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Estimates of the annual emissions of carbon from land use, land-use change, and forestry (LULUCF) are important for constructing global, regional, and national carbon budgets, which in turn help predict future rates of climate change and define potential strategies for mitigation. Here, we update a long-term (1850–2020) series of annual national carbon emissions resulting from LULUCF (https://doi.org/10.7910/DVN/U7GHRH, Houghton and Castanho, 2023), based largely, after 1960, on statistics of land use from the Food and Agriculture Organization (FAO) of the United Nations (http://www.fao.org/faostat/en/#data/, FAO, 2021). Those data suggest that rates of deforestation in the tropics (and thus net emissions of carbon) have decreased over the last 10 years (2011–2020). The data also indicate that the net loss of tropical forest area was greater than the net gain in agricultural lands, and we explore four alternative explanations for this apparent forest conversion, one of which is shifting cultivation. We also discuss how opposing trends in recent estimates of tropical deforestation (and emissions) might be reconciled. The calculated emissions of carbon attributable to LULUCF approximate the anthropogenic component of terrestrial carbon emissions, but limiting national carbon accounting to the anthropogenic component may also limit the potential for managing carbon on land.

Anthropogenic and natural CO2 fluxes on land constitute substantial CO2 emissions and removals but are usually not well distinguished in national greenhouse gas inventories (NGHGIs) submitted to the United Nations Framework Convention on Climate Change (UNFCCC). Instead, countries frequently include natural and indirect human-induced CO2 fluxes on managed land in their estimates of CO2 fluxes from land use, land-use change, and forestry (LULUCF), mostly due to methodological constraints. Comparisons of anthropogenic LULUCF flux estimates from global models and from NGHGI reports thus reveal a substantial gap. Globally, this gap could be successfully reconciled by considering the different definitions used by global models and by NGHGI reports. Recent improvements in LULUCF flux modelling enable such a reconciliation now also at the country-level.We separate natural and land-use-related CO2 fluxes from NGHGI reports in eight countries using global models to assess and improve the attribution of land CO2 fluxes to direct anthropogenic activities. In most investigated countries, the gap between model-based and report-based CO2 flux estimates is reduced (by up to 70%) if natural and indirect human-induced CO2 fluxes on managed land are considered. This confirms that the methodological discrepancies between NGHGI reports and global model estimates of LULUCF emissions are primarily due to differing estimation and reporting definitions, which need to be considered when accounting for country contributions to global climate mitigation targets. Further examinations show that remaining differences are linked to country-specific discrepancies between model-based and report-based estimates, such as incomplete reporting by countries, uncertainties in historical land-use dynamics, and model limitations. Moreover, most countries report the areas considered as managed without explicit information on their location, which prevents a precise spatial identification necessary for a detailed comparison of natural fluxes in managed forests with model-based estimates.Reconciling estimates of LULUCF fluxes in individual countries by separating natural and land-use-related CO2 fluxes at national scales provides an important step toward a transparent assessment of LULUCF fluxes from NGHGI reports and supports a fair burden sharing of climate mitigation across countries.

As the focus of climate policy shifts from pledges to implementation, there is a growing need to track progress on climate change mitigation at the country level, particularly for the land-use sector. Despite new tools and models providing unprecedented monitoring opportunities, striking differences remain in estimations of anthropogenic land-use CO2 fluxes between, on the one hand, the national greenhouse gas inventories (NGHGIs) used to assess compliance with national climate targets under the Paris Agreement and, on the other hand, the Global Carbon Budget and Intergovernmental Panel on Climate Change (IPCC) assessment reports, both based on global bookkeeping models (BMs). Recent studies have shown that these differences are mainly due to inconsistent definitions of anthropogenic CO2 fluxes in managed forests. Countries assume larger areas of forest to be managed than BMs do, due to a broader definition of managed land in NGHGIs. Additionally, the fraction of the land sink caused by indirect effects of human-induced environmental change (e.g. fertilisation effect on vegetation growth due to increased atmospheric CO2 concentration) on managed lands is treated as non-anthropogenic by BMs but as anthropogenic in most NGHGIs. We implement an approach that adds the CO2 sink caused by environmental change in countries' managed forests (estimated by 16 dynamic global vegetation models, DGVMs) to the land-use fluxes from three BMs. This sum is conceptually more comparable to NGHGIs and is thus expected to be quantitatively more similar. Our analysis uses updated and more comprehensive data from NGHGIs than previous studies and provides model results at a greater level of disaggregation in terms of regions, countries and land categories (i.e. forest land, deforestation, organic soils, other land uses). Our results confirm a large difference (6.7 GtCO2 yr−1) in global land-use CO2 fluxes between the ensemble mean of the BMs, which estimate a source of 4.8 GtCO2 yr−1 for the period 2000–2020, and NGHGIs, which estimate a sink of −1.9 GtCO2 yr−1 in the same period. Most of the gap is found on forest land (3.5 GtCO2 yr−1), with differences also for deforestation (2.4 GtCO2 yr−1), for fluxes from other land uses (1.0 GtCO2 yr−1) and to a lesser extent for fluxes from organic soils (0.2 GtCO2 yr−1). By adding the DGVM ensemble mean sink arising from environmental change in managed forests (−6.4 GtCO2 yr−1) to BM estimates, the gap between BMs and NGHGIs becomes substantially smaller both globally (residual gap: 0.3 GtCO2 yr−1) and in most regions and countries. However, some discrepancies remain and deserve further investigation. For example, the BMs generally provide higher emissions from deforestation than NGHGIs and, when adjusted with the sink in managed forests estimated by DGVMs, yield a sink that is often greater than NGHGIs. In summary, this study provides a blueprint for harmonising the estimations of anthropogenic land-use fluxes, allowing for detailed comparisons between global models and national inventories at global, regional and country levels. This is crucial to increase confidence in land-use emissions estimates, support investments in land-based mitigation strategies and assess the countries' collective progress under the Global Stocktake of the Paris Agreement. Data from this study are openly available online via the Zenodo portal (Grassi et al., 2023) at https://doi.org/10.5281/zenodo.7650360.

