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Accurate assessment of anthropogenic carbon dioxide (CO2) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – is important to better understand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO2 emissions (EFF) 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) and terrestrial CO2 sink (SLAND) are estimated with global process models constrained by observations. 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 last decade available (2009–2018), EFF was 9.5±0.5 GtC yr−1, ELUC 1.5±0.7 GtC yr−1, GATM 4.9±0.02 GtC yr−1 (2.3±0.01 ppm yr−1), SOCEAN 2.5±0.6 GtC yr−1, and SLAND 3.2±0.6 GtC yr−1, with a budget imbalance BIM of 0.4 GtC yr−1 indicating overestimated emissions and/or underestimated sinks. For the year 2018 alone, the growth in EFF was about 2.1 % and fossil emissions increased to 10.0±0.5 GtC yr−1, reaching 10 GtC yr−1 for the first time in history, ELUC was 1.5±0.7 GtC yr−1, for total anthropogenic CO2 emissions of 11.5±0.9 GtC yr−1 (42.5±3.3 GtCO2). Also for 2018, GATM was 5.1±0.2 GtC yr−1 (2.4±0.1 ppm yr−1), SOCEAN was 2.6±0.6 GtC yr−1, and SLAND was 3.5±0.7 GtC yr−1, with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 407.38±0.1 ppm averaged over 2018. For 2019, preliminary data for the first 6–10 months indicate a reduced growth in EFF of +0.6 % (range of −0.2 % to 1.5 %) based on national emissions projections for China, the USA, the EU, and India and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. Overall, the mean and trend in the five components of the global carbon budget are consistently estimated over the period 1959–2018, but discrepancies of up to 1 GtC yr−1 persist for the representation of semi-decadal variability in CO2 fluxes. A detailed comparison among individual estimates and the introduction of a broad range of observations shows (1) no consensus in the mean and trend in land use change emissions over the last decade, (2) a persistent low agreement between the different methods on the magnitude of the land CO2 flux in the northern extra-tropics, and (3) an apparent underestimation of the CO2 variability by ocean models outside the tropics. 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 (Le Quéré et al., 2018a, b, 2016, 2015a, b, 2014, 2013). The data generated by this work are available at https://doi.org/10.18160/gcp-2019 (Friedlingstein et al., 2019).

Accurate assessmen of anthropogenic carbon dioxide (CO₂) emissions and their redistribution among the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – is important to betterunderstand the global carbon cycle, support the development of climate policies, and project future climate change. Here we describe data sets and methodology to quantify all major components of the global carbon budget, including their uncertainties, based on the combination of a range of data, algorithms, statistics, and model estimates and their interpretation by a broad scientific community. We discuss changes compared to previous estimates and consistency within and among components, alongside methodology and data limitations. CO₂ emissions from fossil fuels and industry (EFF) are based on energy statistics and cement production data, respec- tively, while emissions from land-use change (ELUC), mainly deforestation, are based on combined evidence from land-cover change data, fire activity associated with deforestation, and models. The global atmospheric CO₂ concentration is measured directly and its rate of growth (GATM) is computed from the annual changes in concentration. The mean ocean CO₂ sink (SOCEAN) is based on observations from the 1990s, while the an- nual anomalies and trends are estimated with ocean models. The variability in SOCEAN is evaluated with data products based on surveys of ocean CO₂ measurements. The global residual terrestrial CO₂ sink (SLAND) is estimated by the difference of the other terms of the global carbon budget and compared to results of independent dynamic global vegetation models. We compare the mean land and ocean fluxes and their variability to estimates from three atmospheric inverse methods for three broad latitude bands. All uncertainties are reported as ± 1σ, reflecting the current capacity to characterise the annual estimates of each component of the global carbon budget. For the last decade available (2006–2015), EFF was 9.3± 0.5 GtC yr⁻¹, ELUC 1.0± 0.5 GtC yr⁻¹,GATM 4.5± 0.1 GtC yr⁻¹, SOCEAN 2.6± 0.5 GtC yr⁻¹, and SLAND 3.1± 0.9 GtC yr⁻¹. For year 2015 alone, the growth in EFF was approximately zero and emissions remained at 9.9± 0.5 GtC yr⁻¹, showing a slowdown in growth of these emissions compared to the average growth of 1.8 % yr⁻¹ that took place during 2006–2015. Also, for 2015, ELUC was 1.3± 0.5 GtC yr⁻¹,GATM was 6.3± 0.2 GtC yr⁻¹, SOCEAN was 3.0± 0.5 GtC yr⁻¹, and SLAND was 1.9± 0.9 GtC yr⁻¹ GATM was higher in 2015 compared to the past decade (2006–2015), reflecting a smaller SLAND for that year. The global atmospheric CO₂ concentration reached 399.4± 0.1 ppm averaged over 2015. For 2016, preliminary data indicate the continuation of low growth in EFF with +0.2 % (range of −1.0 to + 1.8 %) based on national emissions projections for China and USA, and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. In spite of the low growth of EFF in 2016, the growth rate in atmospheric CO₂ concentration is expected to be relatively high because of the persistence of the smaller residual terrestrial sink (SLAND) in response to El Niño conditions of 2015–2016. From this projection of EFF and assumed constant ELUC for 2016, cumulative emissions of CO₂ will reach 565± 55 GtC (2075± 205 GtCO₂) for 1870–2016, about 75 % from EFF and 25 % from ELUC. This living data update documents changes in the methods and data sets used in this new carbon budget compared with previous publications of this data set (Le Quéré et al., 2015b, a, 2014, 2013).

