Top-down environmental policies aim to mitigate environmental risks but inevitably lead to economic losses due to the market entry or exit of enterprises. This study developed a universal dynamic agent-based supply chain model to achieve tradeoffs between environmental risk reduction and economic sustainability. The model was used to conduct high-resolution daily simulations of the dynamic shifts in enterprise operations and their cascading effects on supply chain networks. It includes production, consumption, and transportation agents, attributing economic features to supply chain components and capturing their interactions. It also accounts for adaptive responses to daily external shocks and replicates realistic firm behaviors. By coupling high spatial-temporal resolution firm-level data from 18 916 chemical enterprises, this study investigates the economic and environmental impacts of an environmental policy resulting in the closure of 1 800 chemical enterprises over three years. The results revealed a significant economic loss of 25.8 billion USD, ranging from 23.8 USD to 31.8 billion USD. Notably, over 80% of this loss was attributed to supply chain propagation. Counterfactual analyses indicated that implementing a staggered shutdown strategy prevented 18.8% of supply chain losses, highlighting the importance of a gradual policy implementation to prevent abrupt supply chain disruptions. Furthermore, the study highlights the effectiveness of a multi-objective policy design in reducing economic losses (about 29%) and environmental risks (about 40%), substantially enhancing the efficiency of the environmental policy. The high-resolution simulations provide valuable insights for policy designers to formulate strategies with staggered implementation and multiple objectives to mitigate supply chain losses and environmental risks and ensure a sustainable future.

中文翻译：

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提高环保企业关停效率：基于Agent的高时空分辨率数据建模方法

自上而下的环境政策旨在缓解环境风险，但不可避免地会因企业的进入或退出而造成经济损失。本研究开发了一种通用的基于动态代理的供应链模型，以实现降低环境风险和经济可持续性之间的权衡。该模型用于对企业运营的动态变化及其对供应链网络的级联影响进行高分辨率的日常模拟。它包括生产、消费和运输代理，将经济特征归因于供应链组成部分并捕获它们的相互作用。它还考虑了对日常外部冲击的适应性反应，并复制了现实的公司行为。本研究通过耦合来自 18 916 家化工企业的高时空分辨率企业级数据，调查了三年内导致 1 800 家化工企业关闭的环境政策对经济和环境的影响。结果显示，重大经济损失达258亿美元，从23.8美元到318亿美元不等。值得注意的是，超过 80% 的损失归因于供应链传播。反事实分析表明，实施分阶段关闭策略可以避免 18.8% 的供应链损失，凸显了逐步实施政策以防止供应链突然中断的重要性。此外，研究还强调了多目标政策设计在减少经济损失（约29%）和环境风险（约40%）方面的有效性，大幅提高了环境政策的效率。高分辨率模拟为政策设计者制定分阶段实施和多重目标的战略提供了宝贵的见解，以减轻供应链损失和环境风险并确保可持续的未来。