Carbon peak path of the Chinese iron and steel industry based on the LMDI?STIRPAT model

PAN Chong-chao; WANG Bo-wen; HOU Xiao-wang; GU Yue-qing; XING Yi; LIU Yu-song; WEN Wei; FANG Juan

doi:10.13374/j.issn2095-9389.2022.04.25.002

Volume 45 Issue 6

May 2023

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Article Navigation > Chinese Journal of Engineering > 2023 > 45(6): 1034-1044

PAN Chong-chao, WANG Bo-wen, HOU Xiao-wang, GU Yue-qing, XING Yi, LIU Yu-song, WEN Wei, FANG Juan. Carbon peak path of the Chinese iron and steel industry based on the LMDI?STIRPAT model[J]. Chinese Journal of Engineering, 2023, 45(6): 1034-1044. doi: 10.13374/j.issn2095-9389.2022.04.25.002

Citation:

PAN Chong-chao, WANG Bo-wen, HOU Xiao-wang, GU Yue-qing, XING Yi, LIU Yu-song, WEN Wei, FANG Juan. Carbon peak path of the Chinese iron and steel industry based on the LMDI?STIRPAT model[J]. Chinese Journal of Engineering, 2023, 45(6): 1034-1044. doi: 10.13374/j.issn2095-9389.2022.04.25.002

Citation:

PAN Chong-chao, WANG Bo-wen, HOU Xiao-wang, GU Yue-qing, XING Yi, LIU Yu-song, WEN Wei, FANG Juan. Carbon peak path of the Chinese iron and steel industry based on the LMDI?STIRPAT model[J]. Chinese Journal of Engineering, 2023, 45(6): 1034-1044. doi: 10.13374/j.issn2095-9389.2022.04.25.002

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Carbon peak path of the Chinese iron and steel industry based on the LMDI?STIRPAT model

doi: 10.13374/j.issn2095-9389.2022.04.25.002

PAN Chong-chao^{1, 2
,
,},
WANG Bo-wen^{1, 2
,},
HOU Xiao-wang^{1, 2},
GU Yue-qing^{1, 2},
XING Yi¹,
LIU Yu-song¹,
WEN Wei¹,
FANG Juan¹

1.
School of Energy and Environmental Engineering, University of Science and Technology Beijing, Beijing 100083, China
2.
Smart Energy Research Center, University of Science and Technology Beijing, Beijing 100083, China

More Information

Corresponding author: E-mail: panchch@ustb.edu.cn
Received Date: 2022-04-25
Available Online: 2022-07-27
Publish Date: 2023-05-31

Abstract

Abstract

Low-carbon development of the iron and steel industry is critical to China’s goal of carbon neutrality and emission peaking. The carbon emissions of China’s iron and steel industry are calculated using the emission factor method in this paper, and the influencing factors of emission growth are investigated using the two-stage logarithmic mean divisia index (LMDI). The results show that carbon emissions from the steel industry continue to rise, reaching a stage peak of 1.848 billion tons in 2014 before declining. Carbon emissions fall by 52.4% during this period, energy intensity decreases by 52.9% per ton of steel; the decline in energy intensity will be much smaller in the future. The scale effect is the most important factor in the growth of carbon emission, accounting for 178.17% of the total, whereas energy intensity is the most important restraining factor, accounting for 76.02% of the total. However, the impact of energy structure and emission factors remains unclear. This is due to the small change in the energy mix and emission factors. The scale effect, which is a major contributor to rising carbon emissions, is broken down once more. Capital stock and total factor productivity drive carbon emission growth, whereas labor factors reflect the transition of the industrial population to low-carbon industries. The STIRPAT model predicts future carbon emissions from the iron and steel industry. The results of the scenario analysis show that carbon emissions will peak in 2025 under the baseline scenario, with carbon emissions totaling 1.904 billion tons. The peak time for carbon emissions in the low carbon scenario is 2021, and the peak is lower, with carbon emissions of 1.867 billion tons. Carbon emissions have already peaked in 2020 in the strong low-carbon scenario and will further decline to 1.439 billion tons in 2030, which is equivalent to 2010 carbon emissions. However, the rapid development scenario will not be able to reach a peak in carbon dioxide emissions before 2030. The forecast results show that both social and economic factors, as well as steel production factors, can have a significant impact on the overall industry’s carbon emission, implying that both the supply and demand sides must contribute to emission reductions. Controlling new capacity, transforming process structure, reducing fossil energy consumption, and promoting the use of hydrogen energy in the smelting process will be critical in the future for the industry’s low-carbon development.
- carbon emissions,
- LMDI method,
- C-D production function,
- scenario analysis,
- STIRPAT model

