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首页> 外文期刊>Journal of the Air & Waste Management Association >Modeling of particulate matter dispersion from a poultry facility using AERMOD
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Modeling of particulate matter dispersion from a poultry facility using AERMOD

机译:使用AERMOD对家禽设施中的颗粒物扩散进行建模

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This study evaluates the performance of AERMOD, the current U.S. Environmental Protection Agency (EPA) regulatory model, in simulating particulate matter (PM_(10) and PM_(2.5)) dispersion from a poultry pullet facility. At the source, the daily mean PM_(10) and PM_(2.5) concentrations with strong diurnal patterns were estimated to be 436.01 ± 166.77 μg m~(-3) and 291.09 ± 105.81 μg m~(-3), respectively. This corresponded to daily mean emission rates of PM_(10) and PM_(2.5) as 0.067-0.073 g sec~(-1) and 0.044-0.047g sec~(-1), respectively. The modeled hourly PM concentration showed acceptable accuracy relative to the measured PM concentrations downwind of the source. Increasing the averaging period from hourly to daily resulted in improved prediction. The simulations revealed that PM concentrations at and beyond the property line of the poultry facility were within the National Ambient Air Quality Standards. This study suggested that AERMOD is effective in predicting and assessing the impacts of PM downwind of poultry facilities.
机译:这项研究评估了AERMOD(目前的美国环境保护局(EPA)监管模型)在模拟禽类鸡场设施中的颗粒物(PM_(10)和PM_(2.5))扩散方面的性能。从源头上看,日平均PM_(10)和PM_(2.5)浓度具有强烈的昼夜模式,分别为436.01±166.77μgm〜(-3)和291.09±105.81μgm〜(-3)。这对应于PM_(10)和PM_(2.5)的日平均排放率分别为0.067-0.073 g sec〜(-1)和0.044-0.047g sec〜(-1)。相对于源顺风方向测得的PM浓度,建模的每小时PM浓度显示出可接受的精度。将平均时间从每小时增加到每天可以提高预测效果。模拟显示,家禽设施的性能线内外的PM浓度均在国家环境空气质量标准之内。这项研究表明,AERMOD能有效地预测和评估PM顺风对家禽设施的影响。

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    Department of Food, Agricultural and Biological Engineering, Ohio State University, Columbus, OH, USA;

    Department of Food, Agricultural and Biological Engineering, The Ohio State University, 590 Woody Hayes, Columbus, OH 43210, USA;

    Department of Civil, Environmental and Geodetic Engineering, Ohio State University, Columbus, OH, USA;

    Department of Civil, Environmental and Geodetic Engineering, Ohio State University, Columbus, OH, USA;

    Department of Civil, Environmental and Geodetic Engineering, Ohio State University, Columbus, OH, USA;

    Climate and Atmospheric Science Section, Illinois State Water Survey, Prairie Research Institute, University of Illinois at Urbana-Champaign, Champaign, IL, USA;

    Department of Chemical and Biomolecular Engineering, Ohio State University, Columbus, OH, USA;

    Department of Food, Agricultural and Biological Engineering, Ohio State University, Columbus, OH, USA;

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