Zhaowen Qiu 1 , Huihui Cao 1 Show Affiliations »
Abstract
PURPOSE: To investigate commuter exposures to particulate matter (PM) in urban public transportation buses and subways, PM concentrations were simultaneously monitored for these two modes, over the same routes, in Xi'an, China. METHODS: The microenvironment variabilities in each stage of the total trip were analyzed. Exposure doses for the different commute processes were estimated based on the heart rates of volunteers. Experimental measurements were taken during peak traffic hours in July and October (summer and autumn) on two typical commute routes, for a total of 36 trips. One-way ANOVA was used to analyze the effects of different variables on commuter exposures. RESULTS: On the same route, the average PM exposure concentration of bus commuters was higher than those of subway commuters. For example, on Route 1 in the case study, the average PM10, PM2.5, and PM1 exposure concentrations of bus commuters were 71.6%, 19%, and 10.4% higher, respectively, than those of subway commuters. In the ground transportation mode, the exposure concentration of bus commuters was affected by the type of vehicle. Particle concentrations were significantly higher inside compressed natural gas (CNG) buses, than in pure electric (PE) buses, and in summer, the PM10 concentration in a CNG bus was 4.3 times higher than that in a PE bus. In a CNG bus, commuters in the back door area suffered the highest PM10 exposure concentration (179.6 μg/m3), followed by those in the rear of the carriage (142.8 μg/m3), and then those in the front door area (105.4 μg/m3). CONCLUSION: Commuters' avoidance of ground traffic sources, effective ventilation systems in buses, and the use of screens in subway systems can all help to lower the PM exposure of commuters. For all the modes of transportation in our study, the hottest spots for PM exposure appeared in the period when commuters were waiting for transit vehicles to arrive. © Springer Nature Switzerland AG 2020.
PURPOSE: To investigate commuter exposures to particulate matter (PM) in urban public transportation buses and subways, PM concentrations were simultaneously monitored for these two modes, over the same routes, in Xi'an, China. METHODS: The microenvironment variabilities in each stage of the total trip were analyzed. Exposure doses for the different commute processes were estimated based on the heart rates of volunteers. Experimental measurements were taken during peak traffic hours in July and October (summer and autumn) on two typical commute routes, for a total of 36 trips. One-way ANOVA was used to analyze the effects of different variables on commuter exposures. RESULTS: On the same route, the average PM exposure concentration of bus commuters was higher than those of subway commuters. For example, on Route 1 in the case study, the average PM10, PM2.5, and PM1 exposure concentrations of bus commuters were 71.6%, 19%, and 10.4% higher, respectively, than those of subway commuters. In the ground transportation mode, the exposure concentration of bus commuters was affected by the type of vehicle. Particle concentrations were significantly higher inside compressed natural gas (CNG) buses, than in pure electric (PE) buses, and in summer, the PM10 concentration in a CNG bus was 4.3 times higher than that in a PE bus. In a CNG bus, commuters in the back door area suffered the highest PM10 exposure concentration (179.6 μg/m3), followed by those in the rear of the carriage (142.8 μg/m3), and then those in the front door area (105.4 μg/m3). CONCLUSION: Commuters' avoidance of ground traffic sources, effective ventilation systems in buses, and the use of screens in subway systems can all help to lower the PM exposure of commuters. For all the modes of transportation in our study, the hottest spots for PM exposure appeared in the period when commuters were waiting for transit vehicles to arrive. © Springer Nature Switzerland AG 2020.
Entities: Chemical
Keywords:
Bus; Commuter exposure; Inhaled dose; PM concentration; Subway; Traffic micro-environment
Year: 2020
PMID： 33312574 PMCID： PMC7721829 DOI： 10.1007/s40201-020-00473-0
Source DB: PubMed Journal: J Environ Health Sci Eng