Philippe Thunis , Enrico Pisoni , Stefano Zauli-Sajani , Alexander de Meij
{"title":"Comparison of source apportionment targeting hot-spot concentration and average population exposure","authors":"Philippe Thunis , Enrico Pisoni , Stefano Zauli-Sajani , Alexander de Meij","doi":"10.1016/j.scitotenv.2025.178857","DOIUrl":null,"url":null,"abstract":"<div><div>Source apportionment (SA) is an essential first step in supporting the design of air quality plans. However, SA results can strongly be influenced by the choice of setting parameters, such as the indicator used. In this study, we assess how different choices of indicator for PM<sub>2.5</sub> (hot spot concentrations, average population exposure and average concentration) impact the SA results. Our analysis reveals that, in general, there is a good correlation between results obtained with these three indicators. The correlation is higher for sectors that are well-distributed spatially at city scale, such as residential and traffic, and lower for sectors characterized by important local emissions, such as waste and shipping. In most cases, results based on average indicators (average population exposure and average concentration) underestimates those based on the concentration hot spot location. Interestingly, we find that the choice of indicator has a strong impact on the estimation of the local contribution to air pollution in the city, but the relative share of the sectors is generally preserved across indicators. In other words, the priority sector remains similar, but the resulting scale of action can differ in some cities.</div></div>","PeriodicalId":422,"journal":{"name":"Science of the Total Environment","volume":"968 ","pages":"Article 178857"},"PeriodicalIF":8.2000,"publicationDate":"2025-02-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Science of the Total Environment","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0048969725004929","RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENVIRONMENTAL SCIENCES","Score":null,"Total":0}
引用次数: 0
Abstract
Source apportionment (SA) is an essential first step in supporting the design of air quality plans. However, SA results can strongly be influenced by the choice of setting parameters, such as the indicator used. In this study, we assess how different choices of indicator for PM2.5 (hot spot concentrations, average population exposure and average concentration) impact the SA results. Our analysis reveals that, in general, there is a good correlation between results obtained with these three indicators. The correlation is higher for sectors that are well-distributed spatially at city scale, such as residential and traffic, and lower for sectors characterized by important local emissions, such as waste and shipping. In most cases, results based on average indicators (average population exposure and average concentration) underestimates those based on the concentration hot spot location. Interestingly, we find that the choice of indicator has a strong impact on the estimation of the local contribution to air pollution in the city, but the relative share of the sectors is generally preserved across indicators. In other words, the priority sector remains similar, but the resulting scale of action can differ in some cities.
期刊介绍:
The Science of the Total Environment is an international journal dedicated to scientific research on the environment and its interaction with humanity. It covers a wide range of disciplines and seeks to publish innovative, hypothesis-driven, and impactful research that explores the entire environment, including the atmosphere, lithosphere, hydrosphere, biosphere, and anthroposphere.
The journal's updated Aims & Scope emphasizes the importance of interdisciplinary environmental research with broad impact. Priority is given to studies that advance fundamental understanding and explore the interconnectedness of multiple environmental spheres. Field studies are preferred, while laboratory experiments must demonstrate significant methodological advancements or mechanistic insights with direct relevance to the environment.