PyFluxPro. The standard community approach uses a predefined set of variables (drivers) for gap-filling, which are the same variables for all stations irrespective of location. However, the stations are located in a large range of climate zones, hence the standard gap-filling drivers might not be ideal for all sites. This is because the drivers were chosen for a small set of initial sites and might not be representative for a heating and drying climate.
To identify which drivers were best suited for each station, we developed a random forest model to objectively assess the relative importance of input variables used to gap-fill ustar, carbon, and energy fluxes. We trained this model on the published TERN OzFlux data for all available Australian sites using a large range of input variables. This model then determined the relative importance of variables, mean absolute errors, and R2 for the accuracy of the model prediction for a target variable at each site. Next, we grouped the variables into atmospheric, energy, turbulence and soil categories of drivers, which highlighted a distinct variation in the contribution of each category of driver across sites. To assess the ecological significance of these trends, the model importances were sorted by the aridity index and grouped by the Köppen-Geiger classification of each site. There is a notable shift in the importance of energy, turbulence, and soil groups with decreasing aridity, and driver contributions were generally consistent within Köppen-Geiger classifications. Reprocessing the gap-filling of a representative subsample of sites demonstrated a marked improvement in predicting the gap-filled target variables, highlighting that this approach can inform driver selection at new and established sites and will improve the understanding of the ecological significance of different drivers in various climate regions.
How to cite: Lieff, N., Metzen, D., Ewenz, C., Isaac, P., McHugh, I., and Griebel, A.: Assessing the optimal drivers for flux data gap-filling using random forest networks, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-9368, https://doi.org/10.5194/egusphere-egu25-9368, 2025.
Methane (CH₄) emissions from the Tibetan Plateau, often referred to as the "Third Pole," are critical to understanding global methane dynamics due to the region's extensive wetland ecosystems and unique environmental characteristics. However, quantifying CH₄ fluxes in this region is challenging due to sparse observational data, complex topography, and highly variable climatic and hydrological conditions. This study introduces a high-resolution machine learning framework tailored for the Tibetan Plateau by integrating satellite-based observations, ground measurements, and modeled data. The framework incorporates a diverse set of environmental drivers, including temperature, soil moisture, vegetation indices, and hydrological factors. This approach aims to address spatial and temporal gaps in methane flux estimates while capturing the complex interactions governing CH₄ emissions in high-altitude mountainous ecosystems.
How to cite: Zhang, Z.: High-Resolution Wetland Methane Flux Modeling for the Tibetan Plateau Using Machine Learning, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10099, https://doi.org/10.5194/egusphere-egu25-10099, 2025.
Tropical wetlands are one of the largest natural methane sources but lack of in-situ observations and uncertainty in wetland extent leads to large uncertainly. In this study we analyze the methane budget from three major river basins in South America: the Orinoco, the Amazon, and the Pantanal basins using two atmospheric inversions: the CAMS-CH4inversion, which assimilates satellite and in-situ data and the CarboScope methane inversion system constrained by in-situ data only. We make a comparative analysis focusing on the seasonal cycle, interannual variability, and the total methane budget from 2000 to 2019.
The budget difference in posterior estimates between CAMS-CH4 and CarboScope for these basins are as follows: Amazon Basin: -18.03 TgCH4/yr, Pantanal Basin: -11.65 TgCH4/yr, Orinoco Basin: -0.96 TgCH4/yr. All together the total flux difference is -30.56 TgCH4/yr, indicating that CarboScope estimates larger total methane fluxes than the CAMS-CH4 inversion. Note that a similar difference (30.98 TgCH4/year) is also seen in the prior fluxes, suggesting that the optimization does not reduce the prior difference in the regions of interest. While the Amazon Basin emits largest amount of methane, the Orinoco Basin exhibits the highest emissions per unit area, with 21.2 mgCH4/m²/day. In comparison, Amazon and Pantanal basins have emission of 19.26 mgCH4/m²/day and 13.36 mgCH4/m²/day. This shows the significant contribution of the smallest basin, in terms of methane flux density. Not surprisingly, both models indicate that wetlands are the primary methane source in the Amazon and Orinoco basins (~80%). In the Pantanal, CAMS-CH4 shows equal contributions from wetlands and anthropogenic sources, whereas CarboScope attributes dominance to anthropogenic emissions. Interestingly, seasonal patterns differ between the two models. In CAMS-CH4 there is a strong seasonality, with maximum methane emissions occurring during the wet season across all basins, in CarboScope, there is a double-peak in the Amazon Basin during March (wet) and August (dry). Finally, we investigate the inundation patterns and their relationship to methane emissions trends in these basins, as well as the factors influencing interannual variability to enhance our understanding of the processes driving these emissions.
