School of Civil and Transportation Engineering, Guangdong University of Technology, Guangzhou 510006, China.
Int J Environ Res Public Health. 2020 Jul 9;17(14):4947. doi: 10.3390/ijerph17144947.
During the large-scale outbreak of COVID-19 in China, the Chinese government adopted multiple measures to prevent the epidemic. The consequence was that a sudden variation in residents' travel behavior took place. In order to better evaluate the temporal distribution of air pollution, and to effectively explore the influence of human activities on air quality, especially under the special situation, this study was conducted based on the real data from a case city in China from this new perspective. Two case scenarios were constructed, in which the research before the changes of residents' travel behavior was taken as case one, and the research after the changes in residents' travel behavior as case two. The hourly real-time concentrations of PM, PM, SO, NO, CO and O that have passed the augmented Dickey-Fuller (ADF) test were employed as a data source. A series of detailed studies have been carried out using the correlation method, entropy weight method and the Air Quality Index (AQI) calculation method. Additionally, the research found that the decrease rate of NO concentration is 61.05%, and the decrease rate of PM concentration is 53.68%. On the contrary, the average concentration of O has increased significantly, and its growth rate has reached to 9.82%. Although the air quality in the first week with fewer travels was in the excellent category, and chief pollutant (CP), as well as excessive pollutant (EP), were not found, as traffic volume increased, it became worse in the second and third weeks. In addition to that, special attention should still be paid to the development trend of O, as its average hourly concentration has increased. The findings of this study will have some guiding significance for the study of air pollution prevention, cleaner production, and indoor environmental safety issues, especially for the study of abnormal traffic environments where residents' travel behaviors have changed significantly.
在中国 COVID-19 大规模爆发期间，中国政府采取了多项措施来防止疫情蔓延。结果是居民的出行行为突然发生了变化。为了更好地评估空气污染的时间分布，并有效探索人类活动对空气质量的影响，特别是在特殊情况下，本研究从一个新的角度出发，基于中国一个案例城市的实际数据进行了研究。构建了两个案例场景，其中研究居民出行行为变化前的情况作为案例一，研究居民出行行为变化后的情况作为案例二。经过增广迪基-富勒（ADF）检验的 PM、PM、SO、NO、CO 和 O 的实时小时浓度被用作数据来源。使用相关方法、熵权法和空气质量指数（AQI）计算方法进行了一系列详细的研究。此外，研究发现，NO 浓度的下降率为 61.05%，PM 浓度的下降率为 53.68%。相反，O 的平均浓度显著增加，增长率达到 9.82%。尽管第一周出行较少时空气质量处于优秀水平，且未发现主要污染物（CP）和过度污染物（EP），但随着交通量的增加，第二周和第三周的空气质量变得更差。此外，还应特别注意 O 的发展趋势，因为其平均小时浓度已经增加。本研究的结果将对空气污染防治、清洁生产和室内环境安全问题的研究具有一定的指导意义，特别是对居民出行行为发生显著变化的异常交通环境的研究具有一定的指导意义。
