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Peaking Industrial CO 2 Emission in a Typical Heavy Industrial Region: From Multi-Industry and Multi-Energy Type Perspectives

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  • Haiyan Duan

    (Key Lab of Groundwater Resources and Environment, Ministry of Education, Jilin University, Changchun 130021, China
    College of New Energy and Environment, Jilin University, Changchun 130021, China)

  • Xize Dong

    (College of New Energy and Environment, Jilin University, Changchun 130021, China)

  • Pinlei Xie

    (People’s Government of Daqiao Town, Jiangdu District, Yangzhou 225211, China)

  • Siyan Chen

    (College of New Energy and Environment, Jilin University, Changchun 130021, China)

  • Baoyang Qin

    (College of New Energy and Environment, Jilin University, Changchun 130021, China)

  • Zijia Dong

    (College of New Energy and Environment, Jilin University, Changchun 130021, China)

  • Wei Yang

    (Key Lab of Groundwater Resources and Environment, Ministry of Education, Jilin University, Changchun 130021, China
    College of New Energy and Environment, Jilin University, Changchun 130021, China)

Abstract

Peaking industrial carbon dioxide (CO 2 ) emissions is critical for China to achieve its CO 2 peaking target by 2030 since industrial sector is a major contributor to CO 2 emissions. Heavy industrial regions consume plenty of fossil fuels and emit a large amount of CO 2 emissions, which also have huge CO 2 emissions reduction potential. It is significant to accurately forecast CO 2 emission peak of industrial sector in heavy industrial regions from multi-industry and multi-energy type perspectives. This study incorporates 41 industries and 16 types of energy into the Long-Range Energy Alternatives Planning System (LEAP) model to predict the CO 2 emission peak of the industrial sector in Jilin Province, a typical heavy industrial region. Four scenarios including business-as-usual scenario (BAU), energy-saving scenario (ESS), energy-saving and low-carbon scenario (ELS) and low-carbon scenario (LCS) are set for simulating the future CO 2 emission trends during 2018–2050. The method of variable control is utilized to explore the degree and the direction of influencing factors of CO 2 emission in four scenarios. The results indicate that the peak value of CO 2 emission in the four scenarios are 165.65 million tons (Mt), 156.80 Mt, 128.16 Mt, and 114.17 Mt in 2040, 2040, 2030 and 2020, respectively. Taking ELS as an example, the larger energy-intensive industries such as ferrous metal smelting will peak CO 2 emission in 2025, and low energy industries such as automobile manufacturing will continue to develop rapidly. The influence degree of the four factors is as follows: industrial added value (1.27) > industrial structure (1.19) > energy intensity of each industry (1.12) > energy consumption types of each industry (1.02). Among the four factors, industrial value added is a positive factor for CO 2 emission, and the rest are inhibitory ones. The study provides a reference for developing industrial CO 2 emission reduction policies from multi-industry and multi-energy type perspectives in heavy industrial regions of developing countries.

Suggested Citation

  • Haiyan Duan & Xize Dong & Pinlei Xie & Siyan Chen & Baoyang Qin & Zijia Dong & Wei Yang, 2022. "Peaking Industrial CO 2 Emission in a Typical Heavy Industrial Region: From Multi-Industry and Multi-Energy Type Perspectives," IJERPH, MDPI, vol. 19(13), pages 1-30, June.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:13:p:7829-:d:848152
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    2. Jian Zhang & Jingyang Liu & Li Dong & Qi Qiao, 2022. "CO 2 Emissions Inventory and Its Uncertainty Analysis of China’s Industrial Parks: A Case Study of the Maanshan Economic and Technological Development Area," IJERPH, MDPI, vol. 19(18), pages 1-14, September.
    3. Cao, Yue & Guo, Lingling & Qu, Ying & Wang, Liang, 2024. "Possibility and pathways of China's nonferrous metals industry to achieve its carbon peak target before 2030: A new integrated dynamic forecasting model," Energy, Elsevier, vol. 306(C).
    4. Jiang Zhu & Xiang Li & Huiming Huang & Xiangdong Yin & Jiangchun Yao & Tao Liu & Jiexuan Wu & Zhangcheng Chen, 2023. "Spatiotemporal Evolution of Carbon Emissions According to Major Function-Oriented Zones: A Case Study of Guangdong Province, China," IJERPH, MDPI, vol. 20(3), pages 1-20, January.

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