How to cite: Wagh, S., Basso, L., Fleischmann, A., Amaral, J., Melack, J., Asperen, H., Hantson, S., Schäfer, T., and Botia, S.: Methane budget, seasonality and interannual variability of the three major river basins in Tropical South America, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10374, https://doi.org/10.5194/egusphere-egu25-10374, 2025.
Recent studies highlight the critical role of methane emissions from tropical wetlands in driving the accelerated atmospheric CH4 growth rate observed in the last decade. The Amazon lowland region, where up to 30% of the area can be seasonally flooded, is one of the largest natural methane sources. The total methane flux estimates for the Amazon basin from top-down and bottom-up approaches converge at 31–46 TgCH₄/year. However, understanding methane emission trends and interannual variability—such as inundation extent and seasonality—requires improved attribution of emissions to specific wetland types and habitats. In this study, we present a refined bottom-up estimate of methane fluxes for the lowland Amazon that addresses key challenges to regionalizing fluxes in the basin: i) the large seasonal variation in inundated areas and habitats, ii) the diversity of aquatic ecosystems across the Amazon, and iii) the spatiotemporal variability of methane fluxes.
We link local methane flux measurements collected during more than 20 years of field campaigns to specific river and wetland types and incorporate seasonal variability in inundation extent using dynamic remote sensing products (i.e. open water data from the Global Surface Water for lakes, Global River Width from Landsat (GRWL) for rivers, and wetland inundation extent from the High-Resolution Surface WAterFraction (SWAF-HR, based on SMOS L-band imagery) for the Amazon basin, and (4) GIEMS-D15 (merge of multiple satellites) for the remaining portions of South America). Wetland types (herbaceous and woody vegetation) were obtained from the JERS-1 L-band based classification of Hess et al. (2015) for the Amazon Basin and ESA-CCI land cover for the rest of South America. The magnitude and seasonal variability of our bottom-up fluxes are evaluated against fluxes derived from atmospheric CH4 mole fraction measurements at two Amazonian sites, whose footprints go beyond the Amazon Basin. While our product successfully captures the seasonal variability at both sites, it underestimates the overall magnitude of emissions compared to other estimates, even when accounting for emissions from flooded forest tree stems. Our findings represent an important improvement of bottom-up estimates representing the diversity of wetland habitats and processes driving methane emissions, but further work is needed to understand the mismatch with other methane emissions products.
How to cite: Botía, S., Santos Fleischmann, A., Santamaria Basso, L., Wagh, S., Lavric, J., Al Bitar, A., and Melack, J.: Refining methane emission estimates in the Amazon basin: Addressing spatiotemporal variability and habitat diversity, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-12730, https://doi.org/10.5194/egusphere-egu25-12730, 2025.