Accurate assessment of anthropogenic carbon dioxide (CO₂) emissions and their redistributionamong the atmosphere, ocean, and terrestrial biosphere – the “global carbon budget” – is important to betterunderstand the global carbon cycle, support the development of climate policies, and project future climatechange. Here we describe data sets and methodology to quantify the five major components of the global carbon budget and their uncertainties. Fossil CO₂ emissions (EFF) are based on energy statistics and cement productiondata, while emissions from land use change (ELUC), mainly deforestation, are based on land use and land usechange 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) and terrestrial CO₂ sink (SLAND) are estimated with global process models constrained by observations. The resulting car-bon budget imbalance (BIM), the difference between the estimated total emissions and the estimated changesin 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 last decade available (2009–2018), EFF was 9.5±0.5 GtC yr⁻¹, ELUC 1.5±0.7 GtC yr⁻¹, GATM4.9±0.02 GtC yr⁻¹ (2.3±0.01 ppm yr⁻¹), SOCEAN 2.5±0.6 GtC yr⁻¹, and SLAND 3.2±0.6 GtC yr⁻¹, with a budget imbalance BIM of 0.4 GtC yr⁻¹ indicating overestimated emissions and/or underestimated sinks. For the year 2018 alone, the growth in EFFwas about 2.1 %and fossil emissions increased to 10.0±0.5 GtC yr⁻¹, reaching 10 GtC yr⁻¹ for the first time in history, ELUC was 1.5±0.7 GtC yr⁻¹, for total anthropogenic CO emissions of 11.5±0.9 GtC yr⁻¹ (42.5±3.3 Gt CO₂). Alsofor 2018,GATM was 5.1±0.2 GtC yr⁻¹(2.4±0.1 ppm yr⁻¹), SOCEAN was 2.6±0.6 GtC yr⁻¹, and SLAND was 3.5±0.7 GtC yr⁻¹, with a BIM of 0.3 GtC. The global atmospheric CO2 concentration reached 407.38±0.1 ppmaveraged over 2018. For 2019, preliminary data for the first 6–10 months indicate a reduced growth in EFF of +0.6 % (range of −0.2 % to 1.5 %) based on national emissions projections for China, the USA, the EU, andIndia and projections of gross domestic product corrected for recent changes in the carbon intensity of the economy for the rest of the world. Overall, the mean and trend in the five components of the global carbon budgetare consistently estimated over the period 1959–2018, but discrepancies of up to 1 GtC yr⁻¹ persist for the rep-resentation of semi-decadal variability in CO₂ fluxes. A detailed comparison among individual estimates and theintroduction of a broad range of observations shows (1) no consensus in the mean and trend in land use changeemissions over the last decade, (2) a persistent low agreement between the different methods on the magnitudeof the land CO₂ flux in the northern extra-tropics, and (3) an apparent underestimation of the CO₂ variability byocean models outside the tropics. This living data update documents changes in the methods and data sets usedin this new global carbon budget and the progress in understanding of the global carbon cycle compared withprevious publications of this data set (Le Quéré et al., 2018a, b, 2016, 2015a, b, 2014, 2013).