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논문 기본 정보

자료유형
학술저널
저자정보
김정호 (열린공간) 김필호 (국립환경과학원) 신수현 (국립환경과학원) 김창혁 (국립환경과학원) 박종성 (국립환경과학원) 황규철 (충남연구원) 김종범 (충남연구원 서해안기후환경연구소) 박정민 (국립환경과학원)
저널정보
한국환경분석학회 환경분석과 독성보건 환경분석과 독성보건 제27권 제3호
발행연도
2024.9
수록면
175 - 184 (10page)

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This study examines particulate matter (PM) concentrations, specifically PM10, PM2.5, and PM1.0, at an urban site in Ansan, South Korea. Three BAM-1020 continuous monitors measured PM10, PM2.5, and PM1.0 hourly from January to December 2021, with data acquisition rates of 97.1%, 97.3%, and 93.4%, respectively. Average annual concentrations were 45.7±48.4 μg/m³ (PM10), 26.4±22.7 μg/m³ (PM2.5), and 18.5±14.5 μg/m³ (PM1.0). PM10 was 91% of the annual air quality standard, while PM2.5 exceeded this standard by 176%, indicating severe pollution. Statistical analyses using probability density function (PDF) and cumulative distribution function (CDF) showed 98.5% of data converged at 150 μg/m³ (PM10), 75 μg/m³ (PM2.5), and 50 μg/m³ (PM1.0), with the remaining 1.5% corresponding to approximately 131 hours, annually. In 2021, all six observed yellow dust events occurred in spring (March to May). PM10, PM2.5, and PM1.0 concentrations increased from January to March, peaked in March, decreased until September, and rose again. The coarse fraction ratio increased stepwise from February to May, likely due to yellow dust and episodes of high PM concentration in the spring. The PM1.0 concentration was higher in summer and fall compared with that in spring and winter. The PM1.0/PM2.5 ratio was highest in summer and fall even though the annual PM1.0 concentration was lowest, suggesting a higher secondary formation rate of fine particles during these periods. This underscores the need for further scientific investigation on PM1.0. The study provides insights into the simultaneous observation and distribution characteristics of PM10, PM2.5, and PM1.0, highlighting the mass concentration, distribution, and ratio of PM1.0. These findings are crucial for understanding PM distribution in Ansan, an industrial complex, and can serve as essential data for chemical composition comparisons, data validation, public health strategies, and cost-benefit analyses for regional PM improvement.

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