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References(40)

References

[1]	World Steel Association. World steel statistics 2021 [EB/OL]. Website Online (2021-01-15) [2022-04-25]. https://www.worldsteel.org/zh/steel-by-topic/statistics/about-our-statistics.html
[2]	Du Z L, Lin B Q. Analysis of carbon emissions reduction of China’s metallurgical industry. J Clean Prod, 2018, 176: 1177 doi: 10.1016/j.jclepro.2017.11.178
[3]	Ren L, Zhou S, Peng T D, et al. A review of CO₂ emissions reduction technologies and low-carbon development in the iron and steel industry focusing on China. Renew Sustain Energy Rev, 2021, 143: 110846 doi: 10.1016/j.rser.2021.110846
[4]	朱勤, 彭希哲, 陸志明, 等. 中國能源消費碳排放變化的因素分解及實證分析. 資源科學, 2009, 31(12):2072 Zhu Q, Peng X Z, Lu Z M, et al. Factors decomposition and empirical analysis of variations in energy carbon emission in China. Resour Sci, 2009, 31(12): 2072
[5]	Ling Y T, Xia S M, Cao M Q, et al. Carbon emissions in China’s thermal electricity and heating industry: An input-output structural decomposition analysis. J Clean Prod, 2021, 329: 129608 doi: 10.1016/j.jclepro.2021.129608
[6]	Xu W H, Xie Y L, Xia D H, et al. A multi-sectoral decomposition and decoupling analysis of carbon emissions in Guangdong province, China. J Environ Manag, 2021, 298: 113485 doi: 10.1016/j.jenvman.2021.113485
[7]	Ang B W. The LMDI approach to decomposition analysis: A practical guide. Energy Policy, 2005, 33(7): 867 doi: 10.1016/j.enpol.2003.10.010
[8]	路正南, 楊洋, 王健. 碳結構變動對產業系統碳生產率的影響—基于Laspeyres分解模型的經驗分析. 科技管理研究, 2015, 35(10):234 doi: 10.3969/j.issn.1000-7695.2015.10.045 Lu Z N, Yang Y, Wang J. Effect of carbon structrue change on carbon productivitysystem carbon productivity—An empirical research based on laspeyres decomposition index. Sci Technol Manag Res, 2015, 35(10): 234 doi: 10.3969/j.issn.1000-7695.2015.10.045
[9]	Wang Q, Zhao M M, Li R R. Decoupling sectoral economic output from carbon emissions on city level: A comparative study of Beijing and Shanghai, China. J Clean Prod, 2019, 209: 126 doi: 10.1016/j.jclepro.2018.10.188
[10]	Ang B W, Liu N. Negative-value problems of the logarithmic mean Divisia index decomposition approach. Energy Policy, 2007, 35(1): 739 doi: 10.1016/j.enpol.2005.12.004
[11]	聶銳, 張濤, 王迪. 基于IPAT模型的江蘇省能源消費與碳排放情景研究. 自然資源學報, 2010, 25(9):1557 doi: 10.11849/zrzyxb.2010.09.015 Nie R, Zhang T, Wang D. The scenario analysis on energy consumption and carbon emission based on environmental loads model. J Nat Resour, 2010, 25(9): 1557 doi: 10.11849/zrzyxb.2010.09.015
[12]	Xu J H, Yi B W, Fan Y. A bottom-up optimization model for long-term CO₂ emissions reduction pathway in the cement industry: A case study of China. Int J Greenh Gas Control, 2016, 44: 199 doi: 10.1016/j.ijggc.2015.11.028
[13]	丁甜甜, 李瑋. 經濟增長與減排視角下電力行業碳峰值預測. 科技管理研究, 2019, 39(18):246 doi: 10.3969/j.issn.1000-7695.2019.18.032 Ding T T, Li W. Peak forecast of carbon emissions in the power industry from the perspective of economic growth and emission reduction. Sci Technol Manag Res, 2019, 39(18): 246 doi: 10.3969/j.issn.1000-7695.2019.18.032
