In China, an overwhelming number of cities are resource-based. Resource-based cities have substantial energy consumption, emissions, and pollution, and they expand quickly and economically, significantly enhancing their carbon emissions. Nevertheless, they have considerable potential for emissions reduction and room for development. Hence, searching for low-carbon routes is essential. Assuming “dual-carbon” as a backdrop, this study takes Shanxi Province, the largest coal resource province in China, for case in point, and establishes a carbon emission system dynamics model, constructs five carbon emission systems, namely, economy, energy, population, land, and environment, and sets up four scenarios. Finally, based on the results of the scenario simulation, we explore the optimal path and policy regulations for resource cities to reach carbon peaks. The study’s findings demonstrate the following: (1) All factors are positively correlated with each other, and their influence in the four scenarios is ranked as follows: gross domestic product (GDP)>energy consumption>industrial structure>total population>land-use structure. (2) GDP is a key factor influencing total carbon emissions, and regulating only a single factor cannot achieve the carbon emission target. Thus, all factors need to be considered and synergistically regulated to achieve optimal carbon benefits. (3) Carbon emissions from the Baseline Development Scenario (BDS) and the Fast Development Scenario (FDS), reach 599.32 million tons and 614.48 million tons and continue to rise, especially in the FDS scenario, which reaches the highest value. This indicates that Shanxi Province needs to take effective carbon emission reduction measures to realize low-carbon development, but it is not desirable to focus only on the economic growth rate and industrial restructuring while ignoring environmental protection. (4) The Low-Carbon Optimization model (LOS) and Resource Saving Scenario (RSS), carbon emissions can reach 550.99 million tons and 539.83 million tons。

Carbon Emission; Scenario Simulation;Policy Regulation;System Dynamics Modeling