Adar Sara D, Davey Mark, Sullivan James R, Compher Michael, Szpiro Adam, Liu L-J Sally
Department of Environmental and Occupational Health Sciences, University of Washington, Seattle, WA 98105.
Atmos Environ (1994). 2008 Oct;42(33):7590-7599. doi: 10.1016/j.atmosenv.2008.06.041.
School buses contribute substantially to childhood air pollution exposures yet they are rarely quantified in epidemiology studies. This paper characterizes fine particulate matter (PM(2.5)) aboard school buses as part of a larger study examining the respiratory health impacts of emission-reducing retrofits.To assess onboard concentrations, continuous PM(2.5) data were collected during 85 trips aboard 43 school buses during normal driving routines, and aboard hybrid lead vehicles traveling in front of the monitored buses during 46 trips. Ordinary and partial least square regression models for PM(2.5) onboard buses were created with and without control for roadway concentrations, which were also modeled. Predictors examined included ambient PM(2.5) levels, ambient weather, and bus and route characteristics.Concentrations aboard school buses (21 mug/m(3)) were four and two-times higher than ambient and roadway levels, respectively. Differences in PM(2.5) levels between the buses and lead vehicles indicated an average of 7 mug/m(3) originating from the bus's own emission sources. While roadway concentrations were dominated by ambient PM(2.5), bus concentrations were influenced by bus age, diesel oxidative catalysts, and roadway concentrations. Cross validation confirmed the roadway models but the bus models were less robust.These results confirm that children are exposed to air pollution from the bus and other roadway traffic while riding school buses. In-cabin air pollution is higher than roadway concentrations and is likely influenced by bus characteristics.
校车是儿童空气污染暴露的重要来源,但在流行病学研究中却很少被量化。作为一项关于减排改造对呼吸健康影响的更大规模研究的一部分,本文对校车上的细颗粒物(PM2.5)进行了特征描述。为评估车内浓度,在43辆校车正常行驶的85趟行程中以及在46趟行程中跟随被监测校车行驶的混合动力先导车辆上,收集了连续的PM2.5数据。建立了有和没有控制道路浓度的校车内PM2.5的普通和偏最小二乘回归模型,同时也对道路浓度进行了建模。所考察的预测因素包括环境PM2.5水平、环境天气以及校车和路线特征。校车内的浓度(21微克/立方米)分别比环境和道路水平高4倍和2倍。校车与先导车辆之间PM2.5水平的差异表明,平均有7微克/立方米来自校车自身的排放源。虽然道路浓度主要受环境PM2.5的影响,但校车浓度受校车使用年限、柴油氧化催化剂和道路浓度的影响。交叉验证证实了道路模型,但校车模型的稳健性较差。这些结果证实,儿童在校车乘车过程中会接触到来自校车和其他道路交通的空气污染。车内空气污染高于道路浓度,并且可能受校车特征的影响。