About half of the anthropogenic CO2 emissions remain in the atmosphere and half are taken up by the land and ocean1. If the carbon uptake by land and ocean sinks becomes less efficient, for example, owing to warming oceans2 or thawing permafrost3, a larger fraction of anthropogenic emissions will remain in the atmosphere, accelerating climate change. Changes in the efficiency of the carbon sinks can be estimated indirectly by analysing trends in the airborne fraction, that is, the ratio between the atmospheric growth rate and anthropogenic emissions of CO2 (refs. 4–10). However, current studies yield conflicting results about trends in the airborne fraction, with emissions related to land use and land cover change (LULCC) contributing the largest source of uncertainty7,11,12. Here we construct a LULCC emissions dataset using visibility data in key deforestation zones. These visibility observations are a proxy for fire emissions13,14, which are — in turn — related to LULCC15,16. Although indirect, this provides a long-term consistent dataset of LULCC emissions, showing that tropical deforestation emissions increased substantially (0.16 Pg C decade−1) since the start of CO2 concentration measurements in 1958. So far, these emissions were thought to be relatively stable, leading to an increasing airborne fraction4,5. Our results, however, indicate that the CO2 airborne fraction has decreased by 0.014 ± 0.010 decade−1 since 1959. This suggests that the combined land–ocean sink has been able to grow at least as fast as anthropogenic emissions.

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.

Anthropogenic and natural CO2 fluxes on land constitute substantial CO2 emissions and removals but are usually not well distinguished in national greenhouse gas reporting. Instead, countries frequently combine natural and indirect human-induced CO2 fluxes on managed land in their reports, which diminishes their usefulness for designing policies consistent with climate mitigation targets. Here, we separate natural and land-use-related CO2 fluxes from national reports in eight countries using global models to improve the assessment of attribution of terrestrial CO2 fluxes to direct anthropogenic activities. In most investigated countries, the gap between model-based and report-based CO2 flux estimates is reduced if natural and indirect human-induced CO2 fluxes on managed land are considered. Further examinations show that remaining differences are linked to country-specific discrepancies between model-based and report-based estimates. Separating natural and land-use-related CO2 fluxes at national scales supports a fair burden sharing of climate mitigation across countries and facilitates the assessment of land-based mitigation ambitions. © 2022 The Authors

Estimates of the annual emissions of carbon from Land Use, Land-Use Change, and Forestry (LULUCF) are important for tracking global, regional, and national carbon budgets, which in turn help predict future rates of climate change and help define potential solutions for mitigation. Here we update a long-term (1850–2020) series of annual, national carbon emissions from LULUCF (Houghton and Nassikas, 2017), based largely, after 1960, on statistics of land use from the Food and Agriculture Organization (FAO) of the United Nations (Faostat, 2021). Those data suggest that rates of deforestation in the tropics (and thus net emissions of carbon) have decreased over the last ten years (2011–2020). The data also indicate that the net loss of tropical forests is greater than the net gain in croplands and pastures, and we explore three alternative interpretations of this apparent forest conversion, one of which is shifting cultivation. We note that LULUCF is not equivalent to LULCC (Land-Use and Land-Cover Change), and suggest that the difference between “land use” and “land cover” may contribute to variation among independent estimates of emissions. The calculated emissions of carbon based on LULUCF approximate the anthropogenic component of terrestrial carbon emissions, but carbon management opportunities exist for unmanaged lands as well.

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesise data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land-use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based data-products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the year 2021, EFOS increased by 5.1 % relative to 2020, with fossil emissions at 10.1 ± 0.5 GtC yr-1 (9.9 ± 0.5 GtC yr-1 when the cement carbonation sink is included), ELUC was 1.1 ± 0.7 GtC yr-1, for a total anthropogenic CO2 emission of 11.1 ± 0.8 GtC yr-1 (40.8 ± 2.9 GtCO2). Also, for 2021, GATM was 5.2 ± 0.2 GtC yr-1 (2.5 ± 0.1 ppm yr-1), SOCEAN was 2.9 ± 0.4 GtC yr-1 and SLAND was 3.5 ± 0.9 GtC yr-1, with a BIM of -0.6 GtC yr-1 (i.e. total estimated sources too low or sinks too high). The global atmospheric CO2 concentration averaged over 2021 reached 414.71 ± 0.1 ppm. Preliminary data for 2022, suggest an increase in EFOS relative to 2021 of +1.1 % (0 % to 1.7 %) globally, and atmospheric CO2 concentration reaching 417.3 ppm, more than 50 % above pre-industrial level. Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2021, but discrepancies of up to 1 GtC yr-1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows: (1) a persistent large uncertainty in the estimate of land-use changes emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set (Friedlingstein et al., 2022a; Friedlingstein et al., 2020; Friedlingstein et al., 2019; Le Quéré et al., 2018b, 2018a, 2016, 2015b, 2015a, 2014, 2013). The data presented in this work are available at https://doi.org/10.18160/GCP-2022 (Friedlingstein et al., 2022b).

