BG1.3 | Budgets, Trends, and Drivers of Major Greenhouse Gases from Regional to Global scales
EDI
Budgets, Trends, and Drivers of Major Greenhouse Gases from Regional to Global scales
Co-organized by AS3
Convener: Ana Bastos | Co-conveners: Ben Poulter, Nadine Goris, Jens TerhaarECSECS, Philippe Ciais
Orals
| Thu, 18 Apr, 08:30–12:25 (CEST)
 
Room C
Posters on site
| Attendance Thu, 18 Apr, 16:15–18:00 (CEST) | Display Thu, 18 Apr, 14:00–18:00
 
Hall X1
Orals |
Thu, 08:30
Thu, 16:15
The Paris Agreement on Climate sets the international objective to keep climate warming well below two degrees. This extraordinary challenge requires a dramatic improvement of current scientific capabilities to estimate the budgets and their trends of greenhouse gases (GHG) at regional scale, and how they link up to the global growth rates of the major GHGs (N2O, CH4 and CO2).
This session aims to bring together studies that seek to quantify global and regional budgets, trends and variability of major GHG (N2O, CH4 and CO2), as well as to understand 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, and atmospheric inverse modeling. We encourage contributions from the REgional Carbon Cycle Assessment and Processes phase 2 (RECCAP2), as well as studies 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.

Orals: Thu, 18 Apr | Room C

Chairpersons: Nadine Goris, Jens Terhaar, Ana Bastos
08:30–08:35
Ocean and LOAC
08:35–08:45
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EGU24-16495
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solicited
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On-site presentation
Lavinia Patara, Judith Hauck, Luke Gregor, Cara Nissen, Mark Hague, Precious Mongwe, Seth Bushinsky, Scott C. Doney, Nicolas Gruber, Corinne Le Quéré, Manfredi Manizza, Matthew Mazloff, and Pedro M. S. Monteiro

The Southern Ocean has long been known to be an important region for ocean CO2 uptake, and one which is especially sensitive to changes in the overlying climate. Here we assess the Southern Ocean CO2 uptake (1985–2018) using data sets gathered in the REgional Carbon Cycle Assessment and Processes Project Phase 2 (RECCAP2). These include global ocean biogeochemical models (GOBMs), surface ocean pCO2-products, data-assimilated models, and interior ocean biogeochemical observations. Over this period the Southern Ocean acted as a sink for CO2, with magnitudes which are roughly half of those reported by RECCAP1 for the same region and timeframe. Close agreement is found between GOBMs and pCO2-products, partly due to some compensation of seasonal and regional differences. Seasonal analyses revealed agreement in driving processes in winter (with uncertainty in the magnitude of outgassing), whereas discrepancies are more fundamental in summer, when GOBMs exhibit difficulties in simulating the balance of non-thermal processes of biology and mixing/circulation. The data sets emphasize strong latitudinal variations in the mean and seasonality of the CO2 flux and asymmetries in the mean and amplitude of the CO2 flux between Atlantic, Pacific and Indian sectors. The present-day net uptake is to first order a response to rising atmospheric CO2. This drives large amounts of anthropogenic CO2 (Cant) into the ocean, thereby overcompensating the loss of natural CO2 to the atmosphere driven by the changing climate. The GOBMs show, however, a 20% spread and an overall underestimate of Cant storage in the ocean interior. An apparent knowledge gap is the increase of the sink since 2000, with pCO2-products suggesting a growth that is more than twice as strong and uncertain as that of GOBMs. This is despite nearly identical pCO2 trends in GOBMs and pCO2-products when both products are compared only at the locations where pCO2 was measured.

How to cite: Patara, L., Hauck, J., Gregor, L., Nissen, C., Hague, M., Mongwe, P., Bushinsky, S., Doney, S. C., Gruber, N., Le Quéré, C., Manizza, M., Mazloff, M., and Monteiro, P. M. S.: Mean, Seasonal Cycle, Trends, and Storage of the Southern Ocean carbon cycle in the RECCAP2 assessment (1985-2018), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16495, https://doi.org/10.5194/egusphere-egu24-16495, 2024.

08:45–08:55
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EGU24-4196
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On-site presentation
Galen McKinley, Amanda Fay, Dustin Carroll, and Dimitris Menemenlis

Since the preindustrial era, the ocean has removed roughly 40% of fossil CO2 from the atmosphere, and it will eventually absorb at least 80% of human CO2 emissions. While there is no doubt that the ocean is a critical player in the global carbon cycle, many uncertainties remain and the drivers and magnitude of interannual-to-decadal timescale variability remain poorly constrained. A key question is the extent to which external forcing, specifically the variability of the atmospheric pCO2 growth rate, or internal ocean variability is the dominant mechanism of variability. We use a suite of experiments from the ECCO-Darwin data-assimilative ocean biogeochemistry model to isolate and explore the impact of these two drivers. We demonstrate that at the global scale, external and internal variability equally drive ocean sink variability. However, as the spatial scale becomes more regional, internal variability becomes increasingly dominant. To diagnose the future evolution of the global-scale ocean carbon sink in response to a changing atmospheric growth rate, both skillful observation-based products and data-assimilative models will be required.   

How to cite: McKinley, G., Fay, A., Carroll, D., and Menemenlis, D.: Drivers of ocean carbon sink variability across spatial scales, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4196, https://doi.org/10.5194/egusphere-egu24-4196, 2024.

08:55–09:05
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EGU24-6021
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On-site presentation
Jerry Tjiputra, Shunya Koseki, and Pradeebane Vaittinada Ayar

Both the tropical Pacific and Atlantic upwelling systems are modulated by their respective Ninos (ENSO and Atlantic Nino), which significantly affect the regional and global climate variability. Coincidentally, two of largest ocean carbon outgassing systems are also located in these domains. As a result, the interannual variability of ocean CO2 fluxes in these regions have predominant imprint on the globally integrated variations (Landschutzer et al., 2016). In contrast to the effect of anomalously cold surface temperature, the upwelling of deep-water rich in dissolved inorganic carbon is understood to be the main driver for the mean CO2 outgassing. In the tropical Pacific, El Nino (La Nina) leads to a suppressed (stronger) upwelling condition and an anomalously weaker (stronger) carbon outgassing. On the other hand, the Atlantic Nino and Nina exert considerable variability in the surface freshwater and temperature, which leads to spatially heterogeneous responses in the contemporary CO2 fluxes. In both systems, we discover a critical role of subsurface alkalinity in regulating the observed variability, primarily through altering the surface buffering capacity (Koseki et al., 2023). We show that bias in CMIP6 Earth system models in simulating the mean contemporary alkalinity state in the tropical Pacific leads to contrasting future impacts (Vaittinada Ayar et al., 2022) and could have ramifications on the climate carbon cycle feedback. 

 

References

Koseki, S., J. Tjiputra, F. Fransner, L. R. Crespo, and N. S. Keenlyside (2023), Disentangling the impact of Atlantic Nino on sea-air CO2 fluxes, Nature Communications, 14, 3649, https://doi.org/10.1038/s41467-023-38718-9.

Landschützer, P., N. Gruber, and D. C. E. Bakker (2016), Decadal variations and trends of the global ocean carbon sink, Global Bio- geochem. Cycles, 30, 1396–1417, http://doi.org/10.1002/2015GB005359.

Vaittinada Ayar, P., L. Bopp, J. R. Christian, T. Ilyina, J. P. Krasting, R. Séférian, H. Tsujino, M. Watanabe, A. Yool, and J. Tjiputra (2022), Contrasting projections of the ENSO-driven CO2 flux variability in the equatorial Pacific under high-warming scenario, Earth Syst. Dynam., 13, 1097–1118, https://doi.org/10.5194/esd-13-1097-2022.

How to cite: Tjiputra, J., Koseki, S., and Vaittinada Ayar, P.: Non-intuitive differences in Ninos-driven CO2 flux variability and long-term changes in the tropical Pacific and Atlantic, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-6021, https://doi.org/10.5194/egusphere-egu24-6021, 2024.

09:05–09:15
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EGU24-14038
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ECS
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Virtual presentation
Yaohua Luo, Zhirong Zhang, Jinshun Chen, Yi Xu, Fuqing Cao, Tao Huang, Xianghui Guo, and Minhan Dai

We examined the sub-seasonal to interannual variability and multi-year trend of sea surface CO2 partial pressure (pCO2) and air-sea CO2 flux at a coastal site of the East China Sea (31⁰N, 122.8⁰E) based on high-frequency time-series data collected by a buoy since 2013. Seasonal average sea surface pCO2 was highest in autumn, but the lowest value can appear in winter or spring, depending on the biological productivity in spring. The seasonal amplitude of pCO2 was up to 123 μatm. Based on property-property relationships and a simple mass budget model, we found that temperature change, biological activity, water mixing and air-sea CO2 exchange all made significant contributions to the seasonal variation of pCO2. From winter to summer, seasonal warming and atmospheric CO2 uptake elevated the pCO2, while net biological production, weakened vertical mixing and the retreat of the Yellow Sea Coastal Water (YSCW) lowered the pCO2. Conversely, from summer to winter, seasonal cooling and CO2 emission lowered the pCO2, while respiration, enhanced vertical mixing and the YSCW intrusion raised them up. Over short-term timescale, biological production and respiration frequently drew down or elevated the pCO2 by 150-400 μatm within 5-10 days during warm months. When biological activity was suppressed during cold months, such short-term variations were dominated by water mixing with a smaller pCO2 amplitude of 5-60 μatm within 2-6 days. This site was a sink of atmospheric CO2 in winter and spring, but a CO2 source in summer and autumn. Annually, it was a moderate CO2 source in 2014 (air-sea CO2 flux was 2.88 ± 11.02 mmol m2 d1), a weak CO2 sink in 2016 (-0.21 ± 12.23 mmol m2 d1), and a weak CO2 source in the combined year of the first half of 2017 and the second half of 2018 (0.40 ± 9.11 mmol m2 d1). The relatively high CO2 source in 2014 was likely due to the weaker biological production in spring and more typhoon passage in autumn. From 2013 to 2019, the wintertime sea surface pCO2 didn’t follow the increasing trend of the atmospheric pCO2, leading to an enhancing carbon sink in winter.

How to cite: Luo, Y., Zhang, Z., Chen, J., Xu, Y., Cao, F., Huang, T., Guo, X., and Dai, M.: Sea surface pCO2 variability on different time scales in the East China Sea based on high-frequency time-series observations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14038, https://doi.org/10.5194/egusphere-egu24-14038, 2024.

09:15–09:25
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EGU24-20295
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On-site presentation
Neill Mackay, Jan Zika, Taimoor Sohail, Tobias Ehmen, and Andrew Watson

The ocean is a strong sink for anthropogenic CO2, absorbing around a quarter of emissions since the industrial era. Quantifying the ocean carbon sink is necessary for constraining the global carbon budget; however, discrepancies remain between estimates of the ocean carbon sink over the last 30 years from observation-based data products and those from numerical models. Moreover, larger regional uncertainties highlight the need for a better understanding of the drivers of ocean carbon sink variability, to help improve models and to better constrain future climate projections. A comprehensive understanding of the sink must include knowledge of (1) the air-sea flux of CO2, (2) the accumulation of carbon in the ocean interior, and (3) how it is redistributed within the ocean by changes in the physical circulation. This characterisation is typically achieved using numerical models, which are constrained by resolution and the need to parameterise processes including physical mixing at the sub-grid scale.

