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River networks represent the largest biogeochemical nexus between the continents, ocean and atmosphere. Our current understanding of the role of rivers in the global carbon cycle remains limited, which makes it difficult to predict how global change may alter the timing and spatial distribution of riverine carbon sequestration and greenhouse gas emissions. Here we review the state of river ecosystem metabolism research and synthesize the current best available estimates of river ecosystem metabolism. We quantify the organic and inorganic carbon flux from land to global rivers and show that their net ecosystem production and carbon dioxide emissions shift the organic to inorganic carbon balance en route from land to the coastal ocean. Furthermore, we discuss how global change may affect river ecosystem metabolism and related carbon fluxes and identify research directions that can help to develop better predictions of the effects of global change on riverine ecosystem processes. We argue that a global river observing system will play a key role in understanding river networks and their future evolution in the context of the global carbon budget.

Inland waters are important sources of the greenhouse gasses (GHGs) carbon dioxide (CO2), methane (CH4) and nitrous oxide (N2O) to the atmosphere. While a growing number of global estimates of inland water GHG emissions exists, the integration of inland waters into regional GHG budgets is often hampered by the lack of adequate geo-spatial datasets. Moreover, existing estimates diverge substantially, in part due to persisting uncertainties related to the size and distribution of effective inland water surface areas. In the framework of the 2nd phase of the REgional Carbon Cycle Assessment and Processes (RECCAP-2) initiative, we synthesize existing estimates of GHG emissions from streams, rivers, lakes and reservoirs, and homogenize them with regard to underlying global maps of inland water surface areas and the effects of seasonal ice cover. We then produce estimates of inland water GHG emissions for 10 extensive land regions that are used for the regional land budgets of RECCAP2. According to our synthesis, global inland waters emit 5.6 (3.5-9.1) Pg CO2 yr-1, 101 (83-135) Tg CH4 yr-1 and 326 (254-592) Gg N2O yr-1. South American rivers contribute about one third of global inland water CO2 emissions. North-American and Russian lakes contribute together one third of global inland water CH4 emissions. Finally, North America alone contributes one fourth of global inland water N2O emissions.The global inland water emissions sum up to a global warming potential (GWP) of an equivalent emission of 13.6 (10.0-20.3) and 8.3 (5.8-12.7) Pg CO2 yr-1 at a 20- and 100-year horizon, respectively. At 100-year horizon, the contribution of CO2 dominates the GWP of global inland water GHG emissions, with rivers being the largest emitters. At the 20-year horizon, on the contrary, lakes and rivers are equally important emitters, and the contributions of CH4 to the GWP of inland water GHG emissions even exceed those of CO2. Contributions of N2O to the GWP appear to be less significant at both time horizons. Normalized to the area of the RECCAP-2 land regions, South America and South East Asia show the highest inland water emission rates in terms of GWP, dominated by riverine CO2 emissions.

Accurate national carbon budget assessments allow nations to evaluate their progress in cutting carbon emissions and therefore be aligned with the Paris Climate Agreement goals. To support the initiative of The REgional Carbon Cycle Assessment and Processes (RECCAP-2), we built a synthesis of the Australasia (Australia and New Zealand) terrestrial carbon budget for 2010-2019 based on top-down and bottom-up approaches. Major carbon flux components in the bottom-up budget (e.g., net primary productivity and heterotrophic respiration) were simulated by CABLE model, Biome-BGC model and Cewn simulations. In addition, this budget include carbon flux components from the land-ocean aquatic continuum, such as inland waters, estuaries, blue carbon ecosystems, and continental shelves and carbon fluxes embodied in trade (export and import) of crops, woods, livestock and fossil fuel. We reconciled Australia and New Zealand bottom-up budgets separately with fluxes derived from regional and global OCO-2, GOSAT flux inversions, as well as fluxes obtained from in-situ measurement only (CarbonWatchNZ). We found that annual mean budgets for Australia agree relatively well (within the uncertainty range) with regional and global top-down GOSAT and OCO-2 flux estimates. New Zealand's annual bottom-up carbon budget also agrees relatively well with fluxes derived from CarbonWatchNZ inversion and GOSAT but disagrees with global flux estimates from OCO-2.

Lateral nitrogen (N) transport from land to the ocean through rivers is an important component of global N cycling. In this study, we present the implementation of fluvial transport of nitrogen into ORCHIDEE-CNP (Organising Carbon and Hydrology in Dynamic Ecosystems-CNP), which explicitly simulates N biogeochemistry in terrestrial ecosystems coupled with carbon, water and energy transfers. This new model branch called ORCHIDEE-Nlateral, simulates the lateral transport of water, dissolved inorganic N (DIN), dissolved organic N (DON) and particulate organic N (PON) from land to the ocean through river networks, the decomposition of DON and PON, and the denitrification of DIN in transit. ORCHIDEE-Nlateral was parameterized and evaluated based on global observations of water discharge (Global Runoff and Dara Centre, GRDC) and N concentration in the global river network (Global Water Quality Archive, GRQA). The model reproduces well the observed riverine discharges of water and total nitrogen (TN), and N exports from the land to the ocean. Globally, the TN flowing into rivers, denitrification of DIN and TN export to the ocean all increased from the year 1901 to 2015. The TN export to the ocean increased from 32 Tg N yr-1 to 37 Tg N yr-1 during 1901–2015, which is in good agreement with the corresponding global fluxes calculated from the well-established Global NEWS 2 model. In this study, we further re-assess the spatial and temporal distribution of global riverine N flows and stocks. Overall, our model approach represents a useful tool for simulating large-scale lateral N transfer and for predicting the future feedbacks between lateral N transfers and climate.

Leaching of dissolved organic carbon (DOC) from soils into the river network is an important component of the land carbon (C) budget. At regional to global scales, its significance has been estimated through simple mass budgets, often using multi-year averages of observed fluvial DOC fluxes as a proxy of DOC leaching due to the limited availability of observations of the leaching flux itself. This procedure leads to a systematic underestimation of the leaching flux because of the decay of DOC during fluvial transport. Moreover, this procedure does not allow for revealing spatiotemporal variability in DOC leaching from soils, which is vital to better understand the drivers of DOC leaching and its impact on the local soil C budget. In this study, we use the land surface model (LSM) ORCHILEAK to simulate the terrestrial C budget, including leaching of DOC from the soil and its subsequent reactive transport through the river network of Europe. The model performance is evaluated not only against the sparse observations of the soil DOC leaching rate, but also against the more abundant observations of fluxes and reactivity of DOC in rivers, providing further evidence that our simulated DOC fluxes are realistic. The model is then used to simulate the spatiotemporal patterns of DOC leaching across Europe over the period 1972–2012, quantifying both the environmental drivers of these patterns and the impact of DOC leaching on the land C budget. Over the simulation period, we find that, on average, 14.3 Tg C yr−1 of DOC is leached from land into European rivers, which is about 0.6 % of the terrestrial net primary production (NPP), a fraction significantly lower than that reported for tropical river networks. On average, 12.3 Tg C yr−1 of the leached DOC is finally exported to the coast via the river network, and the rest is respired during transit. DOC leaching presents a large seasonal variability, with the maximum occurring in winter and the minimum in summer, except for most parts of northern Europe, where the maximum occurs in spring due to snowmelt. The DOC leaching rate is generally low in warm and dry regions, and high in the cold and wet regions of Europe. Furthermore, runoff and the ratio between runoff from shallower flow paths on one hand and deep drainage and groundwater flow on the other hand are the main drivers of the spatiotemporal variation of DOC leaching. Temperature, as a major control of DOC production and decomposition rates in the soils, plays only a secondary role.

