Journal
JOURNAL OF CLEANER PRODUCTION
Volume 202, Issue -, Pages 444-455Publisher
ELSEVIER SCI LTD
DOI: 10.1016/j.jclepro.2018.08.179
Keywords
Energy-related carbon emissions; Estimation method; Chinese cities; Fossil fuels
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Funding
- Humanity and Social Science Youth Foundation of the Ministry of Education of China [17YJCZH002]
- Tianjin Natural Science Foundation [15JCQNJC09200]
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China has become the world's largest energy consumer, accounting for approximately 30% of global CO2 emissions. City contributions make up 84% of China's commercial energy consumption. However, energy consumption data for most Chinese cities are not accessible. Many studies have focused on the estimation of carbon emissions at the provincial or national level; city-level carbon emissions are not well studied. In order to solve this problem, this research constructed a top-bottom method for city-scale energy-related carbon emissions estimation in China. Typically, cities are considered the constituent units of a province. Relying on provincial energy balance tables and utilizing the available city-level socioeconomic data as indicators, we scaled down provincial energy consumption to the city level. We compared our estimation results with city-level point-source data, and found that for the 41 Chinese cities to which we applied this method, the difference was within 10%, while for 25 of these cities, the difference was within 5%. Thus, we believe our method is reasonably accurate. We also subdivided the city carbon emissions into three major energy categories (coal-related, oil-related, and gas-related) and found that the difference could be attributed mainly to coal-related energy emissions. The results of the uncertainty analysis indicated that the uncertainty of the coal emission factor was the largest, thus demonstrating that it is critical not only to choose appropriate indicators to characterize coal-based industrial carbon emissions, but also to identify accurate emission factors for coal-related fossil fuels. Both analyses demonstrated China's coal-dominant energy structure. We believe our method is practical and can provide detailed data support for the establishment of city-level carbon emission inventories, furthermore, it will also be helpful for Chinese cities to negotiate carbon reduction responsibilities and allocating carbon reduction tasks. (C) 2018 Elsevier Ltd. All rights reserved.
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