We present a novel method for characterising the ocean carbon sink from a combination of oceanographic datasets, and for reconciling our knowledge of the ocean’s uptake of CO2 with that of interior carbon storage rates. Our Optimal Transformation Method (OTM) uses a water mass framework to diagnose the transport and mixing of tracers such as heat, salt, and carbon consistent with observed interior changes and estimates of boundary forcings. The water mass framework has the advantage that the transport and mixing of conservative tracers are diagnosed exactly, with no need for parameterisation. We validate OTM using outputs from a data-assimilating biogeochemical ocean model and demonstrate its ability to recover the model’s ‘true’ air-sea CO2 fluxes when initialised with biased priors. OTM reduces root-mean-squared errors between diagnosed air-sea CO2 fluxes and the model truth from prior to solution by up to 71%, while simultaneously estimating inter-basin transports of heat, freshwater, and carbon consistent with the model. Following successful validation, we apply OTM to a combination of observational data products to diagnose estimates of the ocean’s uptake and redistribution of carbon since 1990, utilising reanalyses of air-sea heat and freshwater fluxes, interior temperature and salinity, air-sea CO2 fluxes, and machine-learning reconstructions of interior ocean carbon.

How to cite: Mackay, N., Zika, J., Sohail, T., Ehmen, T., and Watson, A.: A water mass transformation method applied to diagnosing ocean carbon uptake, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20295, https://doi.org/10.5194/egusphere-egu24-20295, 2024.

09:25–09:35
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EGU24-12480
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ECS
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On-site presentation
Alban Planchat, Laurent Bopp, and Lester Kwiatkowski

Disparities in estimates of the ocean carbon sink, whether derived from global ocean biogeochemical models or from data products based on observations of surface ocean pCO2, question our ability to accurately assess ocean carbon uptake and its trend over recent decades. A potential factor contributing to the inconsistency between data products and model-based estimates is the pre-industrial air-sea carbon flux that is required to isolate the anthropogenic component from the total air-sea carbon flux estimated from observations. This pre-industrial air-sea carbon flux is thought to stem at the global scale from an imbalance between riverine carbon discharge to the ocean and sediment carbon burial.  Using a mass-balanced approach and comprehensive estimates of carbon inputs to the ocean by rivers and groundwater as well as carbon burial in marine sediments, Regnier et al. (2022) estimated that the pre-industrial ocean was outgassing 0.65 ± 0.30 petagrams of carbon per year. This updated estimation was used in the latest Global Carbon Budget (Friedlingstein et al., 2023) to derive an estimate of the ocean carbon sink over recent decades. In this study, we use a series of ocean biogeochemical pre-industrial simulations with varying assumptions related to carbon riverine input and burial to develop a theoretical framework to determine the ocean carbon outgassing and its spatial distribution. Building upon previous efforts, we integrate a carbon mass-balance approach with consideration of the ocean alkalinity budget. While conventionally assumed that the global alkalinity inventory was in equilibrium during the pre-industrial era — with riverine alkalinity discharge offset by CaCO3 burial — we demonstrate that an imbalance in the pre-industrial ocean alkalinity budget could significantly affect the carbon outgassing flux. This novel conceptual framework allows us to reestimate the pre-industrial carbon flux while considering the ocean alkalinity budget. Furthermore, it provides a simple method to reevaluate this flux in light of new assessments of carbon or alkalinity sources and sinks, while also covering their uncertainty ranges.

How to cite: Planchat, A., Bopp, L., and Kwiatkowski, L.: Reassessing the pre-industrial air-sea carbon flux considering the ocean alkalinity budget, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12480, https://doi.org/10.5194/egusphere-egu24-12480, 2024.

09:35–09:45
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EGU24-14775
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ECS
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On-site presentation
Alizee Roobaert, Pierre Regnier, Peter Landschützer, and Goulven G. Laruelle

The development of high-quality controlled databases of sea surface partial pressure of CO2 (pCO2) combined with robust machine learning-based mapping methods that fill pCO2 gaps in time and space, enable us to quantify the oceanic air-sea CO2 exchange and its spatiotemporal variability only based on in-situ observations (pCO2-products). However, most existing pCO2-products do not explicitly include the coastal ocean or have a spatial resolution that is too coarse (e.g., 1°) to capture the highly heterogeneous spatiotemporal dynamics of pCO2 in these regions thus limiting our ability to resolve long-term trends and the interannual variability of the coastal air-sea CO2 exchange (FCO2).

To address this limitation, we updated the global coastal pCO2-product of Laruelle et al. (2017) using a 2-step machine learning interpolation technique (relying on Self Organizing Maps and a Feed Forward neural Network) combined with the most extensive monthly time series for coastal waters from the Surface Ocean CO2 Atlas (SOCAT), spanning from 1982 to 2020 to reconstruct monthly high spatial resolution (0.25°) continuous coastal pCO2 maps. This updated coastal pCO2-product is then used to reconstruct the temporal evolution of the global coastal FCO2 based on observations.

Our results show that since 1982, the extended coastal ocean, covering an area of 77 million km² in this study, has been acting as an atmospheric CO2 sink, removing -0.4 Pg C yr-1 (-0.2 Pg C yr-1 with a narrower coastal domain roughly equivalent to continental shelves) from the atmosphere. Moreover, the intensity of this CO2 sink has been increasing over time at a rate of 0.1 Pg C yr-1 per decade (0.03 Pg C yr-1 decade-1 in the narrower domain). The long-term change in the air-sea CO2 flux is largely driven by the air-sea pCO2 gradient, dominated by the sea surface pCO2, however wind speed and sea-ice coverage play significant roles, regionally. This new coastal pCO2-product provides a valuable constraint for understanding the strengthening of the global coastal ocean CO2 sink, fill the coastal gap in synthesis studies such as the Global Carbon Budget and serves as a benchmark for evaluating emerging results of ocean biogeochemical models.

How to cite: Roobaert, A., Regnier, P., Landschützer, P., and Laruelle, G. G.: Global coastal ocean CO2 trends over the 1982–2020 period, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14775, https://doi.org/10.5194/egusphere-egu24-14775, 2024.

09:45–09:55
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EGU24-11622
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On-site presentation
Timothy Eglinton, Heather Graven, Frank Hagedorn, Soenke Szidat, Alexander Brunmayr, Margaux Duborgel, Dylan Geissbuehler, Thomas Laemmel, Luisa Minich, Benedict Mittelbach, Timo Rhyner, and Margot White

New constraints on carbon exchanges between atmospheric, terrestrial and aquatic systems are needed to reduce uncertainty in future predictions of the global carbon cycle and climate change. Radiocarbon is a powerful tool for studying the carbon cycle due to its to its ~5700-year half-life that sheds light on processes occuring on centennial to millenial timescales, as well as the 14C “bomb spike” resulting from above-ground nuclear weapons testing in the mid-20th Century that serves as a tracer of carbon flow among more rapidly cycling pools. The “Radiocarbon Inventories of Switzerland” (“RICH”) project is a collaborative initiative that involves undertaking a first-of-its-kind, national-scale 14C survey spanning all major carbon pools and encompassing the five different Swiss ecoregions. The project is acquiring a comprehensive “snapshot” of 14C measurements for carbon species in the atmosphere, soils and the hydrophere (e.g. 14C in atmospheric and soil-derived gas samples, 14C in bulk samples and different sub-fractions of soil, water and sediment samples), and developing historical context through 14C analysis of natural archives and of archived samples spanning the pre-bomb era to the present. The measurements are being used to study various carbon cycle processes, including turnover rates of different soil carbon fractions, budgets of riverine carbon, and anthropogenic emissions of CO2 and CH4. New, integrated atmospheric-terrestrial-aquatic carbon cycle models are being developed and calibrated, and existing models are being evaluated. This presentation will outline the goals and scope of the RICH project, and provide illustrations of the information that is now flowing from this collaborative undertaking. The project structure is envisioned to serve as template that can be  adapted in carbon cycle studies on regional to global scales, and the scientific outcomes will be relevant not only to Switzerland but also to the broader understanding of carbon cycle processes.

How to cite: Eglinton, T., Graven, H., Hagedorn, F., Szidat, S., Brunmayr, A., Duborgel, M., Geissbuehler, D., Laemmel, T., Minich, L., Mittelbach, B., Rhyner, T., and White, M.: Constraining atmosphere-terrestrial-aquatic carbon cycle processes at national and ecoregional scales with radiocarbon data: Introducing the Radiocarbon Inventories of Switzerland (RICH) project, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-11622, https://doi.org/10.5194/egusphere-egu24-11622, 2024.

Land carbon fluxes
09:55–10:05
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EGU24-15104
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solicited
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On-site presentation
Global atmospheric CO2 inversions in RECCAP2 and GCP
(withdrawn)
Ingrid Luijkx and the GCB2023 inverse modelling team
10:05–10:15
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EGU24-15244
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On-site presentation
Julia Pongratz, Lea Dorgeist, Clemens Schwingshackl, and Selma Bultan

As the remaining carbon budget to limit global warming in line with the Paris Agreement is rapidly shrinking, accurate estimates of the emissions from land-use and land cover change (ELUC) and the terrestrial natural CO2 sinks (SLAND) are crucial. In current carbon budgeting approaches, the ELUC and SLAND estimates are conceptually not consistent, since they stem from two different model families that differ in how CO2 fluxes are attributed to environmental or land-use changes. Consequently, anthropogenic and natural budget terms are not fully distinguished. ELUC is estimated by bookkeeping models, which typically use time-invariant carbon densities representing contemporary environmental conditions. They thus assume a steady environmental state and neglect changes in environmental conditions preceding or succeeding a land-use change event, e.g., denser growing forests in response to rising atmospheric CO2 concentrations, which emit more when cleared for agricultural land. SLAND is estimated by dynamic global vegetation models, which account for environmental changes but assume that the land cover distribution remained at its pre-industrial state. They thus include carbon sinks in forests that in reality were cleared decades ago. Here we suggest an approach for consistent budgeting of ELUC and SLAND by integrating the response of vegetation and soil carbon to environmental changes, derived from dynamic global vegetation models, into a spatially explicit bookkeeping model (BLUE). A set of dedicated simulations allows us to disentangle and re-attribute environmental and land-use components of the land-atmosphere CO2 exchange. Our results show that land is a cumulative net source of CO2 since 1850, which contrasts current global carbon budgets indicating a net sink. The underlying reason is both a higher estimate of ELUC than previously suggested as well as a smaller land sink: The implementation of environmental changes increases global ELUC over time (14% compared to current estimates for 2012-2021) mainly due to increased emissions from deforestation and wood harvest, which are only partly offset by increased sinks through reforestation/afforestation and other regrowing vegetation. Our SLAND estimate calculated under actual land cover amounts to 3.0 GtC yr-1 for 2012-2021, which is substantially lower both globally and regionally compared to estimates assuming pre-industrial land cover: we find a SLAND is smaller by 0.7 GtC yr-1 in 2012-2021, i.e., 19% lower as compared to the conventional approach using pre-industrial land cover. The overestimate of SLAND under pre-industrial land cover is particularly pronounced in regions with strong ecosystem degradation, such as Southeast Asia, Brazil, and Equatorial Africa. The consistent estimation of terrestrial carbon fluxes is thus essential not only to provide a tangible estimate to monitor the progress of net-zero emission commitments and the remaining carbon budget, but also to highlight the need to protect remaining natural ecosystems for climate regulation. Our approach provides greater consistency with atmospheric inversions and provides a finer split of anthropogenic and natural fluxes useful for a direct comparison of global carbon cycle models to national greenhouse gas inventories.