Regional land carbon budgets provide insights into the spatial distribution of the land uptake of atmospheric carbon dioxide and can be used to evaluate carbon cycle models and to define baselines for land-based additional mitigation efforts. The scientific community has been involved in providing observation-based estimates of regional carbon budgets either by downscaling atmospheric CO2 observations into surface fluxes with atmospheric inversions, by using inventories of carbon stock changes in terrestrial ecosystems, by upscaling local field observations such as flux towers with gridded climate and remote sensing fields, or by integrating data-driven or process-oriented terrestrial carbon cycle models. The first coordinated attempt to collect regional carbon budgets for nine regions covering the entire globe in the RECCAP-1 project has delivered estimates for the decade 2000–2009, but these budgets were not comparable between regions due to different definitions and component fluxes being reported or omitted. The recent recognition of lateral fluxes of carbon by human activities and rivers that connect CO2 uptake in one area with its release in another also requires better definitions and protocols to reach harmonized regional budgets that can be summed up to a globe scale and compared with the atmospheric CO2 growth rate and inversion results. In this study, using the international initiative RECCAP-2 coordinated by the Global Carbon Project, which aims to be an update to regional carbon budgets over the last 2 decades based on observations for 10 regions covering the globe with a better harmonization than the precursor project, we provide recommendations for using atmospheric inversion results to match bottom-up carbon accounting and models, and we define the different component fluxes of the net land atmosphere carbon exchange that should be reported by each research group in charge of each region. Special attention is given to lateral fluxes, inland water fluxes, and land use fluxes.

Quantification of land surface-atmosphere fluxes of carbon dioxide (CO2) fluxes and their trends and uncertainties is essential for monitoring progress of the EU27+UK bloc as it strives to meet ambitious targets determined by both international agreements and internal regulation. This study provides a consolidated synthesis of fossil sources (CO2 fossil) and natural sources and sinks over land (CO2 land) using bottom-up (BU) and top-down (TD) approaches for the European Union and United Kingdom (EU27+UK), updating earlier syntheses (Petrescu et al., 2020, 2021b). Given the wide scope of the work and the variety of approaches involved, this study aims to answer essential questions identified in the previous syntheses and understand the differences between datasets, particularly for poorly characterized fluxes from managed ecosystems. The work integrates updated emission inventory data, process-based model results, data-driven sectoral model results, and inverse modeling estimates, extending the previous period 1990–2018 to the year 2020 to the extent possible. BU and TD products are compared with European National Greenhouse Gas Inventories (NGHGIs) reported by Parties including the year 2019 under the United Nations Framework Convention on Climate Change (UNFCCC). The uncertainties of the EU27+UK NGHGI were evaluated using the standard deviation reported by the EU Member States following the guidelines of the Intergovernmental Panel on Climate Change (IPCC) and harmonized by gap-filling procedures. Variation in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), originate from within-model uncertainty related to parameterization as well as structural differences between models. By comparing NGHGIs with other approaches, key sources of differences between estimates arise primarily in activities. System boundaries and emission categories create differences in CO2 fossil datasets, while different land use definitions for reporting emissions from Land Use, Land Use Change and Forestry (LULUCF) activities result in differences for CO2 land. The latter has important consequences for atmospheric inversions, leading to inversions reporting stronger sinks in vegetation and soils than are reported by the NGHGI. For CO2 fossil emissions, after harmonizing estimates based on common activities and selecting the most recent year available for all datasets, the UNFCCC NGHGI for the EU27+UK accounts for 3392 ± 49 Tg CO2 yr-1 (926 ± 13 Tg C yr-1), while eight other BU sources report a mean value of 3340 [3238,3401] [25th,75th percentile] Tg CO2 yr-1 (948 [937,961] Tg C yr-1). The sole top-down inversion of fossil emissions currently available accounts for 3800 Tg CO2 yr-1 (1038 Tg C yr-1), a value close to that of the NGHGI, but for which uncertainty estimates are not yet available. For the net CO2 land fluxes, during the most recent five-year period including the NGHGI estimates, the NGHGI accounted for -91 ± 32 Tg C yr-1 while six other BU approaches reported a mean sink of -62 [-117,-49] Tg C yr-1 and a 15-member ensemble of dynamic global vegetation models (DGVMs) reported -69 [-152,-5] Tg C yr-1. The five-year mean of three TD regional ensembles combined with one non-ensemble inversion of -73 Tg C yr-1 has a slightly smaller spread (0th–100th percentile of [-135,45] Tg C yr-1), and was calculated after removing land-atmosphere CO2 fluxes caused by lateral transport of carbon (crops, wood trade and inland waters) resulting in increased agreement with the the NGHGI and bottom-up approaches. Results at the sub-sector level (Forestland, Cropland, Grassland) show generally good agreement between the NGHGI and sub-sector-specific models, but results for a DGVM are mixed. Overall, for both CO2 fossil and net CO2 land fluxes, we find current independent approaches are consistent with the NGHGI at the scale of the EU27+UK. We conclude that CO2 emissions from fossil sources have decreased over the past 30 years in the EU27+UK, while large uncertainties on net uptake of CO2 by the land surface prevent trend identification. In addition, a gap on the order of 1000 Tg C yr-1 between CO2 fossil emissions and net CO2 uptake by the land exists regardless of the type of approach (NGHGI, TD, BU), falling well outside all available estimates of uncertainties. However, uncertainties in top-down approaches to estimate CO2 fossil emissions remain uncharacterized and are likely substantial. The data used to plot the figures are available at https://doi.org/10.5281/zenodo.7365863.

