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Evaluation of Traffic Density Parameters as an Indicator of Vehicle Emission-Related Near-Road Air Pollution: A Case Study with NEXUS Measurement Data on Black Carbon

Author

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  • Shi V. Liu

    (National Exposure Research Laboratory, Office of Research and Development, U. S. Environmental Protection Agency, Durham, NC 27711, USA)

  • Fu-Lin Chen

    (National Exposure Research Laboratory, Office of Research and Development, U. S. Environmental Protection Agency, Durham, NC 27711, USA)

  • Jianping Xue

    (National Exposure Research Laboratory, Office of Research and Development, U. S. Environmental Protection Agency, Durham, NC 27711, USA)

Abstract

An important factor in evaluating health risk of near-road air pollution is to accurately estimate the traffic-related vehicle emission of air pollutants. Inclusion of traffic parameters such as road length/area, distance to roads, and traffic volume/intensity into models such as land use regression (LUR) models has improved exposure estimation. To better understand the relationship between vehicle emissions and near-road air pollution, we evaluated three traffic density-based indices: Major-Road Density (MRD), All-Traffic Density (ATD) and Heavy-Traffic Density (HTD) which represent the proportions of major roads, major road with annual average daily traffic (AADT), and major road with commercial annual average daily traffic (CAADT) in a buffered area, respectively. We evaluated the potential of these indices as vehicle emission-specific near-road air pollutant indicators by analyzing their correlation with black carbon (BC), a marker for mobile source air pollutants, using measurement data obtained from the Near-road Exposures and Effects of Urban Air Pollutants Study (NEXUS). The average BC concentrations during a day showed variations consistent with changes in traffic volume which were classified into high, medium, and low for the morning rush hours, the evening rush hours, and the rest of the day, respectively. The average correlation coefficients between BC concentrations and MRD, ATD, and HTD, were 0.26, 0.18, and 0.48, respectively, as compared with −0.31 and 0.25 for two commonly used traffic indicators: nearest distance to a major road and total length of the major road. HTD, which includes only heavy-duty diesel vehicles in its traffic count, gives statistically significant correlation coefficients for all near-road distances (50, 100, 150, 200, 250, and 300 m) that were analyzed. Generalized linear model (GLM) analyses show that season, traffic volume, HTD, and distance from major roads are highly related to BC measurements. Our analyses indicate that traffic density parameters may be more specific indicators of near-road BC concentrations for health risk studies. HTD is the best index for reflecting near-road BC concentrations which are influenced mainly by the emissions of heavy-duty diesel engines.

Suggested Citation

  • Shi V. Liu & Fu-Lin Chen & Jianping Xue, 2017. "Evaluation of Traffic Density Parameters as an Indicator of Vehicle Emission-Related Near-Road Air Pollution: A Case Study with NEXUS Measurement Data on Black Carbon," IJERPH, MDPI, vol. 14(12), pages 1-11, December.
    • Handle: RePEc:gam:jijerp:v:14:y:2017:i:12:p:1581-:d:123097
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    References listed on IDEAS

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    1. Vlad Isakov & Saravanan Arunachalam & Stuart Batterman & Sarah Bereznicki & Janet Burke & Kathie Dionisio & Val Garcia & David Heist & Steve Perry & Michelle Snyder & Alan Vette, 2014. "Air Quality Modeling in Support of the Near-Road Exposures and Effects of Urban Air Pollutants Study (NEXUS)," IJERPH, MDPI, vol. 11(9), pages 1-17, August.
    2. Dreher, David B. & Harley, Robert A., 1998. "A Fuel-Based Inventory for Heavy-Duty Diesel Truck Emissions," University of California Transportation Center, Working Papers qt46t948fp, University of California Transportation Center.
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    1. Raoul S. Liévanos, 2018. "Retooling CalEnviroScreen: Cumulative Pollution Burden and Race-Based Environmental Health Vulnerabilities in California," IJERPH, MDPI, vol. 15(4), pages 1-26, April.

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