10th International Aerosol Conference
September 2 - September 7, 2018
America's Center Convention Complex
St. Louis, Missouri, USA

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Comparing Real-Time In-Cabin/Outdoor Particulate and CO Concentrations during Car Commutes along Freeway and Non-Freeway Roads, and Whilst Idling at Traffic Lights, in Saint Louis, MO

ANNA LEAVEY, Nathan Reed, Sameer Patel, Kevin Bradley, Pramod Kulkarni, Pratim Biswas, Washington University in St Louis

Abstract Number: 389
Working Group: Aerosol Exposure

Abstract
Exposure to urban air pollution is associated with detrimental health effects and increased morbidity and mortality¹. In developed countries, traffic emissions contribute 25-40% to urban air pollution, and as much as 90% for specific pollutants such as carbon monoxide (CO) and ultrafine particles². An individual may therefore receive a disproportionately high amount of their daily exposure whilst traveling along roads. In the US, 91% of commuters travel to and from work by car. In fact, Missouri car drivers have experienced a 37% increase in the vehicle miles traveled between 1990 and 2013; this is set to increase another 20% by 2030^3,4.

Real-time simultaneous particulate (PM_2.5, lung-deposited surface area (SA), PNC) and gaseous (CO) concentrations were collected outside and inside of an on-road car operating with either windows open or closed, fan on or AC on, during 54 real commutes to and from Washington University in St. Louis. Commutes were then split into: 1) 16 non-freeway (NFW) roads (N = 249); 2) 2 freeways (FW) (N = 84); 3) idling/accelerating from traffic lights (N= 242); 4) following a bus or other high-polluter. The influence of road-type, traffic density, vehicle speed, lane position, and lead vehicle on both outdoor and in-cabin pollution was examined using linear mixed-effects models and ANOVA regression. The aim was to identify ways to minimize in-cabin exposure without modifying the outdoor pollutant environment.

Higher outdoor pollutant concentrations were measured on FWs compared to NFWs (b = 0.39-0.55; p-value <0.01) due to higher densities of vehicles and trucks, although correlations were complicated by vehicle speed. Higher PM_2.5 concentrations were observed whilst traveling on the slow and middle lanes of a FW compared to the fast lane (b = 1.35; b = 1.42; p-values = <0.01), and whilst following a truck (b = 0.034). Decreasing outdoor PNC and lung-deposited SA concentrations were observed on NFWs with decreasing traffic densities, and results suggest a small percentage of “gross-polluters” may be largely responsible for the measured CO concentrations. Outdoor concentrations were the strongest predictors of cabin concentrations (adj-R² values of 0.30-0.95), especially on FWs, although having the windows closed or the AC on produced a protective effect, reducing the infiltration of outdoor particles into the vehicle thus reducing commuter exposure. The ventilation variable influenced PNC the most (R² = 0.06), and CO the least.

Significantly higher outdoor pollutant concentrations were measured during acceleration compared to idling (>8%-17%), but may depend on the vehicle’s position in the idling line, for example, lower outdoor PNC were observed when the vehicle was accelerating from the front of the line versus further back (b = -0.220, p-value = 0.09), supporting transport policies that reduce wait times at traffic lights. Finally, elevated pollutant concentrations were measured whilst following school buses. Transport planners and commuters may mitigate exposures by adjusting traffic-light times, routes traveled, avoiding heavy polluters, and applying a dynamic approach to ventilation choice.

1. Dockery, D.W., et al., An Association between Air Pollution and Mortality in Six U.S. Cities. England Journal of Medicine, 1993. 329(24): p. 1753 – 1759.
2. Keuken, M., et al., Contribution of traffic to levels of ambient air pollution in Europe, in Health effects of transport-related air pollution. WHO. , M. Krzyzanowski, B. Kuna-Dibbert, and J. Schneider, Editors. 2005, WHO Library Cataloguing in Publication Data. p. 53-80.
3. US Department of Transport. Summary of Travel Trends: 2009.
4. TRIP. Missouri Transportation by the Numbers: Meeting the State's Need for Safe and Efficient Mobility. 2015. http://tripnet.org/docs/MO_Transportation_by_the_Numbers_TRIP_Report_April_2015.pdf