Refining particulate matter emission inventories in California: New methods for estimating vehicle activity on unpaved roads

This dissertation presents a new framework for estimating vehicle miles traveled (VMT) on unpaved roads and is designed to improve the estimation of particulate matter emissions for state emission inventories. Unlike previous methods, this framework distinguishes between typical unpaved road travel (nonharvest VMT) and travel due to the hauling of harvested crops in agricultural areas (harvest VMT) using a variety of land use, travel behavior, crop, weather, and road network information. Furthermore, spatial and seasonal variations included in the new framework more finely represent the densities of annual travel activity on unpaved roads in the state. Both a pilot study and an expanded study are presented. The pilot study suggests that land use and paved road density are influential factors in VMT generation on unpaved roads. These findings are supported by the expanded study, although the relationships between variables are less clear.; Using the frameworks developed in both the pilot and expanded studies, the hauling of harvested crops seems to account for only about 1% of the total annual unpaved road VMT when the entire study region is considered. However, using a comparison of harvest VMT from the same county in the expanded study as in the pilot study, we find large discrepancies between the harvest VMT estimates. Further investigation indicates the validity of the expanded study estimates.; Of the nonharvest travel observed in the expanded study, a total of about 9% statewide was attributable to unpaved roads servicing agricultural lands, while the majority of travel was estimated to take place on natural lands (65%). The low proportion of travel associated with roads in agricultural areas indicates that current methods may be overestimating the contribution of this source to particulate matter emission inventories in some areas, while other sources may be underestimated. However, we find great variability between geographical regions. Policy implications of these findings are discussed in the dissertation's final chapter.