Knowledge of the spatial distribution of the fluxes of greenhouse gases (GHGs) and their temporal variability as well as flux attribution to natural and anthropogenic processes is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement and to inform its global stocktake. This study provides a consolidated synthesis of CH4 and N2O emissions using bottom-up (BU) and top-down (TD) approaches for the European Union and UK (EU27 + UK) and updates earlier syntheses (Petrescu et al., 2020, 2021). The work integrates updated emission inventory data, process-based model results, data-driven sector model results and inverse modeling estimates, and it extends the previous period of 1990–2017 to 2019. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported by parties under the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. Uncertainties in NGHGIs, as reported to the UNFCCC by the EU and its member states, are also included in the synthesis. Variations in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arise from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. By comparing NGHGIs with other approaches, the activities included are a key source of bias between estimates, e.g., anthropogenic and natural fluxes, which in atmospheric inversions are sensitive to the prior geospatial distribution of emissions. For CH4 emissions, over the updated 2015–2019 period, which covers a sufficiently robust number of overlapping estimates, and most importantly the NGHGIs, the anthropogenic BU approaches are directly comparable, accounting for mean emissions of 20.5 Tg CH4 yr−1 (EDGARv6.0, last year 2018) and 18.4 Tg CH4 yr−1 (GAINS, last year 2015), close to the NGHGI estimates of 17.5±2.1 Tg CH4 yr−1. TD inversion estimates give higher emission estimates, as they also detect natural emissions. Over the same period, high-resolution regional TD inversions report a mean emission of 34 Tg CH4 yr−1. Coarser-resolution global-scale TD inversions result in emission estimates of 23 and 24 Tg CH4 yr−1 inferred from GOSAT and surface (SURF) network atmospheric measurements, respectively. The magnitude of natural peatland and mineral soil emissions from the JSBACH–HIMMELI model, natural rivers, lake and reservoir emissions, geological sources, and biomass burning together could account for the gap between NGHGI and inversions and account for 8 Tg CH4 yr−1. For N2O emissions, over the 2015–2019 period, both BU products (EDGARv6.0 and GAINS) report a mean value of anthropogenic emissions of 0.9 Tg N2O yr−1, close to the NGHGI data (0.8±55 % Tg N2O yr−1). Over the same period, the mean of TD global and regional inversions was 1.4 Tg N2O yr−1 (excluding TOMCAT, which reported no data). The TD and BU comparison method defined in this study can be operationalized for future annual updates for the calculation of CH4 and N2O budgets at the national and EU27 + UK scales. Future comparability will be enhanced with further steps involving analysis at finer temporal resolutions and estimation of emissions over intra-annual timescales, which is of great importance for CH4 and N2O, and may help identify sector contributions to divergence between prior and posterior estimates at the annual and/or inter-annual scale. Even if currently comparison between CH4 and N2O inversion estimates and NGHGIs is highly uncertain because of the large spread in the inversion results, TD inversions inferred from atmospheric observations represent the most independent data against which inventory totals can be compared. With anticipated improvements in atmospheric modeling and observations, as well as modeling of natural fluxes, TD inversions may arguably emerge as the most powerful tool for verifying emission inventories for CH4, N2O and other GHGs. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.7553800 (Petrescu et al., 2023).

Knowledge of the spatial distribution of the fluxes of greenhouse gases and their temporal variability as well as flux attribution to natural and anthropogenic processes is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement and to inform its Global Stocktake. This study provides a consolidated synthesis of CH4 and N2O emissions using bottom-up (BU) and top-down (TD) approaches for the European Union and UK (EU27+UK) and updates earlier syntheses (Petrescu et al., 2020, 2021). The work integrates updated emission inventory data, process-based model results, data-driven sector model results, inverse modelling estimates, and extends the previous period 1990–2017 to 2020. BU and TD products are compared with European National GHG Inventories (NGHGI) reported by Parties under the United Nations Framework Convention on Climate Change (UNFCCC) in 2021. The uncertainties of NGHGIs were evaluated using the standard deviation obtained by varying parameters of inventory calculations, reported by the EU Member States following the guidelines of the Intergovernmental Panel on Climate Change (IPCC) and harmonized by gap-filling procedures. Variation in estimates produced with other methods, such as atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arise from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. By comparing NGHGIs with other approaches, the activities included are a key source of bias between estimates e.g. anthropogenic and natural fluxes, which, in atmospheric inversions are sensitive to the prior geospatial distribution of emissions. For CH4 emissions, over the updated 2015–2019 period, which covers a sufficiently robust number of overlapping estimates, and most importantly the NGHGIs, the anthropogenic BU approaches are directly comparable, accounting for mean emissions of 20.5 Tg CH4 yr−1 (EDGAR v5v6.0, last year 2018) and 18.4 Tg CH4 yr−1 (GAINS, 2015), close to the NGHGI estimates of 17.5 ± 2.1 Tg CH4 yr−1. TD inversions estimates give higher emission estimates, as they also detect natural emissions. Over the same period, high resolution regional TD inversions report a mean emission of 34 Tg CH4 yr−1. Coarser-resolution global-scale TD inversions result in emission estimates of 23 Tg CH4 yr−1 and 24 Tg CH4 yr−1 inferred from GOSAT and surface (SURF) network atmospheric measurements, respectively. The magnitude of natural peatland and mineral soils emissions from the JSBACH-HIMMELI model, natural rivers, lakes and reservoirs emissions, geological sources and biomass burning together could account for the gap between NGHGI and inversions and account for 8 Tg CH4 yr−1. For N2O emissions, over the 2015–2019 period, both BU products (EDGAR v5v6.0 and GAINS) report a mean value of anthropogenic emissions of 0.9 Tg N2O yr−1, close to the NGHGI data (0.8 ± 55 % Tg N2O yr−1). Over the same period, the mean of TD global and regional inversions was 1.4 Tg N2O yr−1 (excluding TOMCAT which reported no data). The TD and BU comparison method defined in this study can be "operationalized" for future annual updates for the calculation of CH4 and N2O budgets at the national and EU27+UK scales. Future comparability will be enhanced with further steps involving analysis at finer temporal resolutions and estimation of emissions over intra-annual timescales, of great importance for CH4 and N2O, which may help identify sector contributions to divergence between prior and posterior estimates at the annual/inter-annual scale. Even if currently comparison between CH4 and N2O inversions estimates and NGHGIs is highly uncertain because of the large spread in the inversion results, TD inversions inferred from atmospheric observations represent the most independent data against which inventory totals can be compared. With anticipated improvements in atmospheric modelling and observations, as well as modelling of natural fluxes, TD inversions may arguably emerge as the most powerful tool for verifying emissions inventories for CH4, N2O and other GHGs. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.6992472 (Petrescu et al., 2022).

