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Lu C, Xu H, Meng W, Hou W, Zhang W, Shen G, Cheng H, Wang X, Wang X, Tao S. A novel model for regional indoor PM 2.5 quantification with both external and internal contributions included. ENVIRONMENT INTERNATIONAL 2020; 145:106124. [PMID: 32950792 DOI: 10.1016/j.envint.2020.106124] [Citation(s) in RCA: 14] [Impact Index Per Article: 3.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 06/11/2020] [Revised: 09/05/2020] [Accepted: 09/06/2020] [Indexed: 06/11/2023]
Abstract
PM2.5 (particulate matter with an aerodynamic size ≤ 2.5 μm) of indoor origins is a dominant contributor to the overall air pollution exposure. Although some sophisticated models have been developed to simulate indoor air quality for individual households, it is still challenging to quantify indoor PM2.5 on a regional scale, which is critical for health impact assessments. In this study, a new model was developed to predict indoor PM2.5 concentrations by quantifying the external penetration, as well as the internal contributions. The model was parameterized based on a set of simultaneously measured indoor and outdoor PM2.5 concentrations at five-second temporal resolution for 53 households in Beijing. This study found that indoor PM2.5 concentrations were significantly correlated with those in the outdoor environment with an approximately 1-h lag-time on average. Outdoor-to-indoor penetration dominated the contribution to indoor PM2.5 during polluted hours with relatively high ambient PM2.5 concentrations, while the indoor PM2.5, during clean hours, was contributed by internal sources, including smoking, cooking, incense burning, and human disturbance. The influence of windows, house area, and air purifier use was addressed in the new model. The model was applied to evaluate indoor PM2.5 concentrations in six urban districts of Beijing via an uncertainty analysis. The model was developed based on and applied to households using clean residential energy, and it would be interesting also important to evaluate it in households using solid fuels.
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Affiliation(s)
- Cengxi Lu
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing 100871, China
| | - Haoran Xu
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing 100871, China
| | - Wenjun Meng
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing 100871, China
| | - Weiying Hou
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing 100871, China
| | - Wenxiao Zhang
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing 100871, China
| | - Guofeng Shen
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing 100871, China
| | - Hefa Cheng
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing 100871, China
| | - Xuejun Wang
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing 100871, China
| | - Xilong Wang
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing 100871, China
| | - Shu Tao
- College of Urban and Environmental Sciences, Laboratory for Earth Surface Processes, Sino-French Institute for Earth System Science, Peking University, Beijing 100871, China.
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