Multi-scenario PM2.5 distribution and dynamic exposure assessment of university community residents: Development and application of intelligent health risk management system integrated low-cost sensors
Exposure scenario and receptor behavior significantly affect PM2.5 exposure quantity of persons and resident groups, which in turn influenced indoor or outdoor air quality & health management. An Internet of Things (IoT) system, EnvironMax+, was developed to accurately and conveniently asses...
| Main Authors: | , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2024-03-01
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| Series: | Environment International |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S0160412024001259 |
| _version_ | 1797248386496200704 |
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| author | Changhong Ou Fei Li Jingdong Zhang Pei Jiang Wei Li Shaojie Kong Jinyuan Guo Wenbo Fan Junrui Zhao |
| author_facet | Changhong Ou Fei Li Jingdong Zhang Pei Jiang Wei Li Shaojie Kong Jinyuan Guo Wenbo Fan Junrui Zhao |
| author_sort | Changhong Ou |
| collection | DOAJ |
| description | Exposure scenario and receptor behavior significantly affect PM2.5 exposure quantity of persons and resident groups, which in turn influenced indoor or outdoor air quality & health management. An Internet of Things (IoT) system, EnvironMax+, was developed to accurately and conveniently assess residential dynamic PM2.5 exposure state. A university community “QC”, as the application area, was divided into four exposure scenarios and five groups of residents. Low-cost mobile sensors and indoor/outdoor pollution migration (IOP) models jointly estimated multi-scenario real-time PM2.5 concentrations. Questionnaire was used to investigate residents' indoor activity characteristics. Mobile application (app) “Air health management (AHM)” could automatic collect residents' activity trajectory. At last, multi-scenario daily exposure concentrations of each residents-group were obtained. The results showed that residential exposure scenario was the most important one, where residents spend about 60 % of their daily time. Closing window was the most significant behavior affecting indoor contamination. The annual average PM2.5 concentration in the studied scenarios: residential scenario (RS) < public scenario (PS) < outdoor scenario (OS) < catering scenario (CS). Except for CS, the outdoor PM2.5 in other scenarios was higher than indoor by 5–10 μg/m3. The multi-scenario population weighted annual average exposure concentration was 37.1 μg/m3, which was 78 % of the annual average outdoor concentration. The exposure concentration of 5 groups: cooks > outdoor workers > indoor workers > students > the elderly, related to their daily activity time proportion in different exposure scenario. |
| first_indexed | 2024-04-24T20:13:46Z |
| format | Article |
| id | doaj.art-04a2079e117a4006aa5226c13c2f7e52 |
| institution | Directory Open Access Journal |
| issn | 0160-4120 |
| language | English |
| last_indexed | 2024-04-24T20:13:46Z |
| publishDate | 2024-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Environment International |
| spelling | doaj.art-04a2079e117a4006aa5226c13c2f7e522024-03-23T06:22:17ZengElsevierEnvironment International0160-41202024-03-01185108539Multi-scenario PM2.5 distribution and dynamic exposure assessment of university community residents: Development and application of intelligent health risk management system integrated low-cost sensorsChanghong Ou0Fei Li1Jingdong Zhang2Pei Jiang3Wei Li4Shaojie Kong5Jinyuan Guo6Wenbo Fan7Junrui Zhao8Research Center for Environment and Health, Zhongnan University of Economics and Law, Wuhan 430073, China; School of Information and Safety Engineering, Zhongnan University of Economics and Law, Wuhan 430073, ChinaResearch Center for Environment and Health, Zhongnan University of Economics and Law, Wuhan 430073, China; School of Information and Safety Engineering, Zhongnan University of Economics and Law, Wuhan 430073, China; Corresponding authors at: Research Center for Environment and Health, Zhongnan University of Economics and Law, Wuhan 430073, China.Research Center for Environment and Health, Zhongnan University of Economics and Law, Wuhan 430073, China; School of Information and Safety Engineering, Zhongnan University of Economics and Law, Wuhan 430073, China; Corresponding authors at: Research Center for Environment and Health, Zhongnan University of Economics and Law, Wuhan 430073, China.Research Center for Environment and Health, Zhongnan University of Economics and Law, Wuhan 430073, China; School of Information and Safety Engineering, Zhongnan University of Economics and Law, Wuhan 430073, ChinaResearch Center for Environment and Health, Zhongnan University of Economics and Law, Wuhan 