Detecting atmospheric oxidation in the PM2.5 and ozone multilayer complex network

Abstract

Reducing the levels of Fine particulate matter (PM _2.5 ) and ozone (O _3 ) is essential for further improving air quality in China. The intricate and non-linear interactions between PM _2.5 and O _3 on a national scale over long-term records are not well understood. Here, we proposed a novel multi-layer network approach to bridge the gap. Our findings reveal that the variability of O _3 precedes that of PM _2.5 by one day. The degree, weighted degree, and edge distance follow a power-law decay distribution, suggesting that their relationship is not a random process. O _3 concentration in the Yangtze River Delta (YRD) region and eastern Shandong Province significantly impacts the PM _2.5 levels in surrounding areas. Conversely, PM _2.5 concentrations in Shandong Province, Henan Province, YRD and Pearl River Delta (PRD) have a strong influence on O _3 levels. Moreover, we quantified the seasonality of the interactions and elucidated the underlying reasons. The results revealed the interactions between PM _2.5 and O _3 are intricately tied to atmospheric oxidation processes. More specifically, in summer, the atmospheric oxidation has a strong impact on the interactions in key regions, such as the Beijing–Tianjin–Hebei,YRD region and Fenwei Plain. However, the PRD region experiences a more pronounced effect from atmospheric oxidation on this relationship in winter. These findings demonstrate that it is crucial to effectively regulate atmospheric oxidation to mitigate PM _2.5 and O _3 . Our results also serve as a valuable methodological framework for understanding the characteristics of pollutants.

Keywords

• PM2.5
• O3
• multilayer complex network
• atmospheric oxidation