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Carbon dioxide (CO2) is the most important anthropogenic greenhouse gas. Its atmospheric concentration has increased by almost 50 % since the beginning of the industrial era, causing climate change. Fossil fuel combustion is responsible for most of the atmospheric CO2 increase, which originates to a large extent from localized sources such as power stations. Independent estimates of the emissions from these sources are key to tracking the effectiveness of implemented climate policies to mitigate climate change. We developed an automatic procedure to quantify CO2 emissions from localized sources based on a cross-sectional mass-balance approach and applied it to infer CO2 emissions from the Bełchatów Power Station (Poland) using atmospheric observations from the Orbiting Carbon Observatory 3 (OCO-3) in its snapshot area map (SAM) mode. As a result of the challenge of identifying CO2 emission plumes from satellite data with adequate accuracy, we located and constrained the shape of emission plumes using TROPOspheric Monitoring Instrument (TROPOMI) NO2 column densities. We automatically analysed all available OCO-3 overpasses over the Bełchatów Power Station from July 2019 to November 2022 and found a total of nine that were suitable for the estimation of CO2 emissions using our method. The mean uncertainty in the obtained estimates was 5.8 Mt CO 2 yr -1 (22.0 %), mainly driven by the dispersion of the cross-sectional fluxes downwind of the source, e.g. due to turbulence. This dispersion uncertainty was characterized using a semivariogram, made possible by the OCO-3 imaging capability over a target region in SAM mode, which provides observations containing plume information up to several tens of kilometres downwind of the source. A bottom-up emission estimate was computed based on the hourly power-plant-generated power and emission factors to validate the satellite-based estimates. We found that the two independent estimates agree within their 1σ uncertainty in eight out of nine analysed overpasses and have a high Pearson's correlation coefficient of 0.92. Our results confirm the potential to monitor large localized CO2 emission sources from space-based observations and the usefulness of NO2 estimates for plume detection. They also illustrate the potential to improve CO2 monitoring capabilities with the planned Copernicus Anthropogenic CO2 Monitoring (CO2M) satellite constellation, which will provide simultaneously retrieved XCO2 and NO2 maps. [ABSTRACT FROM AUTHOR]

Anthropogenic mercury (Hg) emissions to the atmosphere are a long-lived hazard to human and environmental health. The UN Minamata Convention on Mercury is seeking to lower anthropogenic mercury emissions through a mix of policies from banning Hg uses and trade, to reducing unintentional Hg releases from different activities. In addition to independent Hg policy, greenhouse gas, particulate matter (PM) and SO2 reduction policies may also lower Hg emissions as a co-benefit. This study uses the Greenhouse Gas – Air Pollution Interactions and Synergies (GAINS) model to examine the effect of different clean air and climate policy on future global Hg emissions. The Baseline scenario assumes current energy use and Hg emissions, as well as current legislation for clean air, mercury and climate policy. In addition, we explore the impact of the Minamata Convention, co-benefits of climate policies and of stringent air pollution policies, as well as a maximum feasible reduction scenario for Hg (Hg-MFR). Hg emission projections until 2050 show noticeable reductions in combustion sectors for all scenarios, due to a decrease in global fossil fuels and traditional biomass use, leading to emission reductions of 33 % (Baseline) up to 90 % when combining stringent climate and Hg-MFR. Cement and non-ferrous metal emissions increase in all activity scenarios with current air pollution policy, but can be reduced by up to 72 % and 46 % respectively in 2050 with stringent Hg-specific measures. Other emissions (including waste) are a large source of uncertainty in this study, and projections range between a 22 % increase and 54 % decrease in 2050 depending on both climate and clean air policy. The largest absolute reduction potential for Hg abatement, but also the largest uncertainties of absolute emissions lie in the in small-scale and artisanal gold production, where Hg-specific abatement measures could eliminate annual Hg emissions in the range of 601–1371 t (95 % confidence interval). 90 % of the Hg emissions in GAINS are covered by the Minamata Convention. Overall, the findings emphasize the necessity of implementing targeted Hg control policies in addition to stringent climate, PM and SO2 policies to achieve significant reductions in Hg emissions. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO2) is the most important anthropogenic greenhouse gas. Its atmospheric concentration has increased by almost 50% since the beginning of the industrial era, causing climate change. Fossil fuel combustion is responsible for most of the atmospheric CO2 increase, which originates to a large extent from localized sources such as power stations. Independent estimates of the emissions from these sources are key to tracking the effectiveness of implemented climate policies to mitigate climate change. We developed a procedure to quantify CO2 emissions from localized sources based on a cross-sectional mass-balance approach and applied it to infer CO2 emissions from the Bełchatów Power Station, in Poland, using atmospheric observations from the Orbiting Carbon Observatory 3 (OCO-3) in its Snapshot Area Map (SAM) mode. As a result of the challenge of identifying CO2 emission plumes from satellite data with adequate accuracy, we located and constrained the shape of emission plumes using TROPOspheric Monitoring Instrument (TROPOMI) NO2 column densities. We analysed all available OCO-3 overpasses over the Bełchatów Power Station from July 2019 to November 2022 and found a total of 9 that were suitable for the estimation of CO2 emissions using our method. The mean uncertainty of the obtained estimates was 5.8 Mt CO2y-1 (22.0%), mainly driven by the dispersion of the cross-sectional fluxes downwind of the source, e.g. due to turbulence. This dispersion uncertainty was characterized using a semivariogram, possible thanks to the OCO-3 imaging capability over a target region in SAM mode, which provides observations containing plume information up to several tens of kilometres downwind of the source. A bottom-up emission estimate was computed based on the hourly power plant generated power and emission factors to validate the satellite-based estimates. We found that the two independent estimates agree within their 1σ uncertainty in 8 out of 9 analysed overpasses and have a high Pearson's correlation coefficient of 0.92. Our results confirm the potential for monitoring large localized CO2 emission sources from space-based observations and the usefulness of NO2 estimates for plume detection. They illustrate as well the potential to improve CO2 monitoring capabilities with the planned Copernicus Anthropogenic CO2 Monitoring (CO2M) satellite constellation, which will provide simultaneously retrieved XCO2 and NO2 maps. [ABSTRACT FROM AUTHOR]

