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Predicting airborne particle levels aboard Washington State school buses
AbstractSchool buses contribute substantially to childhood air pollution exposures yet they are rarely quantified in epidemiology studies. This paper characterizes fine particulate matter (PM2.5) aboard school buses as part of a larger study examining the respiratory health impacts of emission reducing retrofits.To assess onboard concentrations, continuous PM2.5 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 squares regression models for PM2.5 onboard buses were created with and without control for roadway concentrations, which were also modeled. Predictors examined included ambient PM2.5 levels, ambient weather, and bus and route characteristics.Average concentrations aboard school buses (21μgm−3) were four and two-times higher than ambient and roadway levels, respectively. Differences in PM2.5 levels between the buses and lead vehicles indicated an average of 7μgm−3 originating from the bus's own emission sources. While roadway concentrations were dominated by ambient PM2.5, 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.
Predicting airborne particle levels aboard Washington State school buses
AbstractSchool buses contribute substantially to childhood air pollution exposures yet they are rarely quantified in epidemiology studies. This paper characterizes fine particulate matter (PM2.5) aboard school buses as part of a larger study examining the respiratory health impacts of emission reducing retrofits.To assess onboard concentrations, continuous PM2.5 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 squares regression models for PM2.5 onboard buses were created with and without control for roadway concentrations, which were also modeled. Predictors examined included ambient PM2.5 levels, ambient weather, and bus and route characteristics.Average concentrations aboard school buses (21μgm−3) were four and two-times higher than ambient and roadway levels, respectively. Differences in PM2.5 levels between the buses and lead vehicles indicated an average of 7μgm−3 originating from the bus's own emission sources. While roadway concentrations were dominated by ambient PM2.5, 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.
Predicting airborne particle levels aboard Washington State school buses
Adar, Sara D. (author) / Davey, Mark (author) / Sullivan, James R. (author) / Compher, Michael (author) / Szpiro, Adam (author) / Sally Liu, L.-J. (author)
Atmospheric Environment ; 42 ; 7590-7599
2008-06-06
10 pages
Article (Journal)
Electronic Resource
English
Air pollution , Diesel , School buses , Particulate matter , Traffic , <italic>C</italic><inf>LV</inf> , Lead vehicle or roadway concentrations , <italic>C</italic><inf>bus</inf> , Bus concentrations , <italic>C</italic><inf>self</inf> , Self-pollution concentrations , CV , Cross validation , DOC , Diesel oxidative catalyst , OLS , Ordinary least square , pDR , Personal DataRAM , PLS , Partial least squares , PSCAA , Puget Sound Clean Air Agency , PM<inf>2.5</inf> , Particulate matter with aerodynamic diameter ≤2.5<hsp></hsp>μm , RH , Relative humidity , SSE , Sum square errors , SST , Total sum square error , TWAC , Time weighted average concentration , ULSD , Ultra-low sulfur diesel , UW , University of Washington
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