[14]	Fang K, Tang Y Q, Zhang Q F, et al. Will China peak its energy-related carbon emissions by 2030? Lessons from 30 Chinese provinces. Appl Energy, 2019, 255: 113852 doi: 10.1016/j.apenergy.2019.113852
[15]	胡長慶, 張春霞, 張旭孝, 等. 鋼鐵聯合企業煉焦過程物質與能量流分析. 鋼鐵研究學報, 2007, 19(6):16 doi: 10.3321/j.issn:1001-0963.2007.06.004 Hu C Q, Zhang C X, Zhang X X, et al. Material and energy flow analysis of coking process in integrated steel plants. J Iron Steel Res, 2007, 19(6): 16 doi: 10.3321/j.issn:1001-0963.2007.06.004
[16]	楊文彪. 我國煉焦產業現狀及綠色發展研究. 煤炭經濟研究, 2019, 39(8):4 Yang W B. Research on the status and green development of China’s coking industry. Coal Econ Res, 2019, 39(8): 4
[17]	李新創, 熊超, 姜曉東, 等. 以提升自發電為突破口加快推進鋼鐵綠色低碳發展. 中國冶金, 2021, 31(7):1 Li X C, Xiong C, Jiang X D, et al. Accelerate green and low-carbon development of iron and steel industry by taking improvement of self-power generation as a breakthrough. China Metall, 2021, 31(7): 1
[18]	蘭德年. 鋼鐵行業節能減排方向及措施. 冶金管理, 2008(7):25 Lan D N. Direction and measures of energy saving and emission reduction in steel industry. China Steel Focus, 2008(7): 25
[19]	Yang J, Cai W, Ma M D, et al. Driving forces of China’s CO₂ emissions from energy consumption based on Kaya-LMDI methods. Sci Total Environ, 2020, 711: 134569 doi: 10.1016/j.scitotenv.2019.134569
[20]	Jehli?ka P, Jacobsson K. The importance of recognizing difference: Rethinking Central and East European environmentalism. Political Geogr, 2021, 87: 102379 doi: 10.1016/j.polgeo.2021.102379
[21]	國家統計局. 年度統計公報 [EB/OL]. 網頁在線 (2020-10-11) [2022-04-25]. http://www.stats.gov.cn/tjsj/tjgb/ndtjgb/ National Bureau of Statistics. Annual statistical bulletin [EB/OL]. Website Online (2020-10-11) [2022-04-25]. http://www.stats.gov.cn/tjsj/tjgb/ndtjgb/
[22]	國家標準化管理委員會. GB/T2589—2020綜合能耗計算通則. 北京: 中國國家標準化委員會, 2020 Standardization Administration of China. GB/ T2589—2020 General Rules for Calculation of Comprehensive Energy Consumption. Beijing: Standardization Administration of China, 2020
[23]	International Energy Agency. Iron and steel technology roadmap [R/OL]. Report Online (2020-10-08) [2022-04-25]. https://iea.blob.core.windows.net/assets/eb0c8ec1-3665-4959-97d0-187ceca189a8/Iron_and_Steel_Technology_Roadmap.pdf
[24]	錢家澍. 當代世界鋼鐵工業發展和“中國方案”建議. 鋼鐵, 2021, 56(2):1 Qian J S. Review on world steel industry development in contemporary and “Chinese Approach” proposal. Iron&Steel, 2021, 56(2): 1
[25]	上官方欽, 劉正東, 殷瑞鈺. 鋼鐵行業“碳達峰”“碳中和”實施路徑研究. 中國冶金, 2021, 31(9):15 Shangguan F Q, Liu Z D, Yin R Y. Study on implementation path of “carbon peak” and “carbon neutrality” in steel industry in China. China Metall, 2021, 31(9): 15
[26]	中華人民共和國國家統計局. 中國電力統計年鑒2020. 北京: 中國統計出版社, 2020 National Bureau of Statistics of people’s Republic of China. China Electric Power Statistical Yearbook 2020. Beijing: China Statistics Press, 2020
[27]	Gao C C, Liu Y H, Jin J, et al. Driving forces in energy-related carbon dioxide emissions in east and south coastal China: commonality and variations. J Clean Prod, 2016, 135: 240 doi: 10.1016/j.jclepro.2016.05.131
[28]	葛好晴. 省級碳排放驅動力及脫鉤狀態研究[學位論文]. 杭州: 浙江大學, 2020 Ge H Q. Driving Forces and Decoupling States of Carbon Emissions at Provincial Level [Dissertation]. Hangzhou: Zhejiang University, 2020
