Construction and application of the carbon peak model for Chinese industries --based on Markal-Macro model

Industrial carbon peaking is a critical pathway toward achieving sustainable development. Given that industrial sectors account for nearly 70% of China’s total carbon emissions, conducting simulation studies on industrial carbon peaking holds significant practical importance. Unlike regional carbon peaking models, industrial carbon peaking models face distinct challenges due to the substantial influence of market dynamics. In this study, we focus on three key objectives: (1) reducing carbon emissions from energy consumption, (2) minimizing process-related carbon emissions, and (3) optimizing industrial profitability. We propose an innovative industrial carbon peaking simulation model, developed by adapting the Markal-Macro framework. Using the iron and steel industry as a case study, we establish five distinct scenarios to simulate carbon peaking trajectories. Our analysis incorporates data on energy consumption, employment, product output, and other key indicators. To enhance computational efficiency, we integrate genetic algorithms with the penalty function method. The results indicate that under the baseline scenario, China’s iron and steel industry could achieve carbon peaking by 2027, with emissions reaching approximately 2.04 billion tonnes of CO 2 . Based on these findings, we provide targeted policy recommendations for carbon peaking in the iron and steel sector. These recommendations address energy structure optimization, clean energy adoption, and technological advancements, aligning with China’s 14th Five-Year Plan objectives and long-term sustainable development goals.