Amanda Kennedy, Regional Plan Association
Imagine a common scenario encountered by planners: a new office building. In this scenario, a company decides to relocate workers from downtown office space to a new headquarters building near a highway interchange. Local officials support the development because of the additional property tax revenue it will produce, and state subsidies help the company build their new facility. However, the consequence for the environment may not be so positive. A move like this may result in a dramatic shift in the miles traveled by employees each day as they adjust to a location farther from transit facilities and their homes.
What if there were ways for planners and developers to predict a crucial impact of siting decisions: the miles that workers and customers will drive to get there? Some existing tools, such as the Center for Neighborhood Technology’s Housing and Transportation Index, illustrate the transportation benefits of living in urban areas. A new tool, enabling planners to quickly and easily estimate the vehicle miles traveled (VMT) generated by a new development would, amongst other things, enable users to measure the project’s carbon emissions footprint and explore greener alternatives. Such a tool has been especially needed in Connecticut, since the state’s existing traffic models weren’t designed to quantify overall VMT impacts of individual projects. Reaching the state’s goal of reducing carbon emissions 80 percent from 2001 levels by 2050 will require planners to encourage development that reduces both our dependence on personal vehicles and the distances that car owners drive. How do we make sure new development will get us there?
With funding support from the Lincoln Institute of Land Policy, the Regional Plan Association has created a tool for Connecticut municipalities that estimates VMT based on neighborhood characteristics such as density, proximity to transit, and nearby jobs and housing. Our base VMT dataset was generated from Census Journey-to-Work data, available at the tract level for everywhere in the United States. Through a combination of GIS and statistical analysis we developed a model that predicts worker commutes based on where they live or work. The result is a spreadsheet-based VMT tool that enables us to quickly estimate the amount of vehicle travel and carbon emissions generated by various development scenarios. California’s SB 375 is the first state planning initiative to require integrating housing and transportation planning specifically to reduce carbon emissions. As other states follow California’s example, tools like this one will be essential to evaluate the emissions generated by our land use patterns so that state and local investments minimize environmental impact while achieving economic development.
Several examples illustrate how useful the tool is in real-world planning situations. The State of Connecticut needs to rebuild a 1970s-era medical school complex, located along a highway in the exurbs of Hartford. If the State were to build the new facility in downtown Meriden instead, it would be at a junction of rail and bus services and central to an existing labor force. The tool estimates that hospital employees would drive 20 percent less to the downtown location than to the current facility. In another example, planners expect that new housing near an existing highway-oriented corporate office park north of Hartford would reduce vehicle travel by allowing more workers to live near their jobs. New housing in Hartford, the state’s largest employment center, is estimated to produce about half the emissions from transportation than new housing located in subdivisions in the region’s outer suburbs.
Vehicle use has been growing faster than the population for years, reflecting the growth of sprawling development and two-income households that must choose housing between two far-flung jobs. The transportation sector (mostly cars and trucks) generates roughly 40 percent of Connecticut’s carbon emissions today. The best estimates indicate that better fuel efficiency and a transition to alternative fuels will not be enough to reduce transportation-related emissions. Connecticut’s Climate Action Plan asks for a very modest improvement in VMT – to reduce growth in VMT from the expected 22 percent by 2020 to 19 percent. This seems simple enough, but in a slow-growing state like Connecticut, infill development and new transit services that could enable transit and pedestrian commute options for residents of every community will come slowly. In order to meet the state’s VMT reduction goals, planners must look beyond measures promoting alternatives to driving. Measures that reduce the miles we drive, such as smarter locations for new employment and housing, are necessary first steps towards meeting our carbon emissions reduction goals.
The author can be reached at amanda (at) rpa (dot) org.