Erin R. Bock

Date of Award


Level of Access Assigned by Author

Open-Access Thesis

Degree Name

Master of Science (MS)


Resource Economics and Policy


Jonathan D. Rubin

Second Committee Member

Mario Teisl

Third Committee Member

Deirdre Mageean


Recreational vehicles produce a significant amount of air pollution. Despite this fact, only recently has regulation been placed into effect by the EPA on air emissions from these sources. Maine has a high amount of recreational vehicle use, and many people travel fiom out of state to utilize Maine's resources in this manner. Until now, there has been no research done to examine the impact of Maine's recreational vehicle sector on air pollution. This thesis focuses on air emissions from several types of recreational vehicles. These are gasoline-powered snowmobiles, all-terrain vehicles (ATVs), and noncommercial watercraft. There were several goals that were accomplished by this research. First, exhaust emissions from these sources were estimated using emissions modeling software developed by the EPA. This was used in conjunction with data collected from three gasoline-consumption surveys for recreational vehicle use conducted by the Margaret Chase Smith Center for Public Policy at the University of Maine. Emissions estimates were obtained for the years 2000, 2010, and 2020. The emissions results obtained using the survey data were much different then the results obtained using EPA's data provided for use by the computer model. Another objective of this research was to examine the effects of emission regulations placed on these vehicles by the EPA for the State of Maine. A recent rule-making covered exhaust and evaporative emissions for snowmobiles and ATVs, and a 1996 ruling covered exhaust emissions from several types of watercraft. Using the costs predicted by the EPA for complying with these regulations, effects on sales of the regulated vehicles, and cost-per-ton estimates for the reduction of pollution from these vehicles were examined. It was found that cost-per-ton estimates using the EPA's data as opposed to the survey data were significantly higher. This is an important result, as it shows the sensitivity of the emissions model to small differences in data, and the consequences this can have when estimating associated costs.