| Autor: |
Changhong Ou, Fei Li, Jingdong Zhang, Pei Jiang, Wei Li, Shaojie Kong, Jinyuan Guo, Wenbo Fan, Junrui Zhao |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Environment International, Vol 185, Iss , Pp 108539- (2024) |
| Druh dokumentu: |
article |
| ISSN: |
0160-4120 |
| DOI: |
10.1016/j.envint.2024.108539 |
| Popis: |
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) outdoor workers > indoor workers > students > the elderly, related to their daily activity time proportion in different exposure scenario. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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Full Text from ScienceDirect