With the focus of climate policy shifting from pledges to implementation, there is an increasing need to track progress on climate change mitigation at country level, especially for the land-use sector. Despite new tools and models offering unprecedented monitoring opportunities, striking differences remain in estimations of anthropogenic land-use CO2 fluxes between the national greenhouse gas inventories (NGHGIs) used to assess compliance with the Paris Agreement, and the Global Carbon Budget and IPCC assessment reports, both based on global bookkeeping models (BMs). Recent evidence showed that these differences are mainly due to inconsistent definitions of anthropogenic forest CO2 fluxes. In particular, the part of the land sink that is caused by the indirect effects of human-induced environmental change (e.g., fertilization effect on vegetation growth due to increase atmospheric CO2 concentration, climate change) on managed lands is treated as non-anthropogenic by BMs, while in most cases is considered anthropogenic in NGHGIs. In addition, countries use a broader definition of managed land than BMs. Building on previous studies, we implement an approach that adds the CO2 sink due to environmental change from countries’ managed forest area (estimated by Dynamic Global Vegetation Models, DGVMs) to the original land-use flux from BMs. This sum is expected to be conceptually more comparable to NGHGIs. Our analysis uses updated and more comprehensive data from NGHGIs than previous studies and provides model results at a greater level of disaggregation in terms of land categories (i.e., forest land, deforestation, organic soils, other land uses) and countries. Our results confirm a large difference in land use CO2 fluxes between the ensemble mean of the BMs, estimating a source of 4.3 GtCO2 yr-1 globally for the period 2001–2020, and NGHGIs, which estimate a sink of -1.7 GtCO2 yr-1. Most of this 6.0 GtCO2 yr-1 gap is found on forest land (3.8 GtCO2 yr-1), with differences also for deforestation (1.1 GtCO2 yr-1), other land uses (1.0 GtCO2 yr-1), and to a lesser extent for organic soils (0.1 GtCO2 yr-1). By adding the DGVM ensemble mean sink arising from environmental change in managed forests (-5.1 GtCO2 yr-1) to BMs estimates, the gap between BMs and NGHGIs becomes significantly smaller both globally (residual gap: 0.9 GtCO2 yr-1) and in most regions and countries. The remaining differences mostly reflect smaller net emissions from deforestation and agricultural land in the NGHGIs of developing countries than in the BMs. By reconciling most of the differences between NGHGIs and global models (BMs and DGVMs), offering a blueprint for operationalizing future comparisons, and identifying areas to be further investigated, this study represents an important step forward for increasing transparency and confidence in land-use CO2 flux estimates at the country level. This is crucial to support land-based mitigation investments and assess the countries’ collective progress under the Paris Agreement’s Global Stocktake.

Constraining the climate crisis requires urgent action to reduce anthropogenic emissions while simultaneously removing carbon dioxide from the atmosphere. Improved information about the maximum magnitude and spatial distribution of opportunities for additional land-based removals of CO2 is needed to guide on-the-ground decision-making about where to implement climate change mitigation strategies. Here, we present a globally consistent spatial dataset (approximately 500-m resolution) of current, potential, and unrealized potential carbon storage in woody plant biomass and soil organic matter. We also provide a framework for prioritizing actions related to the restoration, management, and maintenance of woody carbon stocks and associated soils. By comparing current to potential carbon storage, while excluding areas critical to food production and human habitation, we find 287 petagrams (PgC) of unrealized potential storage opportunity, of which 78% (224 PgC) is in biomass and 22% (63 PgC) is in soil. Improved management of existing forests may offer nearly three-fourths (206 PgC) of the total unrealized potential, with the majority (71%) concentrated in tropical ecosystems. However, climate change is a source of considerable uncertainty. While additional research is needed to understand the impact of natural disturbances and biophysical feedbacks, we project that the potential for additional carbon storage in woody biomass will increase (+17%) by 2050 despite projected decreases (−12%) in the tropics. Our results establish an absolute reference point and conceptual framework for national and jurisdictional prioritization of locations and actions to increase land-based carbon storage.

Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere in a changing climate is critical to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe and synthesize data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFOS) are based on energy statistics and cement production data, while emissions from land-use change (ELUC), mainly deforestation, are based on land-use and land-use change data and bookkeeping models. Atmospheric CO2 concentration is measured directly, and its growth rate (GATM) is computed from the annual changes in concentration. The ocean CO2 sink (SOCEAN) is estimated with global ocean biogeochemistry models and observation-based data-products. The terrestrial CO2 sink (SLAND) is estimated with dynamic global vegetation models. The resulting carbon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changes in the atmosphere, ocean, and terrestrial biosphere, is a measure of imperfect data and understanding of the contemporary carbon cycle. All uncertainties are reported as ±1σ. For the first time, an approach is shown to reconcile the difference in our ELUC estimate with the one from national greenhouse gases inventories, supporting the assessment of collective countries’ climate progress. For the year 2020, EFOS declined by 5.4 % relative to 2019, with fossil emissions at 9.5 ± 0.5 GtC yr−1 (9.3 ± 0.5 GtC yr−1 when the cement carbonation sink is included), ELUC was 0.9 ± 0.7 GtC yr−1, for a total anthropogenic CO2 emission of 10.2 ± 0.8 GtC yr−1 (37.4 ± 2.9 GtCO2). Also, for 2020, GATM was 5.0 ± 0.2 GtC yr−1 (2.4 ± 0.1 ppm yr−1), SOCEAN was 3.0 ± 0.4 GtC yr−1 and SLAND was 2.9 ± 1 GtC yr−1, with a BIM of −0.8 GtC yr−1. The global atmospheric CO2 concentration averaged over 2020 reached 412.45 ± 0.1 ppm. Preliminary data for 2021, suggest a rebound in EFOS relative to 2020 of +4.9 % (4.1 % to 5.7 %) globally. Overall, the mean and trend in the components of the global carbon budget are consistently estimated over the period 1959–2020, but discrepancies of up to 1 GtC yr−1 persist for the representation of annual to semi-decadal variability in CO2 fluxes. Comparison of estimates from multiple approaches and observations shows: (1) a persistent large uncertainty in the estimate of land-use changes emissions, (2) a low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra- tropics, and (3) a discrepancy between the different methods on the strength of the ocean sink over the last decade. This living data update documents changes in the methods and data sets used in this new global carbon budget and the progress in understanding of the global carbon cycle compared with previous publications of this data set (Friedlingstein et al., 2020; Friedlingstein et al., 2019; Le Quéré et al., 2018b, 2018a, 2016, 2015b, 2015a, 2014, 2013). The data presented in this work are available at https://doi.org/10.18160/gcp-2021 (Friedlingstein et al., 2021).

Emissions from land use and land cover change are a key component of the global carbon cycle. However, models are required to disentangle these emissions from the land carbon sink, as only the sum of both can be physically observed. Their assessment within the yearly community-wide effort known as the “Global Carbon Budget” remains a major difficulty, because it combines two lines of evidence that are inherently inconsistent: bookkeeping models and dynamic global vegetation models. Here, we propose a unifying approach that relies on a bookkeeping model, which embeds processes and parameters calibrated on dynamic global vegetation models, and the use of an empirical constraint. We estimate that the global CO2 emissions from land use and land cover change were 1.36±0.42 PgC yr−1 (1σ range) on average over the 2009–2018 period and reached a cumulative total of 206±57 PgC over the 1750–2018 period. We also estimate that land cover change induced a global loss of additional sink capacity – that is, a foregone carbon removal, not part of the emissions – of 0.68±0.57 PgC yr−1 and 32±23 PgC over the same periods, respectively. Additionally, we provide a breakdown of our results' uncertainty, including aspects such as the land use and land cover change data sets used as input and the model's biogeochemical parameters. We find that the biogeochemical uncertainty dominates our global and regional estimates with the exception of tropical regions in which the input data dominates. Our analysis further identifies key sources of uncertainty and suggests ways to strengthen the robustness of future Global Carbon Budget estimates.

The Global Carbon Project (GCP) has published global carbon budgets annually since 2007 (Canadell et al. [2007], Proc Natl Acad Sci USA, 104, 18866-18870; Raupach et al. [2007], Proc Natl Acad Sci USA, 104, 10288-10293). There are many scientists involved, but the terrestrial fluxes that appear in the budgets are not well understood by ecologists and biogeochemists outside of that community. The purpose of this paper is to make the terrestrial fluxes of carbon in those budgets more accessible to a broader community. The GCP budget is composed of annual perturbations from pre-industrial conditions, driven by addition of carbon to the system from combustion of fossil fuels and by transfers of carbon from land to the atmosphere as a result of land use. The budget includes a term for each of the major fluxes of carbon (fossil fuels, oceans, land) as well as the rate of carbon accumulation in the atmosphere. Land is represented by two terms: one resulting from direct anthropogenic effects (Land Use, Land-Use Change, and Forestry or land management) and one resulting from indirect anthropogenic (e.g., CO2 , climate change) and natural effects. Each of these two net terrestrial fluxes of carbon, in turn, is composed of opposing gross emissions and removals (e.g., deforestation and forest regrowth). Although the GCP budgets have focused on the two net terrestrial fluxes, they have paid little attention to the gross components, which are important for a number of reasons, including understanding the potential for land management to remove CO2 from the atmosphere and understanding the processes responsible for the sink for carbon on land. In contrast to the net fluxes of carbon, which are constrained by the global carbon budget, the gross fluxes are largely unconstrained, suggesting that there is more uncertainty than commonly believed about how terrestrial carbon emissions will respond to future fossil fuel emissions and a changing climate.