430073, China; School of Information and Safety Engineering, Zhongnan University of Economics and Law, Wuhan 430073, ChinaResearch Center for Environment and Health, Zhongnan University of Economics and Law, Wuhan 430073, China; School of Information and Safety Engineering, Zhongnan University of Economics and Law, Wuhan 430073, ChinaResearch Center for Environment and Health, Zhongnan University of Economics and Law, Wuhan 430073, China; School of Information and Safety Engineering, Zhongnan University of Economics and Law, Wuhan 430073, ChinaResearch Center for Environment and Health, Zhongnan University of Economics and Law, Wuhan 430073, China; School of Information and Safety Engineering, Zhongnan University of Economics and Law, Wuhan 430073, ChinaResearch Center for Environment and Health, Zhongnan University of Economics and Law, Wuhan 430073, China; School of Information and Safety Engineering, Zhongnan University of Economics and Law, Wuhan 430073, ChinaExposure scenario and receptor behavior significantly affect PM2.5 exposure quantity of persons and resident groups, which in turn influenced indoor or outdoor air quality & health management. An Internet of Things (IoT) system, EnvironMax+, was developed to accurately and conveniently assess residential dynamic PM2.5 exposure state. A university community “QC”, as the application area, was divided into four exposure scenarios and five groups of residents. Low-cost mobile sensors and indoor/outdoor pollution migration (IOP) models jointly estimated multi-scenario real-time PM2.5 concentrations. Questionnaire was used to investigate residents' indoor activity characteristics. Mobile application (app) “Air health management (AHM)” could automatic collect residents' activity trajectory. At last, multi-scenario daily exposure concentrations of each residents-group were obtained. The results showed that residential exposure scenario was the most important one, where residents spend about 60 % of their daily time. Closing window was the most significant behavior affecting indoor contamination. The annual average PM2.5 concentration in the studied scenarios: residential scenario (RS) < public scenario (PS) < outdoor scenario (OS) < catering scenario (CS). Except for CS, the outdoor PM2.5 in other scenarios was higher than indoor by 5–10 μg/m3. The multi-scenario population weighted annual average exposure concentration was 37.1 μg/m3, which was 78 % of the annual average outdoor concentration. The exposure concentration of 5 groups: cooks > outdoor workers > indoor workers > students > the elderly, related to their daily activity time proportion in different exposure scenario.http://www.sciencedirect.com/science/article/pii/S0160412024001259PM2.5Dynamic exposure riskExposure behavior investigationInternet of ThingsLow-cost sensors |
| spellingShingle | Changhong Ou Fei Li Jingdong Zhang Pei Jiang Wei Li Shaojie Kong Jinyuan Guo Wenbo Fan Junrui Zhao Multi-scenario PM2.5 distribution and dynamic exposure assessment of university community residents: Development and application of intelligent health risk management system integrated low-cost sensors Environment International PM2.5 Dynamic exposure risk Exposure behavior investigation Internet of Things Low-cost sensors |
| title | Multi-scenario PM2.5 distribution and dynamic exposure assessment of university community residents: Development and application of intelligent health risk management system integrated low-cost sensors |
| title_full | Multi-scenario PM2.5 distribution and dynamic exposure assessment of university community residents: Development and application of intelligent health risk management system integrated low-cost sensors |
| title_fullStr | Multi-scenario PM2.5 distribution and dynamic exposure assessment of university community residents: Development and application of intelligent health risk management system integrated low-cost sensors |
| title_full_unstemmed | Multi-scenario PM2.5 distribution and dynamic exposure assessment of university community residents: Development and application of intelligent health risk management system integrated low-cost sensors |
| title_short | Multi-scenario PM2.5 distribution and dynamic exposure assessment of university community residents: Development and application of intelligent health risk management system integrated low-cost sensors |
| title_sort | multi scenario pm2 5 distribution and dynamic exposure assessment of university community residents development and application of intelligent health risk management system integrated low cost sensors |
| topic | PM2.5 Dynamic exposure risk Exposure behavior investigation Internet of Things Low-cost sensors |
| url | http://www.sciencedirect.com/science/article/pii/S0160412024001259 |
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