  Air pollution causes widespread environmental and health problems and
severely hinders the life quality of urban residents. Traffic is a critical for
human life and its emissions are a major source of pollution, aggravating urban
air pollution. However, the complex interaction between the traffic emissions
and 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 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 to air pollution by
reconstructing a multi-layer complex network base on traffic index and air
quality index. We uncover that air quality in Beijing-Tianjin-Hebei (BTH),
Chengdu-Chongqing Economic Circle (CCS) and Central China (CC) regions are
significantly influenced by the surrounding traffic conditions after the
outbreak. Under different fights against the epidemic stages, the influence of
traffic 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 and
then decreases, while for CC, the significant impact occurs in Phase 3 among
regions. For other regions, however, the changes are not evident. Our presented
network-based framework provides a new perspective in the field of
transportation and environment, and maybe helpful to guide the government to
formulate air pollution mitigation and traffic restriction policies.