The dynamics of dissolved inorganic carbon (DIC), stable carbon isotopes of DIC (δ13CDIC), and anthropogenic CO2 (CO2ant) in the upper 500 m of the water column were examined in two upwelling-favourable regions: the Sri Lankan Dome (SLD) and the central Bay of Bengal (BOB) in the Northern Indian Ocean over the period 1995 to 2016. This study aimed to investigate the spatiotemporal variability of these carbon parameters and assess the influence of CO2ant in these oceanic environments. Data from the GLODAPv2.2022 database, including cruise-based biogeochemical bottle measurements, were utilized to examine temporal trends in DIC and δ13CDIC. The TrOCA (Tracer combining Oxygen, Carbon, and Alkalinity) approach was employed to calculate CO2ant. Although DIC concentrations showed minimal variability across the water column in both the SLD and central BOB, significant fluctuations in CO2ant and δ13CDIC were observed in the upper 50 m in both regions between 1995 and 2016. Specifically, δ13CDIC values in the upper 50 m decreased by 0.45 ‰ (at a rate of 0.021 ‰ yr-1) in the SLD and by 0.41 ‰ (at a rate of 0.02 ‰ yr-1) in the central BOB over the study period. This decline is likely attributable to the combined effects of upwelling of remineralized DIC and increased CO2ant invasion in the upper 50 m of these oceanic regions, occurring at rates of 0.93 µmol kg-1 yr-1 in the SLD and 1.97 µmol kg-1 yr-1 in the central BOB. Additionally, a weaker correlation between δ13CDIC and CO2ant was observed in the central BOB, whereas a stronger correlation in the SLDsuggests that the invasion of isotopically lighter CO2ant contributed significantly to the observed depletion of δ¹³CDIC in both regions from 1995 to 2016. These findings underscore the significant role of anthropogenic CO2 in influencing carbon dynamics in the upper ocean of these upwelling-prone regions.
How to cite: Kaluthotage, P., Silva, A., Dheerasinghe, M., and Kokuhennadige, H.: Temporal variability in dissolved inorganic carbon, δ13CDIC, and anthropogenic CO2 in the North Indian Ocean from 1995 to 2016: assessing the influence of anthropogenic CO2, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14051, https://doi.org/10.5194/egusphere-egu25-14051, 2025.
The global ocean plays a critical role in mitigating climate change by sequestering atmospheric CO2, removing approximately 26% of anthropogenic carbon emissions since the Industrial Revolution. While significant progress has been made in estimating open-ocean anthropogenic carbon (Canthro), the coastal ocean remains less understood due to its dynamic nature and complex processes and shortage of long-term high-quality datasets. Hence it is challenging to quantify the coastal anthropogenic carbon from the observation data. In this study, we propose a regional empirical regression-based anthropogenic carbon estimation approach (RECA) tailored for coastal regions. Using synthetic data from six different global ocean biogeochemical models, we evaluate the uncertainties in Canthro estimation and assess the contributions of non-steady-state natural and anthropogenic components to estimation biases in the four North American coast oceans. We also compare RECA with established regression-based methods (CAREER and eMLR(C*)) that are widely used in open-ocean regions to determine their applicability in coastal settings. Our results demonstrate that RECA effectively captures overall Canthro with minimal large-scale biases. However, subregional analyses reveal challenges in separating anthropogenic and natural CO2 signals, emphasizing the influence of natural variability. This study provides a unified framework for high-resolution Canthro estimation in coastal waters, evaluates its uncertainties, and paves the way for improved coastal carbon monitoring and climate action.
How to cite: Li, X. and Carter, B.: Regional method to quantify coastal anthropogenic carbon changes, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-14803, https://doi.org/10.5194/egusphere-egu25-14803, 2025.
The northern high latitudes (NHLs) are undergoing rapid environmental changes with global warming, which may trigger feedback mechanisms that amplify natural methane emissions from wetlands and increase contributions from wildfires. Studying year-to-year variations in these emissions can provide understanding of the key factors driving natural methane fluxes. In addition, the NHLs produce substantial methane emissions from fossil fuel production. However, the spatial heterogeneity and overlap of methane sources in the region complicates the attribution of emissions to specific sources.
This study presents an intercomparison of methane emissions estimates across four NHL regions—Russia, Canada, Alaska, and Norway-Sweden-Finland—between 2018 and 2021, focusing on the magnitude and seasonality of emissions. Emissions are compared using a combination of bottom-up and top-down estimates. Bottom-up estimates for key sectors, including anthropogenic activities, biomass burning, and wetlands, are produced by inventories and process models. Top-down estimates are derived from an ensemble of atmospheric inversions that separately optimise anthropogenic and biospheric emissions. The inversions, derived from the CarbonTracker Europe-CH4 model, incorporate a range of prior estimates, uncertainties, and atmospheric methane measurements from in-situ surface stations and satellite observations from TROPOMI and GOSAT.
Preliminary findings indicate that for all four regions, posterior natural emissions are strongly influenced by the choice of prior emissions in shaping both their seasonality and magnitude. The CarbonTracker Europe-CH4 ensemble produces posterior emissions estimates consistent with the Global Carbon Project ensemble, which utilised different inversion models.
