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Abstract
Accurate, long-term, full-coverage carbon dioxide (CO2) data in units of prefecture-level cities are necessary for evaluations of CO2 emission reductions in China, which has become one of the world’s largest carbon-emitting countries. This study develops a novel method to match satellite-based Defense Meteorological Satellite Program’s Operational Landscan System (DMSP/OLS) and Suomi National Polar-orbiting Partnership’s Visible Infrared Imaging Radiometer Suite (NPP/VIIRS) nighttime light data, and estimates the CO2 emissions of 334 prefecture-level cities in China from 1992 to 2017. Results indicated that the eastern and coastal regions had higher carbon emissions, but their carbon intensity decreased more rapidly than other regions. Compared to previous studies, we provide the most extensive and long-term CO2 dataset to date, and these data will be of great value for further socioeconomic research. Specifically, this dataset provides a foundational data source for China’s future CO2 research and emission reduction strategies. Additionally, the methodology can be applied to other regions around the world.
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1 Southwestern University of Finance and Economics, School of Public Administration, Chengdu, China (GRID:grid.443347.3) (ISNI:0000 0004 1761 2353)
2 Curtin University, Curtin University Sustainability Policy Institute, Perth, Australia (GRID:grid.1032.0) (ISNI:0000 0004 0375 4078)
3 Shanghai Lixin University of Accounting and Finance, School of Finance, Shanghai, China (GRID:grid.440634.1) (ISNI:0000 0004 0604 7926); University of Edinburgh, University of Edinburgh Business School, Edinburgh, UK (GRID:grid.4305.2) (ISNI:0000 0004 1936 7988)
4 Anhui University of Finance and Economics, School of Statistics and Applied Mathematics, Bengbu, China (GRID:grid.464226.0) (ISNI:0000 0004 1760 7263)
5 Southwestern University of Finance and Economics, Institute of Development Studies, Chengdu, China (GRID:grid.443347.3) (ISNI:0000 0004 1761 2353)
6 Southwestern University of Finance and Economics, West Center for Economic Research, Chengdu, China (GRID:grid.443347.3) (ISNI:0000 0004 1761 2353)