{"title":"Incorporating meander to account for the impact of low winds in area source modeling; AERMOD as a case study.","authors":"Akula Venkatram, Gavendra Pandey, Saravanan Arunachalam","doi":"10.1080/10962247.2024.2410450","DOIUrl":null,"url":null,"abstract":"<p><p>A variety of sources of pollutant emissions can be represented as area sources. These include manure lagoons, landfills, wastewater treatment ponds, and highways. A group of point sources can also be treated as an area source. The impact of an area source is usually computed by representing the area source as a set of line sources perpendicular to the wind direction. As for point sources, the Gaussian horizontal concentration distribution used to compute the contributions of the line sources is likely to overestimate ground-level concentrations when the wind speed is comparable to the standard deviation of the horizontal velocity fluctuations. A variety of methods are used to mitigate this overestimation under these conditions, referred to as meander. As an example of one these approaches, we examine that of AERMOD, EPA's regulatory model. AERMOD includes meander in modeling the impact of point and volume sources, but has not yet incorporated it into AERMOD's area source algorithm. This paper describes an approach to include meander in AERMOD's area source algorithm and demonstrates its impact on concentrations associated with area sources.<i>Implications</i>: Inclusion of wind direction meander in modeling dispersion when the wind speed is low is important in ensuring that AERMOD does not overestimate concentrations under these conditions. In view of the importance of area sources of pollution, the results presented in this paper represent a potential enhancement of AERMOD's ability to estimate the upper end of the concentration distribution, which forms the basis of the regulatory acceptance of the model.</p>","PeriodicalId":2,"journal":{"name":"ACS Applied Bio Materials","volume":null,"pages":null},"PeriodicalIF":4.6000,"publicationDate":"2024-10-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"ACS Applied Bio Materials","FirstCategoryId":"93","ListUrlMain":"https://doi.org/10.1080/10962247.2024.2410450","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"MATERIALS SCIENCE, BIOMATERIALS","Score":null,"Total":0}
引用次数: 0
Abstract
A variety of sources of pollutant emissions can be represented as area sources. These include manure lagoons, landfills, wastewater treatment ponds, and highways. A group of point sources can also be treated as an area source. The impact of an area source is usually computed by representing the area source as a set of line sources perpendicular to the wind direction. As for point sources, the Gaussian horizontal concentration distribution used to compute the contributions of the line sources is likely to overestimate ground-level concentrations when the wind speed is comparable to the standard deviation of the horizontal velocity fluctuations. A variety of methods are used to mitigate this overestimation under these conditions, referred to as meander. As an example of one these approaches, we examine that of AERMOD, EPA's regulatory model. AERMOD includes meander in modeling the impact of point and volume sources, but has not yet incorporated it into AERMOD's area source algorithm. This paper describes an approach to include meander in AERMOD's area source algorithm and demonstrates its impact on concentrations associated with area sources.Implications: Inclusion of wind direction meander in modeling dispersion when the wind speed is low is important in ensuring that AERMOD does not overestimate concentrations under these conditions. In view of the importance of area sources of pollution, the results presented in this paper represent a potential enhancement of AERMOD's ability to estimate the upper end of the concentration distribution, which forms the basis of the regulatory acceptance of the model.