How to cite: Pongratz, J., Dorgeist, L., Schwingshackl, C., and Bultan, S.: A consistent budgeting of terrestrial carbon fluxes , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-15244, https://doi.org/10.5194/egusphere-egu24-15244, 2024.

Coffee break
Chairpersons: Ana Bastos, Ben Poulter, Philippe Ciais
10:45–10:55
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EGU24-18116
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On-site presentation
Wolfgang Obermeier, Clemens Schwingshackl, Raphael Ganzenmüller, Ana Bastos, Philippe Ciais, Giacomo Grassi, Ingrid Luijkx, Stephen Sitch, and Julia Pongratz

CO2 fluxes from land use and land-use change (FLUC) are a major source of carbon to the atmosphere. They are composed of gross emissions, mainly from deforestation, peat burning, and peat drainage, and gross removals, mainly from re- and afforestation. The importance of FLUC for climate change mitigation strategies is increasing due to the potential of storing large carbon amounts via re- and afforestation, harvested wood products, and other vegetation-based carbon dioxide removal methods, such as bioenergy with carbon capture and storage. Yet, FLUC estimates remain largely uncertain and show substantial discrepancies between different quantification methods, which makes it challenging to provide reliable projections of their potential future evolution.

 

Here, we review the main characteristics, uncertainties, and discrepancies of individual methods used to estimate FLUC, and we highlight promising steps to reduce FLUC uncertainties and to harmonize the various FLUC estimates. Differences between the approaches are mainly due to differing definitions and assumptions, such as the definition of anthropogenic fluxes and managed land (leading to a gap in FLUC of ~1.8 GtC/yr in 2000-2020 between FLUC estimates by bookkeeping models used in the Global Carbon Project and inventory-based estimates reported by countries to the United Nations Framework Convention on Climate Change) and the inclusion of environmental effects on carbon stocks (leading to a gap of ~0.4 GtC/yr in 2000-2020 between FLUC estimates from dynamic global vegetation models and bookkeeping models). Furthermore, the individual estimation methods have large uncertainties, mainly arising from the usage of differing land-use forcing data, missing observational constraints, differences in how models implement individual processes, and the degree of implementation of land use practices in models.

 

To improve the confidence in the individual FLUC estimates, we argue for a systematic model evaluation and an improved parametrization of models, in particular regarding land-use forcing data, carbon densities of vegetation and soils, and the represented processes. Alongside, remaining framework inconsistencies, such as a precise and consistent definition of FLUC and the consideration of transient C densities need to be resolved. This undertaking requires developments in several directions. Earth observations may provide data on carbon densities in vegetation and soil at high spatial resolution, improved estimates of forest regrowth rates as well as impacts of forest management. Models need to be further improved to consider all relevant land-use processes and provide more fine-granular output to guarantee that the different estimates are comparable and/or translatable into each other.

 

Providing harmonized and more accurate FLUC estimates is essential to improve the stocktake of countries' land use-related CO2 emissions, to provide an accurate budget of the global carbon cycle, and to effectively plan and monitor land-based carbon dioxide removal methods.

How to cite: Obermeier, W., Schwingshackl, C., Ganzenmüller, R., Bastos, A., Ciais, P., Grassi, G., Luijkx, I., Sitch, S., and Pongratz, J.: Reviewing differences and uncertainties in land-use CO2 flux estimates, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-18116, https://doi.org/10.5194/egusphere-egu24-18116, 2024.

10:55–11:05
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EGU24-5576
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ECS
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On-site presentation
Yuanyi Gao, Xuhui Wang, Kai Wang, Yuxing Sang, Yilong Wang, Yuzhong Zhang, Songbai Hong, Yao Zhang, Wenping Yuan, and Shilong Piao

As one of the world’s economic engine and the largest greenhouse gases (GHGs) emitter of fossil fuel in the past two decades, China has expressed the recent ambition to reduce GHG emissions by mid-century. The status of GHG balance over terrestrial ecosystems in China, however, remains elusive. Here, we present a synthesis of the three most important long-lived greenhouse gases (CO2, CH4 and N2O) budgets over China during the 2000s and 2010s, following a dual constraint bottom-up and top-down approach. We estimate that China’s terrestrial ecosystems act as a small GHG sink (-29.0 ± 207.5 Tg CO2-eq yr-1 with the bottom-up estimate and -75.3 ± 496.8 Tg CO2-eq yr-1 with the top-down estimate). This net GHG sink includes an appreciable land CO2 sink, which is being largely offset by CH4 and N2O emissions, predominantly coming from the agricultural sector. Emerging data sources and modelling capacities have helped achieve agreement between the top-down and bottom-up approaches to within 25% for all three GHGs, but sizeable uncertainties remain. 

How to cite: Gao, Y., Wang, X., Wang, K., Sang, Y., Wang, Y., Zhang, Y., Hong, S., Zhang, Y., Yuan, W., and Piao, S.: The greenhouse gas budget of terrestrial ecosystems in China since 2000, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5576, https://doi.org/10.5194/egusphere-egu24-5576, 2024.

11:05–11:15
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EGU24-20466
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Highlight
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On-site presentation
Mathew Williams, David Milodowski, Smallman Luke, Iain McNicol, Kyle Dexter, Casey Ryan, Mike O'Sullivan, Aude Valade, Gabi Hegerl, and Stephen Sitch

Miombo woodlands are the world’s largest savanna, covering 2-3 M km2, and are the dominant land cover in the dry tropics of southern Africa. Here we quantify the dynamics of the miombo region carbon cycle, diagnosing stocks and fluxes and their interactions with climate and disturbance, and evaluate their representation in Trendy land surface models (LSMs). We produce a constrained multi-year analysis (2006-2017) using earth observation time series of total wood C (Cwood) and leaf area index to calibrate an intermediate complexity ecosystem model forced with observed climate, deforestation and burned area. Statistical analyses determine the relationships between carbon cycling, environmental and disturbance variables, and evaluate LSMs. The analysis suggests that the regional net biome production is neutral, 0.0 Mg C ha-1 yr-1 (95% Confidence Interval -1.7 - 1.6), with fire emissions contributing ~1.0 Mg C ha-1 yr-1 (95% CI 0.4-2.5). Spatial variation in biogenic fluxes and C pools is strongly correlated with mean annual precipitation. Burned area is also positively correlated with these pools and fluxes. Areas that are more frequently burned tend to have greater precipitation, and shorter residence time of Cwood. Fire-related mortality from Cwood to dead organic matter likely exceeds fire-related emissions from Cwood to atmosphere, and likely exceeds natural rates of Cwood mortality. LSMs match the biogenic fluxes of the analysis, but diverge on C stocks, timings of heterotrophic respiration and magnitude of fire emissions. The analysis suggests that climate, through precipitation, drives spatial variability in Cwood and GPP across the region. Fire disturbance is the major driver of losses from Cwood. Larger annual precipitation is correlated with both greater GPP and greater fire disturbance. These factors have opposing but unbalanced impacts on Cwood, but the precipitation-GPP effect dominates. Patterns of C cycling across the region are a complex outcome of climate controls on production, and vegetation-fire interactions.

How to cite: Williams, M., Milodowski, D., Luke, S., McNicol, I., Dexter, K., Ryan, C., O'Sullivan, M., Valade, A., Hegerl, G., and Sitch, S.: Fire-precipitation interactions control biomass carbon and net biome production across the world’s largest savanna, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20466, https://doi.org/10.5194/egusphere-egu24-20466, 2024.

11:15–11:25
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EGU24-14672
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On-site presentation
Matthias Forkel, Christine Wessollek, Niels Andela, Jos de Laat, Vincent Huijnen, Daniel Kinalczyk, Christopher Marrs, Dave van Wees, Ana Bastos, Philippe Ciais, Dominic Fawcett, Johannes W. Kaiser, Erico Kutchartt, Carine Klauberg, Rodrigo Vieira Leite, Wei Li, Carlos Silva, Stephen Sitch, Jefferson Goncalves De Souza, and Stephen Plummer

Fires in the Amazon are of great concern because they threaten the integrity of the tropical forest biome, the carbon cycle, and air quality. Fire emissions depend on the burning behaviour of vegetation biomass, woody debris, and litter. However, the effects of fuels on the combustion process and on the composition of fire emissions are simplified in current fire emission inventories and models. Several new fire emission approaches have recently been developed to better quantify fire emissions by either making use the improved spatial resolution of modern satellite observations or by developing new modelling approaches. 

Here we compare several current and novel approaches to quantify fuel consumption and fire emissions for the Amazon and Cerrado for the fire season in 2020. The approaches include the widely used GFAS, a top-down approach based on Sentinel-5p observations (KNMI.S5p), a bottom-up approach based on active fire observations from VIIRS (GFA.S4F), two bottom-up approaches based on MODIS burned area data (500-m version of GFED, REFIT.AC), a data-model fusion approach with dynamic emission factors that integrates several Earth observation products (TUD.S4F), and three dynamic global vegetation models in diagnostic mode with prescribed burned area. The different approaches to estimate fire emission show that forest and deforestation fires dominate the regional total fire emissions. However, large differences exist in the very high emissions of individual fires that mainly contribute to the regional total fire emissions. We found a higher agreement in estimated CO and NOx emissions between approaches for savannah fires (normalised RMSE < 20%) than for forest and deforestation fires (nRMSE 30%). We estimate that only 10% of all fire events contribute between 85% and 97% of the regional total fire emissions. By using the TUD.S4F data-model fusion approach with dynamic emission factors, we show that most fire CO emissions originate from the burning of woody debris, which burns with low combustion efficiency and hence has higher emission factors for CO. Comparisons with regional field-based investigations show, however, large differences in estimates of surface fuel loads and fuel consumption. Our results demonstrate the advantage of exploring several complementary fire emission approaches to better understand the underlying processes and to account for regional to global fire emissions and their uncertainties.

How to cite: Forkel, M., Wessollek, C., Andela, N., de Laat, J., Huijnen, V., Kinalczyk, D., Marrs, C., van Wees, D., Bastos, A., Ciais, P., Fawcett, D., Kaiser, J. W., Kutchartt, E., Klauberg, C., Leite, R. V., Li, W., Silva, C., Sitch, S., Goncalves De Souza, J., and Plummer, S.: Multiple approaches for quantifying fuels, combustion dynamics, and regional fire emissions in the Amazon and Cerrado, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14672, https://doi.org/10.5194/egusphere-egu24-14672, 2024.

11:25–11:35
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EGU24-5271
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ECS
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On-site presentation
Nicolas Behrens, Klaus-Holger Knorr, and Mana Gharun

Peatlands are the world’s largest storage of soil organic carbon. While natural peatlands act as sinks of atmospheric carbon, drainage and disturbance (e.g., due to land use and climate change) turn peatlands into net carbon sources. Greenhouse gas (GHG) emissions from drained peatlands are therefore part of national GHG-emission reports, guided by the IPCC wetlands supplement. Herein, default emission factors (EF) are defined both for drained and rewetted peatlands, the former split into tropical and boreal/temperate wetlands, the latter further sub-categorized into nutrient poor and rich peatlands. These default emission factors are to date largely based on a limited number of static chamber-based studies, many measured over relatively short periods of time (1-3 years). As carbon flux measurements on peatlands have gained more attention, recent publications have added several new datasets to the EF calculations, significantly reducing the EF and narrowing confidence intervals. However, the final values are still almost entirely derived from chamber-based measurements with inherent limitations and uncertainties.

