title: Comparing lifetime emissions of natural gas and conventional fuel vehicles: an application of the generalized ANCOVA model.
abstract: New regulations and incentives are encouraging the use of clean, alternative fuel vehicles (AFVs) in urban areas. These vehicles are seen as one option for reducing air pollution from mobile sources. However, because of the limited number of AFVs on the road, little is known about actual lifetime emissions characteristics of in-use AFVs. This study describes the use of a generalized analysis of covariance model to evaluate and compare the emissions from natural gas vehicles with emissions from reformulated gasoline vehicles. The model describes fleet-wide emissions deterioration, while also accounting for individual vehicle variability within the fleet. This ability to measure individual vehicle variability can then be used to provide realistic bounds for the emissions deterioration in individual vehicles and the fleet as a whole. In order to illustrate the use of the model, the carbon monoxide, oxides of nitrogen (NOx), non-methane hydrocarbon (NMHC), and carbon dioxide emissions characteristics of a fleet of dedicated natural gas Dodge Ram vans and a fleet of dedicated reformulated gasoline Dodge Ram vans operating in the U.S. government fleet are explored. The analysis demonstrates the utility of the statistical method and suggests a potential for natural gas Dodge Ram vans to be generally cleaner than their conventional fuel counterparts. However, in the case of NOx and NHMCs, the analysis also suggests that these emissions benefits might be reduced over the vehicle lifetime due to higher emissions deterioration rates for natural gas vehicles. As this paper is aimed at illustrating the analysis of the covariance model, the results reported herein should be considered within the context of a more comprehensive study of these data before general conclusions are possible. Generalization of these findings to other vehicle models and alternative fuel technologies is not justified without further study.
authors.affiliation: James Madison University, Integrated Science and Technology Program, Harrisonburg, Virginia.
authors.forename: M L
authors.initials: ML
authors.lastname: Deaton
authors.forename: J J
authors.initials: JJ
authors.lastname: Winebrake
mesh_terms: D000393:Air Pollutants; D000397:Air Pollution / Q000517:prevention & control*; D000465:Algorithms; D005579:Fossil Fuels; D008962:Models, Theoretical; D014481:United States; D014484:United States Environmental Protection Agency
chemical_list: D000393:Air Pollutants; D005579:Fossil Fuels