Assessment of Regional Source Contribiution of PM2.5 in the Gwangyang Bay Area

Hye-young K Park, Gil-young Oh, Hyun-Su Park, Hak-Rim Kim, Bo-ram Lee, Chan-O Park, H. Lim, Gui-Hwan Park, Jong-su Park, M. Bae
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Abstract

Fine particulate matter (PM-2.5) samples were collected over 15 months in the Yeosu and Gwangyang areas from March, 2019 to June 2020. Samples were analyzed for organic carbon, elemental carbon, water-soluble ionic compounds, and trace elements. Source apportionment model (Positive Matrix Factorization) was applied to the data understand monthly and seasonal contributing sources of PM-2.5. Nine source categories with reasonably stable profiles were identified in the Yeosu area such as secondary sulfate (38%), oil combustion (14%), mobile (14%), biomass burning (13%), roadway emission (10%), secondary nitrate (6%), industry activity (3%), sea salt (2%), and coal combustion (0.7%). In the Gwangyang area, the main and relatively different source contributions were secondary sulfate (37%), biomass burning (21%), mobile (13%), industry activity (13%), secondary nitrate (5%), oil combustion (3%), sea salt (3%), and roadway emission (0.7%). The companion model such as conditional probability function, revealed that the sources of secondary sulfate, nitrate, and biomass burning facilities can significantly affect the pollution levels at the specific locations.
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光阳湾地区PM2.5区域源贡献评价
从2019年3月到2020年6月,在丽水和光阳地区采集了15个月的细颗粒物(PM-2.5)样本。对样品进行了有机碳、元素碳、水溶性离子化合物和微量元素的分析。采用源分配模型(正矩阵分解)对数据进行分析,了解pm2.5的月度和季节性贡献源。丽水地区确定了9种相对稳定的来源类型,分别是二次硫酸盐(38%)、石油燃烧(14%)、移动(14%)、生物质燃烧(13%)、道路排放(10%)、二次硝酸盐(6%)、工业活动(3%)、海盐(2%)和煤炭燃烧(0.7%)。在光阳地区,次生硫酸盐(37%)、生物质燃烧(21%)、移动(13%)、工业活动(13%)、次生硝酸盐(5%)、石油燃烧(3%)、海盐(3%)和道路排放(0.7%)是主要和相对不同的来源。条件概率函数等伴生模型表明,二次硫酸盐、硝酸盐和生物质燃烧设施的来源对特定地点的污染水平有显著影响。
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