Patterns Discovery Dataset for Particulate Matter (PM2.5) Pollution Trends in Japan

Air pollution is a leading risk factor for mortality in Japan. Despite improvements in air quality, Particulate Matter 2.5 (PM_2.5) remains a significant concern due to its severe health impacts. Although previous studies have analyzed PM_2.5 trends in Japan, they often overlook regions consistently exposed to high PM_2.5 levels, primarily due to the lack of comprehensive, high-quality datasets. To address this gap, we developed a large-scale dataset containing five years of hourly PM_2.5 measurements from approximately 1,900 sensors across Japan. The dataset employs an ER-Schema that isolates PM_2.5 data, ensuring a focused analysis by excluding other pollutants. This extensive temporal and spatial coverage enables a more precise examination of long-term PM_2.5 exposure patterns. Finally, we validated the dataset by applying established pattern mining models, demonstrating its effectiveness in identifying regions with consistently high PM_2.5 levels. The proposed dataset provides a valuable resource for air quality research, supporting the development of targeted mitigation strategies and enhancing understanding of pollution dynamics in Japan.