Determinants of Indoor and Personal Exposure to PM(2.5) of Indoor and Outdoor Origin during the RIOPA Study.
Determinants of Indoor and Personal Exposure to PM(2.5) of Indoor and Outdoor Origin during the RIOPA Study.
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DOI：
10.1016/j.atmosenv.2009.07.066
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发表时间：
2009-11
影响因子：
5
通讯作者：
Turpin, Barbara
中科院分区：
文献类型：
--
作者：
Meng, Qing Yu;Spector, Dalia;Colome, Steven;Turpin, Barbara
研究了物理/环境因素对细颗粒物（PM2.5）暴露、室外至室内迁移和空气交换率（AER）的影响。室内环境PM2.5的发现分数（FINF）和人们暴露的分数（α）改变了个人对环境PM2.5的暴露。由于FINF、α和AER很少被测量，一些人使用空调（AC）作为环境PM2.5暴露的调节剂。我们发现没有单一的变量可以很好地预测AER。FINF和α的变化分别有50%和40%可以用AER和其他活性变量来解释。仅AER就分别解释了36%和24%的FINF和α的变化。其他的预测因子，包括中央空调操作，占了不到4%的变化。这突出了AER测量对预测FINF和α的重要性。现有的证据表明，室外温度和家庭通风特征影响颗粒损失和AER，并且影响不同。利用个人活动和微环境方法重建个人暴露于PM2.5质量/种类的总量，并与直接个人测量结果进行比较。室外浓度是PM2.5质量和大多数物种室内和个人暴露的主要预测因子（偏R2 = 30-70%）和最大贡献者（20-90%）。对于少数暴露于或从事这些活动的研究参与者来说，一些活动（包括吸烟和木工）对个人PM2.5质量/种类暴露产生了巨大影响。在室外PM2.5的基础上加入个人活动，提高了个人活动模型对PM2.5质量/种类的预测能力；需要更多关于个人活动和室内来源的详细信息，以进一步改进（特别是Ca， K， OC）。充分考虑颗粒在室内的渗透和持久性以及接触非环境源，可能会增强将健康影响与颗粒接触联系起来的流行病学分析的能力。
Effects of physical/environmental factors on fine particle (PM2.5) exposure, outdoor-to-indoor transport and air exchange rate (AER) were examined. The fraction of ambient PM2.5 found indoors (FINF) and the fraction to which people are exposed (α) modify personal exposure to ambient PM2.5. Because FINF, α, and AER are infrequently measured, some have used air conditioning (AC) as a modifier of ambient PM2.5 exposure. We found no single variable that was a good predictor of AER. About 50% and 40% of the variation in FINF and α, respectively, was explained by AER and other activity variables. AER alone explained 36% and 24% of the variations in FINF and α, respectively. Each other predictor, including Central AC Operation, accounted for less than 4% of the variation. This highlights the importance of AER measurements to predict FINF and α. Evidence presented suggests that outdoor temperature and home ventilation features affect particle losses as well as AER, and the effects differ. Total personal exposures to PM2.5 mass/species were reconstructed using personal activity and microenvironmental methods, and compared to direct personal measurement. Outdoor concentration was the dominant predictor of (partial R2 = 30–70%) and the largest contributor to (20–90%) indoor and personal exposures for PM2.5 mass and most species. Several activities had a dramatic impact on personal PM2.5 mass/species exposures for the few study participants exposed to or engaged in them, including smoking and woodworking. Incorporating personal activities (in addition to outdoor PM2.5) improved the predictive power of the personal activity model for PM2.5 mass/species; more detailed information about personal activities and indoor sources is needed for further improvement (especially for Ca, K, OC). Adequate accounting for particle penetration and persistence indoors and for exposure to non-ambient sources could potentially increase the power of epidemiological analyses linking health effects to particulate exposures.
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DOI：
10.1097/ede.0b013e3181812bb7
发表时间：
2008-09
期刊：
Epidemiology (Cambridge, Mass.)
影响因子：
--
作者：
Franklin M;Koutrakis P;Schwartz P
通讯作者：
Schwartz P
影响因子：
5
作者：
Lunden, MM;Revzan, KL;Brown, NJ
通讯作者：
Brown, NJ
影响因子：
11.4
作者：
Meng, Qing Yu;Turpin, Barbara J.;Winer, Arthur
通讯作者：
Winer, Arthur
DOI：
10.1038/sj.jea.7500229
发表时间：
2002-07-01
期刊：
JOURNAL OF EXPOSURE ANALYSIS AND ENVIRONMENTAL EPIDEMIOLOGY
影响因子：
--
作者：
Wallace, LA;Emmerich, SJ;Howard-Reed, C
通讯作者：
Howard-Reed, C
DOI：
10.1038/sj.jes.7500532
发表时间：
2007-08-01
影响因子：
4.5
作者：
Baxter, Lisa K.;Clougherty, Jane E.;Levy, Jonathan I.
通讯作者：
Levy, Jonathan I.