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Time allocation shifts and pollutant exposure due to traffic congestion: an analysis using the national human
Kai Zhang1, Stuart A Batterman
1Environmental Health Sciences, University of Michigan, Ann Arbor, MI 48109-2029, USA.
Abstract:
Traffic congestion increases air pollutant exposures of commuters and urban populations due to the increased time spent in traffic and the increased vehicular emissions that occur in congestion, especially "stop-and-go" traffic. Increased time in traffic also decreases time in other microenvironments, a trade-off that has not been considered in previous time activity pattern (TAP) analyses conducted for exposure assessment purposes. This research investigates changes in time allocations and exposures that result from traffic congestion. Time shifts were derived using data from the National Human Activity Pattern Survey (NHAPS), which was aggregated to nine microenvironments (six indoor locations, two outdoor locations and one transport location). After imputing missing values, handling outliers, and conducting other quality checks, these data were stratified by respondent age, employment status and period (weekday/weekend). Trade-offs or time-shift coefficients between time spent in vehicles and the eight other microenvironments were then estimated using robust regression. For children and retirees, congestion primarily reduced the time spent at home; for older children and working adults, congestion shifted the time spent at home as well as time in schools, public buildings, and other indoor environments. Changes in benzene and PM(2.5) exposure were estimated for the current average travel delay in the U.S. (9 min day(-1)) and other scenarios using the estimated time shifts coefficients, concentrations in key microenvironments derived from the literature, and a probabilistic analysis. Changes in exposures depended on the duration of the congestion and the pollutant. For example, a 30 min day(-1) travel delay was determined to account for 21+/-12% of current exposure to benzene and 14+/-8% of PM(2.5) exposure. The time allocation shifts and the dynamic approach to TAPs improve estimates of exposure impacts from congestion and other recurring events.
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