Spatiotemporal evolution of PM2.5 diffusion in Cheng-Yu urban agglomeration in response to COVID-19 lockdown using complex network

TL;DR

This study investigates how COVID-19 lockdown measures affected PM2.5 pollution diffusion in Cheng-Yu urban agglomeration using complex network analysis, revealing changes in spillover patterns and regional resilience.

Contribution

It introduces a complex network approach to analyze city-scale PM2.5 diffusion patterns during COVID-19, highlighting the impact of lockdown measures on pollution dynamics.

Findings

PM2.5 spillovers were concentrated during lockdown and dispersed during recovery

Lockdown reduced the impact of pollution sources and altered input/output patterns

Spillover relationships became simpler during lockdown and more complex during recovery

Abstract

As the decrease in human activities resulting from the COVID-19 control measures had a significant impact on air quality, the epidemic provided an opportunity to investigate the extent to which air pollution is influenced by human activities and review existing measures. However, the corresponding diffusion pattern on a city scale is seldom mentioned at present stage, therefore, we chose the Cheng-Yu urban agglomeration, which is the largest city cluster in Southwest China, as our study area during the COVID-19 period, and attempted to investigate the process of PM2.5 diffusion using a complex network method. The results displayed that there was an evident external spillover effect of PM2.5 across all regions, and the PM2.5 spillovers were concentrated in several cities in the Cheng-Yu urban agglomeration during the lockdown period, whereas they are more dispersed during the recovery period. The overall decline in the impact of PM2.5 pollution source areas on receptor areas from a normal year to the pandemic year, and the intensity of PM2.5 spillover decreases gradually as the distance from the center increases. The implementation of the lockdown measures had an impact on both the input and output patterns of PM2.5 pollution in the region, the input pattern of PM2.5 pollution exhibited higher vulnerability, while the output pattern showed higher resilience. Additionally, the spillover relationship of PM2.5 pollution varies between different blocks, with relatively simple spillover relationships observed during the lockdown period and more complex dynamics during the recovery period. These findings have highlighted the importance of joint controls in combating regional air pollution.