By integrating a wide range of emissions estimates, this study aims to improve our understanding of the NHL methane budget. The findings contribute to ongoing methane emission assessments under the Eye-CLIMA, IM4CA (Investigating Methane for Climate Action), ESA SMART-CH4 (Satellite Monitoring of Atmospheric Methane) projects and ESA-AMPAC (Arctic Methane and Permafrost Challenge).
How to cite: Ward, R., Tenkanen, M., Tsuruta, A., Hyvärinen, S., Mengistu, A., Lindqvist, H., Tamminen, J., Markkanen, T., Raivonen, M., Leppänen, A., and Aalto, T.: Assessing Bottom-Up and Top-Down Methane Emission Estimates in Northern High Latitude Regions (2018–2021) , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15075, https://doi.org/10.5194/egusphere-egu25-15075, 2025.
Atmospheric methane (CH₄) is a significant greenhouse gas with a warming potential 84 times greater than that of CO₂ over a 20-year time horizon. Given its relatively short atmospheric lifetime of approximately 10 years and its high warming potential, reducing anthropogenic methane emissions is crucial for limiting near-term increases in global temperatures. Methane is emitted from both natural and anthropogenic sources and is primarily consumed through reactions with hydroxyl (OH) radicals in the atmosphere. To a lesser extent, it is also removed through soil interactions. The limited understanding of the interplay between sources and sinks leads to an unclear explanation of the interannual variability in atmospheric methane concentrations over the past decades. Moreover, there are growing concerns about the possibility that climate change could amplify natural CH₄ fluxes. Here we present an inverse model-based reanalysis of global CH₄ emissions (2018-2021). To achieve this, we employ the TM5-4DVAR inverse model system, which is driven by ECMWF-ERA5 meteorological data at a resolution of 1° x 1° for both latitude and longitude, and encompasses 137 vertical levels. This four-dimensional inverse system generates monthly global fields of CH₄ fluxes across four source categories: wetlands, rice fields, biomass burning, and anthropogenic activities. The methane fluxes are optimized using high-resolution surface-based measurements from the NOAA Earth System Research Laboratory (ESRL) global cooperative air sampling network, as well as column-averaged dry mixing ratio XCH₄ data from the GOSAT satellite. The primary aim of this work is to identify the major geographical areas and source categories driving the interannual variability and trends of global CH₄ fluxes during the study period. Moreover, the temporal variability of natural methane fluxes is analysed in relation to physical parameters to investigate how natural CH4 emissions respond to climate factors (e.g. temperature).
How to cite: Graziosi, F., Manca, G., Segato, D., Dobricic, S., and Arriga, N.: Inverse modelling of global CH4 emissions using surface based measurements and GOSAT satellites retrievals., EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-15454, https://doi.org/10.5194/egusphere-egu25-15454, 2025.
Accurate simulation of regional carbon dioxide (CO2) concentrations is essential for understanding carbon flux dynamics, refining emission inventories, and supporting climate mitigation policies. Using the WRF-Chem-VPRM model at 3 km resolution, this study simulated CO2 concentrations in Jiangsu Province, China, with hourly outputs. Model verification against nine ground-based CO2 monitoring stations confirmed its reliability.
Before integrating emission inventories into the model, we conducted a comprehensive analysis of six widely used emission inventories (ODIAC, EDGAR, MEIC, CHRED, GID, GRACED), revealing significant discrepancies in total emissions and spatial patterns in China. Provincial-scale annual carbon emissions discrepancies reached 52%, whereas urban-scale discrepancies averaged 137%, attributed to differences in emission proxies and spatial resolution.
Sensitivity experiments for July and December 2022, representing summer and winter, assessed the impacts of spatial, temporal, and vertical allocation processes. Vertical allocation coefficients emerged as a critical factor, particularly under stable nighttime boundary layer conditions, where deviations exceeded 50 ppm. Their influence equaled or even surpassed that of emission inventory selection, underscoring the necessity of precise vertical parameterization.