The Eddy-Covariance (EC) method is an alternative, established method to quantify carbon fluxes from ecosystems, spatially and temporally integrated (typically every 30 min throughout the year, representing a “flux-footprint” covering a whole ecosystem). As EC-based measurements are increasingly applied and such data are now available from several disturbed peatlands over several years, it is plausible to revise the default EFs. In this study we compile global EC time series for CO2 fluxes from disturbed peatlands of different land use categories with a focus on drained and rewetted peatlands affected by no or by  minor extensive management practices.  We investigate the diurnal, seasonal and annual variability of the fluxes. The net carbon emissions are compared to the EFs currently in use. With available ancillary data such as climate, water table depths, nutrients, ecosystem type and (succession-) state of the ecosystem we asses controlling factors for carbon fluxes. This investigation yields important context to evaluate the uncertainty and reliability of default emission factors for disturbed peatlands. Additionally, we apply a process-based model (CoupModel) to an own study-site to generate a higher-tier emission factor, including seasonality and climate variations.

How to cite: Behrens, N., Knorr, K.-H., and Gharun, M.: Peatland IPCC emission factors in the light of new EC carbon flux time series, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-5271, https://doi.org/10.5194/egusphere-egu24-5271, 2024.

11:35–11:45
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EGU24-10840
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ECS
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Highlight
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On-site presentation
Anna Virkkala, Isabel Wargowsky, Judith Vogt, McKenzie Kuhn, Susan Natali, Brendan Rogers, Mathias Goeckede, Kyle Arndt, Jennifer Watts, Tiffany Windholz, and Simran Madaan

The Arctic-boreal zone and its permafrost regions have historically been sparsely measured for carbon dioxide and methane fluxes. This data sparsity has created significant uncertainties in Arctic-boreal carbon budget estimates. However, over the past decade, the availability of Arctic-boreal carbon flux data has increased substantially. Yet, it remains scattered across different repositories, papers, and unpublished sources, making it hard to estimate more accurate Arctic-boreal carbon budgets. To address this research gap, we have compiled a database of Arctic-boreal carbon fluxes (ABCFlux v2) from flux repositories, literature, and site principal investigators, which will be openly distributed. The database includes carbon dioxide fluxes of gross primary production, ecosystem respiration, and net ecosystem exchange, and plant-mediated, diffusive, ebullitive, and storage methane fluxes measured with eddy covariance and chamber techniques with supporting methodological and environmental metadata from terrestrial (including wetland) and freshwater ecosystems. It has in total over 12,000 site-months and 30,000 unique monthly flux values, therefore almost doubling earlier synthesis efforts in the region. Here, we present preliminary results on carbon flux magnitudes across key land cover types and multidecadal trends based on the in-situ data and machine-learning based upscaling. These indicate, for example, that the Arctic-boreal region has been an increasing annual terrestrial net ecosystem CO2 sink with the boreal biome primarily driving this trend. This collaborative initiative, involving contributions from over 100 researchers, serves as an important step in reducing uncertainties in Arctic-boreal carbon budgets and enhancing our understanding of climate feedbacks.

How to cite: Virkkala, A., Wargowsky, I., Vogt, J., Kuhn, M., Natali, S., Rogers, B., Goeckede, M., Arndt, K., Watts, J., Windholz, T., and Madaan, S.: A new synthesis of Arctic-boreal carbon fluxes for improved carbon budget estimates, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-10840, https://doi.org/10.5194/egusphere-egu24-10840, 2024.

11:45–11:55
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EGU24-7366
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Virtual presentation
Luke Smallman and Eleanor Burke

Globally permafrost soils store huge quantities of carbon (C) in dead organic matter (DOM). Currently, the permafrost region is estimated to be a small net C sink. However, as the climate warms permafrost soils have begun to thaw, making a massive quantity of DOM available for potential decomposition and likely shifting the region to a net source of C. Process-models of terrestrial ecosystems are a vital tool in evaluating our understanding of ecosystem function, but also in generating forecasts of C emissions under varied climate change scenarios in support of decision support. But different models contain competing hypothesise of ecosystem functioning, leading to divergent forecasts despite convergent estimates of contemporary net C emissions. These process-models also result in contrasting estimates of the internal C-cycling. We currently lack a consistent, rigorous observational constraint on ecosystem C-stocks and dynamics (particularly below ground) due to varied challenges across both in-situ and satellite-based Earth Observation (EO). Here, we present a Bayesian model-data fusion approach (CARDAMOM) which combines diverse observations of terrestrial ecosystems (e.g. leaf area, soil C, biomass, net C exchange) to calibrate an intermediate complexity model (DALEC). CARDAMOM generates a probabilistic estimates of DALEC parameters at pixel scale based on local information. Using these local calibrations, DALEC offers a probabilistic, data-constrained estimate of current ecosystem C-cycling including its internal dynamics, which can be used to evaluate large scale process-models. We evaluate process-model estimates of key ecosystem properties, e.g. DOM residence time, and their climate sensitivity. Through this process we can identify and exclude process-models which are inconsistent with data from forecast analyses.

How to cite: Smallman, L. and Burke, E.: Quantifying permafrost C-cycling by fusing process-models and observations , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7366, https://doi.org/10.5194/egusphere-egu24-7366, 2024.

11:55–12:05
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EGU24-8175
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On-site presentation
Luana Basso, Christian Rödenbeck, Victor Brovkin, Goran Georgievski, and Mathias Göckede

Atmospheric methane levels (the second largest contributor to climate change) have more than doubled over the last 200 years, though with highly variable trends over time. The relative contribution of different sources and sinks to the global CH4 budget remains uncertain despite ongoing efforts to improve the estimates based on various approaches, and particularly the causes for an accelerated increase in recent years remain unclear. Therefore, understanding and quantifying methane sources at global to regional scales is essential to reduce uncertainties in the global methane budget and its feedback with the climate system.

Within the Arctic region, wetlands and lakes constitute a major natural source of methane. With temperatures rising at rates at least twice the global average over the last decades, Arctic permafrost is increasingly thawing. Associated disturbance processes hold the potential to increase methane emissions, and as a consequence result in a positive feedback to climate change. However, until now neither observations nor model estimates could provide clear evidence of such a trend in emissions. As a consequence, current and possible future contributions of Arctic ecosystems to the accelerated increase in the global atmospheric methane levels remain highly uncertain.

To help reduce methane emission uncertainties in the high northern latitudes, we estimated global CH4 fluxes to the atmosphere using the Jena CarboScope Global Inversion System, with a strong focus of our analysis on the Arctic region. We used wetland flux from JSBACH model as prior and assimilated atmospheric observations from regional networks available over the last years for the region above 60°N latitude (a total of 23 towers) to quantify the methane emissions over this region between 2010 to 2020. We found a clear seasonal pattern with emission peaks during July and August. As a sensitivity test to evaluate the improvement to constrain the Arctic methane fluxes with the assimilation of the regional data, we also conducted an inversion using just the global background surface stations (a total of 30 global stations). We found higher mean annual methane flux to the atmosphere when assimilating the regional data, with the largest difference between May to August. These estimates were finally evaluated against an ensemble of inverse model estimates from Global Methane Project available for the period between 2010 to 2017.

How to cite: Basso, L., Rödenbeck, C., Brovkin, V., Georgievski, G., and Göckede, M.: Estimating methane emissions at high northern latitudes using regional data and global inverse modelling, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8175, https://doi.org/10.5194/egusphere-egu24-8175, 2024.

12:05–12:15
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EGU24-12481
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Highlight
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On-site presentation
Martin R. Manning, Euan G. Nisbet, Sylvia E. Michel, Xin Lan, Ed Dlugokencky, David Lowry, Rebecca E. Fisher, and James L. France

From 2020, the atmospheric methane burden has grown at the fastest rate in the detailed observational record. This rise has been accompanied by an unprecedented plunge in d13C(CH4). The causes of recent accelerated growth are as yet uncertain but the geographic spread of growth and the rapid isotopic plunge suggest strong rises in isotopically light emissions from both Tropical and Boreal wetlands. These emissions may be due to rising precipitation and temperatures in parts of the tropics, and by rising temperatures in northern Canada, Siberia, and Europe. Over the longer period since 2007, methane’s actual growth is comparable to methane’s growth in the ‘worst case’ very high baseline emission scenario RCP8.5 (8.5 W/m2 forcing increase relative to pre-industrial). If the recent trend were to continue for more than another decade it could make the 2°C target as hard to achieve as the 1.5°C target is now. Natural feedbacks to climate warming in wetlands need to be included in future modelling and should be incorporated in climate modelling projects such as CMIP7. Methane’s recent accelerated growth also has wide implications for climate negotiations as it reduces the permissible total anthropogenic greenhouse gas emissions if the Paris Agreement is to be achieved. Strong growth in non-anthropogenic methane emissions, driven by feedback impacts on natural and quasi-natural sources, was not expected in modelling at the time of the Paris Agreement and shows the urgency of improving our understanding of the feedback impacts of climate change. The simplest way to limit methane’s growth is for all nations,  including non-signatory countries, to cut anthropogenic emissions urgently and sharply, meeting or exceeding the targets of the Global Methane Pledge.

How to cite: Manning, M. R., Nisbet, E. G., Michel, S. E., Lan, X., Dlugokencky, E., Lowry, D., Fisher, R. E., and France, J. L.: Methane’s record rise 2020-2023: likely causes, impacts and consequences, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12481, https://doi.org/10.5194/egusphere-egu24-12481, 2024.

12:15–12:25
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EGU24-2492
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On-site presentation
Ulas Im, Kostas Tsigaridis, Susanne Bauer, Sabine Eckhardt, Drew Shindell, Lise Lotte Sørensen, and Simon Wilson

We have used the NASA Goddard Institute for Space Studies (GISS) Earth system model GISS-E2.1 to study the future budgets and trends of global and regional CH4 under different emission scenarios. GISS-E2.1 is one of the few ESMs that can be driven by anthropogenic CH4 emissions, as well as interactive natural sources such as wetlands, and can simulate the tropospheric CH4 chemistry. In frame of the recent short-lived climate forcers (SLCFs) assessment by the Arctic Monitoring and Assessment Programme (AMAP), we used the GISS-E2.1 model with prescribed long-lived greenhouse gas (GHG) concentrations. In the present study, we have supplemented these simulations using the interactive CH4 sources and sinks in order to quantify the model performance and the sensitivity to CH4 sources and sinks. We have used the Current Legislation (CLE) and the Maximum Feasible Reduction (MFR) emission scenarios from the Eclipse V6b emission database to simulate the future chemical composition and climate impacts from 2015 to 2050. We have also simulated 1995-2014 in order to evaluate the model performance following the AMAP-SLCF protocol.

The prescribed GHG version underestimates the Global Atmospheric Watch (GAW) surface CH4 observations during the period between 1995 and 2023 by 1% [-8.4%-2.0%], with a correlation (r) of 0.71 [-0.41 0.99]. The largest underestimations are over the continental emission regions such as North America, Europe, and Asia, while biases are smallest over oceans. On the other hand, the simulation with interactive sources and sinks underestimates the GAW observations more than the prescribed simulation, by 18.5% [-25% -10.4%], with a lower r of 0.36 [-0.82 0.93]. Opposite to the prescribed simulation, the biases are largest over oceans and smaller over the continents, however they are still larger over land than the prescribed simulation. The interactive simulation, with large sources virtually over land and strong sink over oceans, has a land/ocean ratio larger than 1 while the prescribed simulation has this ratio equal to 1 as it distributes the global prescribed CH4 concentration equally in longitude over a given latitude. This clearly shows that the interactive sources and sinks should be represented in models in order to realistically simulate the chemical composition and the oxidative capacity of the atmosphere.

