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Hou W, Wang J, Hu R, Chen Y, Shi J, Lin X, Qin Y, Zhang P, Du W, Tao S. Systematically quantifying the dynamic characteristics of PM 2.5 in multiple indoor environments in a plateau city: Implication for internal contribution. ENVIRONMENT INTERNATIONAL 2024; 186:108641. [PMID: 38621323 DOI: 10.1016/j.envint.2024.108641] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/23/2023] [Revised: 04/04/2024] [Accepted: 04/08/2024] [Indexed: 04/17/2024]
Abstract
People generally spend most of their time indoors, making a comprehensive evaluation of air pollution characteristics in various indoor microenvironments of great significance for accurate exposure estimation. In this study, field measurements were conducted in Kunming City, Southwest China, using real-time PM2.5 sensors to characterize indoor PM2.5 in ten different microenvironments including three restaurants, four public places, and three household settings. Results showed that the daily average PM2.5 concentrations in restaurants, public spaces, and households were 78.4 ± 24.3, 20.1 ± 6.6, and 18.0 ± 4.3 µg/m3, respectively. The highest levels of indoor PM2.5 in restaurants were owing to strong internal emissions from cooking activities. Dynamic changes showed that indoor PM2.5 levels increased during business time in restaurants and public places, and cooking time in residential kitchens. Compared with public places, restaurants generally exhibit more rapid increases in indoor PM2.5 due to cooking activities, which can elevate indoor PM2.5 to high levels (5.1 times higher than the baseline) in a short time. Furthermore, indoor PM2.5 in restaurants were dominated by internal emissions, while outdoor penetration contributed mostly to indoor PM2.5 in public places and household settings. Results from this study revealed large variations in indoor PM2.5 in different microenvironments, and suggested site-specific measures for indoor PM2.5 pollution alleviation.
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Affiliation(s)
- Weiying Hou
- Yunnan Provincial Key Laboratory of Soil Carbon Sequestration and Pollution Control, Faculty of Environmental Science & Engineering, Kunming University of Science &Technology, Kunming 650500, China
| | - Jinze Wang
- Laboratory of Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
| | - Ruijing Hu
- Yunnan Provincial Key Laboratory of Soil Carbon Sequestration and Pollution Control, Faculty of Environmental Science & Engineering, Kunming University of Science &Technology, Kunming 650500, China; Southwest United Graduate School, Kunming 650092, China
| | - Yuanchen Chen
- Key Laboratory of Microbial Technology for Industrial Pollution Control of Zhejiang Province, College of Environment, Zhejiang University of Technology, Hangzhou, Zhejiang 310032, China
| | - Jianwu Shi
- Faculty of Environmental Science & Engineering, Kunming University of Science &Technology, Kunming 650500, China
| | - Xianbiao Lin
- Key Laboratory of Marine Chemistry Theory and Technology, Ministry of Education, Ocean University of China, Qingdao 266100, China
| | - Yiming Qin
- School of Energy and Environment, City University of Hong Kong, Hong Kong SAR 999077, China
| | - Peng Zhang
- Yunnan Provincial Key Laboratory of Soil Carbon Sequestration and Pollution Control, Faculty of Environmental Science & Engineering, Kunming University of Science &Technology, Kunming 650500, China
| | - Wei Du
- Yunnan Provincial Key Laboratory of Soil Carbon Sequestration and Pollution Control, Faculty of Environmental Science & Engineering, Kunming University of Science &Technology, Kunming 650500, China.
| | - Shu Tao
- Laboratory of Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing 100871, China
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