Spatial allocation discrepancies primarily affected urban concentrations, where dense and diverse sources contributed to higher variability. Winter simulations exhibited increased uncertainties due to heightened heating emissions and limited vertical mixing.
These findings highlight the importance of refining vertical and spatial allocation in emission inventories to improve regional CO2 modeling. The study provides insights for advancing carbon inversion methodologies and supporting robust Monitoring, Reporting, and Verification (MRV) systems in urbanizing regions.
Emission inventories analyzed include:
• ODIAC: Open-source Data Inventory for Anthropogenic CO2,
• EDGAR: The Emissions Database for Global Atmospheric Research,
• MEIC: The Multi-resolution Emission Inventory for China,
• CHRED: China High-resolution Emission Database,
• GID: Global Infrastructure emissions Detector,
• GRACED: Global Gridded Daily CO2 Emissions Dataset.
How to cite: Feng, W., Tang, X., Zhu, J., and Zhou, X.: High-Resolution simulation of CO2 Concentrations Over Jiangsu Province in China Based on WRF-Chem-VPRM and Six Emission Inventories, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16464, https://doi.org/10.5194/egusphere-egu25-16464, 2025.
North Atlantic tropical cyclones (i.e. hurricanes) are observed to drive intense air-sea CO2 exchange and trigger primary production by phytoplankton. However, Earth system models (ESMs) with coarse spatial resolution are not able to capture such effects. Here, we address this limitation and resolve the impacts of hurricanes on the ocean carbon cycle in an ESM for the first time. We present the first 1-year global, coupled, high-resolution (5 km ocean, 5 km atmosphere) ESM simulation including ocean biogeochemistry with the ICON (ICOsahedral Non-hydrostatic) model framework. Our simulation realistically reproduces the effects of hurricanes at: 1) instantaneously increasing air-sea CO2 fluxes by a factor of 10-30 due to strong surface winds (>58 m/s, hurricane category 4); 2) promoting longer-lasting surface ocean cooling by 2-4°C, and thus decreasing surface ocean partial pressure of CO2 (pCO2); and 3) triggering large-scale phytoplankton blooms, spatially modulated by mesoscale ocean eddies. We show that the hurricane-driven sea-surface cooling is mainly caused by extreme latent heat loss (>1200 W/m2), whose impact on decreasing pCO2 outweighs the mixing and upwelling of dissolved inorganic carbon. Our simulated hurricanes contribute to inverting the direction of the local air-sea pCO2 imbalance, thus promoting ocean CO2 uptake. Intense wind speeds also trigger vertical diffusion of nutrients, as well as near-inertial oscillations, which become the dominant mode of subsurface ocean variability in the wake of the cyclones. While the proportion of intense tropical cyclones is projected to increase with climate change, their future role in the ocean carbon cycle remains unclear. Resolving tropical cyclones in ESMs will allow us to better understand their response and impact to ongoing climate change at regional and global scales.
How to cite: Nielsen, D. M., Chegini, F., Serra, N., U. Kumar, A., Brueggemann, N., Hohenegger, C., and Ilyina, T.: Hurricanes trigger ocean CO2 uptake and phytoplankton bloom in a high-resolution Earth system model simulation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-1596, https://doi.org/10.5194/egusphere-egu25-1596, 2025.
Siberia’s extensive wetlands, permafrost, and boreal forests are significant sources of methane, positioning this region as crucial for global methane (CH4) monitoring. However, Siberia remains sparsely monitored by atmospheric and ecosystem observatories, highlighting the need to leverage existing datasets to refine CH4 budgets with better spatial and temporal precision. Utilising the ZOtino Tall Tower Observatory (ZOTTO; 60°48' N, 89°21' E) dataset, which provides continuous, high-resolution CH4 mole fraction and meteorological measurements from six heights up to 301 meters, combined with ERA5 meteorological data at 60°75' N, 89°25' E, we conducted a comprehensive analysis of long-term trends and variations in atmospheric CH4 at ZOTTO, examining its diurnal and seasonal patterns from 2010 to 2021. Our analysis reveals a significant increase in the summer diurnal amplitude of CH4, which could be driven by both forest and meteorological dynamics, through the effects of daytime mixing and nighttime stability on the CH4 mole fraction, and ecosystem CH4 flux. We found that while atmospheric dynamics showed no significant trends contributing to this diurnal amplitude increase, there was an increasing trend in nighttime CH4 ecosystem flux in summer (predominantly August) over the 11-year period, with high emissions predominantly originating from the west and southwest of the station. Additionally, episodic high methane CH4 was observed in 2012 and 2019, linked to wildfires, and in 2016, attributed to enhanced wetland activity. Lastly, there were significant positive correlations between the calculated CH4 surface flux and soil temperature and moisture at ZOTTO.