International audience; In support of the global stocktake of the Paris Agreement on climate change, this study presents a comprehensive framework to process the results of an ensemble of atmospheric inversions in order to make their net ecosystem exchange (NEE) carbon dioxide (CO2) flux suitable for evaluating national greenhouse gas inventories (NGHGIs) submitted by countries to the United Nations Framework Convention on Climate Change (UNFCCC). From inversions we also deduced anthropogenic methane (CH4) emissions regrouped into fossil and agriculture and waste emissions, as well as anthropogenic nitrous oxide (N2O) emissions. To compare inversion results with national reports, we compiled a new global harmonized database of emissions and removals from periodical UNFCCC inventories by Annex I countries, and from sporadic and less detailed emissions reports by non-Annex I countries, given by national communications and biennial update reports. No gap filling was applied. The method to reconcile inversions with inventories is applied to selected large countries covering ∼90 % of the global land carbon uptake for CO2 and top emitters of CH4 and N2O. Our method uses results from an ensemble of global inversions produced by the Global Carbon Project for the three greenhouse gases, with ancillary data. We examine the role of CO2 fluxes caused by lateral transfer processes from rivers and from trade in crop and wood products and the role of carbon uptake in unmanaged lands, both not accounted for by NGHGIs. Here we show that, despite a large spread across the inversions, the median of available inversion models points to a larger terrestrial carbon sink than inventories over temperate countries or groups of countries of the Northern Hemisphere like Russia, Canada and the European Union. For CH4, we find good consistency between the inversions assimilating only data from the global in situ network and those using satellite CH4 retrievals and a tendency for inversions to diagnose higher CH4 emission estimates than reported by NGHGIs. In particular, oil- and gas-extracting countries in central Asia and the Persian Gulf region tend to systematically report lower emissions compared to those estimated by inversions. For N2O, inversions tend to produce higher anthropogenic emissions than inventories for tropical countries, even when attempting to consider only managed land emissions. In the inventories of many non-Annex I countries, this can be tentatively attributed to a lack of reporting indirect N2O emissions from atmospheric deposition and from leaching to rivers, to the existence of natural sources intertwined with managed lands, or to an underestimation of N2O emission factors for direct agricultural soil emissions. Inversions provide insights into seasonal and interannual greenhouse gas fluxes anomalies, e.g., during extreme events such as drought or abnormal fire episodes, whereas inventory methods are established to estimate trends and multi-annual changes. As a much denser sampling of atmospheric CO2 and CH4 concentrations by different satellites coordinated into a global constellation is expected in the coming years, the methodology proposed here to compare inversion results with inventory reports (e.g., NGHGIs) could be applied regularly for monitoring the effectiveness of mitigation policy and progress by countries to meet the objective of their pledges. The dataset constructed by this study is publicly available at https://doi.org/10.5281/zenodo.5089799 (Deng et al., 2021).

In support of the Global Stocktake of the Paris Agreement on Climate change, this study presents a comprehensive framework to process the results of atmospheric inversions in order to make them suitable for evaluating UNFCCC national inventories of land-use carbon dioxide (CO2) emissions and removals, corresponding to the Land Use, Land Use Change and Forestry and waste sectors. We also deduced anthropogenic methane (CH4) emissions regrouped into fossil and agriculture and waste emissions, and anthropogenic nitrous oxide (N2O) emissions from inversions. To compare inversions with national reports, we compiled a new global harmonized database of national emissions and removals from periodical UNFCCC inventories by Annex I countries, and from sporadic and less detailed emissions reports by Non-Annex I countries, given by National Communications and Biennial Update Reports. The method to reconcile inversions with inventories is applied to selected large countries covering 78 % of the global land carbon uptake for CO2, as well as emissions and removals in the land use, land use change and forestry sector, and top-emitters of CH4 and N2O. Our method uses results from an ensemble of global inversions produced by the Global Carbon Project for the three greenhouse gases, with ancillary data. We examine the role of CO2 fluxes caused by lateral transfer processes from rivers and from trade in crop and wood products, and the role of carbon uptake in unmanaged lands, both not accounted for by the rules of inventories. Here we show that, despite a large spread across the inversions, the median of available inversion models points to a larger terrestrial carbon sink than inventories over temperate countries or groups of countries of the Northern Hemisphere like Russia, Canada and the European Union. For CH4, we find good consistency between the inversions assimilating only data from the global in-situ network and those using satellite CH4 retrievals, and a tendency for inversions to diagnose higher CH4 emissions estimates than reported by inventories. In particular, oil and gas extracting countries in Central Asia and the Persian Gulf region tend to systematically report lower emissions compared to those estimated by inversions. For N2O, inversions tend to produce higher anthropogenic emissions than inventories for tropical countries, even when attempting to consider only managed land emissions. In the inventories of many non-Annex I countries, this can be tentatively attributed to either a lack of reporting indirect N2O emissions from atmospheric deposition and from leaching to rivers, or to the existence of natural sources intertwined with managed lands, or to an under-estimation of N2O emission factors for direct agricultural soil emissions. The advantage of inversions is that they provide insights on seasonal and interannual greenhouse gas fluxes anomalies, e.g. during extreme events such as drought or abnormal fire episodes, whereas inventory methods are established to estimate trends and multi-annual changes. As a much denser sampling of atmospheric CO2 and CH4 concentrations by different satellites coordinated into a global constellation is expected in the coming years, the methodology proposed here to compare inversion results with inventory reports could be applied regularly for monitoring the effectiveness of mitigation policy and progress by countries to meet the objective of their pledges.

Leaching of dissolved organic carbon (DOC) from soils to the river network is an important component of the land carbon (C) budget. At regional to global scales, its significance has been estimated through simple mass budgets, often using multi-year averages of observed fluvial DOC fluxes as proxy of DOC leaching due to the limited availability of observations of the leaching flux itself. This procedure leads to a systematic underestimation of the leaching flux because of the reactivity of DOC during fluvial transport. Moreover, this procedure does not allow to reveal spatio-temporal variability in DOC leaching from soils, which is needed to better understand the drivers of DOC leaching and its impact on the local soil C budget. In this study, we use the land surface model ORCHILEAK to simulate the terrestrial C budget including leaching of DOC from the soil and its subsequent reactive transport through the river network of Europe. The model performance is not only evaluated against the sparse observations of DOC leaching, but also against the more abundant observations of fluxes and reactivity of DOC in rivers, providing further evidence that our simulated DOC leaching fluxes are realistic. The model is then used to simulate the spatio-temporal patterns of DOC leaching across Europe over the period 1972 to 2012, quantifying both the environmental drivers of these patterns as well as the impact of DOC leaching on the land C budget. Over the simulation period, we find that on average 14.3 TgC yr−1 of DOC is leached from land to European rivers, which is only about 0.6 % of the terrestrial net primary production, a fraction about one order of magnitude lower than reported for tropical river networks. Of the DOC leaching, on average 12.3 TgC yr−1 is exported to the coast via the river network, the rest being respired in transit. DOC leaching presents a large seasonal variability, with a maximum occurring in winter and a minimum in summer, except for the Northern most part of Europe where the maximum occurs in spring due to the snow melt. DOC leaching rate is generally lower in warm and dry regions, and higher in cold and wet regions of Europe. Furthermore, runoff, and the ratio between runoff from shallower flow paths vs. deep drainage and groundwater flow, is the main driver of the spatial variation of DOC leaching. Temperature, as a major control of DOC production and decomposition rates in the soils, plays only a secondary role.