[29]	陳詩一. 中國工業分行業統計數據估算: 1980—2008. 經濟學(季刊), 2011, 10(3):735 Chen S Y. Reconstruction of sub-industrial statistical data in China (1980—2008). China Econ Q, 2011, 10(3): 735
[30]	人民日報. 多年打擊未絕的“地條鋼”10月清零[EB/OL]. 中華人民共和國中央人民政府 (2017-12-13) [2022-04-25]. http://www.gov.cn/xinwen/2017-12/13/content_5246392.htm People’s Daily. The “ground strip steel” which has been attacked for many years was cleared in October [EB/OL]. The central people’s government of the People’s Republic of China (2017-12-13) [2022-04-25]. http://www.gov.cn/xinwen/2017-12/13/content_5246392.htm
[31]	石枕. 怎樣理解和計算“全要素生產率”的增長——評一個具體技術經濟問題的計量分析. 數量經濟技術經濟研究, 1988, 5(12):68 Shi Z. How to understand and calculate the growth of “total factor productivity”—a quantitative analysis of a specific technical and economic problem. Th J Quant &Tech Econ, 1988, 5(12): 68
[32]	鐘少芬, 郭曉娟, 劉煜平, 等. 基于STRPAT模型的碳排放情景分析. 科技管理研究, 2019, 39(17):253 doi: 10.3969/j.issn.1000-7695.2019.17.034 Zhong S F, Guo X J, Liu Y P, et al. Scenario analysis on carbon emission based on the STIRPAT model. Sci Technol Manag Res, 2019, 39(17): 253 doi: 10.3969/j.issn.1000-7695.2019.17.034
[33]	政府信息公開專欄. 國務院關于印發國家人口發展規劃(2016—2030年)的通知 [EB/OL]. 網頁在線 (2019-10-15) [2022-04-25]. http://www.gov.cn/zhengce/content/2017-01/25/content_5163309.html Government Information Disclosure Column. Circular of the state council on the issuance of the national population development plan (2016−2030) [EB/OL]. Website Online (2019-10-15) [2022-04-25]. http://www.gov.cn/zhengce/content/2017-01/25/content_5163309.html
[34]	聯合國經濟和社會事務部. 《世界城鎮化展望報告》[EB/OL]. 網頁在線 (2014-07-20) [2022-04-25]. https://www.un.org/development/desa/zh/news/population/world-urbanization-prospects-2014.html The United Nations economic and social affairs. World urbanization outlook report [EB/OL]. Website Online (2014-07-20) [2022-04-25]. https://www.un.org/development/desa/zh/news/population/world-urbanization-prospects-2014.html
[35]	Shen J L, Zhang Q, Xu L S, et al. Future CO₂ emission trends and radical decarbonization path of iron and steel industry in China. J Cleaner Prod, 2021, 326: 129354 doi: 10.1016/j.jclepro.2021.129354
[36]	International Energy Agency. 2020 world energy outlook, Paris [R/OL]. Report Online (2021-10-08) [2022-04-25]. https://iea.blob.core.windows.net/assets/a72d8abf-de08-4385-8711-b8a062d6124a/WEO2020.pdf
[37]	Zhao F, Yue Q, He J H, et al. Quantifying China’s iron in-use stock and its driving factors analysis. J Environ Manag, 2020, 274: 111220 doi: 10.1016/j.jenvman.2020.111220
[38]	邢奕, 崔永康, 田京雷, 等. 鋼鐵行業碳中和低碳技術路徑探索. 工程科學學報, https://doi.org/10.13374/j.issn2095-9389.2021.08.01.001 Xing Yi, Cui Y K, Tian J L, et al. Carbon neutral and low carbon technology path exploration in steel industry. Chin J Eng, https://doi.org/10.13374/j.issn2095-9389.2021.08.01.001
[39]	Zhang X, Jiao K, Zhang J, et al. A review on low carbon emissions projects of steel industry in the World. J Cleaner Prod, 2021, 206: 127259
[40]	Kim J, Sovacool B K, Bazilian M, et al. Decarbonizing the iron and steel industry: A systematic review of sociotechnical systems, technological innovations, and policy options. Energy Res Social Sci, 2022, 89: 102565 doi: 10.1016/j.erss.2022.102565