How to cite: Tran, D. A., Vilà-Guerau de Arellano, J., Luijkx, I., Botía, S., Faassen, K., Gerbig, C., and Zaehle, S.: Increasing Methane Summer Diurnal Amplitude in Siberia: A 2010–2021 Analysis from the ZOtino Tall Tower Observatory (ZOTTO), EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2043, https://doi.org/10.5194/egusphere-egu25-2043, 2025.
Since June 2018, ground-based remote sensing measurements are performed at the suburban Xianghe site in China, situated in the heart of the densely populated Beijing-Tianjin-Hebei megalopolis. These observations are performed with Fourier Transform Infrared (FTIR) spectrometers and provide column-averaged dry-air concentrations of gases such as CO2, CH4 and CO. They are affiliated to the international Total Column Carbon Observing Network (TCCON). Co-located with these measurements is a PICARRO cavity ring-down spectroscopy (CRDS) analyser observing in situ concentrations of CO2 and CH4 at an altitude of 60 m.
To gain a better understanding of the causes of the observed temporal variabilities at this site, we employed the Weather Research and Forecasting model coupled with Chemistry in its greenhouse gas configuration (WRF-GHG). Our study analyses both column-averaged (XCO2) and surface in situ CO2 concentrations and simultaneously evaluates the model’s performance at Xianghe. The CO2 exchange with the biosphere is simulated with the integrated Vegetation Photosynthesis and Respiration Model (VPRM), while the anthropogenic emissions are taken from the global CAMS-GLOB-ANT inventory and transported in separate tracers according to their source sector.
The model shows good performance, achieving correlation coefficients of 0.70 for XCO2 and 0.75 for afternoon in situ concentrations. For XCO2, a mean bias of -1.43 ppm relative to TCCON is found, primarily attributed to biases in the CAMS reanalysis used as initial and lateral boundary conditions. Anthropogenic emissions from the industry and energy sectors emerged as dominant contributors to CO2 concentrations, alongside the biosphere, which acts as a sink for XCO2 from April to September and becomes a source for the rest of the year. Synoptic weather patterns were shown to strongly determine the variation in CO2 levels, with enhanced impacts during summer due to the large spatial and temporal heterogeneity of biogenic fluxes in the region. Near the surface, the observed large diurnal variation associated to the evolution of the planetary boundary layer is relatively well simulated by WRF-GHG.
Our analysis demonstrates the utility of WRF-GHG in simulating both column and surface CO2 concentrations, offering insights into the sectoral and meteorological drivers of variability at Xianghe and its surrounding region.
How to cite: Callewaert, S., De Mazière, M., Zhou, M., Wang, T., Langerock, B., Wang, P., and Mahieu, E.: Analysis of ground-based column and in situ surface concentrations of CO2 at Xianghe, China, using WRF-Chem simulations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6416, https://doi.org/10.5194/egusphere-egu25-6416, 2025.
2025 started with the launch of the H-Europe project IM4CA to enhance the quantification and understanding of methane emissions and sinks. A consortium of 25 partners joins forces to investigate pressing questions about the evolution atmospheric methane levels in recent decades, to reduce the uncertainty in future projections and design efficient solutions for monitoring and mitigating emissions in and outside of Europe. It will build new measurement and modelling infrastructure for improved monitoring of the progress toward short- and long-term emission reduction targets, with a prominent role for existing and upcoming satellite missions for measuring atmospheric composition and land surface properties.
The changing European methane emissions are an important focus of the project, which we keep track of with help of eastward extensions of the ICOS monitoring network in Poland and Romania. Intensive measurement campaigns in Rumania are conducted combining surface, aircraft, and total column measurements to improve the accuracy of emission quantification techniques using satellite data. The world-wide applicability of these techniques will extend the impact of our campaigns far beyond European borders.