As expected, the MFR scenario simulates lower global surface CH4 concentrations and burdens compared to the CLE scenario, however in both cases, global surface CH4 and burden continue to increase through 2050 compared to present day.  In the CLE scenario, increases are largest over the equatorial belt, in particular over India and East China, while the MFR scenario shows increases over the whole Southern Hemisphere, however much smaller compared to CLE. Finally, the interactive simulation shows that the chemical CH4 sink increases in the CLE scenario, while it slightly decreases in the MFR, leading to a larger CH4 lifetime in the MFR scenario compared to in the CLE scenario.

How to cite: Im, U., Tsigaridis, K., Bauer, S., Eckhardt, S., Shindell, D., Sørensen, L. L., and Wilson, S.: Future CH4 budgets as modelled by a fully coupled Earth system model using prescribed GHG concentrations vs. interactive CH4 sources and sinks, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2492, https://doi.org/10.5194/egusphere-egu24-2492, 2024.

Posters on site: Thu, 18 Apr, 16:15–18:00 | Hall X1

Display time: Thu, 18 Apr 14:00–Thu, 18 Apr 18:00
X1.1
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EGU24-19922
Raffaele Bernardello, Valentina Sicardi, Vladimir Lapin, Pablo Ortega, Yohan Ruprich-Robert, Etienne Tourigny, and Eric Ferrer

Given the role of the ocean in mitigating climate change through CO2 absorption, it is important to improve our abil ity to quantify the historical ocean CO2 uptake, including its natural variability, for carbon budgeting purposes. In this study we present an exhaustive intercomparison between two ocean modelling practices that can be used to reconstruct the historical ocean CO2 uptake. By comparing the simulations to a wide array of ocean physical and biogeochemical observational datasets, we show how constraining the ocean physics towards observed temperature and salinity results in a better representation of global biogeochemistry. We identify the main driver of this improvement to be a more realistic representation of large scale meridional overturning circulation together with improvements in mixed layer depth and sea surface temperature. Nevertheless, surface chlorophyll was rather insensitive to these changes, and, in some regions, its representation worsened. We identified the causes of this response to be a combination of a lack of robust parameter optimization and limited changes in environmental conditions for phytoplankton. We conclude that although the direct validation of CO2 fluxes is challenging, the pervasive improvement observed in most aspects of biogeochemistry when applying data assimilation of observed temperature and salinity is encouraging; therefore, data assimilation should be included in multi-method international efforts aimed at reconstructing the ocean CO2 uptake.

How to cite: Bernardello, R., Sicardi, V., Lapin, V., Ortega, P., Ruprich-Robert, Y., Tourigny, E., and Ferrer, E.: Ocean biogeochemical reconstructions to estimate historical ocean CO2 uptake, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-19922, https://doi.org/10.5194/egusphere-egu24-19922, 2024.

X1.2
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EGU24-13846
Laurie Menviel, Paul Spence, Andrew Kiss, Matthew Chamberlain, Hakase Hayashida, Matthew England, and Darryn Waugh

While the Southern Ocean (SO) provides the largest oceanic sink of carbon, some observational studies have suggested that the SO total CO2 (tCO2) uptake exhibited large (~0.3 GtC/yr) decadal-scale variability over the last 30 years, with a similar SO tCO2 uptake in 2016 as in the early 1990s. Here, using an eddy-rich ocean, sea-ice, carbon cycle model, with a nominal resolution of 0.1°, we explore the changes in total, natural and anthropogenic SO CO2 fluxes over the period 1980-2021 and the processes leading to the CO2 flux variability.

The simulated tCO2 flux exhibits decadal-scale variability with an amplitude of ~0.1 GtC/yr globally in phase with observations. Notably, two stagnation in tCO2 uptake are simulated between 1982 and 2000 as well as since 2012, while a re-invigoration is simulated between 2000 and 2012. This decadal-scale variability is primarily due to changes in natural CO2  (nCO2) fluxes south of the polar front associated with variability in the Southern Annular Mode (SAM). Positive phases of the SAM lead to enhanced SO nCO2 outgassing due to higher surface natural dissolved inorganic carbon (DIC) brought about by a combination of Ekman-driven vertical advection and DIC diffusion at the base of the mixed layer. The pattern of the CO2 flux anomalies indicate a dominant control of the interaction between the mean flow south of the polar front and the main topographic features. While positive phases of the SAM also lead to enhanced anthropogenic CO2 (aCO2) uptake south of the polar front, the amplitude of the changes in aCO2 fluxes is only 25% of the changes in nCO2 fluxes. Due to the larger nCO2 outgassing compared to aCO2 uptake as the SH westerlies strengthen and shift poleward, the SO tCO2 uptake capability thus reduced since 1980 in response to the shift towards positive phases of the SAM.

 

How to cite: Menviel, L., Spence, P., Kiss, A., Chamberlain, M., Hayashida, H., England, M., and Waugh, D.: Reduced Southern Ocean CO2 uptake due to the positive SAM trend, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13846, https://doi.org/10.5194/egusphere-egu24-13846, 2024.

X1.3
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EGU24-12756
Nicolas Mayot, Corinne Le Quéré, and Andrew Manning

Despite major advances in the estimation of all fluxes in the global cycles of carbon and oxygen, mathematical imbalances continue to arise when these fluxes are combined. Between 1997 and 2022, the global budget imbalances (BIM) for CO2 and O2 budgets – a quantification of the missing sources and/or sinks of CO2 and O2 – are -18 Tmol/yr and 41 Tmol/yr, respectively. The CO2 BIM has tended to become increasingly negative over the last decade, while the O2 BIM has tended to become increasingly positive. To identify the origins of the BIMs, we carried out a systematic analysis of the combination and permutation of all available individual flux estimates provided by a sub-set of contributors to the Global Carbon Budget 2023 update. We first examine the possibility that inaccuracies in the ocean air-sea fluxes contributes to the CO2 and O2 BIM. We show that the interannual variability of the air-sea O2 flux required for a reduction of the O2 BIM tends to be close to that simulated by several ocean models. An in-depth analysis of the Southern Ocean has confirmed their ability to simulate reasonable interannual variability in the air-sea fluxes of O2 and CO2. We conclude that in order to simultaneously reduce the negative trend in CO2 BIM and the positive trend in O2 BIM in the recent decade, a reduction in the increasing trend in the terrestrial CO2 sink over the last decade is most likely required.

How to cite: Mayot, N., Le Quéré, C., and Manning, A.: Identifying the origins of the global carbon budget imbalance using oxygen, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12756, https://doi.org/10.5194/egusphere-egu24-12756, 2024.

X1.4
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EGU24-2178
Qianlai Zhuang

Land and freshwater ecosystems play a significant role in affecting the global methane budget. With future warming, the increase of methane emissions could create large positive feedbacks to the global climate system.  We have used observation data of methane fluxes from diverse land and freshwater ecosystems to calibrate and evaluate extant land and freshwater biogeochemistry models of the Terrestrial Ecosystem Model (TEM) and the Arctic Lake Biogeochemistry Model (ALBM) to quantify the global methane emissions for the past few decades and the 21st century in a temporally and spatially explicit manner. Land ecosystems could emit methane from wetlands while uplands could uptake atmospheric methane. TEM simulates that global wetlands emissions are 212 ± 62 and 212 ± 32 Tg CH4 yr−1 due to uncertain parameters and wetland type distribution, respectively, during 2000–2012. After combining the global upland methane consumption of −34 to −46 Tg CH4 yr−1, we estimate that the global net land methane emissions are 149–176 Tg CH4 yr−1 due to uncertain wetland distribution and meteorological input. During 1950–2016, both wetland emissions and upland consumption increased during El Niño events and decreased during La Niña events. For freshwater ecosystems, we find that current emissions are 24.0 ± 8.4 Tg CH4 yr−1 from lakes larger than 0.1 km2. Future projections under the RCP8.5 scenario suggest a 58–86% growth in emissions from lakes.  Warming enhanced methane oxidation in lake water can be an effective sink to reduce the net release from global lakes. Additionally, these studies identify the key biogeochemical and physical processes of controlling methane production, consumption, and transport in various hotspot emission regions.  We also highlight the need for more in situ methane flux data, more accurate wetland and lake type and their area distribution dynamics information to better constrain the quantification uncertainty of global biogenic methane emissions across the landscape.

How to cite: Zhuang, Q.: Quantifying global biogenic methane emissions from land and freshwater ecosystems across the landscape , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2178, https://doi.org/10.5194/egusphere-egu24-2178, 2024.

X1.5
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EGU24-9609
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ECS
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Sanam Noreen Vardag, Lukas Artelt, Eva-Marie Metz, Sourish Basu, Martin Jung, and André Butz

Understanding terrestrial carbon fluxes is a prerequisite for accurately predicting the global biospheric uptake and release of CO2 under climate change and other environmental stressors. Terrestrial carbon fluxes in the southern hemisphere still exhibit quite large uncertainties due to limited measurements and a lack of comprehensive process understanding. This study focuses on the South American Temperate (SAT) region, employing various Dynamic Global Vegetation Model (DGVM) models (TRENDY v9) to investigate carbon flux dynamics. We find significant discrepancies between these DGVM models in terms of both phasing and magnitude. To address this, atmospheric XCO2 measurements from the Greenhouse Gases Observing Satellite (GOSAT) during the period 2009-2018 are incorporated into an atmospheric inversion using the model TM5-4DVar to obtain net CO2 fluxes. We identify DGVM models that match the inversion results, particularly showing the same phasing and similar magnitude of net ecosystem exchange (NEE) as the inversion results. The matching DGVMs show that the increase in NEE during the mid of the year is driven by an early increase in heterotrophic respiration whereas the autotrophic respiration remains in phase with the gross primary production (GPP) and is delayed with respect to heterotrophic respiration. The observed flux behavior is linked to the onset of rainfall in the semi-arid regions of SAT, resembling findings in Australia by Metz et al. (2023). We hypothesize that soil rewetting processes in semi-arid areas play an important role in constraining the global carbon budget and should be represented more accurately in global carbon cycle models to improve the estimation of the global carbon budget.  

 

Metz, E.-M., Vardag, S.N., Basu, S., Jung, M., Ahrens, B., El-Madany, T., Sitch, S., Arora, V.  K., Briggs, P. R., Friedlingstein, P., Goll, D.S., Jain, A.K.,  Kato, E., Lombardozzi, D., Nabel,J .E. M. S., Poulter, B., Séférian, R., Tian, H., Wiltshire, A., Yuan, W., Yue, X., Zaehle, S.,  Deutscher, N.M.,  Griffith, D.W.T., Butz, A. Soil respiration–driven CO2 pulses dominate Australia’s flux variability. Science, 379, 1332-1335, https://doi.org/10.1126/science.add7833, 2023. 

How to cite: Vardag, S. N., Artelt, L., Metz, E.-M., Basu, S., Jung, M., and Butz, A.: Terrestrial Carbon Flux Dynamics in the Southern American Temperate Region: Insights from Dynamic Global Vegetation Models and GOSAT XCO2 Measurements  , EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9609, https://doi.org/10.5194/egusphere-egu24-9609, 2024.

X1.6
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EGU24-4150
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ECS
Wahaj Habib and John Connolly

Climate change poses a significant environmental challenge for humanity, and accurately predicting its intensity as well as its impact on terrestrial ecosystems is crucial. To achieve this, monitoring, modelling, and mapping greenhouse gas (GHG) exchanges between the biosphere and the atmosphere is essential. Monitoring is also important to achieve the European Union’s goal to achieve a balance between GHG emissions and removals by 2050 and maintain negative emissions thereafter. While in situ measurement techniques, such as the eddy covariance flux tower (ECFT), have been used for decades to measure ecosystem-level exchanges of carbon, such as Net Ecosystem Exchange (NEE) of CO2, their footprint is limited to only 1 km². To overcome this limitation, satellite remote sensing data has been used to upscale these measurements to regional and global scales, but previous work has relied on low-resolution remote sensing data, such as the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor (at 250m or 500m spatial resolution).