Given the short time-frame to limit global warming, and the current emissions gap, it is critical to prioritise mitigation actions. To date, scant attention has been paid to the mitigation benefits of primary forest protection. We estimated tropical forest ecosystem carbon stocks and flows. The ecosystem carbon stock of primary tropical forests is estimated at 141–159 Pg C (billion tonnes of carbon) which is some 49–53% of all tropical forest carbon, the living biomass component of which alone is 91–103% of the remaining carbon budget to limit global warming to below 1.5 degrees above pre-industrial levels. Furthermore, tropical forests have ongoing sequestration rates 0.47–1.3 Pg C yr−1, equivalent to 8–13% of annual global anthropogenic CO2 (carbon dioxide) emissions. We examined three main forest-based strategies used in the land sector—halting deforestation, increasing forest restoration and improving the sustainable management of production forests. The mitigation benefits of primary forest protection are contingent upon how degradation is defined and accounted for, while those from restoration also depend on how restoration is understood and applied. Through proforestation, reduced carbon stocks in secondary forests can regrow to their natural carbon carrying capacity or primary forest state. We evaluated published data from studies comparing logged and unlogged forests. On average, primary forests store around 35% more carbon. While comparisons are confounded by a range of factors, reported biomass carbon recovery rates were from 40 to 100+ years. There is a substantive portfolio of forest-based mitigation actions and interventions available to policy and decision-makers, depending on national circumstances, in addition to SFM and plantation focused approaches, that can be grouped into four main strategies: protection; proforestation, reforestation and restoration; reform of guidelines, accounting rules and default values; landscape conservation planning. Given the emissions gap, mitigation strategies that merely reduce the rate of emissions against historic or projected reference levels are insufficient. Mitigation strategies are needed that explicitly avoid emissions where possible as well as enabling ongoing sequestration.

Southeast Asia is a region known for active land-use changes (LUC) over the past 60 years; yet, how trends in net CO2 uptake and release resulting from LUC activities (net LUC flux) have changed through past decades remains uncertain. The level of uncertainty in net LUC flux from process-based models is so high that it cannot be concluded that newer estimates are necessarily more reliable than older ones. Here, we examined net LUC flux estimates of Southeast Asia for the 1980s−2010s from older and newer sets of Dynamic Global Vegetation Model simulations (TRENDY v2 and v7, respectively), and forcing data used for running those simulations, along with two book-keeping estimates (H&N and BLUE). These estimates yielded two contrasting historical LUC transitions, such that TRENDY v2 and H&N showed a transition from increased emissions from the 1980s to 1990s to declining emissions in the 2000s, while TRENDY v7 and BLUE showed the opposite transition. We found that these contrasting transitions originated in the update of LUC forcing data, which reduced the loss of forest area during the 1990s. Further evaluation of remote sensing studies, atmospheric inversions, and the history of forestry and environmental policies in Southeast Asia supported the occurrence of peak emissions in the 1990s and declining thereafter. However, whether LUC emissions continue to decline in Southeast Asia remains uncertain as key processes in recent years, such as conversion of peat forest to oil-palm plantation, are yet to be represented in the forcing data, suggesting a need for further revision., Global Biogeochemical Cycles, 36 (1), ISSN:0886-6236, ISSN:1944-9224

Carbon budget accounting relies heavily on Food and Agriculture Organization land-use data reported by governments. Here we develop a new land-use and cover-change database for China, finding that differing historical survey methods biased China's reported data causing large errors in Food and Agriculture Organization databases. Land ecosystem model simulations driven with the new data reveal a strong carbon sink of 8.9 ± 0.8 Pg carbon from 1980 to 2019 in China, which was not captured in Food and Agriculture Organization data-based estimations due to biased land-use and cover-change signals. The land-use and cover-change in China, characterized by a rapid forest expansion from 1980 to 2019, contributed to nearly 44% of the national terrestrial carbon sink. In contrast, climate changes (22.3%), increasing nitrogen deposition (12.9%), and rising carbon dioxide (8.1%) are less important contributors. This indicates that previous studies have greatly underestimated the impact of land-use and cover-change on the terrestrial carbon balance of China. This study underlines the importance of reliable land-use and cover-change databases in global carbon budget accounting.

Fluxes from deforestation, changes in land cover, land use and management practices (FLUC for simplicity) contributed to approximately 14 % of anthropogenic CO2 emissions in 2009–2018. Estimating FLUC accurately in space and in time remains, however, challenging, due to multiple sources of uncertainty in the calculation of these fluxes. This uncertainty, in turn, is propagated to global and regional carbon budget estimates, hindering the compilation of a consistent carbon budget and preventing us from constraining other terms, such as the natural land sink. Uncertainties in FLUC estimates arise from many different sources, including differences in model structure (e.g. process based vs. bookkeeping) and model parameterisation. Quantifying the uncertainties from each source requires controlled simulations to separate their effects. Here, we analyse differences between the two bookkeeping models used regularly in the global carbon budget estimates since 2017: the model by Hansis et al. (2015) (BLUE) and that by Houghton and Nassikas (2017) (HN2017). The two models have a very similar structure and philosophy, but differ significantly both with respect to FLUC intensity and spatiotemporal variability. This is due to differences in the land-use forcing but also in the model parameterisation. We find that the larger emissions in BLUE compared to HN2017 are largely due to differences in C densities between natural and managed vegetation or primary and secondary vegetation, and higher allocation of cleared and harvested material to fast turnover pools in BLUE than in HN2017. Besides parameterisation and the use of different forcing, other model assumptions cause differences: in particular that BLUE represents gross transitions which leads to overall higher carbon losses that are also more quickly realised than HN2017.