Resolving regional carbon budgets is critical for informing land-based mitigation policy. For nine regions covering nearly the whole globe, we collected inventory estimates of carbon-stock changes complemented by satellite estimates of biomass changes where inventory data are missing. The net land–atmospheric carbon exchange (NEE) was calculated by taking the sum of the carbon-stock change and lateral carbon fluxes from crop and wood trade, and riverine-carbon export to the ocean. Summing up NEE from all regions, we obtained a global ‘bottom-up’ NEE for net land anthropogenic CO2 uptake of –2.2 ± 0.6 PgC yr−1 consistent with the independent top-down NEE from the global atmospheric carbon budget during 2000–09. This estimate is so far the most comprehensive global bottom-up carbon budget accounting, which set up an important milestone for global carbon-cycle studies. By decomposing NEE into component fluxes, we found that global soil heterotrophic respiration amounts to a source of CO2 of 39 PgC yr−1 with an interquartile of 33–46 PgC yr−1—a much smaller portion of net primary productivity than previously reported., info:eu-repo/semantics/published

International audience; We synthesized N2O emissions over North America using 17 bottom-up (BU) estimates from 1980–2016 and five top-down (TD) estimates from 1998 to 2016. The BU-based total emission shows a slight increase owing to U.S. agriculture, while no consistent trend is shown in TD estimates. During 2007–2016, North American N2O emissions are estimated at 1.7 (1.0–3.0) Tg N yr−1 (BU) and 1.3 (0.9–1.5) Tg N yr−1 (TD). Anthropogenic emissions were twice as large as natural fluxes from soil and water. Direct agricultural and industrial activities accounted for 68% of total anthropogenic emissions, 71% of which was contributed by the U.S. Our estimates of U.S. agricultural emissions are comparable to the EPA greenhouse gas (GHG) inventory, which includes estimates from IPCC tier 1 (emission factor) and tier 3 (process-based modeling) approaches. Conversely, our estimated agricultural emissions for Canada and Mexico are twice as large as the respective national GHG inventories.Nitrous oxide (N2O) is the third most important greenhouse gase (GHG) after CO2 and CH4 causing global warming. Among world regions, North America (defined herein as U.S., Canada, and Mexico) is the second largest source of N2O emissions globally, and previous source estimates for this region vary widely. This study aims to provide a comprehensive N2O assessment over North America including all available estimates based on a number of approaches. We report total emissions, and emissions from four anthropogenic source sectors, over the past four decades. Agriculture and industry are two major N2O sources in North America. Our results show a minor increase in the total N2O emission due to agricultural trends in the U.S. Our bottom-up estimate of U.S. agricultural N2O emissions are close to those in the EPA national GHG inventory that includes both empirical and model results. The high consistency suggests the need to take process-based modeling results into account for future national GHG inventories.

Reliable quantification of the sources and sinks of atmospheric carbon dioxide (CO 2 ), including that of their trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Kyoto Protocol and the Paris Agreement. This study provides a consolidated synthesis of estimates for all anthropogenic and natural sources and sinks of CO 2 for the European Union and UK (EU27 + UK), derived from a combination of state-of-the-art bottom-up (BU) and top-down (TD) data sources and models. Given the wide scope of the work and the variety of datasets involved, this study focuses on identifying essential questions which need to be answered to properly understand the differences between various datasets, in particular with regards to the less-well-characterized fluxes from managed ecosystems. The work integrates recent emission inventory data, process-based ecosystem model results, data-driven sector model results and inverse modeling estimates over the period 1990–2018. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported under the UNFCCC in 2019, aiming to assess and understand the differences between approaches. For the uncertainties in NGHGIs, we used the standard deviation obtained by varying parameters of inventory calculations, reported by the member states following the IPCC Guidelines. Variation in estimates produced with other methods, like atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arises from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. In comparing NGHGIs with other approaches, a key source of uncertainty is that related to different system boundaries and emission categories (CO 2 fossil) and the use of different land use definitions for reporting emissions from land use, land use change and forestry (LULUCF) activities (CO 2 land). At the EU27 + UK level, the NGHGI (2019) fossil CO 2 emissions (including cement production) account for 2624 Tg CO 2 in 2014 while all the other seven bottom-up sources are consistent with the NGHGIs and report a mean of 2588 ( ± 463 Tg CO 2 ). The inversion reports 2700 Tg CO 2 ( ± 480 Tg CO 2 ), which is well in line with the national inventories. Over 2011–2015, the CO 2 land sources and sinks from NGHGI estimates report −90 Tg C yr −1 ± 30 Tg C yr −1 while all other BU approaches report a mean sink of −98 Tg C yr −1 ( ± 362 Tg of C from dynamic global vegetation models only). For the TD model ensemble results, we observe a much larger spread for regional inversions (i.e., mean of 253 Tg C yr −1 ± 400 Tg C yr −1 ). This concludes that (a) current independent approaches are consistent with NGHGIs and (b) their uncertainty is too large to allow a verification because of model differences and probably also because of the definition of “CO 2 flux” obtained from different approaches. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.4626578 (Petrescu et al., 2020a).

Reliable quantification of the sources and sinks of greenhouse gases, together with trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement. This study provides a consolidated synthesis of CH4 and N2O emissions with consistently derived state-of-the-art bottom-up (BU) and top-down (TD) data sources for the European Union and UK (EU27 + UK). We integrate recent emission inventory data, ecosystem process-based model results and inverse modeling estimates over the period 1990-2017. BU and TD products are compared with European national greenhouse gas inventories (NGHGIs) reported to the UN climate convention UNFCCC secretariat in 2019. For uncertainties, we used for NGHGIs the standard deviation obtained by varying parameters of inventory calculations, reported by the member states (MSs) following the recommendations of the IPCC Guidelines. For atmospheric inversion models (TD) or other inventory datasets (BU), we defined uncertainties from the spread between different model estimates or model-specific uncertainties when reported. In comparing NGHGIs with other approaches, a key source of bias is the activities included, e.g. anthropogenic versus anthropogenic plus natural fluxes. In inversions, the separation between anthropogenic and natural emissions is sensitive to the geospatial prior distribution of emissions. Over the 2011-2015 period, which is the common denominator of data availability between all sources, the anthropogenic BU approaches are directly comparable, reporting mean emissions of 20.8 Tg CH4 yr-1 (EDGAR v5.0) and 19.0 Tg CH4 yr-1 (GAINS), consistent with the NGHGI estimates of 18.9 ± 1.7 Tg CH4 yr-1. The estimates of TD total inversions give higher emission estimates, as they also include natural emissions. Over the same period regional TD inversions with higher-resolution atmospheric transport models give a mean emission of 28.8 Tg CH4 yr-1. Coarser-resolution global TD inversions are consistent with regional TD inversions, for global inversions with GOSAT satellite data (23.3 Tg CH4 yr-1) and surface network (24.4 Tg CH4 yr-1). The magnitude of natural peatland emissions from the JSBACH-HIMMELI model, natural rivers and lakes emissions, and geological sources together account for the gap between NGHGIs and inversions and account for 5.2 Tg CH4 yr-1. For N2O emissions, over the 2011-2015 period, both BU approaches (EDGAR v5.0 and GAINS) give a mean value of anthropogenic emissions of 0.8 and 0.9 Tg N2O yr-1, respectively, agreeing with the NGHGI data (0.9 ± 0.6 Tg N2O yr-1). Over the same period, the average of the three total TD global and regional inversions was 1.3 ± 0.4 and 1.3 ± 0.1 Tg N2O yr-1, respectively. The TD and BU comparison method defined in this study can be operationalized for future yearly updates for the calculation of CH4 and N2O budgets both at the EU+UK scale and at the national scale. The referenced datasets related to figures are visualized at. (Petrescu et al. 2020b)., SCOPUS: re.j, info:eu-repo/semantics/published

