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Air pollution causes widespread environmental and health problems andseverely hinders the life quality of urban residents. Traffic is a critical forhuman life and its emissions are a major source of pollution, aggravating urbanair pollution. However, the complex interaction between the traffic emissionsand the air pollution in the cities has not yet been revealed. In particular,the spread of the COVID-19 has caused various cities to implement differenttraffic restriction policies according to the local epidemic situation, whichprovides the possibility to explore the relationship between urban traffic andair pollution. Here we explore the influence of traffic to air pollution byreconstructing a multi-layer complex network base on traffic index and airquality index. We uncover that air quality in Beijing-Tianjin-Hebei (BTH),Chengdu-Chongqing Economic Circle (CCS) and Central China (CC) regions aresignificantly influenced by the surrounding traffic conditions after theoutbreak. Under different fights against the epidemic stages, the influence oftraffic in other cities on the air pollution reached the maximum in stage 2(also called Initial Progress in Containing the Virus). For BTH and CC regions,the impact of traffic on air quality becomes larger in the first two stages andthen decreases, while for CC, the significant impact occurs in Phase 3 amongregions. For other regions, however, the changes are not evident. Our presentednetwork-based framework provides a new perspective in the field oftransportation and environment, and maybe helpful to guide the government toformulate air pollution mitigation and traffic restriction policies.

Network approach reveals the spatiotemporal influence of traffic to air pollution under the COVID-19