About half of the anthropogenic CO

Fluxes from deforestation, changes in land-cover, land-use and management practices (FLUC for simplicity) contributed to circa 14 % of anthropogenic CO2 emissions in 2009–2018. Estimating FLUC accurately in space and in time remains, however, challenging, due to multiple sources of uncertainty in the calculation of these fluxes. This uncertainty, in turn, is propagated to global and regional carbon budget estimates, hindering the compilation of a consistent carbon budget and preventing us from constraining other terms, such as the natural land sink. Uncertainties in FLUC estimates arise from many different sources, including differences in model structure (e.g., process- based vs. bookkeeping) and model parameterization. Quantifying the uncertainties from each source requires controlled simulations to separate their effects. Here we analyze differences between the two bookkeeping models used regularly in the global carbon budget estimates since 2017: the model by Hansis et al. (Hansis et al., 2015) (BLUE) and that by Houghton and Nassikas (Houghton and Nassikas, 2017) (HN2017). The two models have a very similar structure and philosophy, but differ significantly both with respect to FLUC intensity and spatio-temporal variability. This is due to differences in the land-use forcing, but also in the model parameterization. We find that the larger emissions in BLUE compared to HN2017 are largely due to differences in C densities between natural and managed vegetation or primary and secondary vegetation, and higher allocation of cleared and harvested material to fast turnover pools in BLUE than in HN2017. Beside parameterization and the use of different forcing, other model assumptions cause differences, in particular that BLUE represents gross transitions which leads to overall higher carbon losses that are also more quickly realized than HN2017.

Managing forests for climate change mitigation requires action by diverse stakeholders undertaking different activities with overlapping objectives and spatial impacts. To date, several forest carbon monitoring systems have been developed for different regions using various data, methods and assumptions, making it difficult to evaluate mitigation performance consistently across scales. Here, we integrate ground and Earth observation data to map annual forest-related greenhouse gas emissions and removals globally at a spatial resolution of 30 m over the years 2001–2019. We estimate that global forests were a net carbon sink of −7.6 ± 49 GtCO2e yr−1, reflecting a balance between gross carbon removals (−15.6 ± 49 GtCO2e yr−1) and gross emissions from deforestation and other disturbances (8.1 ± 2.5 GtCO2e yr−1). The geospatial monitoring framework introduced here supports climate policy development by promoting alignment and transparency in setting priorities and tracking collective progress towards forest-specific climate mitigation goals with both local detail and global consistency.

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).

To constrain global warming, we must strongly curtail greenhouse gas emissions and capture excess atmospheric carbon dioxide1,2. Regrowing natural forests is a prominent strategy for capturing additional carbon3, but accurate assessments of its potential are limited by uncertainty and variability in carbon accumulation rates2,3. To assess why and where rates differ, here we compile 13,112 georeferenced measurements of carbon accumulation. Climatic factors explain variation in rates better than land-use history, so we combine the field measurements with 66 environmental covariate layers to create a global, one-kilometre-resolution map of potential aboveground carbon accumulation rates for the first 30 years of natural forest regrowth. This map shows over 100-fold variation in rates across the globe, and indicates that default rates from the Intergovernmental Panel on Climate Change (IPCC)4,5 may underestimate aboveground carbon accumulation rates by 32 per cent on average and do not capture eight-fold variation within ecozones. Conversely, we conclude that maximum climate mitigation potential from natural forest regrowth is 11 per cent lower than previously reported3 owing to the use of overly high rates for the location of potential new forest. Although our data compilation includes more studies and sites than previous efforts, our results depend on data availability, which is concentrated in ten countries, and data quality, which varies across studies. However, the plots cover most of the environmental conditions across the areas for which we predicted carbon accumulation rates (except for northern Africa and northeast Asia). We therefore provide a robust and globally consistent tool for assessing natural forest regrowth as a climate mitigation strategy. A one-kilometre-resolution map of aboveground carbon accumulation rates of forest regrowth shows 100-fold variation across the globe, with rates 32% higher on average than IPCC estimates.

Nature-based solutions (NbS) can address climate change, biodiversity loss, human well-being and their interactions in an integrated way. A major barrier to achieving this is the lack of comprehensiveness in current carbon accounting which has focused on flows rather than stocks of carbon and led to perverse outcomes. We propose a new comprehensive approach to carbon accounting based on the whole carbon cycle, covering both stocks and flows, and linking changes due to human activities with responses in the biosphere and atmosphere. We identify enhancements to accounting, namely; inclusion of all carbon reservoirs, changes in their condition and stability, disaggregated flows, and coverage of all land areas. This comprehensive approach recognises that both carbon stocks (as storage) and carbon flows (as sequestration) contribute to the ecosystem service of global climate regulation. In contrast, current ecosystem services measurement and accounting commonly use only carbon sequestration measured as net flows, while greenhouse gas inventories use flows from sources to sinks. This flow-based accounting has incentivised planting and maintaining young forests with high carbon uptake rates, resulting, perversely, in failing to reveal the greater mitigation benefit from protecting larger, more stable and resilient carbon stocks in natural forests. We demonstrate the benefits of carbon storage and sequestration for climate mitigation, in theory as ecosystem services within an ecosystem accounting framework, and in practice using field data that reveals differences in results between accounting for stocks or flows. Our proposed holistic and comprehensive carbon accounting makes transparent the benefits, trade-offs and shortcomings of NbS actions for climate mitigation and sustainability outcomes. Adopting this approach is imperative for revision of ecosystem accounting systems under the System of Environmental-Economic Accounting and contributing to evidence-based decision-making for international conventions on climate (UNFCCC), biodiversity (CBD) and sustainability (SDGs).

