Bridging urban industrial carbon-peaking targets and feasible transition pathways through an extended Kaya–system dynamics framework

The urban industrial sector is central to China's carbon peaking targets, yet feasible and affordable city-level peaking pathways remain unresolved. Existing carbon-emission models show limited depth and transferability because core decision-making factors, including industrial structure, energy mix, and technology adoption rate, are difficult to quantify and are often treated as exogenous. This study develops an Extended Kaya and system dynamics framework to model interactions among economic activity, industrial structure, energy mix, technology adoption rate, and CO 2 emission coefficient for the urban industrial sector. The model couples indicator transparency with endogenous feedbacks and is calibrated using historical series on carbon emissions, energy consumption, energy intensity, and industrial structure. Three policy portfolios are evaluated. Industrial structure regulation improves emission intensity but leaves sizable residual emissions. Energy mix regulation achieves larger reductions through fuel switching and electrification as the grid CO 2 emission intensity declines. The integrated portfolio aligns structural optimization, energy transition, and technological upgrading and delivers the most feasible outcome. Under this pathway, peak emissions reach 91.54 MtCO 2 in 2030, and CO 2 emission intensity reaches 0.58 tCO 2 per 10 4 RMB, both improvements relative to the current-policy case. The findings provide actionable guidance for industrial planning, fuel and power procurement, and retrofit programs, and they supply a quantitative basis for monitoring, reporting, and verification aligned with urban practice. Because the framework requires only limited parameter recalibration, it can be adapted to other cities to inform tailored strategies that advance carbon peaking and, over a longer horizon, carbon neutrality.