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.
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。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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