Emissions from land-use and land-cover change are a key component of the global carbon cycle. Models are required to disentangle these emissions and the land carbon sink, however, because only the sum of both can be physically observed. Their assessment within the yearly community-wide effort known as the Global Carbon Budget remains a major difficulty, because it combines two lines of evidence that are inherently inconsistent: bookkeeping models and dynamic global vegetation models. Here, we propose a unifying approach relying on a bookkeeping model that embeds processes and parameters calibrated on dynamic global vegetation models, and the use of an empirical constraint. We estimate global CO2 emissions from land-use and land-cover change were 1.36 ± 0.42 Pg C yr−1 (1-σ range) on average over 2009–2018, and 206 ± 57 Pg C cumulated over 1750–2018. We also estimate that land-cover change induced a global loss of additional sink capacity – that is, a foregone carbon removal, not part of the emissions – of 0.68 ± 0.57 Pg C yr−1 and 32 ± 23 Pg C over the same periods, respectively. Additionally, we provide a breakdown of our results' uncertainty following aspects that include the land-use and land-cover change data sets used as input, and the model's biogeochemical parameters. We find the biogeochemical uncertainty dominates our global and regional estimates, with the exception of tropical regions in which the input data dominates. Our analysis further identifies key sources of uncertainty, and suggests ways to strengthen the robustness of future Global Carbon Budgets.

The magnitude of gross sources and sinks of carbon from current land management practices suggests that, if deforestation and forest degradation from human activities were stopped, and forests were allowed to recover (e.g., harvested forests and the fallows of shifting cultivation), an estimated 4.4 PgC might be removed from the atmosphere each year for the next century or more. Although the cumulative removal by 2100 would amount to ~ 360 PgC, this long-term estimate represents a gross removal. The net removal would be considerably less because carbon held presently in wood products and in cultivated and disturbed soils would be emitted to the atmosphere even if further deforestation and harvests were stopped. Accounting for these committed emissions, a more likely estimate is that 100–130 PgC might be removed from the atmosphere by 2100 in recovering forests. The quantity is not enough to counter emissions under a business-as-usual future, but it is large (30–60%) relative to the carbon emissions allowable for staying under a warming of 2°C. Thus, land management, and forest management in particular, could help stabilize concentrations of CO2 in the atmosphere and provide a bridge for the transition from fossil fuels to renewable forms of energy.

International audience; The terrestrial carbon sink accelerated during 1998-2012, concurrently with the slow warming period, but the mechanisms behind this acceleration are unclear. Here we analyse recent changes in the net land carbon sink (NLS) and its driving factors, using atmospheric inversions and terrestrial carbon models. We show that the linear trend of NLS during 1998-2012 is about 0.17 ± 0.05 Pg C yr-2 , which is three times larger than during 1980-1998 (0.05 ± 0.05 Pg C yr-2). According to terrestrial carbon model simulations, the intensification of the NLS cannot be explained by CO2 fertilization or climate change alone. We therefore use a bookkeeping model to explore the contribution of changes in land-use emissions and find that decreasing land-use emissions are the dominant cause of the intensification of the NLS during the slow warming period. This reduction of land-use emissions is due to both decreased tropical forest area loss and increased afforestation in northern temperate regions. The estimate based on atmospheric inversions shows consistently reduced land-use emissions, whereas another bookkeeping model did not reproduce such changes, probably owing to missing the signal of reduced tropical deforestation. These results highlight the importance of better constraining emissions from land-use change to understand recent trends in land carbon sinks.

Interactions between land-use change and climate-carbon cycle feedbacks include biological processes, such as CO2-enhanced productivity of lands managed for food, energy, or wood; an increased terrestrial carbon sink as a consequence of an expanded area of secondary forests; and the effects of land cover on biophysical properties affecting climate (e.g., albedo, roughness, evapotranspiration). Interactions also result at a conceptual level because of the methods used to evaluate terrestrial terms in the global carbon budget. For example, net carbon emissions from land-use change help define the airborne fraction, as well as the magnitude of the residual terrestrial carbon sink. And the lost additional sink capacity (LASC) determined with dynamic global vegetation models (DGVMs) reveals an indirect long-term consequence of land-use change: the loss of a carbon sink as a result of converting forests to open lands. Three different terrestrial carbon fluxes are important for understanding perturbations to the global carbon cycle: the net annual emissions from land-use change, the residual terrestrial carbon sink, and the LASC.

In their recent contribution, Scully et al (2021 Environ. Res. Lett. 16 043001) review and revise past life cycle assessments of corn-grain ethanol’s carbon (C) intensity to suggest that a current ‘central best estimate’ is considerably less than all prior estimates. Their conclusion emerges from selection and recombination of sector-specific greenhouse gas emission predictions from disparate studies in a way that disproportionately favors small values and optimistic assumptions without rigorous justification nor empirical support. Their revisions most profoundly reduce predicted land use change (LUC) emissions, for which they propose a central estimate that is roughly half the smallest comparable value they review (figure 1). This LUC estimate represents the midpoint of (a) values retained after filtering the predictions of past studies based on a set of unfounded criteria; and (b) a new estimate they generate for domestic (i.e. U.S.) LUC emissions. The filter the authors apply endorses a singular means of LUC assessment which they assert as the ‘best practice’ despite a recent unacknowledged review (Malins et al 2020 J. Clean. Prod. 258 120716) that shows this method almost certainly underestimates LUC. Moreover, their domestic C intensity estimate surprisingly suggests that cropland expansion newly sequesters soil C, counter to ecological theory and empirical evidence. These issues, among others, prove to grossly underestimate the C intensity of corn-grain ethanol and mischaracterize the state of our science at the risk of perversely affecting policy outcomes.

