Simulation study reveals tailored subsidies and rapid technology diffusion boost waste recycling to 34% by 2035, highlighting the need to coordinate policy design with technological innovation.
Municipal solid waste treatment frequently suffers from structural imbalances because waste disposal institutions prioritize profit over environmental suitability. Policies are often developed in isolation, and technological diffusion is frequently overlooked in dynamic modeling. This study incorporates an aging chain and an SIR-based transition mechanism to simulate the diffusion of advanced incineration and recycling technologies. It develops a system dynamics model that endogenously couples this technological diffusion with multi-policy interactions. The model is calibrated and validated with historical data from Beijing (2013–2024) and forecasts trends through 2035. Results indicate that under current policies, the balance of treatment methods will become severely skewed by 2035, with incineration dominating (64%), recycling stagnating (18%), and landfill rates remaining high (13%). To address this, we used the model to analyze the impact of three existing policies. It shows that precisely calibrated waste disposal subsidies can optimize the treatment structure; maintaining classification accuracy within a suitable range maximizes recycling benefits, while overly high accuracy results in diminishing returns; and a gradual reduction in feed-in tariffs effectively controls incineration. The study also performs a sensitivity analysis of key factors influencing technological diffusion and confirms when the selected policy package is combined with accelerated diffusion, recycling reaches 34% and incineration falls to 48% by 2035, representing a significant positive synergy. These findings highlight the importance of integrating policy design with technological innovation to achieve sustainable municipal solid waste management. The proposed model offers a transferable tool for evidence-based decision making in other urban settings.
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Sun et al. (2026) studied this question.
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