Reliable quantification of the sources and sinks of atmospheric carbon dioxide (CO2), including that of their trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Kyoto Protocol and the Paris Agreement. This study provides a consolidated synthesis of estimates for all anthropogenic and natural sources and sinks of CO2 for the European Union and UK (EU27 + UK), derived from a combination of state-of-the-art bottom-up (BU) and top-down (TD) data sources and models. Given the wide scope of the work and the variety of datasets involved, this study focuses on identifying essential questions which need to be answered to properly understand the differences between various datasets, in particular with regards to the less-well characterized fluxes from managed ecosystems. The work integrates recent emission inventory data, process-based ecosystem model results, data-driven sector model results, and inverse modelling estimates, over the period 1990–2018. BU and TD products are compared with European national GHG inventories (NGHGI) reported under the UNFCCC in 2019, aiming to assess and understand the differences between approaches. For the uncertainties in NGHGI, we used the standard deviation obtained by varying parameters of inventory calculations, reported by the Member States following the IPCC guidelines. Variation in estimates produced with other methods, like atmospheric inversion models (TD) or spatially disaggregated inventory datasets (BU), arise from diverse sources including within-model uncertainty related to parameterization as well as structural differences between models. In comparing NGHGI with other approaches, a key source of uncertainty is that related to different system boundaries and emission categories (CO2 fossil) and the use of different land use definitions for reporting emissions from Land Use, Land Use Change and Forestry (LULUCF) activities (CO2 land). At the EU27 + UK level, the NGHGI (2019) fossil CO2 emissions (including cement production) account for 2624 Tg CO2 in 2014 while all the other seven bottom-up sources are consistent with the NGHGI and report a mean of 2588 (± 463 Tg CO2). The inversion reports 2700 Tg CO2 (± 480 Tg CO2), well in line with the national inventories. Over 2011–2015, the CO2 land sources/sinks from NGHGI estimates report −90 Tg C yr−1 ± 30 Tg C while all other BU approaches report a mean sink of −98 Tg yr−1 (± 362 Tg C from DGVMs only). For the TD model ensemble results, we observe a much larger spread for regional inversions (i.e., mean of 253 Tg C yr−1 ± 400 T g C yr−1). This concludes that a) current independent approaches are consistent with NGHGI b) their uncertainty is too large to allow a verification because of model differences and probably also because of the definition of CO2 flux obtained from different approaches. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.4288883 (Petrescu et al., 2020).

Reliable quantification of the sources and sinks of greenhouse gases, together with trends and uncertainties, is essential to monitoring the progress in mitigating anthropogenic emissions under the Paris Agreement. This study provides a consolidated synthesis of CH4 and N2O emissions with consistently derived state-of-the-art bottom-up (BU) and top-down (TD) data sources for the European Union and UK (EU27+UK). We integrate recent emission inventory data, ecosystem process-based model results, and inverse modelling estimates over the period 1990–2018. BU and TD products are compared with European National GHG Inventories (NGHGI) reported to the UN climate convention secretariat UNFCCC in 2019. For uncertainties, we used for NGHGI the standard deviation obtained by varying parameters of inventory calculations, reported by the Member States following the IPCC guidelines recommendations. For atmospheric inversion models (TD) or other inventory datasets (BU), we defined uncertainties from the spread between different model estimates or model specific uncertainties when reported. In comparing NGHGI with other approaches, a key source of bias is the activities included, e.g. anthropogenic versus anthropogenic plus natural fluxes. In inversions, the separation between anthropogenic and natural emissions is sensitive to the geospatial prior distribution of emissions. Over the 2011–2015 period, which is the common denominator of data availability between all sources, the anthropogenic BU approaches are directly comparable, reporting mean emissions of 20.8 Tg CH4 yr−1 (EDGAR v5.0) and 19.0 Tg CH4 yr−1 (GAINS), consistent with the NGHGI estimates of 18.9 ± 1.7 Tg CH4 yr−1. TD total inversions estimates give higher emission estimates, as they also include natural emissions. Over the same period regional TD inversions with higher resolution atmospheric transport models give a mean emission of 28.8 Tg CH4 yr−1. Coarser resolution global TD inversions are consistent with regional TD inversions, for global inversions with GOSAT satellite data (23.3 Tg CH4yr−1) and surface network (24.4 Tg CH4 yr−1). The magnitude of natural peatland emissions from the JSBACH-HIMMELI model, natural rivers and lakes emissions and geological sources together account for the gap between NGHGI and inversions and account for 5.2 Tg CH4 yr−1. For N2O emissions, over the 2011–2015 period, both BU approaches (EDGAR v5.0 and GAINS) give a mean value of anthropogenic emissions of 0.8 and 0.9 Tg N2O yr−1 respectively, agreeing with the NGHGI data (0.9 ± 0.6 Tg N2O yr−1). Over the same period, the average of the three total TD global and regional inversions was 1.3 ± 0.4 and 1.3 ± 0.1 Tg N2O yr−1 respectively, compared to 0.9 Tg N2O yr−1 from the BU data. The TU and BU comparison method defined in this study can be operationalized for future yearly updates for the calculation of CH4 and N2O budgets both at EU+UK scale and at national scale. The referenced datasets related to figures are visualized at https://doi.org/10.5281/zenodo.4288969 (Petrescu et al., 2020).

Terrestrial ecosystems absorb, at present, about one-fourth of anthropogenic CO2 emissions, which is accumulating in the carbon (C) stocks of vegetation and soils. Land-surface models are used to project the 21st century evolution of this CO2 sink, which mitigates the expected increase in atmospheric CO2 concentration and, thus, climate change. However, classical land-surface models neglect that a fraction of the anthropogenic C absorbed by terrestrial ecosystems is not accumulating on land but is instead exported through the river network. Using the Amazon basin as a case study and a novel land-surface model that represents C exports through rivers, we prove that classical land-surface models such as those used for the Assessment Reports of the IPCC underestimate the CO2 uptake by terrestrial ecosystems and overestimate the amount of anthropogenic C sequestered within vegetation and soils. We provide reasons justifying that similar biases are to be expected at global scale., SCOPUS: ar.j, info:eu-repo/semantics/published

Inland waters receive important amounts of dissolved organic carbon (DOC) from surrounding soils, which drives an important net-heterotrophy and subsequent CO2 emission from these systems. At the same time, this DOC transfer decreases the soil carbon sequestration capacity, which may limit the efficiency of the land carbon sink. The variation of DOC stocks and fluxes in time and space is modeled using the ORCHILEAK model that couples terrestrial ecosystem processes, carbon emissions from soils to headwater streams by runoff and drainage, as well as carbon decomposition and transport in rivers until export to the coastal ocean. The runs were performed at the resolution of 0.5°, taking advantage of the relatively dense observations of soil and river DOC available for European catchments. The model was first evaluated for the hydrology by comparing the discharge at different stations along several large European rivers. The DOC measurements were used to calibrate the different parameters of the ORCHILEAK model and to evaluate the model results. ORCHILEAK was then used to generate the first European map of DOC stocks and leaching for the four seasons. We estimate a soil DOC stock at 71 TgC and a DOC leaching flux of 7,8 TgC/yr, largely dominated by runoff exports during the winter season. Our model results also allow to identify the underlying processes controlling the fraction of terrestrial NPP exported to the European inland water network. The next step will be to use the model to hindcast historical DOC fluxes and predict their evolution over the 21st century using climate change and land use projections from the SSP-RCP scenarios developed for the IPCC assessment report.

