Time-Series Analysis of Above-Road Particulate Matter at the Caldecott Tunnel Exit

ABSTRACT

On November 18, 1997, above-road particulate matter (PM) lidar (light detection and ranging) signals and heavy-duty (HD) and light-duty (LD) vehicle counts were simultaneously collected for 894 10-sec sampling periods at the Caldecott Tunnel in Orinda, CA, for the purpose of measuring the relative contributions of LD and HD vehicles to the PM lidar signal under real-world driving conditions. The relationship between the PM lidar signal and traffic activity (i.e., LD and HD traffic volumes) was examined using a time-series analysis technique, multilagged regression. The time-series model results indicate that the PM lidar signal in the current sampling period (PM_t) depended on the level recorded in the previous three sampling periods (i.e., PM_t-1, PM_t-2, and PM_t-3), the number of LD vehicles in the seventh past sampling period (LD_t-7), and the number of HD vehicles measured 80 sec previous to the current sampling period (HD_t-8). On a 10-sec period basis, the model results indicate that HD vehicles contributed, on average, 3 times more to above-road PM li-dar signals than did LD vehicles. The observed lag in the relationship between vehicle types and the lidar signal 20 m above the road suggests that resuspended road dust, rather than tailpipe exhaust emissions, was the main source of the detected PM. Detection of road dust at such heights above the road suggests the need for investigating the processes governing the vertical transport and recycling of PM over the road as a function of vehicle dynamics under a range of meteorological conditions.