Characteristics of PM2.5 distribution and its Hot Spot using Scanning LiDAR

Over recent decades, air quality has become major concern over the Korean peninsula. Because of the growing concern, the Korean government regulated air pollutants management policies and developed the technologies for improving air quality. Thus, the long-term trends of PM₁₀ emissions are gradually decreased. However, industrial complexes including various industries are concentrated and distributed with insufficient prevention management for air pollutant emission facilities. In addition, these facilities are emitted high concentrations of PM_2.5 and the emissions are dispersed nearby residential areas, which can have a direct adverse effect on the environment and health. Therefore, it is judged that efficient management of the emission of air pollutants in industrial complex areas is necessary. So this study to identify major and illegal emission sources in industrial complexes and propose management measures.
In this study, we investigated that the characteristics of the concentration of PM_2.5 from the industrial complex in Siheung-si, Gyeonggi-do are using Scanning LiDAR for analyzing spatiotemporal distribution and identifing Hot Spots. We were analyzed hourly, daily, and monthly average of PM₁₀ and PM_2.5 concentrations based on scanning LiDAR measurement datasets. Distributions of Hot Spots in PM_2.5 were selected and visualized using the GIS Heat map technique. The result showed that the concentration of hourly averaged PM_2.5 gradually increased from 08:00 to work. And from 09:00 to 13:00, the high concentration phenomenon appeared. And the concentration increased again from 15 to 17:00, and then the concentration gradually decreased from 18:00. Heat map showed that a total of 7 Hot Spots from A to G were identified within the Scanning LiDAR observation area. Moreover, it was found that high-concentration of PM_2.5 was emitted in the three areas of E, F, and G. The three main emission sources were classified into manufacturing industries such as food manufacturing and metal steel factory. Therefore, it can be used as basic data for efficient emission sources and hotspot management improving air quality.

Acknowledgment: This research was supported by a grant (2023-MOIS-20024324) of Ministry-Cooperation R&D Program of Disaster-Safety funded by Ministry of Interior and Safety (MOIS, Korea) and Metropolitan Environment Management Office in Gyeonggi-do Province, Korea.