11.522 UIS Research Seminar (Fall 2015) Discussion notes
Monday, October 19, 2015, Part 2
The challenge of reducing transportation emissions has been one of the perennial foci of academic planners and practitioners for decades. Following from projections of increasingly harmful climate change impacts, many policy makers have supported goals of reducing emissions by 80% relative to 2005 by 2050. Yet the EIA projects that transportation emissions, which account for 27% of U.S. emissions, will only decline about 0.2% per year through 2040.
Every year dozens of new studies are published aiming to project the impact of policies that aim to reduce emissions, through reduced travel demand or reduced emissions per mile. The first reading I have selected for today, the executive summary of Cambridge Systematics’s Moving Cooler report, represents a recent attempt at synthesizing knowledge about travel behavior to project the impacts of several packages of policy efforts, taken together. The key question is how much leverage can be obtained from any given policy, which depends on the magnitude of the effort and the elasticity of the response to the policy. Much of the literature focuses on how planning interventions can directly reduce vehicle miles traveled, or VMT, through changes in the built environment. For this, I recommend skimming Ewing & Cervero (2010) for their discussion of the impact of the “6 D’s”- density, diversity of land use, design of the urban environment, destination accessibility, distance to transit, and demand management.
An equally necessary concept to address is the elasticity of VMT with respect to price, which tells us the percent change in VMT that can be expected through a unit percent change in the cost of driving, which is an important metric to consider when evaluating the potential impacts of a gas tax or carbon pricing. This elasticity should be thought of in the context of the characteristics of the physical environment where a driver lives and works as well as other macroeconomic variables. The political feasibility of pricing instruments aimed at reducing transportation emissions is a function of perceptions of who benefits and who is burdened from such policies and the relative political clout of the prospective winners and losers. Therefore it is important to use the data available to test our assumptions about who wins and loses. The article by Wang and Chen uses NTHS survey data to show the different impacts of fuel price changes on travel behavior of both poor and affluent populations. Recently, vast datasets of vehicle inspection records from Massachusetts, Pennsylvania, Colorado, and California have been released, enabling researchers to look at time series information on the driving patterns of individual vehicles. This enables them to explore how VMT varies spatially and how it relates to variables such as vehicle age and type, MPG, and macroeconomic conditions. Gillingham et al have shown significant variability of elasticity by vehicle fuel economy and age. I intend to explore the Massachusetts dataset to test whether similar patterns exist and whether more spatial explanations can be incorporated.
Readings:
Discussion Questions: