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Quantifying the contribution of activity patterns to PM2.5 exposure inequity between urban and rural residents by a novel method
Wei Du; Zhanpeng Cui; Jinze Wang; Yuqiong Wang; Yungui Li; Xiaoan Li; Yan Zhou; Tao Jiang; Kang Mao; Xianbiao Lin; Jianwu Shi; Dengzhou Gao; Yiming Qin
2024
Source PublicationBuilding Simulation
Volume17Issue:8Pages:1323-1333
Abstract

PM2.5 pollution variations in different microenvironments would result in PM2.5 exposure inequity between rural and urban residents. In this study, the real-time PM2.5 exposure of urban and rural residents in China was examined based on portable PM2.5 sensors together with activity patterns derived from questionnaire surveys, with a focus on students and senior citizens who are sensitive to air pollution. The results showed that PM2.5 exposure varied significantly among different resident groups, with higher PM2.5 exposure of rural residents than those of urban residents. PM2.5 exposure peaks mostly occurred during (Accompanied) cooking activities owing to strong emissions. Sleeping and resting were the main activities that affected PM2.5 exposures of different resident groups, accounting for 60.7%–94.5% of total daily exposures. Furthermore, the long duration of sleeping makes it the predominant activity contributing to PM2.5 exposure inequity. It is necessary to obtain point-to-point respiratory volume (respiratory rate) data when measuring real-time PM2.5 exposure data and incorporate respiratory volume (respiratory rate) into the analysis of PM2.5 exposure. For the first time, this study quantified the PM2.5 exposure inequality based on a novel method and can provide useful information for further studies on the exposure inequity.

DOI10.1007/s12273-024-1166-x
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Indexed ByEI
Language英语
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Document Type期刊论文
Identifierhttp://ir.gyig.ac.cn/handle/42920512-1/15804
Collection环境地球化学国家重点实验室
Affiliation1.Yunnan Provincial Key Laboratory of Soil Carbon Sequestration and Pollution Control, Faculty of Environmental Science & Engineering, Kunming University of Science & Technology, Kunming, 650500, China
2.Laboratory of Earth Surface Processes, College of Urban and Environmental Sciences, Peking University, Beijing, 100871, China
3.Department of Environmental Engineering, Southwest University of Science and Technology, Mianyang, 621010, China
4.NHC Key Laboratory of Nuclear Technology Medical Transformation, Mianyang Central Hospital, School of Medicine, University of Electronic Science and Technology of China, Mianyang, 621000, China
5.State Key Laboratory of Environmental Geochemistry, Institute of Geochemistry, Chinese Academy of Sciences, Guiyang, 550081, China
6.Key Laboratory of Marine Chemistry Theory and Technology, Ministry of Education, Ocean University of China, Qingdao, 266100, China
7.Key Laboratory for Humid Subtropical Eco-Geographical Processes of the Ministry of Education, School of Geographical Sciences, Fujian Normal University, Fuzhou, 350117, China
8.School of Energy and Environment, City University of Hong Kong, Hong Kong, China
Recommended Citation
GB/T 7714
Wei Du,Zhanpeng Cui,Jinze Wang,et al. Quantifying the contribution of activity patterns to PM2.5 exposure inequity between urban and rural residents by a novel method[J]. Building Simulation,2024,17(8):1323-1333.
APA Wei Du.,Zhanpeng Cui.,Jinze Wang.,Yuqiong Wang.,Yungui Li.,...&Yiming Qin.(2024).Quantifying the contribution of activity patterns to PM2.5 exposure inequity between urban and rural residents by a novel method.Building Simulation,17(8),1323-1333.
MLA Wei Du,et al."Quantifying the contribution of activity patterns to PM2.5 exposure inequity between urban and rural residents by a novel method".Building Simulation 17.8(2024):1323-1333.
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