 

This study aims to use a combination of high-resolution remote sensing data and measurements from in situ ECFT data to model the NEE of CO2 across ~92% of Ireland's terrestrial area, covering major land covers such as wetlands (coastal and peatlands), grassland, and forestry. The model will integrate datasets from both ESA (Copernicus Sentinel-1 and 2) and NASA (MODIS PAR) with the light response curve parameters derived from the ECFT data in Ireland, to model NEE CO2 at a national scale. The results will be useful for monitoring, reporting, and verifying NEE across a range of ecosystems in Ireland. They can also be used to enhance National Inventory Reporting and national ambitions on climate, influence targeted policymaking, and verify land management decisions.

How to cite: Habib, W. and Connolly, J.: Satellite-driven model to upscale Irish CO2 Net Ecosystem Exchange (ICONEEx), EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4150, https://doi.org/10.5194/egusphere-egu24-4150, 2024.

X1.7
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EGU24-6930
|
ECS
Updates of a Global CO2 Emission Inventory (1960–2019) with Highly Resolved Source Information
(withdrawn)
Ruibin Xu
X1.8
|
EGU24-12156
Anjumol Raju, Sophie Wittig, Martin Vojta, Omid Nabavi, Peter Redl, Antje Hoheisel, Marcus Hirtl, Christine Groot Zwaaftink, and Andreas Stohl

Atmospheric carbon dioxide (CO2) is a significant greenhouse gas, and its concentration has increased by 51% compared to the pre-industrial value. Concerning its impact on the earth’s climate system, there is an urge to reduce CO2 emissions, hence mitigating global warming and climate change. This requires adequate knowledge of its source-sink distribution and quantification of the CO2 budget. Inverse modeling has emerged as an effective tool to constrain greenhouse gas (GHG) fluxes using the spatiotemporal pattern of atmospheric concentration measurements. In this regard, this study focuses on estimating CO2 fluxes over Europe using the Bayesian inverse modelling framework FLEXINVERT during the year 2021. In-situ CO2 concentrations were taken from various locations across Europe (World Data Centre for Greenhouse Gases, WDCGG) and data were averaged every 3 hours. The Lagrangian Particle Dispersion Model FLEXPART (FLEXible PARTicle) is employed to calculate the source-receptor relationship (SRR). The FLEXPART model has been run backward in time to trace back the particles (released from the locations of observation sites) for 10 days. Background CO2 concentrations are calculated using the sensitivity of concentration at the termination points from FLEXPART and the global 3D concentration from the FLEXible PARTicle-chemical transport model (FLEXPART-CTM). The uncertainty reduction, calculated from posterior and prior flux uncertainties, indicates how well the prior fluxes are optimized. In addition, longer backward simulations can be carried out to assess the impact of transport on background CO2 concentrations and the uncertainty reduction.

How to cite: Raju, A., Wittig, S., Vojta, M., Nabavi, O., Redl, P., Hoheisel, A., Hirtl, M., Zwaaftink, C. G., and Stohl, A.: Constraining CO2 fluxes over Europe using FLEXINVERT and in-situ measurements, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12156, https://doi.org/10.5194/egusphere-egu24-12156, 2024.

X1.9
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EGU24-8349
|
ECS
Ida Bagus Mandhara Brasika, Pierre Friedlingstein, Stephen Sitch, and Michael O'Sullivan

Indonesia is currently known as one of the three largest contributors of carbon emissions from land and land cover change (LULCC) globally, together with Brazil & the Democratic Republic of Congo. However, there is a limited reliable data on LULCC across Indonesia, leading to a lack of agreement on drivers and trends in carbon emissions. This can also be seen in the annual global carbon budget (GCB). Here, we assess the new satellite-based land cover dataset from Mapbiomas over Indonesia to illustrate how changes in forest and agriculture (mainly palm oil) areas across Indonesia determine trends in carbon emissions from land use change (ELUC). ELUC is simulated with a process-based Dynamic Global Vegetation Model, JULES-ES using annually varying LULCC maps from Mapbiomas as input. Our results show that the forest loss and agriculture expansion have a strong correlation and trend in the last two decades. Furthermore, palm oil plantation is the major contribution to the forest-agriculture dynamics, mainly appearing in Kalimantan & Sumatera island. This dynamic has a major impact on Indonesia ELUC with a positive trend in ELUC of 0.06 PgC/yr2 since 2000 . The use of the satellite-based dataset, Mapbiomas, is shown to improve our understanding of the LULCC dynamics over Indonesia, hopefully contributing to a reduction of the ELUC uncertainty for Indonesia and the SE Asia region.

How to cite: Brasika, I. B. M., Friedlingstein, P., Sitch, S., and O'Sullivan, M.: Drivers and trends in Land-use change and associated carbon emissions over Indonesia, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8349, https://doi.org/10.5194/egusphere-egu24-8349, 2024.

X1.10
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EGU24-7267
|
ECS
Chaerin Park and Sujong Jeong

The global atmospheric CO2 growth rate is a product of the combined effects of emissions and uptake from both anthropogenic and natural carbon sources. Therefore, an evaluation of the global CO2 growth rate should be preceded to understand the global carbon-climate process. In this study, we analyzed the long-term changes in the global CO2 growth rate from 1991 to 2020, using data from 42 global sites and model simulations to assess recent changes in the global carbon-climate feedback process. Our results indicate that the annual CO2 growth rate has increased by 0.032 ppm yr-2 since the 2000s. A comprehensive assessment of carbon cycle components contributing to atmospheric CO2 growth rate changes reveals that the strengthening of this rate is linked to a decline in terrestrial carbon absorption over the last decade. This decline is primarily associated with a slowdown in the increasing trend of Net Primary Productivity. Consequently, the reduced terrestrial carbon uptake in recent decades contributed to an approximately 3 ppm increase in global CO2 concentration by 2020. Our findings highlight that the vegetation's carbon uptake capacity can no longer offset anthropogenic CO2 emissions, underscoring the importance of achieving global carbon neutrality in climate change mitigation.

 

This work was supported by Korea Environment Industry & Technology Institute(KEITI) through Project for developing an observation-based GHG emissions geospatial information map, funded by Korea Ministry of Environment(MOE) (RS-2023-00232066)

How to cite: Park, C. and Jeong, S.: Recent increasing trend of global CO2 growth rate due to a slowdown in terrestrial carbon uptake, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7267, https://doi.org/10.5194/egusphere-egu24-7267, 2024.

X1.11
|
EGU24-3721
Zhenchuan Niu

Radiocarbon can be used as an independent and objective tracer to evaluate fossil fuel CO2 (CO2ff) emissions, because of its complete depletion in fossil fuel sources. Here, we present a study on the CO2ff emissions reduction during the COVID-19 lockdowns in 2020 based on atmospheric Δ14CO2 observation at Chinese background sites. We observed obvious enhancements (several per mill to dozens of per mill) of atmospheric Δ14CO2 during the COVID-19 lockdowns compared with that in the same period. A preliminary analysis showed that these enhancements indicate several percepts to dozens of percents CO2ff emissions reduction from Eurasia (exclude China) and different parts in China during the COVID-19 lockdowns.

How to cite: Niu, Z.: Decrease in fossil fuel CO2 emissions during COVID-19 lockdowns based on  Δ14CO2 observation, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-3721, https://doi.org/10.5194/egusphere-egu24-3721, 2024.

X1.12
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EGU24-9459
Giulia Zazzeri, Francesco Apadula, Andrea Lanza, and Stephan Henne

Methane and carbon dioxide mole fractions are measured continuously at the atmospheric station at Plateau Rosa since 2018, with a Picarro cavity ring down spectrometer G2301. The station, at 3480 meter MSL, represents an ideal location for, on one hand, measurements of background air and, on the other hand, intercepting air with recent boundary layer contact. Since 2021 the site contributes as an atmospheric station to the ICOS network.

In this study we present the methodology used to filter background data, and we provide an analysis of the continuous record of CH4 since 2018. We used Hysplit back trajectories and the FLEXPART atmospheric transport model coupled with EDGAR inventories to identify source areas in Europe. We focused our analysis on April 2022, when the CH4 increment above the baseline was consistently high.

We demonstrate how the CH4 mole fraction data measured at the station at Plateau Rosa provide information on the global CH4 trend, and that, with our continuous record, we can detect high emissions events over Europe.

How to cite: Zazzeri, G., Apadula, F., Lanza, A., and Henne, S.: The methane record at the ICOS background station at Plateau Rosa: identification of source areas in Europe, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-9459, https://doi.org/10.5194/egusphere-egu24-9459, 2024.

X1.13
|
EGU24-8601
|
ECS
Sophie Wittig, Anjumol Raju, Seyed Omid Nabavi, Martin Vojta, Peter Redl, Antje Hoheisel, Marcus Hirtl, Christine Groot Zwaaftink, and Andreas Stohl

In recent years, methane (CH4) has attracted increasing scientific attention as the second most abundant anthropogenic greenhouse gas (GHG) in the atmosphere. Due to the high reduction potential and the relatively short atmospheric lifetime of around 9 years, mitigation measures can become effective within a relatively short period of time. However, the current estimates of CH4 fluxes from emission inventories are still subject to uncertainties at both global and regional scale.

An effort to reduce uncertainties from those bottom-up flux estimates is given by inverse modelling, which provides a robust tool to verify GHG emissions by combining GHG observations as well as atmospheric transport modelling and statistical optimization.

In this study, we use an inverse modelling approach to estimate CH4 fluxes at European scale for the year 2022. Additionally, we use the European in-situ observation network to explore the feasibility of reducing uncertainties in CH4 fluxes in Austria, a European country with a limited availability of stationary observations. This work is part of the Austrian ASAP18 flagship project “GHG-KIT: Keep it traceable”.

Hereby, the inverse modelling tool FLEXINVERT is used, which is based on the backward simulations of the Lagrangian particle dispersion model FLEXPART (FLEXible PARTicle). In particular, we investigate to what extent prolonged backward trajectories of 50 to 100 days contribute to better constrain the CH4 fluxes. In an attempt to estimate background concentrations as accurately as possible, we use global CH4 concentration fields obtained with the chemical transport model FLEXPART (CTM).

How to cite: Wittig, S., Raju, A., Nabavi, S. O., Vojta, M., Redl, P., Hoheisel, A., Hirtl, M., Groot Zwaaftink, C., and Stohl, A.: Estimation of methane emissions at European scale with a special focus on Austria, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-8601, https://doi.org/10.5194/egusphere-egu24-8601, 2024.

