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Traffic-related air emissions in Houston: Effects of light-rail transit

Park, Eun Sug, Sener, Ipek Nese
The Science of the total environment 2019 v.651 pp. 154-161
BTEX (benzene, toluene, ethylbenzene, xylene), air, air pollution, air quality, automobiles, benzene, carbon monoxide, data collection, emissions, ethylbenzene, infrastructure, monitoring, time series analysis, toluene, traffic, weather, xylene
Recent studies have suggested that automobile pollution poses significantly more harmful health impacts than previously realized. Light-rail transit (LRT) is a major type of transportation infrastructure, but there has been little research assessing the air quality effects of LRT based on the actual air pollution data. This study aimed to assess the effects of LRT on automobile-related air emissions in Houston. Specifically, we examined the effects of LRT on key tailpipe pollutants-carbon monoxide and acetylene-as well as other traffic pollution surrogates referred to as BTEX (benzene, toluene, ethylbenzene, and xylene), measured from ambient air monitoring stations.An interrupted time series design and analysis was used to determine the impact of an intervention, where the intervention was the opening of an LRT on January 1, 2004, with two years (2002−2003) of before and two years (2004–2005) of after period data. We found that, after controlling for weather, the opening of the LRT was associated with statistically significant reductions in traffic-related air emissions. Specifically, at the exposure sites, the daily maximum carbon monoxide level was reduced roughly by 24%, and the daily level of toluene was reduced roughly by 60% (33% after accounting for the reduction at the comparison site). Our findings lend support to the air quality benefits of LRT by providing suggestive evidence of positive effects of LRT based on actual air pollution monitoring data. This study's findings also emphasize the importance of developing effective measures to assess traffic-related pollution and call for advanced data collection strategies of additional data, including traffic volume and speed data.