Hodas Natasha, Meng Qingyu, Lunden Melissa M, Turpin Barbara J
Department of Environmental Sciences, Rutgers University, 14 College Farm Rd., New Brunswick, NJ 08901, USA.
School of Public Health, Rutgers University, 683 Hoes Lane West, Piscataway, NJ 08854, USA ; Environmental and Occupational Health Sciences Institute, 170 Frelinghuysen Rd., Piscataway, NJ 08854, USA.
Atmos Environ (1994). 2014 Feb 1;83:229-236. doi: 10.1016/j.atmosenv.2013.11.026.
Because people spend the majority of their time indoors, the variable efficiency with which ambient PM penetrates and persists indoors is a source of error in epidemiologic studies that use PM concentrations measured at central-site monitors as surrogates for ambient PM exposure. To reduce this error, practical methods to model indoor concentrations of ambient PM are needed. Toward this goal, we evaluated and refined an outdoor-to-indoor transport model using measured indoor and outdoor PM species concentrations and air exchange rates from the Relationships of Indoor, Outdoor, and Personal Air Study. Herein, we present model evaluation results, discuss what data are most critical to prediction of residential exposures at the individual-subject and populations levels, and make recommendations for the application of the model in epidemiologic studies. This paper demonstrates that not accounting for certain human activities (air conditioning and heating use, opening windows) leads to bias in predicted residential PM exposures at the individual-subject level, but not the population level. The analyses presented also provide quantitative evidence that shifts in the gas-particle partitioning of ambient organics with outdoor-to-indoor transport contribute significantly to variability in indoor ambient organic carbon concentrations and suggest that methods to account for these shifts will further improve the accuracy of outdoor-to-indoor transport models.
由于人们大部分时间都待在室内，环境颗粒物穿透并留存于室内的效率各不相同，这在流行病学研究中会导致误差，这类研究将中心站点监测器测量的颗粒物浓度用作环境颗粒物暴露的替代指标。为减少这一误差，需要有对环境颗粒物室内浓度进行建模的实用方法。为实现这一目标，我们利用室内、室外颗粒物种类浓度以及来自室内、室外和个人空气关系研究的空气交换率，对一个室外到室内的传输模型进行了评估和优化。在此，我们展示模型评估结果，讨论在个体和人群层面预测住宅暴露时哪些数据最为关键，并就该模型在流行病学研究中的应用提出建议。本文表明，不考虑某些人类活动（使用空调和暖气、开窗）会导致在个体层面预测的住宅颗粒物暴露出现偏差，但在人群层面不会。所呈现的分析还提供了定量证据，即环境有机物在从室外到室内传输过程中气粒分配的变化对室内环境有机碳浓度的变异性有显著贡献，并表明考虑这些变化的方法将进一步提高室外到室内传输模型的准确性。
