AAAR 35th Annual Conference October 17 - October 21, 2016 Oregon Convention Center Portland, Oregon, USA
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Characterization of Traffic Emissions Exposure Metrics in the Dorm Room Inhalation to Vehicle Emissions (DRIVE) Study
JENNIFER L. MOUTINHO, Donghai Liang, Karoline Johnson, Rachel Golan, Chandresh Ladva, Roby Greenwald, Rodney J. Weber, Stefanie Ebelt Sarnat, Vishal Verma, Dean Jones, Jeremy Sarnat, Armistead G. Russell, Georgia Institute of Technology
Abstract Number: 62 Working Group: Urban Aerosols
Abstract Detailed measurements and dispersion modeling was conducted to develop more accurate integrated or biologically-relevant metrics to assess exposure to potentially high pollutant levels of primary traffic emissions. A 13-week intensive sampling campaign was conducted at six ambient and two indoor monitoring sites surrounding the busiest highway segment in the US with the study area focusing on the Georgia Institute of Technology campus. Fifty-four college students living in dorms near (20 m) or far (1.4 km) from the highway were recruited for personal exposure monitor sampling and biomonitoring, which included saliva and blood sampling. Traffic-related contaminant indicators selected to capture the heterogeneity of primary traffic emissions were measured at each site, including particle mass and number, elemental and organic carbon, nitrogen oxides, and carbon monoxide. Dispersion models, RLINE and AERMOD, were used to develop spatial concentration fields at a 250m resolution over the Atlanta area and a 25 m resolution over the area of primary exposures. Initial RLINE results were biased, due either to errors in the emissions or the model. Analysis suggests that both may be important, depending upon species. Both the measurement observations and dispersion modeling results show that the highway has a substantial impact on primary traffic pollutant (particularly elemental carbon and carbon monoxide) concentrations and capture the prominent spatial gradients across the Georgia Tech campus, though the gradients were highly species dependent. Results were further used to develop an overall indicator of exposure to traffic related emissions for use in health assessments. In addition to quantifying a multipollutant traffic exposure indicator, metabolic response was evaluated by finding elevated levels of specific metabolites in plasma samples. These results were used to identify which exposure metrics are most predictive of biologically-relevant responses to primary traffic exposures that could be used for large panel-based epidemiologic studies.