X1.14
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EGU24-12441
|
ECS
Nicole Montenegro, Marielle Saunois, Antoine Berchet, Adrien Martinez, Philippe Bousquet, and Isabelle Pison

Methane (CH4) is the second most important greenhouse gas, contributing to approximately 30% of the additional greenhouse effect since 1750. Its varied sources and relatively short lifetime in the atmosphere (~9 years) offer interesting mitigation opportunities. To develop practical strategies for mitigating climate change, precise quantification of methane fluxes and a better understanding of its spatial distribution and biogeochemical cycling are imperative. The observations currently used to infer methane sources and sinks face limitations affecting calculation accuracy. Surface stations measuring CH4 are sparse and notably absent in major emitting regions. In contrast, satellite-derived data, while providing broader coverage, present systematic errors and estimate atmospheric composition with an accuracy range of 1-10%. Additionally, passive satellite shortwave infrared (SWIR) measurements exhibit higher sensitivity near surface emission sources but are less effective in high latitude regions. Conversely, passive satellite thermal infrared (TIR) measurements have a higher sensitivity between the free troposphere and the stratosphere.Current worksare currently being developed to integrate TIR and SWIR to obtain consolidated CH4 information on the vertical atmospheric profile. This studyaims on improving methane flux estimates using the top-down approach, which integrates observations, flux priors, and an atmospheric chemical transport model utilizing Bayesian methodology. This will be perfomed on the inversion system developed at the LSCE (Community Inversion Framework – CIF) using the global transport model LMDz. We analyze the information provided by different observing systems (TIR, SWIR and surface network) at the global scale and for a period between June 2018 and June 2020. In a first step, the sensitivity of the fluxes to the observations is estimated. In a second step, Observing System Simulation Experiments are performed to evaluate the performance of the different observations system to retrieve the target fluxes. Considering both steps, observing systems are chosen to provide the best information in terms of sensitivity and spatial representation (vertical and horizontal).

How to cite: Montenegro, N., Saunois, M., Berchet, A., Martinez, A., Bousquet, P., and Pison, I.: Estimating methane sources and sinks by assimilating satellite data in a global atmospheric inverse system., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12441, https://doi.org/10.5194/egusphere-egu24-12441, 2024.

X1.15
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EGU24-2479
|
ECS
Songyan Zhu and Jian Xu

In light of the challenges posed by climate change, global governments, including the United Kingdom (UK), have committed to addressing and mitigating the impacts of climate change, emphasizing the pursuit of Net Zero objectives. The terrestrial ecosystems on a global scale, functioning as pivotal carbon reservoirs, assume a critical role in climate change mitigation, especially within the context of an imminent scenario marked by accelerated warming and drying conditions. Recognizing that the carbon sequestration capacity of ecosystems is intricately linked to their energy and water cycling dynamics, this study presents the Uniform FLUXes (UFLUX)-ensemble dataset (https://sites.google.com/view/uflux) that accurately quantifies carbon, water, and energy fluxes across ecosystems in a consistent and mutually comparable manner. The UFLUX ensemble, relying on the upscaling of in-situ eddy covariance (EC) tower measurements using satellite vegetation proxies and meteorology reanalysis, constitutes the methodological foundation of this research.

The UFLUX originated from our prior investigations into filling gaps in EC fluxes. This is due to the analogous nature of the procedures involved in flux gap-filling and upscaling, wherein both entail the interpolation/extrapolation of fluxes, albeit in the temporal and spatial domains, respectively. The fluxes in UFLUX are upscaled through the application of a uniform set of algorithms and environmental determinants, aiming to mitigate the sources of uncertainty. The UFLUX methodology has demonstrated effectiveness in capturing the global CO2 fertilization effect. Furthermore, it has exhibited resilience to agricultural management interventions and has adeptly captured flux variability at a high spatial resolution of 20 meters in southwest England. These accomplishments lay the groundwork for generating the UFLUX-ensemble dataset.

The resulting UFLUX-ensemble dataset incorporates 60 members considering specific advantages of multiple satellite and meteorology reanalysis products. Aligned with the Net Zero vision articulated by nations, and recognizing the imperative of addressing data storage requirements, the dataset is made available on three scales: 1) daily 100-m resolution for the UK, 2) half-yearly 100-m resolution for Europe, and 3) monthly 0.25°×0.25°resolution for the entire globe. This diverse data provision is designed to assist climate actions, particularly in countries grappling with specific socio-economic challenges. A rigorous technical validation underscores the merits of the UFLUX ensemble, demonstrating its ability to capture 0.8 % of the flux variability with errors amounting to 0.76 g C m-2 d-1 and 11.67 W m-2. The UFLUX-ensemble dataset serves as a valuable resource, offering insights to inform land management practices, including nature-based solutions, with the overarching objective of augmenting carbon sequestration in terrestrial ecosystems and contributing to the realization of a carbon-neutral future.

How to cite: Zhu, S. and Xu, J.: The UFLUX ensemble of multiple-scale carbon, water, and energy fluxes., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2479, https://doi.org/10.5194/egusphere-egu24-2479, 2024.

X1.16
|
EGU24-4472
Mounia Mostefaoui, Philippe Ciais, Matthew Joseph McGrath, Philippe Peylin, Prabir K. Patra, and Yolandi Ernst

 A key goal of the Paris Agreement (PA) is to reach net-zero greenhouse gas (GHG) emissions by 2050 globally, which requires mitigation efforts from all countries. Africa’s rapidly growing population and gross domestic product (GDP) make this continent important for GHG emission trends. In this project we study the emissions of carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) in Africa over 3 decades. We compare bottom-up (BU) approaches, including United Nations Convention Framework on Climate Change (UNFCCC) national inventories, FAO, PRIMAP-hist, process-based ecosystem models for CO2 fluxes in the land use, land use change and forestry (LULUCF) sector and global atmospheric inversions. For inversions, we applied different methods to separate anthropogenic CH4 emissions. The BU inventories show that, over the decade 2010–2018, fewer than 10 countries represented more than 75 % of African fossil CO2 emissions. With a mean of 1373 Mt CO2 yr−1, total African fossil CO2 emissions over 2010–2018 represent only 4 % of global fossil emissions. However, these emissions grew by +34% from 1990–1999 to 2000–2009 and by +31% from 2000–2009 to 2010–2018, which represents more than a doubling in 30 years. This growth rate is more than 2 times faster than the global growth rate of fossil CO2 emissions. The anthropogenic emissions of CH4 grew by 5 % from 1990–1999 to 2000–2009 and by 14.8 % from 2000–2009 to 2010–2018. The N2O emissions grew by 19.5 % from 1990–1999 to 2000–2009 and by 20.8 % from 2000–2009 to 2010–2018. When using the mean of the estimates from UNFCCC reports (including the land use sector) with corrections from outliers, Africa was a mean source of greenhouse gases of 2622 (min: 2186, max: 3239) Mt CO2 eq. yr−1 from all BU estimates (the min–max  indicate range uncertainties) and of +2637 (min: 1761, max: 5873) Mt CO2 eq. yr−1 from top-down (TD) methods during their overlap period from 2001 to 2017. Although the mean values are consistent, the range of TD estimates is larger than the one of the BU estimates, indicating that sparse atmospheric observations and transport model errors do not allow us to use inversions to reduce the uncertainty in BU estimates. The main source of uncertainty comes from CO2 fluxes in the LULUCF sector, for which the spread across inversions is larger than 50 %, especially in central Africa. Moreover, estimates from national UNFCCC communications differ widely depending on whether the large sinks in a few countries are corrected to more plausible values using more recent national sources following the methodology of Grassi et al. (2022). The medians of CH4 emissions from inversions based on satellite retrievals and surface station networks are consistent with each other within 2 % at the continental scale. The inversion ensemble also provides consistent estimates of anthropogenic CH4 emissions with BU inventories such as PRIMAP-hist. For N2O, inversions systematically show higher emissions than inventories, either because natural N2O sources cannot be separated accurately from anthropogenic ones in inversions or because BU estimates ignore indirect emissions and underestimate emission factors. 

How to cite: Mostefaoui, M., Ciais, P., McGrath, M. J., Peylin, P., Patra, P. K., and Ernst, Y.: Greenhouse gas emissions and their trends over the last three decades across Africa, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-4472, https://doi.org/10.5194/egusphere-egu24-4472, 2024.

X1.17
|
EGU24-5180
CAS-ESM2 successfully reproduces historical atmospheric CO2 in a coupled carbon-climate simulation
(withdrawn)
Jiawen Zhu, Juanxiong He, Duoying Ji, Yangchun Li, He Zhang, Minghua Zhang, Xiaodong Zeng, Kece Fei, and Jiangbo Jin
X1.18
|
EGU24-16630
|
ECS
Alexander Buzacott, Bart Kruijt, Laurent Bataille, Hanne Berghuis, Jan Biermann, Quint van Giersbergen, Christian Fritz, Reinder Nouta, Merit van den Berg, Ype van der Velde, and Jacobus van Huissteden

Drained peatlands need to be rewetted to reduce carbon dioxide (CO2) emissions caused by microbial peat oxidation and to limit soil subsidence. Raising groundwater levels will subsequently increase the chance of methane (CH4) emissions, a much more potent greenhouse gas (GHG) gas than CO2. While intact peatlands are long-term carbon sinks and have a net cooling effect, despite the CH4 emissions, how disturbed peatlands will respond to rewetting is less certain. There are several rewetting strategies outside of returning the land to unproductive uses, such as paludiculture (agriculture on inundated soils) and installing water infiltration systems (WIS) in pastures.

In the Netherlands, more than 85% of the peatlands are used for agriculture and have been extensively drained. Rewetting these peatlands is necessary to reduce CO2 emissions, however the effect this will have on CH4 emissions needs to be understood such that optimal rewetting strategies can be chosen to minimise GHG emissions. In this presentation, we report our efforts into monitoring CH4 emissions across Dutch peatlands with a network of eddy covariance (EC) systems since 2020 for the Netherlands Research Programme on Greenhouse Gas Dynamics in Peatlands and Organic Soils (NOBV) project. Fluxes of CO2 and CH4 have been observed across 20 field sites that cover the current Dutch peatland extent using a combination of permanent and mobile (alternating between two paired sites) EC towers that measured the land uses of paludiculture, semi-natural, pastures with WIS, pastures with high and low groundwater levels, and a lake. We focus on the main drivers of CH4 emissions in Dutch peatlands, evaluate the impact of land use on annual CH4 emissions, and emission upscaling.

How to cite: Buzacott, A., Kruijt, B., Bataille, L., Berghuis, H., Biermann, J., van Giersbergen, Q., Fritz, C., Nouta, R., van den Berg, M., van der Velde, Y., and van Huissteden, J.: Methane emissions from Dutch peatlands measured by a national eddy covariance network, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-16630, https://doi.org/10.5194/egusphere-egu24-16630, 2024.

X1.19
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EGU24-13246
|
ECS
Xin Lin, Shushi Peng, Philippe Ciais, Didier Hauglustaine, Xin Lan, Gang Liu, Michel Ramonet, Yi Xi, Yi Yin, and Zhen Zhang and the Coauthors

Record breaking atmospheric methane growth rates were observed in 2020 and 2021 (15.2±0.4 and 17.6±0.5 ppb yr-1), reaching their highest level since the commencement of ground-based observations in the early 1980s. Here we use an ensemble of atmospheric inversions informed by surface or satellite methane concentration observations to infer emission changes during these two years relative to 2019. We found a global increase of methane emissions of 20.3±9.9 Tg CH4 in 2020 and 24.8±3.1 Tg CH4 in 2021. The emission rise was dominated by tropical and boreal regions with inundated areas, as a result of elevated groundwater table. Strong, synchronous, and persistent emission increases occurred in regions such as the Niger River basin, the Congo basin, the Sudd swamp, the Ganges floodplains and Southeast Asian deltas and the Hudson Bay lowlands. These regions alone contributed about 70% and 60% of the net global increases in 2020 and 2021, respectively. Comparing our top-down estimates with simulation of wetland emissions by biogeochemical models, we find that the bottom-up models significantly underestimate the intra- and inter-annual variability of methane sources from tropical inundated areas. This discrepancy likely arises from the models’ limitations in accurately representing the dynamics of tropical wetland extents and the response of methane emissions to environmental changes. Our findings demonstrate the critical role of tropical inundated areas in the recent surge of methane emissions and highlight the value of integrating multiple data streams and modeling tools to better constrain tropical wetland emissions.

