潘崇超, 王博文, 侯孝旺, 古月清, 邢奕, 刘育松, 温维, 方娟. 基于LMDI−STIRPAT模型的中国钢铁行业碳达峰路径研究[J]. 工程科学学报, 2023, 45(6): 1034-1044. DOI: 10.13374/j.issn2095-9389.2022.04.25.002
引用本文: 潘崇超, 王博文, 侯孝旺, 古月清, 邢奕, 刘育松, 温维, 方娟. 基于LMDI−STIRPAT模型的中国钢铁行业碳达峰路径研究[J]. 工程科学学报, 2023, 45(6): 1034-1044. DOI: 10.13374/j.issn2095-9389.2022.04.25.002
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

基于LMDI−STIRPAT模型的中国钢铁行业碳达峰路径研究

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

  • 摘要: 基于排放因子法核算中国钢铁行业2000—2019年碳排放,运用两阶段对数平均迪式分解法(LMDI)和STIRPAT模型分析碳排放增长的影响因素和2030年碳排放。结果表明,碳排放持续增长,2014年达到阶段峰值18.48亿吨。规模因素是碳排放增加的主要原因,能源强度是最大的抑制因素。情景分析表明,基准情景下将在2025年达峰,碳排放量为19.04亿吨;低碳情景下碳达峰时间为2021年,碳排放量为18.67亿吨;强低碳情景已于2020年达到碳排放峰值,碳排放量为18.52亿吨;快速发展情景则无法在2030年前实现碳达峰。

     

    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.

     

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