On-Road measurement of particulate matter emissions from vehicles: particle concentration, size distribution and morphology

During summer 2010, we conducted a field experiment in Southern Michigan to measure on-road vehicle emissions. During the campaign, particulate matter (PM) concentrations were monitored with a Light Detection and Ranging (Lidar) and transmissometer system. The Lidar and transmissometer system measures PM mass concentration of vehicle exhaust using backscatter and extinction of an ultraviolet laser beam directed across the road. Collocated with the Lidar system we deployed an extractive system inclusive of a LiCor 840 to monitor CO2 concentrations, a laser aerosol spectrometer to measure particle size distributions for PM with diameter larger than 0.1 µm, and a portable condensation particle counter to estimate the total particle number concentration for particles with diameters between~30nm and 1 µm. In addition, road-side vehicle exhaust particles were collected on nuclepore filters for scanning electron microscopy analysis during selected periods of time. In this study we analyze fuel-based mass and number PM emission factors from passing vehicles. The emission factors are estimated normalizing the PM data by the CO2 concentration. The morphology of the particulates is also investigated with electron microscopy analysis. Type of vehicles and traffic counts were recorded by one of the researchers during the sampling period to evaluate the influence on particle morphology due to traffic volume and fuel type. Image processing and fractal geometry are used to estimate various morphological parameters and fractal dimension. Diurnal variation of particle morphology descriptors and fractal dimension of soot particles are investigated and compared with CO2 emissions, particle size distribution and particle number concentration for selected subsets of the data. Variations of PM emission factors and PM morphology are also investigated for different traffic conditions and days of the week. The analysis of the PM data is of particular importance in monitoring vehicle emissions and in designing emission reduction strategies to improve air quality and public health.