Meng Qing Yu, Spector Dalia, Colome Steven, Turpin Barbara
Research Fellow at National Center for Environmental Assessment, Office of Research and Development, US EPA, Research Triangle Park, NC 27711, USA.
Atmos Environ (1994). 2009 Nov;43(36):5750-5758. doi: 10.1016/j.atmosenv.2009.07.066.
Effects of physical/environmental factors on fine particle (PM(2.5)) exposure, outdoor-to-indoor transport and air exchange rate (AER) were examined. The fraction of ambient PM(2.5) found indoors (F(INF)) and the fraction to which people are exposed (alpha) modify personal exposure to ambient PM(2.5). Because F(INF), alpha, and AER are infrequently measured, some have used air conditioning (AC) as a modifier of ambient PM(2.5) exposure. We found no single variable that was a good predictor of AER. About 50% and 40% of the variation in F(INF) and alpha, respectively, was explained by AER and other activity variables. AER alone explained 36% and 24% of the variations in F(INF) and alpha, 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 F(INF) and alpha. 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 PM(2.5) mass/species were reconstructed using personal activity and microenvironmental methods, and compared to direct personal measurement. Outdoor concentration was the dominant predictor of (partial R(2) = 30-70%) and the largest contributor to (20-90%) indoor and personal exposures for PM(2.5) mass and most species. Several activities had a dramatic impact on personal PM(2.5) 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 PM(2.5)) improved the predictive power of the personal activity model for PM(2.5) 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.
研究了物理/环境因素对细颗粒物（PM(2.5)）暴露、室外到室内传输以及空气交换率（AER）的影响。室内发现的环境PM(2.5)比例（F(INF)）以及人们暴露的比例（α）会改变个人对环境PM(2.5)的暴露。由于F(INF)、α和AER很少被测量，一些人将空调（AC）用作环境PM(2.5)暴露的调节因素。我们没有发现单一变量能很好地预测AER。F(INF)和α变化的约50%和40%分别由AER和其他活动变量解释。仅AER就分别解释了F(INF)和α变化的36%和24%。包括中央空调运行在内的其他每个预测因素占变化的比例均小于4%。这凸显了测量AER对预测F(INF)和α的重要性。所提供的证据表明，室外温度和家庭通风特征会影响颗粒物损失以及AER，且影响有所不同。使用个人活动和微环境方法重建了个人对PM(2.5)质量/成分的总暴露，并与直接个人测量结果进行比较。室外浓度是（偏R(2)=30 - 70%）的主要预测因素，也是PM(2.5)质量和大多数成分的室内和个人暴露的最大贡献者（20 - 90%）。对于少数接触或参与其中的研究参与者，一些活动对个人PM(2.5)质量/成分暴露有显著影响，包括吸烟和木工。纳入个人活动（除了室外PM(2.
