Research on Carbon Emission Reduction Cost Calculation and Path Optimization Based on Life-Cycle Assessment: A Case Study of China’s Steel Industry

In order to balance carbon emissions and cost reduction in China’s steel firms, this study proposes a multi-objective optimization model for carbon emission reduction based on life-cycle assessment. The baseline scenario technique was used to forecast carbon emissions at every stage of the life cycle by 2025, and the costs of reduction for four major initiatives—clean electricity procurement, recycling of scrap steel, fossil fuel consumption reduction, and clean transportation share increase—were systematically accounted. Kernel PCA and NSGA-II algorithms were used to create a multi-objective optimization model with the goal of maximizing emission reductions and reducing reduction costs. The greatest potential and economic gain, according to the results, come from using more scrap steel and using fewer fossil fuels. At 823 million CNY, the cost–benefit balanced solution reduces CO 2 by 3.0358 Mt. This approach achieved virtually maximum emissions reductions at only 10.9% of the cost of the maximum reduction scenario. This study makes two key contributions. First, it provides a systematic life-cycle cost accounting framework for major CO 2 reduction measures in the steel industry. Second, it develops a Kernel PCA-NSGA-II multi-objective optimization model that explicitly resolves the trade-off between abatement cost and emission reduction volume, offering decision support for steel enterprises under different policy and economic scenarios.