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Sarnat JA, Russell A, Liang D, et al. Developing Multipollutant Exposure Indicators of Traffic Pollution: The Dorm Room Inhalation to Vehicle Emissions (DRIVE) Study. Res Rep Health Eff Inst. 2018;(196):3-75
Sarnat, J. A., Russell, A., Liang, D., Moutinho, J. L., Golan, R., Weber, R. J., Gao, D., Sarnat, S. E., Chang, H. H., Greenwald, R., & Yu, T. (2018). Developing Multipollutant Exposure Indicators of Traffic Pollution: The Dorm Room Inhalation to Vehicle Emissions (DRIVE) Study. Research report (Health Effects Institute), (196), 3-75.
Sarnat, J A, et al. "Developing Multipollutant Exposure Indicators of Traffic Pollution: The Dorm Room Inhalation to Vehicle Emissions (DRIVE) Study." Research report (Health Effects Institute) vol. ,196 (2018): 3-75.
Sarnat JA, Russell A, Liang D, Moutinho JL, Golan R, Weber RJ, Gao D, Sarnat SE, Chang HH, Greenwald R, Yu T. Developing Multipollutant Exposure Indicators of Traffic Pollution: The Dorm Room Inhalation to Vehicle Emissions (DRIVE) Study. Res Rep Health Eff Inst. 2018 Apr;(196):3-75. PMID: 31872750.
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Res Rep Health Eff Inst. 2018 Apr;(196):3-75.

Developing Multipollutant Exposure Indicators of Traffic Pollution: The Dorm Room Inhalation to Vehicle Emissions (DRIVE) Study.

Research report (Health Effects Institute)

J A Sarnat, A Russell, D Liang, J L Moutinho, R Golan, R J Weber, D Gao, S E Sarnat, H H Chang, R Greenwald, T Yu

Affiliations

  1. Department of Environmental Health, Rollins School of Public Health of Emory University, Atlanta, Georgia.
  2. School of Civil and Environmental Engineering, Georgia Institute of Technology, Atlanta.
  3. Department of Epidemiology, Ben Gurion University of the Negev, Beer-Sheva, Israel.
  4. Department of Biostatistics and Bioinformatics, Rollins School of Public Health, Emory University, Atlanta, Georgia.
  5. Department of Environmental Health, Georgia State University, Atlanta.

PMID: 31872750

Abstract

INTRODUCTION: The Dorm Room Inhalation to Vehicle Emissions (DRIVE

METHODS: Intensive field sampling was conducted on the campus of the Georgia Institute of Technology (GIT) between September 2014 and January 2015 at 8 monitoring sites (2 indoors and 6 outdoors) ranging from 5 m to 2.3 km from the busiest and most congested highway artery in Atlanta. In addition, 54 GIT students living in one of two dormitories either near (20 m) or far (1.4 km) from the highway were recruited to conduct personal exposure sampling and weekly biomonitoring. The pollutants measured were selected to provide information about the heterogeneous particulate and gaseous composition of primary traffic emissions, including the traditional traffic-related species (e.g., carbon monoxide [CO], nitrogen dioxide [NO

RESULTS: Pollutant levels measured during the study showed a low impact by this highway hotspot source on its surrounding vicinity. These findings are broadly consistent with results from other studies throughout North America showing decreased relative contributions to urban air pollution from primary traffic emissions. We view these reductions as an indication of a changing near-road environment, facilitated by the effectiveness of mobile source emission controls. Many of the primary pollutant species, including NO, CO, and BC, decreased to near background levels by 20 to 30 m from the highway source. Patterns of correlation among the sites also varied by pollutant and time of day. NO

CONCLUSIONS: An immediate implication of the changing near-road environment is that future studies aimed at characterizing hotspots related to mobile sources and their impacts on health will need to consider multiple approaches for characterizing spatial gradients and exposures. Specifically and most directly, the mobile source contributions to ambient concentrations of single-pollutant indicators of traffic exposure are not as distinguishable to the degree that they have been in the past. Collectively, the study suggests that characterizing exposures to traffic-related pollutants, which is already difficult, will become more difficult because of the reduction in traffic-related emissions. Additional multi-tiered approaches should be considered along with traditional measurements, including the use of alternative OP measures beyond those based on DTT assays, metabolomics, low-cost sensors, and air quality modeling.

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