A Framework for Characterizing the Multilateral and Directional Interaction Relationships Between PM Pollution at City Scale: A Case Study of 29 Cities in East China, South Korea and Japan

Transboundary particulate matter (PM) pollution has become an increasingly significant public health issue around the world due to its impacts on human health. However, transboundary PM pollution is difficult to address because it usually travels across multiple urban jurisdictional boundaries with varying transportation directions at different times, therefore posing a challenge for urban managers to figure out who is potentially polluting whose air and how PM pollution in adjacent cities interact with each other. This study proposes a statistical analysis framework for characterizing directional interaction relationships between PM pollution in cities. Compared with chemical transport models (CTMs) and chemical composition analysis method, the proposed framework requires less data and less time, and is easy to implement and able to reveal directional interaction relationships between PM pollution in multiple cities in a quick and computationally inexpensive way. In order to demonstrate the application of the framework, this study applied the framework to analyze the interaction relationships between PM2.5 pollution in 29 cities in East China, South Korea and Japan using one year of hourly PM2.5 measurement data in 2018. The results show that the framework is able to reveal the significant multilateral and directional interaction relationships between PM2.5 pollution in the 29 cities in Northeast Asia. The analysis results of the case study show that the PM2.5 pollution in China, South Korea and Japan are linked with each other, and the interaction relationships are mutual. This study further evaluated the framework's validity by comparing the analysis results against the wind vector data, the back trajectory data, as well as the results extracted from existing literature that adopted CTMs to study the interaction relationships between PM pollution in Northeast Asia. The comparisons show that the analysis results produced by the framework are consistent with the wind vector data, the back trajectory data as well as the results using CTMs. The proposed framework provides an alternative for exploring transportation pathways and patterns of transboundary PM pollution between cities when CTMs and chemical composition analysis would be too demanding or impossible to implement.

Automated summary

This study proposes a statistical analysis framework to explore the directional interaction relationships between particulate matter (PM) pollution in cities. By analyzing PM2.5 pollution data from 29 cities in East China, South Korea, and Japan, the study reveals significant multilateral and directional interaction relationships. The framework provides a quick and consistent alternative to traditional models and chemical composition analysis.