Abstract

Under the vision of carbon neutrality, China's iron and steel industry (CISI) urgently needs to achieve low-carbon development. To formulate effective and targeted emission reduction policies for CISI, the driving forces of carbon dioxide (CO 2 ) emissions and future emission reduction pathways in CISI are explored in this paper. The Logarithmic Mean Divisia Index (LMDI) method and the Mean Impact Value (MIV) technique are adopted to analyze the driving factors of CO 2 emissions in CISI at historical and prospective dimensions, respectively. Furthermore, the extreme learning machine (ELM) model optimized by the bat algorithm (BA) is established to project the carbon emission reduction pathways of CISI during 2020–2050 under the business-as-usual (BAU) scenario, the low-speed, medium-speed, and high-speed development scenarios considering the constraint of the carbon neutrality target. The results reveal that production capacity and energy efficiency are essential drivers of CO 2 emissions in CISI. Consequently, aimed at achieving carbon neutrality, CISI should focus on eliminating backward capacity and simultaneously accelerating the deployment of advanced technologies. Additionally, it is difficult to accomplish the carbon neutrality goal by 2060 under the BAU scenario. Conversely, under the optimal emission reduction pathway determined by the high-speed development scenario, CISI will reach its peak in 2022 with a peak value of 2143.42 million tons of CO 2 (MtCO 2 ). The average annual emission abatement rate during 2022–2050 is maintained at approximately 4.47% and the cumulative reduction rate in 2050 will exceed 70% compared to the base year 2019. CISI is required to develop more stringent emission reduction measures to achieve significant emission abatement. The crude steel production capacity should be reduced to 533 Mt in 2050 and the capacity utilization rate should be maintained beyond 80%. The energy consumption per ton of steel must be decreased to 264 Kg of coal equivalent (Kgce) in 2050.

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