城市机动车限行对PM_(2.5)的影响与效果检验

Analysis of the Impact and Effect Test of Urban Vehicles Restriction on PM Emission

为缓解城市道路拥堵与交通污染问题,全国多地陆续实施机动车限行政策,但针对不同城市不同限行政策对大气污染的影响却鲜有文献研究。根据政策特征,本文将限行政策分为一般限行和特殊限行两类。基于双重差分模型,采用2001-2017年我国各省会城市及直辖市的面板数据,本文分别研究了不同类型的限行政策对城市PM_(2.5)污染的改善作用。研究发现:首先,机动车PM_(2.5)排放已经成为了城市PM_(2.5)排放的主要来源之一,机动车限行措施也越来越多地被运用到治理城市空气污染的过程中;第二,一般限行政策和特殊限行政策均不同程度地缓解了大气污染,但相对而言,特殊限行政策的减排效果更明显;第三,限行政策的力度,如限行区域的相对大小和限制机动车的相对数量均能影响政策效果,一般来说,限行区域越大,限行的车辆越多,减排效果越显著;第四,在剔除特殊样本"北京"和"限购"政策的影响后,限行政策依然有效。本文从机动车PM_(2.5)排放的角度实证检验了限行政策对大气污染的影响和效果,为政府进一步制定更高效合理的道路交通污染防治措施提供了参考依据。

Many cities in China have implemented to take traffic restrictions policy to alleviate road congestion and control vehicle pollution.However,there are few studies which focus on the effects of different kinds of restriction regulations on air pollution from the perspective of cities.In this paper,the policies are classified as general restriction and specialized restriction.Based on the Difference-in-Difference model using panel data of provincial capitals and municipality cities in China from 2001 to 2017,the effects of different traffic restrictive regulations on PM_(2.5)emission are evaluated.The results presents as follows.Firstly,the vehicles have become one of the main sources of urban PM_(2.5)emission,and vehicle restriction measures are increasingly used during the urban air pollution control.Secondly,both general restriction and specialized restriction can effectively reduce PM_(2.5)emission,but the effect of specialized restriction policy is more significant.Thirdly,the intensity of traffic restrictions,like the factors of the restricted area and the restricted numbers of vehicle,can apparently influence the policy effects.Fourthly,according to the robustness test,the restrictive policy is still valid after removing the effect of sample"Beijing city"and all cities with"purchasing restrictive"policies.The impact of the vehicle restrictive regulation on mitigating PM_(2.5)emission is demonstrated,and the findings can provide more efficient and reasonable policy supports for the decision-makers.