Besides changing anthropogenic emissions, climate impacts on natural sources and sinks of methane are an important focus of IM4CA also. The four-year research program will initiate new measurement infrastructure in Congo to help characterize emissions from tropical wetlands in Africa. Campaigns will be conducted in Northern Scandinavia along a transect of disappearing permafrost to investigate impacts on vegetation and methane emissions using techniques that can be applied to high-resolution satellite instruments for circumpolar emission mapping.
This presentation will provide an overview of the planned activities and goals of IM4CA. The project offers a great opportunity to learn about methane in a cooperative spirit and to reach out and provide support to those who can turn knowledge about methane into climate action.
How to cite: Houweling, S., Petrescu, R., Zaidi, M., Roeckmann, T., Paris, J.-D., Sachs, T., Aalto, T., Gloor, M., Boesch, H., Stohl, A., Denier van der Gon, H., Saunois, M., Thompson, R., Gromov, S., Höglund-Isakkson, L., and Koffi, E.: Let’s Investigate Methane for Climate Action, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-13556, https://doi.org/10.5194/egusphere-egu25-13556, 2025.
The functions of terrestrial ecosystems are various, and recent study suggests the major three functions which are carbon, water, and energy cycling. They are all originated from land, the fundamental components of terrestrial ecosystems. Land consists of major five land cover: cropland, grassland, built-up area, wetland, and forest land. Forest land is described as high potential to remove Greenhouse gases under climate change era and thus the forest carbon management has been raised for effective land management in terms of carbon removal. Korean peninsula, South Korea and North Korea, has undergone the severe war between them and it damaged the whole territory, which consists of more than 60% of forest land. Therefore, two countries tried to revegetate and implemented forestation plans for recover the forest land over 50 years. Therefore, this study assessed the forest carbon management on the Korean Peninsula using Net Primary Productivity(NPP) from the 1980s to 2010s. To estimate NPP, Carnegie-Ames-Stanford Approach(CASA) model was applied. The study adopted the carbon demand and supply method for assessment. We defined carbon demand as amount of carbon loss from forest land in previous year due to forest land changes, and carbon supply as amount of newly updated carbon sink from forest land due to afforestation. According to research findings, even though South Korea achieved successful forest expansion, it only focused on the amount of forest area rather the quality of carbon management. However, the situation in North Korea described not only the failure of increasing forest area but also forest carbon management. Further research would be analyzed the outcomes with forest plans in South Korea and North Korea.
How to cite: Kim, W., Song, C., and Lee, W.-K.: Assessment of Forest Carbon Management Using Net Primary Productivity on the Korean Peninsula, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-17087, https://doi.org/10.5194/egusphere-egu25-17087, 2025.
The climate change over the Mediterranean region poses serious concerns about the role of open vegetation fires in the emissions of climate-altering species. The aim of this work is to review the current methodologies for quantifying the emissions of greenhouse gases and black carbon from open vegetation fires, as well as the data provided by four state-of-the-art inventories of emissions of carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O) and black carbon (BC) in the Mediterranean region for the period 2003–2020.
A limited number of studies specifically addressed the quantification of emissions from open fires in the Mediterranean region. Our data review of fire emissions in the Mediterranean region, where “top-down” methods have not yet implemented, reveals discrepancies across the four inventories examined (GFED v4.1s, GFAS v1.2, FINN v2.5, and EDGAR v8.0). Among these, FINN v2.5 consistently reported the highest emissions, while GFED v4.1s reported the lowest. We observed that the relative ranking of total emissions between the inventories varied for the species considered (e.g. CO2 vs. CH4) and that different proportions of emissions were attributed to the individual countries included in the Mediterranean domain. We argued that these differences were related to the different spatial resolutions of the input data used to detect the occurrence of fires, the different approaches to calculating the amount of fuel available, and the emission factors used.
