Optimizing the Chinese Electricity Mix for CO2 Emission Reduction: An Input–Output Linear Programming Model with Endogenous Capital

The current paper combines multi-regional input-output model and linear programming model to identify industrial shift strategies for CO2 emissions reduction in China. As a supplement to the previous studies, the optimal sequence of demand regulation for various products is explored. The results show that demand side regulation would pose negative effect on both GDP and CO2 emissions. However, certain strategies can be adopted to decrease CO2 emissions at the minimum decrease in GDP. According to the optimal sequence analysis, a group of key final products, such as the metallurgy products, the nonmetal products, the metal products, and the chemical products should be firstly regulated. Most of these key products concentrate in the eastern and coastal regions in China. Our model can be used to aid policy makers in design of effective industrial restructuring policy to achieve the national emissions targets.

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Electrifying light-duty passenger transport for CO2 emissions reduction: A stochastic-robust input–output linear programming model

Energy Economics ◽

10.1016/j.eneco.2021.105623 ◽

2021 ◽

pp. 105623

Author(s):

Jidong Kang ◽

Tsan Sheng Ng ◽

Bin Su ◽

Alexandre Milovanoff

Keyword(s):

Linear Programming ◽

Co2 Emissions ◽

Programming Model ◽

Linear Programming Model ◽

Emissions Reduction ◽

Passenger Transport ◽

Input Output ◽

Light Duty

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

Sustainability ◽

10.3390/su13084172 ◽

2021 ◽

Vol 13 (8) ◽

pp. 4172

Author(s):

Fan He ◽

Yang Yang ◽

Xin Liu ◽

Dong Wang ◽

Junping Ji ◽

...

Keyword(s):

Co2 Emissions ◽

High Precision ◽

Emission Reduction ◽

Co2 Emission ◽

Assessment Model ◽

Raw Material ◽

Input Output ◽

Output Analysis ◽

Co2 Emission Reduction ◽

Emission Data

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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