How to cite: Lin, X., Peng, S., Ciais, P., Hauglustaine, D., Lan, X., Liu, G., Ramonet, M., Xi, Y., Yin, Y., and Zhang, Z. and the Coauthors: Recent methane surges reveal heightened emissions from tropical inundated areas, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13246, https://doi.org/10.5194/egusphere-egu24-13246, 2024.

X1.20
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EGU24-2140
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ECS
|
Highlight
Linda Ort, Lenard Lukas Röder, Peter Hoor, Jos Lelieveld, and Horst Fischer

Recently, global mean methane concentrations have increased strongly. Methane is one of the most important greenhouse gases and plays a key role in atmospheric chemistry. Especially, due to its long lifetime of approx. 10 years and its significant effect on Earth’s climate change, a detailed knowledge of its source regions and their temporal evolution is crucial.

In this study, we present a unique data set of methane measured in situ over the Amazon rainforest region during the wet season in the CAFE Brazil (Chemistry of the Atmosphere Field Experiment) aircraft campaign from December 2022 to January 2023 in Manaus, Brazil. Methane was measured with an infrared quantum cascade laser absorption spectrometer on board the High Altitude and LOng-range aircraft (HALO). These observations show enhanced concentrations of methane in and above the boundary layer of the Amazon rainforest. Locally, dry air mixing ratios of up to approx. 2100 ppbv could be measured up to 4 km of altitude. Detailed analysis shows only a small contribution from anthropogenic sources. Especially over permanent wetlands and deforested areas, the methane concentrations were enhanced. Furthermore, the data has been compared to satellite measurements from the National Oceanic and Atmospheric Administration (NOAA), indicating good agreement in the free troposphere. Nevertheless, the mean levels directly above the Amazon rainforest are approx. 100 ppbv higher than the global background. Moreover, a global distribution based on airborne data from several campaigns (PHILEAS 2023, CAFE Brazil 2022/23, SouthTrac 2019, CAFE Africa 2018, WISE 2017, ATom 2016/17, OMO 2015, ESMVal 2012) shows that the methane surface concentrations over the Amazon rainforest has a local maximum. This calls for more detailed investigations of methane near the surface in the Amazon and raises an important question: Have we underestimated the Amazon rainforest as a significant source of the global methane budget?

How to cite: Ort, L., Röder, L. L., Hoor, P., Lelieveld, J., and Fischer, H.: Enhanced methane concentrations measured over the Amazon rainforest, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-2140, https://doi.org/10.5194/egusphere-egu24-2140, 2024.

X1.21
|
EGU24-6974
|
ECS
Near-real-time monitoring of fossil CH4 emission from fossil fuel activities
(withdrawn)
Xinyu Dou, Philippe Ciais, Xin Lin, Zhu Liu, Xuanren Song, and Qingyang Wu
X1.22
|
EGU24-13094
|
ECS
Anteneh Getachew Mengistu, Aki Tsuruta, Maria Tenkanen, Tiina Markkanen, Maarit Raivonen, Antti Leppänen, Antoine Berchet, Rona Thompson, Hannakaisa Lindqvist, and Tuula Aalto

Accurate estimation of critical greenhouse gas fluxes, particularly carbon dioxide (CO2) and methane (CH4), is vital for shaping effective climate change policies. Leveraging the state-of-the-art Community Inversion Framework (CIF), we estimate high-resolution emissions across Europe (-12°E to 37°E, 35°N to 73°N). Using the Lagrangian Particle Dispersion Model (FLEXPART) with ECMWF meteorological data, we calculate surface flux footprints at 0.2° × 0.2° resolution, enhancing comparisons with national inventories. Assimilating data from 40+ in-situ observations, including ICOS and non-ICOS stations, our 4-dimensional variational optimization refines prior high-resolution flux estimates. Diverse sources contribute to the total flux, including fossil fuel emissions, biomass burning, land emissions, air-sea exchange. Flux corrections enhance accuracy, yielding posterior estimates with reduced bias and heightened correlation. Major CH4 emitters (France, Germany, Italy, Spain, Poland, and the UK) collectively contribute 72% of total emissions. The EU27 + UK average is 16.47 ± 1.33 Tg CH4/yr. Posterior anthropogenic emissions reveal a regional mean reduction of > 5 gC/m2/month in summer compared to prior estimates, highlighting seasonal emission dynamics.

How to cite: Mengistu, A. G., Tsuruta, A., Tenkanen, M., Markkanen, T., Raivonen, M., Leppänen, A., Berchet, A., Thompson, R., Lindqvist, H., and Aalto, T.: High-Resolution Inversion Modeling of Carbon Dioxide and Methane Emissions in Europe: Assessing Accuracy and  Dynamics, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-13094, https://doi.org/10.5194/egusphere-egu24-13094, 2024.

X1.23
|
EGU24-8833
|
ECS
Quantifying the Greenhouse Gas Emission and Nitrogen Losses in the Rice-Wheat Rotation System in the Tai Lake Basin, China
(withdrawn)
Minye Zhu, Chuanhui Gu, and Yufan Gao
X1.24
|
EGU24-825
|
ECS
Quantifying Wetland Methane Emissions from the Southeastern United States: A Data-driven Approach, Key Variables, and Spatiotemporal Distributions
(withdrawn)
Keqi He, Wenhong Li, Yu Zhang, Angela Zeng, Inge de Graaf, Maricar Aguilos, Ge Sun, Steven McNulty, John King, Neal Flanagan, and Curtis Richardson
X1.25
|
EGU24-14545
|
ECS
Muhammad Kamil Sardar Ali, Thomas Schindler, Hanna Vahter, Ain Kull, Ülo Mander, Andis Lazdiņš, Ieva Līcīte, Arta Bārdule, Aldis Butlers, Dovilė Čiuldienė, Egidijus Vigricas, Jyrki Jauhiainen, Raija Laiho, and Kaido Soosaar

Peatland ecosystem degradation and changes made in hydrology by artificial drainage may affect the biogeochemistry of peatlands and, together with projected global warming, may lead to significant changes in greenhouse gas (GHG) fluxes. Drainage of peatlands increases organic matter's aerobic decomposition, changes native vegetation, and may decrease the storage of C. The vegetative characteristics of forest ecosystem types may change a net GHG sink peatland to a source in drained organic soils.

However, soil CH4 and N2O fluxes in peatlands are spatially and temporally (interannual, seasonal) variable, and detailed data from drained nutrient-rich organic soils in the hemiboreal zone is lacking. We conducted a study spanned over two years comprising drained (n=18) and undrained (n=7) peatland forests with dominant tree species of Scots pine (Pinus sylvestris), Norway spruce (Picea abies), birch (Betula sp.), and black alder (Alnus glutinosa) spread across Estonia, Latvia, and Lithuania. Instantaneous fluxes of CH4 and N2O were measured monthly for the whole year using the manual static chamber method. Environmental parameters in soil, such as soil water level (WTL), moisture, and temperatures at depths (0-40 cm), were monitored continuously, and detailed soil chemical analyses were conducted. To constrain the factors regulating temporal fluxes of various environmental conditions and differentiate annual emissions between land use in the Baltic region.

The results show that all drained forest soils were annual CH4 sinks (−37.0 ± 4.5 μg C m−‍2 h−‍1), while undrained forests were emitters on average 388.5 ± 142. Mean annual CH4 uptake is significantly higher in deep-drained soils −45.5 ± 3.6 μg C m−‍2 h−‍1 (WTL > −50cm) than in poorly drained soils (p<0.05), regardless of dominant tree species. The in situ and annual CH4 fluxes statistically correlated with soil water level and temperature. Most of the drained sites emitted N2O (49.4 ± 17.8 μg N m−‍2 h−‍1); drained wet forest sites were higher emitters (84.7 ± 32.4) than drier sites (23.67 ± 15.6) in comparison to tree species. The instantaneous N2O fluxes were directly controlled by soil surface temperature and oxygen concentration of soil water, whereas variability in annual N2O emissions was associated with soil water content. Moreover, soil nutrient status regulated by specific ground vegetation functional groups has significantly impacted the emissions of nutrient-rich organic soils.

This research was supported by the LIFE programme project "Demonstration of climate change mitigation potential of nutrients-rich organic soils in the Baltic States and Finland" (2019-2023, LIFE OrgBalt, LIFE18 274CCM/LV/001158).

How to cite: Sardar Ali, M. K., Schindler, T., Vahter, H., Kull, A., Mander, Ü., Lazdiņš, A., Līcīte, I., Bārdule, A., Butlers, A., Čiuldienė, D., Vigricas, E., Jauhiainen, J., Laiho, R., and Soosaar, K.: Soil CH4 and N2O fluxes from drained and undrained peatland forests in the Baltic region., EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-14545, https://doi.org/10.5194/egusphere-egu24-14545, 2024.

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EGU24-20413
Rostyslav Bun, Gregg Marland, Tomohiro Oda, Linda See, Enrique Puliafito, Zbigniew Nahorski, Matthias Jonas, Vasyl Kovalyshyn, Iolanda Ialongo, Orysia Yashchun, and Zoriana Romanchuk

Quantifying greenhouse gas (GHG) emissions is a critical task for climate monitoring and mitigation actions.  Under the Paris Agreement, for example, accounting and reporting of GHG emissions are mandatory for Parties.  Reported emissions are often calculated using activity data approaches.  The robustness of the activity data collection is a key for obtaining accurate emission estimates; however, in a period of open conflict or war, the systems for data collection can be desperately damaged and destroyed and thus the ability of achieving robust GHG estimates and transparent reporting can be significantly hampered.  Also, military emissions, which are thought to be often poorly quantified, should increase significantly than peace times. 

We attempted to quantify GHG emissions during the first 18 months of the 2022/2023 full-scale war in Ukraine.  We first identified major, war-related, emission drivers and processes from the territory of Ukraine.  We analyzed publicly available data and used expert judgment to estimate emissions from (1) the use of bombs, missiles, barrel artillery, and mines; (2) the consumption of oil products for military operations; (3) fires at petroleum storage depots and refineries; (4) fires in buildings and infrastructure facilities; (5) fires on forest and agricultural lands; and (6) the decomposition of war-related garbage/waste.  Those sources are often not covered by current GHG inventory guidelines, and thus are not likely to be included in national inventory reports. 

Our estimate of the war-related emissions of carbon dioxide (CO2), methane, (CH4) and nitrous oxide (N2O) for the first 18 months of the war in Ukraine is 77 MtCO2-eq. with a relative uncertainty of ±22 % (95 % confidence interval).  It is important to note that these emissions are considered to be emissions from Ukraine in reporting because the emissions occurred within the territory of Ukraine.  The current emission accounting system (e.g. UNFCCC) is not designed to account war/conflict time emissions adequately.  The uncertainties due to the unaccounted emissions are also aliasing to our global and regional carbon budget calculations.

How to cite: Bun, R., Marland, G., Oda, T., See, L., Puliafito, E., Nahorski, Z., Jonas, M., Kovalyshyn, V., Ialongo, I., Yashchun, O., and Romanchuk, Z.: Quantifying unaccounted greenhouse gas emissions due to the war in Ukraine – driver analysis, emission estimation, and implications to emission reporting, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-20413, https://doi.org/10.5194/egusphere-egu24-20413, 2024.