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M.Sc. (Mechanical Engineering) / Please refer to full text to view abstract

No description available.

Air pollution is a threat to the environment and human health. Freight trucking in particular is the main source of freight transportation emissions. Heavy-duty trucks emit large amounts of toxic air pollutants that cause serious diseases and harm public health. In addition, heavy-duty trucks emit great amounts of greenhouse gas (GHG), which is the leading cause of global warming. Despite increased environmental restrictions on air pollution and rising trucking greenhouse gas emissions in the past decades, no economic study has examined the potential GHG and air pollution reductions in the trucking sector and the associated private abatement costs to the industry. This study accounts for GHG emissions and toxic air pollutants in measuring and evaluating efficiency and productivity for the trucking industry in the 48 contiguous states. Moreover, the private costs of abatement to the industry were also estimated. When only GHG was incorporated in the production model, the results showed that each state could expand desirable output and reduce GHG by an average of 11 percent per year between 2000 and 2007. The Malmquist-Luenberger productivity indexes showed that omitting or ignoring GHG in trucking service production yielded biased estimates. On the other hand, due to increased environmental regulations, most of the toxic air pollutants decreased dramatically between 2002 and 2005. The analytical results showed that inefficiency decreased during this period. The private costs of abatement averaged $73 million per state in 2005. When GHG and six toxic air pollutants were incorporated in the production model, the estimated private abatement cost was $76 million per state, which was equivalent to 0.7 percent of the industry output in 2005.

This research examines the use of archived weigh-in-motion (WIM) data to estimate link-based heavy-vehicle emissions for Oregon highways. This research combined data on vehicle speed, highway grade, and gross vehicle weight and relationship between these elements in published research to estimate the carbon dioxide (CO2) and nitrogen oxide (NOx) emissions from trucks. Sensitivity analysis was conducted on the impact of uphill grade and gross vehicle weight on truck speed and emissions. The results suggest that with the data available in the weigh-in-motion archive and with a reasonable set of assumptions, link-based emissions for heavy-duty vehicles can be estimated. The carbon dioxide (CO2) and nitrogen oxide (NOx) emissions are found to increase when the speed, gross vehicle weight, or road grade increases. The relationship between nitrogen oxide (NOx) emissions and vehicle weight was estimated to be linear. The potential to estimate the link-based heavy-vehicle emissions for Oregon highways using the weigh-in-motion data archive, which was mainly designed to estimate truck counts, has a great value in setting new measures to mitigate the heavy-vehicle emissions.