Future land carbon (C) uptake under climate changes and rising atmospheric CO2 is influenced by nitrogen (N) and phosphorus (P) constraints. A few existing land surface models (LSMs) account for both N and P dynamics, but lack comprehensive evaluation. This will lead to large uncertainty in estimating the P effect on terrestrial C cycles. With the increasing number of measurements and data-driven products for N- and P- related variables, comprehensive model evaluations on large scale is becoming feasible.In this study, we evaluated the performance of ORCHIDEE-CNP (v1.2) which explicitly simulates N and P cycles in plant and soil, in four aspects: 1) terrestrial C fluxes, 2) N and P fluxes and budget, 3) leaf and soil stoichiometry and 4) resource use efficiencies. We found that ORCHIDEE-CNP improves the simulation of the magnitude of gross primary productivity (GPP) due to more realistic strength of the CO2 fertilization effect of GPP than the without-nutrient-version ORCHIDEE. However, ORCHIDEE-CNP cannot capture the positive and increasing C sink in North Hemisphere over past decades, which is mainly due to that a large fraction of N and P ‘locked’ in soil organic matter cannot be re-allocated into vegetation and leads to a strong N and P limitation on plant growth. ORCHIDEE-CNP generally simulates comparable global total N and P fluxes (e.g. N biofixation, P weathering, N and P uptake etc.) for both natural and agricultural biomes. Overall, ORCHIDEE-CNP doesn’t performance worse in C fluxes than ORCHIDEE, and gives reasonable N and P cycles, which is acceptable in simulating the coupling relationships between C, N and P cycles can be used to explore the nutrient limitations on land C sink from present to the future.

The rivers of the Arctic permafrost region discharge about 11% of the global volumetric river water flux into oceans, doing so into an ocean (the Arctic) with 1% of global ocean water volume and a very high surface area: volume ratio, making it comparatively sensitive to influxes of terrestrially derived matter. This river flux is sourced from precipitation as either rain or snow, which, upon initial contact with the landscape has the immediate potential to interact with carbon(C) in one of two ways: Water running over carbonate or silicate –bearing rocks will cause a reaction whose reactant requires the uptake of atmospheric CO2, which is subsequently transported in river water. This ‘inorganic’ C derived from interaction of water, atmosphere and lithosphere thus represents a C storage or ‘sink’ vector. In addition, water interacting with organic matter in tree canopies, litter or soil can dissolve C contained therein, and transfer it via surface and subsurface water flows into rivers, whereupon it may either be metabolised to the atmosphere or exported to the sea. Recent improvements in understanding of terrestrial C dynamics indicate that this hydrologic transfer of organic matter represents the dominant fate of organic carbon, after plant and soil respiration are accounted for. In the context of amplified Arctic anthropogenic warming, the thermal exposure imposed on the permafrost C stock with expectations of enhanced future precipitation point toward substantial shifts in the lateral flux-mediated organic and inorganic C cycle. However, the complex totality of the processes involved make prediction of this shift difficult.Here, we build upon previous advances in earth system modelling to include the production and lateral transport of dissolved organic C (DOC), respiration-derived CO2, and rock-weathering derived alkalinity in a global land surface model (ORCHIDEE) previously developed to specifically resolve permafrost-region processes. By subjecting the resulting model to state of the art soil, water, vegetation and climatology datasets, we are able to reproduce existing lateral transport processes and fluxes, and project them into the future. In what follows, we show that while Pan-Arctic alkalinity exports and attendant CO2 uptake increase over the 20th and 21st Centuries under warming, DOC fluxes decline largely as a result of deeper soil water flow-paths and the resulting changes in carbon-water interactions. Rather than displaying a clear continuous (linear or non-linear) temperature sensitivity, future Arctic DOC release can increase or decrease with temperature depending on changes in the thermal state and hydrologic flow paths in the deep soil. The net marine effect of these fluxes is to decrease future terrestrially derived seawater acidification. Conversely, our simulations show that CO2 uptake from chemical weathering exceeds its evasion from river water, meaning that when weathering is considered, the inland water carbon cycle shifts from being a net C-source to a sink. Further, this sink increases into the 21st C, partially buffering soil C loss from permafrost thaw.

The Global Carbon Budget 2018 (GCB2018) estimated by the atmospheric CO2 growth rate, fossil fuel emissions, and modeled (bottom-up) land and ocean fluxes cannot be fully closed, leading to a “budget imbalance,” highlighting uncertainties in GCB components. However, no systematic analysis has been performed on which regions or processes contribute to this term. To obtain deeper insight on the sources of uncertainty in global and regional carbon budgets, we analyzed differences in Net Biome Productivity (NBP) for all possible combinations of bottom-up and top-down data sets in GCB2018: (i) 16 dynamic global vegetation models (DGVMs), and (ii) 5 atmospheric inversions that match the atmospheric CO2 growth rate. We find that the global mismatch between the two ensembles matches well the GCB2018 budget imbalance, with Brazil, Southeast Asia, and Oceania as the largest contributors. Differences between DGVMs dominate global mismatches, while at regional scale differences between inversions contribute the most to uncertainty. At both global and regional scales, disagreement on NBP interannual variability between the two approaches explains a large fraction of differences. We attribute this mismatch to distinct responses to El Niño–Southern Oscillation variability between DGVMs and inversions and to uncertainties in land use change emissions, especially in South America and Southeast Asia. We identify key needs to reduce uncertainty in carbon budgets: reducing uncertainty in atmospheric inversions (e.g., through more observations in the tropics) and in land use change fluxes, including more land use processes and evaluating land use transitions (e.g., using high-resolution remote-sensing), and, finally, improving tropical hydroecological processes and fire representation within DGVMs.