Forests out of balance Are tropical forests a net source or net sink of atmospheric carbon dioxide? As fundamental a question as that is, there still is no agreement about the answer, with different studies suggesting that it is anything from a sizable sink to a modest source. Baccini et al. used 12 years of MODIS satellite data to determine how the aboveground carbon density of woody, live vegetation has changed throughout the entire tropics on an annual basis. They find that the tropics are a net carbon source, with losses owing to deforestation and reductions in carbon density within standing forests being double that of gains resulting from forest growth. Science , this issue p. 230

Forest growth provides negative emissions of carbon that could help keep the earth's surface temperature from exceeding 2°C, but the global potential is uncertain. Here we use land-use information from the FAO and a bookkeeping model to calculate the potential negative emissions that would result from allowing secondary forests to recover. We find the current gross carbon sink in forests recovering from harvests and abandoned agriculture to be -4.4 PgC/year, globally. The sink represents the potential for negative emissions if positive emissions from deforestation and wood harvest were eliminated. However, the sink is largely offset by emissions from wood products built up over the last century. Accounting for these committed emissions, we estimate that stopping deforestation and allowing secondary forests to grow would yield cumulative negative emissions between 2016 and 2100 of about 120 PgC, globally. Extending the lifetimes of wood products could potentially remove another 10 PgC from the atmosphere, for a total of approximately 130 PgC, or about 13 years of fossil fuel use at today's rate. As an upper limit, the estimate is conservative. It is based largely on past and current practices. But if greater negative emissions are to be realized, they will require an expansion of forest area, greater efficiencies in converting harvested wood to long-lasting products and sources of energy, and novel approaches for sequestering carbon in soils. That is, they will require current management practices to change.

The net flux of carbon from land use and land cover change (LULCC) is an important term in the global carbon balance. Here we report a new estimate of annual fluxes from 1850 to 2015, updating earlier analyses with new estimates of both historical and current rates of LULCC and including emissions from draining and burning of peatlands in Southeast Asia. For most of the 186 countries included we relied on data from Food and Agriculture Organization to document changes in the areas of croplands and pastures since 1960 and changes in the areas of forests and “other land” since 1990. For earlier years we used other sources of information. We used a bookkeeping model that prescribed changes in carbon density of vegetation and soils for 20 types of ecosystems and five land uses. The total net flux attributable to LULCC over the period 1850–2015 is calculated to have been 145 ± 16 Pg C (1 standard deviation). Most of the emissions were from the tropics (102 ± 5.8 Pg C), generally increasing over time to a maximum of 2.10 Pg C yr−1 in 1997. Outside the tropics emissions were roughly constant at 0.5 Pg C yr−1 until 1940, declined to zero around 1970, and then became negative. For the most recent decade (2006–2015) global net emissions from LULCC averaged 1.11 (±0.35) Pg C yr−1, consisting of a net source from the tropics (1.41 ± 0.17 Pg C yr−1), a net sink in northern midlatitudes (−0.28 ± 0.21 Pg C yr−1), and carbon neutrality in southern midlatitudes.

The recent ‘warming hiatus’ presents an excellent opportunity to investigate climate sensitivity of carbon cycle processes. Here we combine satellite and atmospheric observations to show that the rate of net biome productivity (NBP) has significantly accelerated from −0.007 ± 0.065 PgC yr−2 over the warming period (1982 to 1998) to 0.119 ± 0.071 PgC yr−2 over the warming hiatus (1998–2012). This acceleration in NBP is not due to increased primary productivity, but rather reduced respiration that is correlated (r = 0.58; P = 0.0007) and sensitive (γ = 4.05 to 9.40 PgC yr−1 per °C) to land temperatures. Global land models do not fully capture this apparent reduced respiration over the warming hiatus; however, an empirical model including soil temperature and moisture observations better captures the reduced respiration. Satellite and atmospheric observations show that the rate of net biome productivity has accelerated over the warming ‘hiatus’ period (1998–2012). This net gain results from reduced respiration, rather than increased primary productivity.

Consistent long-term estimates of fire emissions are important to understand the changing role of fire in the global carbon cycle and to assess the relative importance of humans and climate in shaping fire regimes. However, there is limited information on fire emissions from before the satellite era. We show that in the Amazon region, including the Arc of Deforestation and Bolivia, visibility observations derived from weather stations could explain 61% of the variability in satellite-based estimates of bottom-up fire emissions since 1997 and 42% of the variability in satellite-based estimates of total column carbon monoxide concentrations since 2001. This enabled us to reconstruct the fire history of this region since 1973 when visibility information became available. Our estimates indicate that until 1987 relatively few fires occurred in this region and that fire emissions increased rapidly over the 1990s. We found that this pattern agreed reasonably well with forest loss data sets, indicating that although natural fires may occur here, deforestation and degradation were the main cause of fires. Compared to fire emissions estimates based on Food and Agricultural Organization's Global Forest and Resources Assessment data, our estimates were substantially lower up to the 1990s, after which they were more in line. These visibility-based fire emissions data set can help constrain dynamic global vegetation models and atmospheric models with a better representation of the complex fire regime in this region.