Hongyu Lu , Daejin Kim , Haobing Liu , Tian Xia , William Reichard , Michael O. Rodgers , Randall Guensler
{"title":"按声源类型划分的 AERMOD (V21112) RLINEXT 扩散模式输出结果对单一噪声屏障高度和间隔距离变化的敏感性","authors":"Hongyu Lu , Daejin Kim , Haobing Liu , Tian Xia , William Reichard , Michael O. Rodgers , Randall Guensler","doi":"10.1016/j.apr.2024.102318","DOIUrl":null,"url":null,"abstract":"<div><div>The U.S. Environmental Protection Agency (USEPA) introduced the RLINEXT modeling feature in the latest versions of AERMOD (since version v21112) to predict traffic-induced pollutant concentration when noise barriers are present. The research presented in this paper explores the impacts of noise barrier characteristics on AERMOD-predicted concentrations. The research finds that because AERMOD can currently only attach one barrier to each road side, and because that barrier only impacts the source to which it is attached, it is also important to split links so that they properly pair with barriers. Given the sensitivity of AERMOD-predicted concentrations to barrier characteristics (i.e., barrier heights and distances to roadway), the research also concludes that barriers must be appropriately matched with input links. This study investigated the sensitivity of CO concentration predicted by the latest AERMOD under various noise barrier conditions (barrier heights and distances between road and barrier) and meteorological conditions (wind directions and wind speeds). The results indicate that ground-level concentration of downwind receptors decreases with increased barrier heights, and that distant barriers have less of an impact on predicted concentrations. This study also explored the impact of noise barrier on both horizontal and vertical concentration profiles, indicating that concentrations rise behind the barrier as plumes are predicted to loft over the barrier. The sensitivity analysis associated with splitting roadway links to match with barriers indicated an impact on predicted concentration for certain receptors of up to 10%, but the overall the impact on maximum concentrations was marginal.</div></div>","PeriodicalId":8604,"journal":{"name":"Atmospheric Pollution Research","volume":"15 12","pages":"Article 102318"},"PeriodicalIF":3.9000,"publicationDate":"2024-09-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Sensitivity of AERMOD (V21112) RLINEXT dispersion model outputs by source type to variability in single noise barrier height and separation distance\",\"authors\":\"Hongyu Lu , Daejin Kim , Haobing Liu , Tian Xia , William Reichard , Michael O. Rodgers , Randall Guensler\",\"doi\":\"10.1016/j.apr.2024.102318\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>The U.S. Environmental Protection Agency (USEPA) introduced the RLINEXT modeling feature in the latest versions of AERMOD (since version v21112) to predict traffic-induced pollutant concentration when noise barriers are present. The research presented in this paper explores the impacts of noise barrier characteristics on AERMOD-predicted concentrations. The research finds that because AERMOD can currently only attach one barrier to each road side, and because that barrier only impacts the source to which it is attached, it is also important to split links so that they properly pair with barriers. Given the sensitivity of AERMOD-predicted concentrations to barrier characteristics (i.e., barrier heights and distances to roadway), the research also concludes that barriers must be appropriately matched with input links. This study investigated the sensitivity of CO concentration predicted by the latest AERMOD under various noise barrier conditions (barrier heights and distances between road and barrier) and meteorological conditions (wind directions and wind speeds). The results indicate that ground-level concentration of downwind receptors decreases with increased barrier heights, and that distant barriers have less of an impact on predicted concentrations. This study also explored the impact of noise barrier on both horizontal and vertical concentration profiles, indicating that concentrations rise behind the barrier as plumes are predicted to loft over the barrier. The sensitivity analysis associated with splitting roadway links to match with barriers indicated an impact on predicted concentration for certain receptors of up to 10%, but the overall the impact on maximum concentrations was marginal.</div></div>\",\"PeriodicalId\":8604,\"journal\":{\"name\":\"Atmospheric Pollution Research\",\"volume\":\"15 12\",\"pages\":\"Article 102318\"},\"PeriodicalIF\":3.9000,\"publicationDate\":\"2024-09-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Atmospheric Pollution Research\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1309104224002836\",\"RegionNum\":3,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENVIRONMENTAL SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Atmospheric Pollution Research","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1309104224002836","RegionNum":3,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
Sensitivity of AERMOD (V21112) RLINEXT dispersion model outputs by source type to variability in single noise barrier height and separation distance
The U.S. Environmental Protection Agency (USEPA) introduced the RLINEXT modeling feature in the latest versions of AERMOD (since version v21112) to predict traffic-induced pollutant concentration when noise barriers are present. The research presented in this paper explores the impacts of noise barrier characteristics on AERMOD-predicted concentrations. The research finds that because AERMOD can currently only attach one barrier to each road side, and because that barrier only impacts the source to which it is attached, it is also important to split links so that they properly pair with barriers. Given the sensitivity of AERMOD-predicted concentrations to barrier characteristics (i.e., barrier heights and distances to roadway), the research also concludes that barriers must be appropriately matched with input links. This study investigated the sensitivity of CO concentration predicted by the latest AERMOD under various noise barrier conditions (barrier heights and distances between road and barrier) and meteorological conditions (wind directions and wind speeds). The results indicate that ground-level concentration of downwind receptors decreases with increased barrier heights, and that distant barriers have less of an impact on predicted concentrations. This study also explored the impact of noise barrier on both horizontal and vertical concentration profiles, indicating that concentrations rise behind the barrier as plumes are predicted to loft over the barrier. The sensitivity analysis associated with splitting roadway links to match with barriers indicated an impact on predicted concentration for certain receptors of up to 10%, but the overall the impact on maximum concentrations was marginal.
期刊介绍:
Atmospheric Pollution Research (APR) is an international journal designed for the publication of articles on air pollution. Papers should present novel experimental results, theory and modeling of air pollution on local, regional, or global scales. Areas covered are research on inorganic, organic, and persistent organic air pollutants, air quality monitoring, air quality management, atmospheric dispersion and transport, air-surface (soil, water, and vegetation) exchange of pollutants, dry and wet deposition, indoor air quality, exposure assessment, health effects, satellite measurements, natural emissions, atmospheric chemistry, greenhouse gases, and effects on climate change.