{"title":"Evaluation of long-term exposure to pollutants by means of a dispersion model","authors":"G. Latini, G. Passerini, F. Principi","doi":"10.1109/EESMS.2009.5341318","DOIUrl":null,"url":null,"abstract":"Ancona Province includes an area that has been claimed “Highly at risk of environmental crisis” due to the presence of a multitude of anthropogenic pollution sources. Most of these sources emit an amount of airborne pollutants. In 2006, Local Authorities started to monitor vascular diseases within the risky area trying to assess their correlation with long-term exposure to Particulate Matter. Researchers found that monitored data were available only from 2001 and that several data sets were corrupted. They asked us how to deal with this lack of data and we suggested performing a complete dispersion analysis over the entire area and upon ten years of time spam, by applying a well-known state-of-the-art regulatory model such as AERMOD. Here we present the preliminary results of our study.","PeriodicalId":320320,"journal":{"name":"2009 IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems","volume":"538 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2009-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2009 IEEE Workshop on Environmental, Energy, and Structural Monitoring Systems","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/EESMS.2009.5341318","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Ancona Province includes an area that has been claimed “Highly at risk of environmental crisis” due to the presence of a multitude of anthropogenic pollution sources. Most of these sources emit an amount of airborne pollutants. In 2006, Local Authorities started to monitor vascular diseases within the risky area trying to assess their correlation with long-term exposure to Particulate Matter. Researchers found that monitored data were available only from 2001 and that several data sets were corrupted. They asked us how to deal with this lack of data and we suggested performing a complete dispersion analysis over the entire area and upon ten years of time spam, by applying a well-known state-of-the-art regulatory model such as AERMOD. Here we present the preliminary results of our study.