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

Authors: Fan He; Yang Yang; Xin Liu; Dong Wang; Junping Ji; Zhibin Yi;

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

Abstract

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.

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Keywords

Environmental effects of industries and plants, input–output analysis, TJ807-830, TD194-195, Renewable energy sources, Environmental sciences, energy allocation, life cycle assessment, GE1-350, carbon emissions

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citations
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
5
Top 10%
Average
Top 10%
gold