Year: 2025
Type: data-paper
Abstract: As the world’s largest CO2 emitter, China needs accurate city-level CO2 emission accounts to formulate effective low-carbon policies. However, previous studies mainly accounted for emissions from fossil fuel combustion and overlooked process-related CO2 emissions from industrial production (e.g., mineral, chemical, metal products), which account for approximately 13% of China’s total emissions. In this study, we built the first time-series dataset of process-related CO2 emissions for 289 Chinese cities from 2000 to 2021. The dataset covers 11 industrial products and adheres to the methodology recommended by the Intergovernmental Panel on Climate Change (IPCC). We applied China-specific emission factors and compiled industrial output data from city statistical yearbooks and bulletins. Missing output data were imputed using missForest models. The estimated uncertainty of the process-related emissions in our dataset ranges from 3.87% to 3.91%. Our dataset provides a robust foundation for analyzing emission patterns at the city level and for designing targeted low-carbon policies.
Source: Scientific Data
Authors: Sijia Cai, Jinghang Xu, Yuru Guan, Miaomaio Liu, Chang Tan, Jun Bi, Yuli Shan
Language: English
Subfield: Environmental Engineering
Field: Environmental Science
Domain: Physical Sciences
Open Access status: gold
Estimated APC paid: $2,490
Funders: UK Research and Innovation, European Commission, National Natural Science Foundation of China, Ministry of Science and Technology of the People's Republic of China, Government of Jiangsu Province, Natural Science Foundation of Jiangsu Province, Horizon 2020 Framework Programme, HORIZON EUROPE Framework Programme, National Key Research and Development Program of China
OpenAlex ID: W4413257403