Impacts of High Energy Costs on Transportation in a Mega-Region

According to a March 2010 Federal Highway Administration (FHWA) Strategic Plan, mega-regions are likely to become the “nation’s operative regions when competing in the future global economy.” A mega-region is defined as a set of interconnected central cities and their economically linked hinterland. The concept of mega-regions is derived from the observation that as urban regions growth and transportation and communication links improve, it is in their best interest for multiple urban areas to act together as an economic unit.

Mega-regions need analysis tools to evaluate planning scenarios and assess the broad impacts of various projects and policies. These tools have to cover areas larger than those typically covered by metropolitan planning organization (MPO) models, and even many state department of transportation (DOT) models. In addition, such tools need to integrate systems beyond transportation, such as economic, land-use, and environmental modules. This article reviews a mega-region case study executed by Parsons Brinckerhoff and the National Center for Smart Growth Research and Education at the University of Maryland between 2010 and 2012. The study was funded by the FHWA’s Exploratory Advanced Research Program, using a modeling framework to address the impact of high energy prices in the Chesapeake Bay mega-region around Washington D.C. (Box 1). The article describes the model and presents findings from its analysis of future energy price scenarios based on the economy, land use, and transportation patterns at the mega-regional scale.

Basic Methodology

The Chesapeake Bay mega-region analysis framework began as an effort by the Maryland State Highway Administration to develop a tool to analyze freight travel, rural travel, and travel between MPOs in Maryland. The model geography was extended to cover the Chesapeake Bay mega-region area. The travel demand models adopted from local MPOs were upgraded, including adding various indicator models. An economic model was built to inform freight movements. A top-down land-use allocation model was developed to link the economic forecasts to the travel model, while a parcel-based bottomup model enabled the use of environmental indicator models by estimating land cover at a detailed level. Several additional upgrades were made for this case study to ensure model sensitivity to the impact of significant increases in energy prices on transportation, land use and the mega-regional economy.

Model Development Tailored to Issues/Context

Box 2 shows the implemented Chesapeake Bay mega-region analysis framework. The modules cover the recommended framework elements by including multidiscipline components (economic, land use, transport, environmental, and other indicators) and multi-modal freight and passenger (long and short) flows, all within a multi-level geographic approach (global, mega-regional, and MPO reconciliation).

Several components of the basic Chesapeake Bay mega-region model noted in Box 2 were enhanced to enable better responsiveness to the policy scenario of interest—high energy prices. These changes are exhibited in Box 3.A market reconnaissance analysis assessment explored available data and models, and revealed key regional issues, industry clusters, and urban area strengths. The resulting modeling framework includes sophisticated long-distance personal and freight transportation components, as well as strong short-distance personal travel mode choice and pricing components tailored to the region’s high transit usage and regional issues of interest. Short-distance travel models were initially borrowed from MPOs, with upgrades developed based on needs identified during validation and sensitivity testing.

Mega-Region Case Study Scenarios and Results

Three possible future scenarios were identified spanning the possible effects of energy prices: business-as-usual or the Baseline scenario, in which the price of petroleum rises slightly and average vehicle fuel efficiency remains the same; a slow Steady Price Rise, in which the price of petroleum rises to a high level but slowly over a long period of time, allowing people and the economy to adjust; and a Price Spike in which the price of energy remains relatively constant through 2029, then jumps to a very high level in a very short period of time.

The analysis provides some intriguing findings regarding the mega-region’s resilience to a high-cost energy future, including results directly from analysis and those conjectured based on our understanding of the modeling tools and work to date. This latter category included the Steady Price Rise scenario, which was not modeled, as well as the full effects of the economic and land use impacts (assumed fixed) and environmental models (analysis too expensive to perform under this effort) of the Price Spike scenario.

Analysis showed that the more dispersed land use pattern of the 2030 Baseline scenario led to an improvement in the jobs-housing balance across the region, but put residents and businesses in vulnerable locations that reduced their resilience to higher gas prices. This was largely the result of a lower cost of travel, with federal Corporate Average Fuel Economy (CAFE) standards improving vehicle efficiency while fuel prices remain low. Despite a large growth in miles traveled and associated congestion, air quality is improved in future years as a result of more efficient vehicles. Agriculture is expected to decline in the region, a boon to water quality, with the associated reduction in fertilizer run-off.

In contrast, the Price Spike scenario had a significant impact on travel, leading to shorter trips, more carpooling, and increased transit use where available. The sharp drop in auto miles travelled had the benefit of increasing speed and rolling back congestion despite the region’s 30 percent population growth. The higher energy prices proved to be beneficial to transport-dependent industries in the regional economy, allowing goods to move faster in more developed areas and facilitating economic linkages. Under this scenario, building on the benefits of the federal CAFE standards, air quality further improves due to the decline in vehicle miles traveled. It is hypothesized that a Steady Price Rise scenario would show less effect on vehicle miles travel versus the Baseline scenario. First, the economy is likely to be smaller as industries face higher costs and households spend less. The consistent rising price signal would be expected to lead to long-term decisions by businesses and residents that would reduce their vulnerability to higher gas prices. These include: more compact development, use of alternative modes including carpooling, and faster turnover to higher-efficiency vehicles. As a result, although we still expect a reduction in travel, it would likely be less than under the Price Spike scenario, with less disruption to travel patterns and household budgets. However, this would mean less congestion relief, and associated impacts to freight movement and the economy than the Price Spike scenario.



  1. All blue boxes operate within the mega-region geography. The economic and transport models also extend into the global geography. The transport model can be reconciled at the urban geography.


Image Header Source:  NASA Goddard Space Flight Center (Creative Commons)