Carbon dioxide (CO2) is the most important anthropogenic greenhouse gas. Its atmospheric concentration has increased by almost 50 % since the beginning of the industrial era, causing climate change. Fossil fuel combustion is responsible for most of the atmospheric CO2 increase, which originates to a large extent from localized sources such as power stations. Independent estimates of the emissions from these sources are key to tracking the effectiveness of implemented climate policies to mitigate climate change. We developed a procedure to quantify CO2 emissions from localized sources based on a cross-sectional mass-balance approach and applied it to infer CO2 emissions from the Bełchatów Power Station, in Poland, using atmospheric observations from the Orbiting Carbon Observatory 3 (OCO-3) in its Snapshot Area Map (SAM) mode. As a result of the challenge of identifying CO2 emission plumes from satellite data with adequate accuracy, we located and constrained the shape of emission plumes using TROPOspheric Monitoring Instrument (TROPOMI) NO2 column densities. We analysed all available OCO-3 overpasses over the Bełchatów Power Station from July 2019 to November 2022 and found a total of 9 that were suitable for the estimation of CO2 emissions using our method. The mean uncertainty of the obtained estimates was 5.8 Mt CO2 y−1 (22.0 %), mainly driven by the dispersion of the cross-sectional fluxes downwind of the source, e.g. due to turbulence. This dispersion uncertainty was characterized using a semivariogram, possible thanks to the OCO-3 imaging capability over a target region in SAM mode, which provides observations containing plume information up to several tens of kilometres downwind of the source. A bottom-up emission estimate was computed based on the hourly power plant generated power and emission factors to validate the satellite-based estimates. We found that the two independent estimates agree within their 1 sigma uncertainty in 8 out of 9 analysed overpasses and have a high Pearson's correlation coefficient of 0.92. Our results confirm the potential for monitoring large localized CO2 emission sources from space-based observations and the usefulness of NO2 estimates for plume detection. They illustrate as well the potential to improve CO2 monitoring capabilities with the planned Copernicus Anthropogenic CO2 Monitoring (CO2M) satellite constellation, which will provide simultaneously retrieved XCO2 and NO2 maps. [ABSTRACT FROM AUTHOR]

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). [ABSTRACT FROM AUTHOR]