• Energy Research

Comprehensive and reliable information on anthropogenic sources of greenhouse gas emissions is required to track progress towards keeping warming well below 2��C as agreed upon in the Paris Agreement. Here we provide a dataset on anthropogenic GHG emissions 1970-2019 with a broad country and sector coverage. We build the dataset from recent releases from the ���Emissions Database for Global Atmospheric Research��� (EDGAR) for CO2 emissions from fossil fuel combustion and industry (FFI), CH4 emissions, N2O emissions, and fluorinated gases and use a well-established fast-track method to extend this dataset from 2018 to 2019. We complement this with information on net CO2 emissions from land use, land-use change and forestry (LULUCF) from three available bookkeeping models. The metadata in the previous version (#4) indicated that AR5 100 year global warming potentials (GWPs) were applied. This was incorrect. The metadata has been corrected, and both AR5 and AR6 100 year GWPs are now included as variables for convenient switching between metrics.

Comprehensive and reliable information on anthropogenic sources of greenhouse gas emissions is required to track progress towards keeping warming well below 2°C as agreed upon in the Paris Agreement. Here we provide a dataset on anthropogenic GHG emissions 1970-2019 with a broad country and sector coverage. We build the dataset from recent releases from the “Emissions Database for Global Atmospheric Research” (EDGAR) for CO2 emissions from fossil fuel combustion and industry (FFI), CH4 emissions, N2O emissions, and fluorinated gases and use a well-established fast-track method to extend this dataset from 2018 to 2019. We complement this with information on net CO2 emissions from land use, land-use change and forestry (LULUCF) from three available bookkeeping models.

AbstractSulfur hexafluoride (SF6) is a potent greenhouse gas. Here we use long-term atmospheric observations to determine SF6 emissions from China between 2011 and 2021, which are used to evaluate the Chinese national SF6 emission inventory and to better understand the global SF6 budget. SF6 emissions in China substantially increased from 2.6 (2.3-2.7, 68% uncertainty) Gg yr−1 in 2011 to 5.1 (4.8-5.4) Gg yr−1 in 2021. The increase from China is larger than the global total emissions rise, implying that it has offset falling emissions from other countries. Emissions in the less-populated western regions of China, which have potentially not been well quantified in previous measurement-based estimates, contribute significantly to the national SF6 emissions, likely due to substantial power generation and transmission in that area. The CO2-eq emissions of SF6 in China in 2021 were 125 (117-132) million tonnes (Mt), comparable to the national total CO2 emissions of several countries such as the Netherlands or Nigeria. The increasing SF6 emissions offset some of the CO2 reductions achieved through transitioning to renewable energy in the power industry, and might hinder progress towards achieving China’s goal of carbon neutrality by 2060 if no concrete control measures are implemented.

Significance Hydrofluorocarbons (HFCs) are among the atmosphere’s fastest growing, and most potent, greenhouse gases. Proposals have been made to phase down their use over the coming decades. Such initiatives may largely be informed by existing emissions inventories, which, we show, are the subject of significant uncertainty. In this work, we use atmospheric models and measurements to examine the accuracy of these inventories for five major HFCs. We show that, when aggregated together, reported emissions of these HFCs from developed countries are consistent with the atmospheric measurements, and almost half of global emissions now originate from nonreporting countries. However, the agreement between our results and the inventory breaks down for individual HFC emissions, suggesting inaccuracies in the reporting methods for individual compounds.

AbstractWe present the first spatially resolved wetland δ13C(CH4) source signature map based on data characterizing wetland ecosystems and demonstrate good agreement with wetland signatures derived from atmospheric observations. The source signature map resolves a latitudinal difference of ~10‰ between northern high‐latitude (mean −67.8‰) and tropical (mean −56.7‰) wetlands and shows significant regional variations on top of the latitudinal gradient. We assess the errors in inverse modeling studies aiming to separate CH4 sources and sinks by comparing atmospheric δ13C(CH4) derived using our spatially resolved map against the common assumption of globally uniform wetland δ13C(CH4) signature. We find a larger interhemispheric gradient, a larger high‐latitude seasonal cycle, and smaller trend over the period 2000–2012. The implication is that erroneous CH4 fluxes would be derived to compensate for the biases imposed by not utilizing spatially resolved signatures for the largest source of CH4 emissions. These biases are significant when compared to the size of observed signals.

The perfluorocarbons tetrafluoromethane (CF 4 , PFC-14) and hexafluoroethane (C 2 F 6 , PFC-116) are potent greenhouse gases with near-permanent atmospheric lifetimes relative to human timescales and global warming potentials thousands of times that of CO 2 . Using long-term atmospheric observations from a Chinese network and an inverse modeling approach (top–down method), we determined that CF 4 emissions in China increased from 4.7 (4.2-5.0, 68% uncertainty interval) Gg y −1 in 2012 to 8.3 (7.7-8.9) Gg y −1 in 2021, and C 2 F 6 emissions in China increased from 0.74 (0.66-0.80) Gg y −1 in 2011 to 1.32 (1.24-1.40) Gg y −1 in 2021, both increasing by approximately 78%. Combined emissions of CF 4 and C 2 F 6 in China reached 78 Mt CO 2 -eq in 2021. The absolute increase in emissions of each substance in China between 2011-2012 and 2017-2020 was similar to (for CF 4 ), or greater than (for C 2 F 6 ), the respective absolute increase in global emissions over the same period. Substantial CF 4 and C 2 F 6 emissions were identified in the less-populated western regions of China, probably due to emissions from the expanding aluminum industry in these resource-intensive regions. It is likely that the aluminum industry dominates CF 4 emissions in China, while the aluminum and semiconductor industries both contribute to C 2 F 6 emissions. Based on atmospheric observations, this study validates the emission magnitudes reported in national bottom–up inventories and provides insights into detailed spatial distributions and emission sources beyond what is reported in national bottom–up inventories.