A comprehensive PM2.5 vulnerability index for medium-sized cities based on environmental big data

In 2021, the World Health Organization (WHO) tightened its particulate matter advisory standards for the first time in 16 years. This means that even small amounts of airborne particles can cause adverse health effects. Therefore, comprehensive and multidimensional approaches are required to effective PM management. This study aims to develop a comprehensive PM2.5 vulnerability index utilizing dynamic data that changes in time to provide real-time information on PM2.5 vulnerability in areas with limited social infrastructures. The target area is Chuncheon City, which is located in the downwind area of Seoul and is surrounded by mountains, making it prone to pollutant stagnation. The target period is the winter season of January-March 2022 (i.e., the post COVID-19 period). To utilize data with different individual units, normalization was performed using the Min-Max method, and the vulnerability index was calculated using the Principal Component Analysis (PCA) method to resolve multicollinearity among variables. In Chuncheon, a remote region (e.g., Dongsan-myeon) showed the lowest PM2.5 vulnerability index and a sub-rural region (e.g., Sinbuk-eup) showed the highest one. The difference in the vulnerability index depending on each region is expected to be utilized as basic data for establishing measures to deal with PM2.5 problems.

Acknowledgment

This research was supported by Particulate Matter Management Specialized Graduate Program through the Korea Environmental Industry & Technology Institute(KEITI) funded by the Ministry of Environment(MOE) and thank you to National Air Emission Inventory and Research Center for providing the data and this work was suported by the National Research Foundation of Korea(NRF) grant funded by the Korea government(MSIT) (RS-2024-00356913).