The three inventories reporting wildfire emissions were consistent in identifying the occurrence of peaks in the emissions for the years 2007, 2012 and 2017. We hypothesized that La Niña events could partially contribute to triggering the occurrence of these emission peaks.To increase the accuracy and consistency of climate-altering emission data related to open vegetation fires in the Mediterranean region, we recommend to integrate bottom-up approaches with top-down inversion methods based on satellite and in-situ atmospheric observations.
How to cite: Hundal, R. A., Annadate, S., Cesari, R., Collalti, A., Maione, M., and Cristofanelli, P.: Emissions of climate-altering species from open vegetation fires in the Mediterranean region - A review on methods and data, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18709, https://doi.org/10.5194/egusphere-egu25-18709, 2025.
In this case study, we derive and compare estimates of annual net community production (NCP) in the Greenland Sea from Argo float data of nitrate, oxygen, and dissolved inorganic carbon (DIC). We added tracers of the inorganic carbon system, nitrate, dissolved oxygen, and air-sea gas exchange to the 1-D Price-Weller-Pinkel mixing model (Price et al., 1986) tuned to the Greenland Sea (Moore et al., 2015; Brakstad et al., 2019). By reinitializing the model with every Argo profile, we were able to estimate NCP as the difference between the abiotic model output and the Argo profiles. This method has previously been employed in various other regions (Plant et al. 2016; Briggs et al. 2017, Mork et al. 2024). While we here compare NCP estimates from both nitrate, oxygen, and DIC, previous work has considered maximum two of these concurrently. Through our comparison, we discovered quantitative discrepancies in the NCP and annual NCP (ANCP) estimates. These results were sensitive to trends in the raw data and artefacts deriving from processes that were unresolved in the model, such as internal waves. Effects from internal waves were challenging to remove without introducing new artefacts. Qualitatively, the NCP seasonal cycle was well resolved: the summer of 2019, NCP fluctuated between periods of weak net biological production and periods of weak net heterotrophy. NCP was close to zero through winter, before two strong blooms were observed in late April and May 2020. However, the amplitude of the NCP signal from DIC was somewhat larger than from nitrate and oxygen. DIC derived NCP also exhibited stronger signs of remineralization from November 2019 to January 2020 compared to the two other estimates. Thus, this work shows the importance of careful consideration when utilizing biogeochemical Argo data in the Greenland Sea.
How to cite: Sælemyr, I., Olsen, A., Becker, M., Lauvset, S. K., Mork, K. A., Brakstad, A., and Fransner, F.: Net community production in the Greenland Sea: a comparative case study using Argo data of nitrate, oxygen, and DIC, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-18920, https://doi.org/10.5194/egusphere-egu25-18920, 2025.
China is among the top nitrous oxide (N2O)-emitting countries, but existing national inventories do not provide full-scale emissions including both natural and anthropogenic sources. We conducted a four-decade (1980–2020) of comprehensive quantification of Chinese N2O inventory using empirical emission factor method for anthropogenic sources and two up-to-date process-based models for natural sources. Total N2O emissions peaked at 2287.4 (1774.8–2799.9) Gg N2O yr-1 in 2018, and agriculture-developed regions, like the East, Northeast, and Central, were the top N2O-emitting regions. Agricultural N2O emissions have started to decrease after 2016 due to the decline of nitrogen fertilization applications, while, industrial and energetic sources have been dramatically increasing after 2005. N2O emissions from agriculture, industry, energy, and waste represented 49.3%, 26.4%, 17.5%, and 6.7% of the anthropogenic emissions in 2020, respectively, which revealed that it is imperative to prioritize N2O emission mitigation in agriculture, industry, and energy. Natural N2O sources, dominated by forests, have been steadily growing from 317.3 (290.3–344.1) Gg N2O yr-1 in 1980 to 376.2 (335.5–407.2) Gg N2O yr-1 in 2020. Our study produces a Full-scale Annual N2O dataset in China (FAN2020), providing emergent counting to refine the current national N2O inventories.
How to cite: Liang, M., Zhou, Z., Ren, P., Xiao, H., Xu, R., Hu, Z., Piao, S., Tian, H., Tong, Q., Zhou, F., Wei, J., and Yuan, W.: Four decades of full-scale nitrous oxide emission inventory in China, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-6054, https://doi.org/10.5194/egusphere-egu25-6054, 2025.
