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Input–Output Analysis of China’s CO2 Emissions in 2017 Based on Data of 149 Sectors

by 1,2, 1,2, 3, 1,2, 1,2,* and 4
1
School of Economics and Management, Harbin Institute of Technology, Shenzhen, Shenzhen 518055, China
2
Shenzhen Engineering Laboratory of Big Data for Low-Carbon Cities, Harbin Institute of Technology, Shenzhen, Shenzhen 518055, China
3
School of Environment and Energy, Peking University Shenzhen Graduate School, Shenzhen 518055, China
4
College of Tourism and Service Management, Nankai University, Tianjin 300350, China
*
Author to whom correspondence should be addressed.
Academic Editor: Silvia Fiore
Sustainability 2021, 13(8), 4172; https://doi.org/10.3390/su13084172
Received: 26 February 2021 / Revised: 6 April 2021 / Accepted: 6 April 2021 / Published: 8 April 2021
(This article belongs to the Section Air, Climate Change and Sustainability)
High-precision CO2 emission data by sector are of great significance for formulating CO2 emission reduction plans. This study decomposes low-precision energy consumption data from China into 149 sectors according to the high-precision input–output (I–O) table for 2017. An economic I–O life cycle assessment model, incorporating sensitivity analysis, is constructed to analyze the distribution characteristics of CO2 emissions among sectors. Considering production, the electricity/heat production and supply sector contributed the most (51.20%) to the total direct CO2 emissions. The top 10 sectors with the highest direct CO2 emissions accounted for >80% of the total CO2 emissions. From a demand-based perspective, the top 13 sectors with the highest CO2 emissions emitted 5171.14 Mt CO2 (59.78% of the total), primarily as indirect emissions; in particular, the housing construction sector contributed 23.97% of the total. Based on these results, promoting decarbonization of the power industry and improving energy and raw material utilization efficiencies of other production sectors are the primary emission reduction measures. Compared with low-precision models, our model can improve the precision and accuracy of analysis results and more effectively guide the formulation of emission reduction policies. View Full-Text
Keywords: carbon emissions; input–output analysis; energy allocation; life cycle assessment carbon emissions; input–output analysis; energy allocation; life cycle assessment
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MDPI and ACS Style

He, F.; Yang, Y.; Liu, X.; Wang, D.; Ji, J.; Yi, Z. Input–Output Analysis of China’s CO2 Emissions in 2017 Based on Data of 149 Sectors. Sustainability 2021, 13, 4172. https://doi.org/10.3390/su13084172

AMA Style

He F, Yang Y, Liu X, Wang D, Ji J, Yi Z. Input–Output Analysis of China’s CO2 Emissions in 2017 Based on Data of 149 Sectors. Sustainability. 2021; 13(8):4172. https://doi.org/10.3390/su13084172

Chicago/Turabian Style

He, Fan, Yang Yang, Xin Liu, Dong Wang, Junping Ji, and Zhibin Yi. 2021. "Input–Output Analysis of China’s CO2 Emissions in 2017 Based on Data of 149 Sectors" Sustainability 13, no. 8: 4172. https://doi.org/10.3390/su13084172

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