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Abstract
We present a near-real-time global gridded daily CO2 emissions dataset (GRACED) throughout 2021. GRACED provides gridded CO2 emissions at a 0.1° × 0.1° spatial resolution and 1-day temporal resolution from cement production and fossil fuel combustion over seven sectors, including industry, power, residential consumption, ground transportation, international aviation, domestic aviation, and international shipping. GRACED is prepared from the near-real-time daily national CO2 emissions estimates (Carbon Monitor), multi-source spatial activity data emissions and satellite NO2 data for time variations of those spatial activity data. GRACED provides the most timely overview of emissions distribution changes, which enables more accurate and timely identification of when and where fossil CO2 emissions have rebounded and decreased. Uncertainty analysis of GRACED gives a grid-level two-sigma uncertainty of value of ±19.9% in 2021, indicating the reliability of GRACED was not sacrificed for the sake of higher spatiotemporal resolution that GRACED provides. Continuing to update GRACED in a timely manner could help policymakers monitor energy and climate policies’ effectiveness and make adjustments quickly.
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1 Tsinghua University, Department of Earth System Science, Beijing, China (GRID:grid.12527.33) (ISNI:0000 0001 0662 3178)
2 Tsinghua University, Department of Computer Science and Technology, Beijing, China (GRID:grid.12527.33) (ISNI:0000 0001 0662 3178)
3 Université Paris-Saclay, Laboratoire des Sciences du Climat et de l’Environnement, LSCE/IPSL, CEA-CNRS-UVSQ, Gif-sur-Yvette, France (GRID:grid.460789.4) (ISNI:0000 0004 4910 6535)
4 Ocean University of China, Key Laboratory of Marine Environment and Ecology, and Frontiers Science Center for Deep Ocean Multispheres and Earth System, Ministry of Education, Qingdao, China (GRID:grid.4422.0) (ISNI:0000 0001 2152 3263)
5 University of North Carolina at Chapel Hill, Environmental Sciences and Engineering, Chapel Hill, USA (GRID:grid.10698.36) (ISNI:0000000122483208)
6 Northeast Forestry University, Key Laboratory of Sustainable Forest Ecosystem Management, Harbin, China (GRID:grid.412246.7) (ISNI:0000 0004 1789 9091)
7 Tianjin University, School of Environmental Science and Engineering, Tianjin, China (GRID:grid.33763.32) (ISNI:0000 0004 1761 2484)
8 Chinese Academy of Sciences, Key Laboratory of Land Surface Pattern and Simulation, Institute of Geographical Sciences and Natural Resources Research, Beijing, China (GRID:grid.9227.e) (ISNI:0000000119573309)
9 University of California, Department of Earth System Science, Irvine, USA (GRID:grid.266093.8) (ISNI:0000 0001 0668 7243)
10 European Commission, Joint Research Centre (JRC), Ispra, Italy (GRID:grid.434554.7) (ISNI:0000 0004 1758 4137)
11 Product and Solution & Website Business Unit, Alibaba Cloud, Hangzhou, China (GRID:grid.12527.33)
12 Tsinghua University, Department of Earth System Science, Beijing, China (GRID:grid.12527.33) (ISNI:0000 0001 0662 3178); Product and Solution & Website Business Unit, Alibaba Cloud, Hangzhou, China (GRID:grid.12527.33)