• Energy Research

In this paper, a joint model of vehicle type choice and utilization is formulated and estimated on a data set of vehicles drawn from the 2000 San Francisco Bay Area Travel Survey. The joint discrete–continuous model system formulated in this study explicitly accounts for common unobserved factors that may affect the choice and utilization of a certain vehicle type (i.e., self-selection effects). A new copula-based methodology is adopted to facilitate model estimation without imposing restrictive distribution assumptions on the dependency structures between the errors in the discrete and continuous choice components. The copula-based methodology is found to provide statistically superior goodness-of-fit when compared with previous estimation approaches for joint discrete–continuous model systems. The model system, when applied to simulate the impacts of a doubling in fuel price, shows that individuals are more likely to shift vehicle type choices than vehicle usage patterns.

Abstract This paper investigates methodologies to quantify CO2 emissions from cars and light trucks in Florida. The most widely used methodology to calculate greenhouse gas emissions in the transportation sector at the local level uses a harmonic average (HA) methodology based on nationally averaged fuel economies that assume 55% city and 45% highway VMTs. This paper presents a local condition (LC) methodology that accounts for county-level variations in city and highway VMTs, as opposed to assumed uniform driving conditions. Both HA and LC methodologies were used to estimate and compare absolute and per capita CO2 emissions both statewide and counties for 2000 and 2008. From 2000 to 2008, statewide absolute and per capita CO2 emissions increased similarly using HA and LC methodologies; however, the percent change varied considerably among counties. Statewide CO2 emissions calculated from HA and LC methodologies differed by only −0.2% (2000) and 1.7% (2008); however, the differences in the county-level emissions ranged from −8.0% to 14.9% (2000) and from −5.6% to 17.0% (2008). While either the HA or the LC methodology yields a similar result statewide, significant variation exists at the county level, warranting the need to consider local driving conditions when estimating county-level emissions.