Department of Occupational and Environmental Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan 430030, Hubei, China.
Department of Occupational and Environmental Health, Ministry of Education and State Key Laboratory of Environmental Health (Incubating), School of Public Health, Tongji Medical College, Huazhong University of Science and Technology, 13 Hangkong Road, Wuhan 430030, Hubei, China.
Sci Total Environ. 2021 Aug 10;781:146618. doi: 10.1016/j.scitotenv.2021.146618. Epub 2021 Mar 19.
Existing estimations of air pollution from automobile sources are based on either experiments or small-scale governmental interventions. China's nationwide traffic control during the coronavirus disease 2019 outbreak provided us a unique opportunity to assess the direct dose-effect relationship between vehicle density and air pollution. We found that, during the coronavirus disease 2019 outbreak, the nationwide reduced air pollution (except for O) could be largely explained by traffic control measures. During the traffic control period, every doubling of vehicle density was associated with a decrease of 4.2 (2.0, 6.4) μg/m in PM, 5.5 (2.9, 8.1) μg/m in PM, 1.5 (0.9, 2.0) μg/m in NO, and 0.04 (0.02, 0.07) mg/m in CO comparing cities with different vehicle densities. Similarly, for every 10% increase in the truck proportion, PM decreased by 12.3 (4.1, 20.6) μg/m, PM decreased by 14.3 (4.6, 23.9) μg/m, and CO decreased by 0.14 (0.05, 0.23) mg/m. Moreover, the associations between vehicle density and reduction in PM, PM, and CO during the traffic control period were stronger and showed near-complete linearity in cities with low green coverage rate (All P < 0.05 for interaction). According to our estimation, PM emissions from every doubling of vehicle density can lead to over 8000 excess deaths per year, 66% of which were caused by cardiopulmonary diseases. This natural experiment study is the first to observe the dose-effect relationship between on-road traffic and traffic-generated air pollution, as well as the mitigating effect of urban greening. Findings provide key evidence to the assessment and control of traffic-generated air pollution and its public health impact.
现有汽车污染源的空气污染估计是基于实验或小规模政府干预得出的。在中国 2019 冠状病毒病期间实施的全国性交通管制为我们提供了一个独特的机会，可以评估车辆密度与空气污染之间的直接剂量-效应关系。我们发现，在 2019 冠状病毒病期间，全国范围内减少的空气污染（除了 O 之外）在很大程度上可以用交通管制措施来解释。在交通管制期间，车辆密度每增加一倍，PM 浓度就会降低 4.2（2.0，6.4）μg/m，PM 浓度降低 5.5（2.9，8.1）μg/m，NO 浓度降低 1.5（0.9，2.0）μg/m，CO 浓度降低 0.04（0.02，0.07）mg/m，而不同车辆密度的城市之间存在差异。同样，卡车比例每增加 10%，PM 浓度就会降低 12.3（4.1，20.6）μg/m，PM 浓度降低 14.3（4.6，23.9）μg/m，CO 浓度降低 0.14（0.05，0.23）mg/m。此外，在交通管制期间，车辆密度与 PM、PM 和 CO 减少之间的关系在绿色覆盖率较低的城市中更强，并且呈近乎完全线性关系（所有交互作用 P<0.05）。根据我们的估计，车辆密度每增加一倍，PM 排放量就会导致每年超过 8000 人超额死亡，其中 66%是由心肺疾病引起的。这项自然实验研究首次观察到了道路交通与交通产生的空气污染之间的剂量-效应关系，以及城市绿化的缓解作用。研究结果为评估和控制交通产生的空气污染及其对公众健康的影响提供了关键证据。
