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Apportioning sources of PM_(2.5) in St. Louis, MO using speciation trends network data

机译:使用物种趋势网络数据在密苏里州圣路易斯分配PM_(2.5)的来源

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摘要

Positive matrix factorization (PMF) model was utilized along with wind direction and backward trajectory analyses, to identify and apportion local and regional sources to airborne PM_(2.5) in the metropolitan St. Louis, MO, area using data from the US Environmental Protection Agency's Speciation Trends Network. Local non-ferrous metal smelting and steel processing factors were identified by combining PMF contributions and wind direction analysis. Mobile (gasoline and diesel) sources were also resolved. Secondary sulfate and secondary nitrate factors appeared to have regional source origins that are located in the Ohio River Valley and the Midwestern agricultural farm lands, respectively. The transport of agriculturally emitted ammonia appears to be a major contributing factor to secondary nitrate formation in the Midwest. Impacts of African dust transport to the Midwestern PM_(2.5) were observed as well as transport of biomass burning aerosol from southern US area. This study presents an application of PMF and surface and upper air wind data to source identification of Midwestern fine aerosol.
机译:正矩阵分解(PMF)模型与风向和后向轨迹分析一起使用,使用美国环境保护署(US Environmental Protection Agency)的数据,识别和分配密苏里州大都会地区机载PM_(2.5)的本地和区域来源并将其分配给物种趋势网络。结合PMF贡献和风向分析,确定了当地有色金属冶炼和钢铁加工因素。移动(汽油和柴油)源也得到解决。次生硫酸盐和次生硝酸盐因素似乎具有区域来源,分别位于俄亥俄州河谷和中西部农业用地。农业排放的氨的运输似乎是中西部二次硝酸盐形成的主要因素。观察到非洲粉尘运输对中西部PM_(2.5)的影响以及来自美国南部地区的燃烧生物质气溶胶的运输。这项研究提出了PMF和地面和高空风数据在中西部精细气溶胶源识别中的应用。

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