To address the increasingly serious problem of “haze” pollution, this analysis uses the motor vehicle as an example and introduces the strategies of penalties, air pollution charging fees, and subsidies in a successive manner to tackle this issue. In addition, a collaborative strategy model for motor vehicle pollutant emission reduction combined with the system dynamics of the VEMSIM software is constructed. Using a causal loop analysis and simulation analysis, it was found that an air pollution charging fee policy would have a “double dividend” effect, which could achieve the dual goals of congestion alleviation and emission reduction. However, at the same time, it would induce the growth of illegal trips. Although a single penalty policy could effectively reduce the number of illegal trips of vehicles and make up for the deficiency of the air pollution charging fee policy, it would greatly reduce the public transport supply level. Subsidies would significantly improve the public transport supply level, but this policy also showed a certain “weak congestion alleviation” effect and “weak emission reduction” effect. A collaborative strategy that has multiple performances and complementary advantages would overcome the limitations of a single policy. These findings have provide a decision-making basis to improve haze control schemes.

为了解决日益严重的“霾”污染问题，本分析以机动车为例，并依次介绍了惩罚，空气污染收费和补贴的策略来解决这一问题。另外，结合VEMSIM软件的系统动力学，建立了机动车污染物减排协同策略模型。使用因果循环分析和模拟分析发现，空气污染收费政策将产生“双重红利”效应，可以实现缓解拥堵和减少排放的双重目标。但是，与此同时，这会导致非法旅行的增加。尽管一项单一的罚款政策可以有效地减少车辆的非法出行次数，并弥补空气污染收费政策的不足，但它将大大降低公共交通的供应水平。补贴将大大改善公共交通的供应水平，但该政策也显示出一定的“缓解拥挤弱”效应和“减少排放微弱”效应。具有多种性能和互补优势的协作策略将克服单个策略的局限性。这些发现为改善雾霾控制方案提供了决策依据。但是该政策也表现出一定的“缓解交通拥挤”和“减少减排”的效果。具有多种性能和互补优势的协作策略将克服单个策略的局限性。这些发现为改善雾霾控制方案提供了决策依据。但是该政策也表现出一定的“缓解交通拥挤”和“减少减排”的效果。具有多种性能和互补优势的协作策略将克服单个策略的局限性。这些发现为改善雾霾控制方案提供了决策依据。