Identification of Factors Determining Household PM2.5 Variations at Regional Scale and Their Implications for Pollution Mitigation

被引:3
作者
Liu, Xinlei [1 ,2 ]
Li, Yaojie [1 ]
Luo, Zhihan [1 ]
Xing, Ran [1 ]
Men, Yatai [1 ]
Huang, Wenxuan [1 ]
Jiang, Ke [1 ]
Zhang, Lu [1 ]
Sun, Chao [3 ]
Xie, Longjiao [4 ]
Cheng, Hefa [1 ]
Shen, Huizhong [5 ]
Chen, Yuanchen [6 ]
Du, Wei [7 ]
Shen, Guofeng [1 ]
Tao, Shu [1 ]
机构
[1] Peking Univ, Coll Urban & Environm Sci, Lab Earth Surface Proc, Beijing 100871, Peoples R China
[2] Northeast Agr Univ, Key Lab Agr Renewable Resource Utilizat Technol, Harbin 150006, Peoples R China
[3] Shandong Warm Valley New Energy & Environm Protect, Yantai 264001, Peoples R China
[4] Peking Univ, Hlth Sci Ctr, Beijing 100871, Peoples R China
[5] Southern Univ Sci & Technol, Coll Environm Sci & Technol, Shenzhen 518055, Peoples R China
[6] Zhejiang Univ Technol, Coll Environm, Res Ctr Environm Sci, Key Lab Microbial Technol Ind Pollut Control Zheji, Hangzhou 310032, Peoples R China
[7] Kunming Univ Sci & Technol, Fac Environm Sci & Engn, Kunming 650500, Peoples R China
关键词
household air pollution; energy stacking; interhousehold variation; source contribution; biomass pellet; AIR-POLLUTANTS; INDOOR PM2.5; CHINA; IMPACT; FUELS;
D O I
10.1021/acs.est.2c05750
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Indoor PM2.5, particulate matter no more than 2.5 mu m in aerodynamic equivalent diameter, has very high spatiotemporal variabilities; and exploring the key factors influencing the variabilities is critical for purifying air and protecting human health. Here, we conducted a longer-term field monitoring campaign using low-cost sensors and evaluated interand intra-household PM2.5 variations in rural areas where energy or stove stacking is common. Household PM2.5 varied largely across different homes but also within households. Using generalized linear models and dominance analysis, we estimated that outdoor PM2.5 explained 19% of the intrahousehold variation in indoor daily PM2.5, whereas factors like the outdoor temperature and indoor-outdoor temperature difference that was associated with energy use directly or indirectly, explained 26% of the temporal variation. Inter-household variation was lower than intrahousehold variation. The inter-household variation was strongly associated with distinct internal sources, with energy-use-associated factors explaining 35% of the variation. The statistical source apportionment model estimated that solid fuel burning for heating contributed an average of 31%-55% of PM2.5 annually, whereas the contribution of sources originating from the outdoors was & LE;10%. By replacing raw biomass or coal with biomass pellets in gasifier burners for heating, indoor PM2.5 could be significantly reduced and indoor temperature substantially increased, providing thermal comforts in addition to improved air quality.
引用
收藏
页码:3722 / 3732
页数:11
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