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

TL;DR

This study uses a network-based approach to analyze how traffic influences air pollution across different Chinese regions during COVID-19, revealing significant spatiotemporal effects linked to epidemic control stages.

Contribution

The paper introduces a novel multi-layer complex network framework to quantify the dynamic impact of traffic on air quality during COVID-19 restrictions.

Findings

Traffic significantly affects air pollution in key regions during epidemic stages.

The influence of traffic varies across regions and stages, peaking at different times.

The framework offers new insights for policy-making in urban environmental management.

Abstract

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.