This study compared the levels of particulate matter (PM2.5, PM10) and their associated meteorological and air pollutant factors before, during, and after the COVID-19 pandemic across three regions in South Korea with distinct characteristics: Baengnyeongdo (a background concentration site); Ansan, Gyeonggi Province (an industrial complex); and Eunpyeong-gu, Seoul (a densely populated urban area). Using eight years (2017~2024) of hourly air-quality and meteorological observations, temporal and seasonal trends were examined by directly aggregating the hourly observations by period and season. Meanwhile, Pearson correlation and multiple regression analyses were likewise conducted directly on the hourly observations to assess relationships between PM concentrations and SO2, NO2, O3, CO, temperature, humidity, precipitation, and pressure across three periods: pre-COVID-19 (2017~2019), during COVID-19 (2020~2022), and post-COVID-19 (2023~2024). All three regions showed a marked decrease in PM2.5 and PM10 after the pandemic (PM2.5: –17% in Baengnyeongdo, –19% in the greater Seoul Metropolitan Area, and –13% in Gyeonggi Province), while combustion-related pollutants (NO2, SO2) decreased mainly in the urban and industrial regions, and O3 increased in all three regions, consistent with a weakened titration effect. Both the period-specific correlation analysis and the hourlybased multiple regression analysis indicated that CO was consistently the strongest explanatory factor for PM2.5 in the industrial and urban regions. Additionally, NO2 was also a leading factor in the correlation analysis, and O3 emerged as a comparatively important factor once other pollutants were controlled for in the multiple regression. The hourly correlation analysis further showed that the background site also exhibited a moderate-to-strong association with CO, which is consistent with a stronger role of long-range transport. In contrast, the background site’s association with SO2 remained comparatively weaker than that of the industrial region. An additional, indirect emission-source linkage analysis based on gaseous-pollutant concentrations (CO, NO2, SO2) indicated that PM2.5 variations in the industrial and urban regions were more closely tied to domestic emission activity than at the background site. However, this approach has inherent limitations that warrant future incorporation of quantitative activity indicators, such as energy consumption, economic activity, and traffic volume. These results suggest that region-specific PM2.5 management strategies tailored to local emission structures are needed alongside nationwide policy measures.

Abstract
1. 서 론
2. 연구 방법
    2.1 연구 대상지역 설정 및 기상자료 수집
    2.2 대기오염물질 농도 자료 수집 및 추이 분석
    2.3 대기오염물질 오염도에 따른 상관성 분석
    2.4 시간 자료 활용 다중회귀 분석
    2.5 배출원과 연계 분석 특성
3. 연구 결과 및 고찰
    3.1 백령, 안산 및 서울 지역의 기상 특성
    3.2 백령, 서울 안산지역의 대기오염물질 평가
    3.3 백령, 서울 및 안산 지역의 대기오염물질 농도의 상관성 분석
    3.4 시간 단위 자료를 활용한 다중회귀분석
    3.5 배출원과 연계분석
4. 결 론
감사의 글
References
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• 박영복(안양대학교 환경공학과, 환경보건기술연구원) | YoungBok Park (Environmental Engineering, Anyang University, Environmental Health Technology Institute)
• 백정덕(안양대학교 환경공학과) | JeongDeok Beak (Environmental Engineering, Anyang University)
• 주흥수(안양대학교 환경공학과) | HungSoo Joo (Environmental Engineering, Anyang University) Corresponding author