In this second part of a two-part study, we performed a simulation of the carbon and water budget of the Lena catchment with the land surface model ORCHIDEE MICT-LEAK, enabled to simulate dissolved organic carbon (DOC) production in soils and its transport and fate in high-latitude inland waters. The model results are evaluated for their ability to reproduce the fluxes of DOC and carbon dioxide (CO2) along the soil-inland-water continuum and the exchange of CO2 with the atmosphere, including the evasion outgassing of CO2 from inland waters. We present simulation results over the years 1901-2007 and show that the model is able to broadly reproduce observed state variables and their emergent properties across a range of interacting physical and biogeochemical processes. These include (1) net primary production (NPP), respiration and riverine hydrologic amplitude, seasonality, and inter-annual variation; (2) DOC concentrations, bulk annual flow, and their volumetric attribution at the sub-catchment level; (3) high headwater versus downstream CO2 evasion, an emergent phenomenon consistent with observations over a spectrum of high-latitude observational studies. These quantities obey emergent relationships with environmental variables like air temperature and topographic slope that have been described in the literature. This gives us confidence in reporting the following additional findings: of the ĝ'1/434TgCyr-1 left over as input to soil matter after NPP is diminished by heterotrophic respiration, 7TgCyr-1 is leached and transported into the aquatic system. Of this, over half (3.6TgCyr-1) is evaded from the inland water surface back into the atmosphere and the remainder (3.4TgCyr-1) flushed out into the Arctic Ocean, mirroring empirically derived studies. These riverine DOC exports represent ĝ'1/41.5% of NPP. DOC exported from the floodplains is dominantly sourced from recent more "labile" terrestrial production in contrast to DOC leached from the rest of the watershed with runoff and drainage, which is mostly sourced from recalcitrant soil and litter. All else equal, both historical climate change (a spring-summer warming of 1.8ĝ' C over the catchment) and rising atmospheric CO2 (+85.6ppm) are diagnosed from factorial simulations to contribute similar significant increases in DOC transport via primary production, although this similarity may not hold in the future., SCOPUS: ar.j, info:eu-repo/semantics/published

International audience; Robust estimates of CO2 budget, CO2 exchanged between the atmosphere and terrestrial biosphere, are necessary to better understand the role of the terrestrial biosphere in mitigating anthropogenic CO2 emissions. Over the past decade, this field of research has advanced through understanding of the differences and similarities of two fundamentally different approaches: “top-down” atmospheric inversions and “bottom-up” biosphere models. Since the first studies were undertaken, these approaches have shown an increasing level of agreement, but disagreements in some regions still persist, in part because they do not estimate the same quantity of atmosphere–biosphere CO2 exchange. Here, we conducted a thorough comparison of CO2 budgets at multiple scales and from multiple methods to assess the current state of the science in estimating CO2 budgets. Our set of atmospheric inversions and biosphere models, which were adjusted for a consistent flux definition, showed a high level of agreement for global and hemispheric CO2 budgets in the 2000s. Regionally, improved agreement in CO2 budgets was notable for North America and Southeast Asia. However, large gaps between the two methods remained in East Asia and South America. In other regions, Europe, boreal Asia, Africa, South Asia, and Oceania, it was difficult to determine whether those regions act as a net sink or source because of the large spread in estimates from atmospheric inversions. These results highlight two research directions to improve the robustness of CO2 budgets: (a) to increase representation of processes in biosphere models that could contribute to fill the budget gaps, such as forest regrowth and forest degradation; and (b) to reduce sink–source compensation between regions (dipoles) in atmospheric inversion so that their estimates become more comparable. Advancements on both research areas will increase the level of agreement between the top-down and bottom-up approaches and yield more robust knowledge of regional CO2 budgets.

Soil erosion by rainfall and runoff is an important process behind the redistribution of soil organic carbon (SOC) over land, hereby impacting the exchange of carbon (C) between land, atmosphere and rivers. However, the net role of soil erosion in the global C cycle is still unclear as it involves small-scale SOC removal, transport and re-deposition processes that can only be addressed over selected small regions with measurements and models. This leads to uncertainties in future projections of SOC stocks and complicates the evaluation of strategies to mitigate climate change through increased SOC sequestration. In this study we present the parsimonious process-based Carbon Erosion DYNAMics model (CE-DYNAM) that links sediment dynamics resulting from water erosion with the C cycle along a cascade of hillslopes, floodplains and rivers. The model simulates horizontal soil and C transfers triggered by erosion across landscapes and the resulting changes in land-atmosphere CO2 fluxes at a resolution of about 8 km at the catchment scale. CE-DYNAM is the result of the coupling of a previously developed coarse-resolution sediment budget model and the ecosystem C cycle and erosion removal model derived from the ORCHIDEE land surface model. CE-DYNAM is driven by spatially explicit historical land use change, climate forcing, and global atmospheric CO2 concentrations affecting ecosystem productivity, erosion rates and residence times of sediment and C in deposition sites. The main features of CE-DYNAM are (1) the spatially explicit simulation of sediment and C fluxes linking hillslopes and floodplains, (2) the low number of parameters that allow running the model at large spatial scales and over long-time scales, and (3) its compatibility with any global land surface model, hereby, providing opportunities to study the effect of soil erosion under global changes. We present the model structure, concepts, and evaluation at the scale of the Rhine catchment for the period 1850–2005 AD. Model results are validated against independent estimates of gross and net soil and C erosion rates, and the spatial variability of SOC stocks from high-resolution modeling studies and observational datasets. We show that despite local differences, the resulting soil and C erosion rates, and SOC stocks from our rather coarse-resolution modelling approach are comparable to high-resolution estimates and observations at sub-basin level. The model also shows that SOC storage increases exponentially with basin area for floodplains in contrast to hillslopes as is seen in observations. We find that soil erosion mobilized 159 Tg (1012 g) of C under changing climate and land use, assuming that the erosion loop of the C cycle was in near steady-state by 1850. This caused a net C sink equal to 1 % of the Net Primary Productivity of the Rhine catchment over 1850–2005 AD. This sink is a result of the dynamic replacement of C on eroding sites that increases in this period due to rising atmospheric CO2 concentrations enhancing the litter C input to the soil from primary production.

The river‐floodplain network plays an important role in the carbon (C) cycle of the Amazon basin, as it transports and processes a significant fraction of the C fixed by terrestrial vegetation, most of which evades as CO2 from rivers and floodplains back to the atmosphere. There is empirical evidence that exceptionally dry or wet years have an impact on the net C balance in the Amazon. While seasonal and interannual variations in hydrology have a direct impact on the amounts of C transferred through the river‐floodplain system, it is not known how far the variation of these fluxes affects the overall Amazon C balance. Here, we introduce a new wetland forcing file for the ORCHILEAK model, which improves the representation of floodplain dynamics and allows us to closely reproduce data‐driven estimates of net C exports through the river–floodplain network. Based on this new wetland forcing and two climate forcing datasets, we show that across the Amazon, the percentage of net primary productivity (NPP) lost to the river–floodplain system is highly variable at the interannual timescale, and wet years fuel aquatic CO2 evasion. However, at the same time overall net ecosystem productivity (NEP) and C sequestration are highest during wet years, partly due to reduced decomposition rates in water‐logged floodplain soils. It is years with the lowest discharge and floodplain inundation, often associated with El Nino events, that have the lowest NEP and the highest total (terrestrial plus aquatic) CO2 emissions back to atmosphere. Furthermore, we find that aquatic C fluxes display greater variation than terrestrial C fluxes, and that this variation significantly dampens the interannual variability in NEP of the Amazon basin. These results call for a more integrative view of the C fluxes through the vegetation‐soil‐river‐floodplain continuum, which directly places aquatic C fluxes into the overall C budget of the Amazon basin.