Characterising personal, household, and community PM2.5 exposure in one urban and two rural communities in China
Characterising personal, household, and community PM2.5 exposure in one urban and two rural communities in China
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描述中国一个城市和两个农村社区的个人、家庭和社区 PM2.5 暴露特征
DOI：
10.1101/2023.04.10.23288228
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发表时间：
2023
期刊：
影响因子：
--
通讯作者：
Chan K
中科院分区：
文献类型：
--
作者：
Chan K
背景家庭中的烹饪和取暖对全世界的空气污染有重要影响。但对实测细颗粒物调查不足（PM2.5）暴露水平、变异性、季节性和与这些行为相关的空间动态。（厨房和客厅），和社区PM2.5的夏季（2017年5月至9月）和冬季（2017年11月至2018年1月）在中国的一个城市和两个农村社区的477名参与者。经过严格的数据清理后，每个微环境有67，326 - 80，980人-小时（ntotal= 441; nsummer= 384; nwinter= 364; 307人在两个季节都有重复的PM2.5数据）的处理数据。年龄和性别调整的PM2.5的几何平均值计算的关键参与者的特征，整体和季节。斯皮尔曼相关系数之间的PM2.5水平在不同的微environments.FindingsOverall，26.4%的报告使用固体燃料做饭和取暖。固体燃料使用者的个人和厨房24小时平均PM2.5暴露量比清洁燃料使用者高92%。同样，从夏季到冬季，他们的个人和家庭PM2.5也有更大的增加（83%对26%），而不同燃料类别的PM2.5社区水平在冬季高出2-4倍。与清洁燃料使用者相比，固体燃料使用者的个人PM2.5加权年平均暴露量显著高于清洁燃料使用者，（78.2 [95% CI 71.6-85.3] μg/m3 vs 41.6 [37.3-46.5] μg/m3），厨房（102.4 [90.4-116.0] μg/m3 vs 52.3 [44.8-61.2] μg/m3）和客厅（62.1 [57.3-67.3] μg/m3 vs 41.0 [37.1-45.3] μg/m3）微环境。不同微环境中PM2. 5暴露量的日变化显著，5 min移动平均值在10 μg/m3 ~ 700 ~ 1200 μg/m3之间。个人PM2.5与居室环境中度相关（斯皮尔曼r：0.64-0.66）和厨房（0.52-0.59）水平，但与群落水平的相关性较弱，尤其是在夏天（0.15-0.34）和固体燃料用户（0.11-0.31）。结论与清洁燃料使用者相比，使用固体燃料做饭和取暖与个人和家庭PM2.5暴露量高得多有关。家庭PM2.5似乎比社区PM2.5更好地代表个人暴露。
BackgroundCooking and heating in households contribute importantly to air pollution exposure worldwide. However, there is insufficient investigation of measured fine particulate matter (PM2.5) exposure levels, variability, seasonality, and inter-spatial dynamics associated with these behaviours.MethodsWe undertook parallel measurements of personal, household (kitchen and living room), and community PM2.5in summer (May–September 2017) and winter (November 2017-Janauary 2018) in 477 participants from one urban and two rural communities in China. After stringent data cleaning, there were 67,326–80,980 person-hours (ntotal= 441; nsummer= 384; nwinter= 364; 307 had repeated PM2.5data in both seasons) of processed data per microenvironment. Age- and sex-adjusted geometric means of PM2.5were calculated by key participant characteristics, overall and by season. Spearman correlation coefficients between PM2.5levels across different microenvironments were computed.FindingsOverall, 26.4 % reported use of solid fuel for both cooking and heating. Solid fuel users had 92 % higher personal and kitchen 24-h average PM2.5exposure than clean fuel users. Similarly, they also had a greater increase (83 % vs 26 %) in personal and household PM2.5from summer to winter, whereas community levels of PM2.5were 2–4 times higher in winter across different fuel categories. Compared with clean fuel users, solid fuel users had markedly higher weighted annual average PM2.5exposure at personal (78.2 [95 % CI 71.6–85.3] μg/m3vs 41.6 [37.3–46.5] μg/m3), kitchen (102.4 [90.4–116.0] μg/m3vs 52.3 [44.8–61.2] μg/m3) and living room (62.1 [57.3–67.3] μg/m3vs 41.0 [37.1–45.3] μg/m3) microenvironments. There was a remarkable diurnal variability in PM2.5exposure among the participants, with 5-min moving average from 10 μg/m3to 700–1200 μg/m3across different microenvironments. Personal PM2.5was moderately correlated with living room (Spearman r: 0.64–0.66) and kitchen (0.52–0.59) levels, but only weakly correlated with community levels, especially in summer (0.15–0.34) and among solid fuel users (0.11–0.31).ConclusionSolid fuel use for cooking and heating was associated with substantially higher personal and household PM2.5exposure than clean fuel users. Household PM2.5appeared a better proxy of personal exposure than community PM2.5.
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DOI：
10.3390/s17081879
发表时间：
2017-08-16
期刊：
Sensors (Basel, Switzerland)
影响因子：
--
作者：
Pillarisetti A;Allen T;Ruiz-Mercado I;Edwards R;Chowdhury Z;Garland C;Hill LD;Johnson M;Litton CD;Lam NL;Pennise D;Smith KR
通讯作者：
Smith KR
空气污染对公众健康的影响
DOI：
--
发表时间：
2020
期刊：
影响因子：
--
作者：
K. Chan;Katherine Newell;K. H. Lam
通讯作者：
K. H. Lam
影响因子：
11.8
作者：
Shupler, Matthew;Hystad, Perry;Brauer, Michael
通讯作者：
Brauer, Michael
基于生物学的流行病学暴露评估
DOI：
--
发表时间：
2013
期刊：
影响因子：
--
作者：
Thomas J. Smith;D. Kriebel
通讯作者：
D. Kriebel
影响因子：
11.8
作者：
Snider G;Carter E;Clark S;Tseng JTW;Yang X;Ezzati M;Schauer JJ;Wiedinmyer C;Baumgartner J
通讯作者：
Baumgartner J