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Network approach reveals the spatiotemporal influence of traffic on air pollution under COVID-19.
Wang, Weiping; Yang, Saini; Yin, Kai; Zhao, Zhidan; Ying, Na; Fan, Jingfang.
  • Wang W; School of National Safety and Emergency Management, Beijing Normal University, Zhuhai 519087, China.
  • Yang S; School of National Safety and Emergency Management, Beijing Normal University, Zhuhai 519087, China.
  • Yin K; School of Traffic and Transportation, Beijing Jiaotong University, Beijing 100044, China.
  • Zhao Z; China Complexity Computation Lab, Department of Computer Science, School of Engineering, Shantou University, Shantou 515063, China.
  • Ying N; China State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China.
  • Fan J; School of Systems Science, Beijing Normal University, Beijing 100875, China.
Chaos ; 32(4): 041106, 2022 Apr.
Article in English | MEDLINE | ID: covidwho-1830316
ABSTRACT
Air pollution causes widespread environmental and health problems and severely hinders the quality of life of urban residents. Traffic is critical for human life, but its emissions are a major source of pollution, aggravating urban air pollution. However, the complex interaction between traffic emissions and air pollution in cities and regions has not yet been revealed. In particular, the spread of COVID-19 has led various cities and regions to implement different traffic restriction policies according to the local epidemic situation, which provides the possibility to explore the relationship between urban traffic and air pollution. Here, we explore the influence of traffic on air pollution by reconstructing a multi-layer complex network base on the traffic index and air quality index. We uncover that air quality in the Beijing-Tianjin-Hebei (BTH), Chengdu-Chongqing Economic Circle (CCS), and Central China (CC) regions is significantly influenced by the surrounding traffic conditions after the outbreak. Under different stages of the fight against the epidemic, the influence of traffic in some regions on air pollution reaches the maximum in stage 2 (also called Initial Progress in Containing the Virus). For the BTH and CC regions, the impact of traffic on air quality becomes bigger in the first two stages and then decreases, while for CC, a significant impact occurs in phase 3 among the other regions. For other regions in the country, however, the changes are not evident. Our presented network-based framework provides a new perspective in the field of transportation and environment and may be helpful in guiding the government to formulate air pollution mitigation and traffic restriction policies.
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Full text: Available Collection: International databases Database: MEDLINE Main subject: Air Pollution / Traffic-Related Pollution / COVID-19 Type of study: Observational study Limits: Humans Language: English Journal: Chaos Journal subject: Science Year: 2022 Document Type: Article Affiliation country: 5.0087844

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Full text: Available Collection: International databases Database: MEDLINE Main subject: Air Pollution / Traffic-Related Pollution / COVID-19 Type of study: Observational study Limits: Humans Language: English Journal: Chaos Journal subject: Science Year: 2022 Document Type: Article Affiliation country: 5.0087844