Spatiotemporal distribution, trend, forecast, and influencing factors of transboundary and local air pollutants in Nagasaki Prefecture, Japan

Abstract

Abstract The study of PM2.5 and NO2 has been emphasized in recent years due to their adverse effects on public health. To better understand these pollutants, many studies have researched the spatiotemporal distribution, trend, forecast, or influencing factors of these pollutants. However, rarely studies have combined these to generate a more holistic understanding that can be used to assess air pollution and implement more effective strategies. In this study, we analyze the spatiotemporal distribution, trend, forecast, and factors influencing PM2.5 and NO2 in Nagasaki Prefecture by using ordinary kriging, pearson's correlation, random forest, mann–kendall, auto-regressive integrated moving average and error trend and seasonal models. The results indicated that PM2.5, due to its long-range transport properties, has a more substantial spatiotemporal variation and affects larger areas in comparison to NO2, which is a local pollutant. Despite tri-national efforts, local regulations and legislation have been effective in reducing NO2 concentration but less effective in reducing PM2.5. This multi-method approach provides a holistic understanding of PM2.5 and NO2 pollution in Nagasaki prefecture, which can aid in implementing more effective pollution management strategies. It can also be implemented in other regions where studies have only focused on one of the aspects of air pollution and where a holistic understanding of air pollution is lacking.