California has adopted innovative legislation to tackle climate change. Energy-efficient buildings, lower-emissions industrial processes, and more fuel-efficient transportation vehicles operating on cleaner fuels are among the many strategies that are being implemented. However, to attain the needed reductions, California must find additional strategies to reduce greenhouse-gas emissions, especially from the transportation sector, which is a large fraction of the total emissions problem. This paper discusses the efforts that are underway to further increase transportation efficiency, shift transportation to less CO2-intensive modes, and slow or reverse growth in vehicle-kilometers of travel (VKT). The legislative mandate is leading to a new focus on methods for quantifying travel changes and emissions reductions, ranging from spreadsheet approaches to integrated transportation-land use models. It also is renewing interest in travel-demand management and land-use policies that could reduce overall travel. While a number of cities have embraced these strategies, their success in the face of the state’s continuing growth will likely depend on both federal and state policies and funding incentives.

Transport is one of the fastest growing sources of emissions of greenhouse gases. Some European countries have adopted comprehensive “sustainable transport” policies, in which climate change is addressed. This paper looks into how sustainable transport policy frameworks deal with climate change challenges in three countries: the Netherlands, Sweden, and the United Kingdom. In particular, the focus is on the role of follow-up and monitoring systems to keep the policies on track. For the United Kingdom, a critical analysis is made of strengths and weaknesses of the policy monitoring regime. The analysis shows that the monitoring approach, while ambitious, has suffered some deficits that may have weakened the role of the high-level strategies. Current efforts to strengthen the system are discussed.

Climate change has been identified by many scientists, engineers, and public officials as one of the significant challenges facing society over the next several decades. And of civil engineered facilities, the transportation network is likely to be one of the systems most affected by changing climate, weather, and local environmental conditions. This paper examines the current practice of looking at transportation system adaptation to climate changes and develops a conceptual framework of the different components of transportation infrastructure that will be affected differently by a range of climate changes. An adaptive systems management approach is suggested as one approach for transportation engineers to anticipate likely climate changes, identify vulnerabilities in the transportation system, and assess different strategies for mitigating potential impacts. The result of this approach is a strategic perspective on what transportation agencies should do today and in the future to respond to changing environmental conditions. Developing an organizational strategy for dealing with the different elements of these changes is a critical component of this strategic perspective.

The goal of this paper was to develop a performance measurement–based approach for transportation agencies, such as state departments of transportation, to evaluate and enhance sustainability. This research proposes a performance measurement–based framework and evaluation methodology for sustainable transportation, linked to agency strategic planning goals. The methodology was applied and tested for the Texas Department of Transportation (TxDOT). This sustainability enhancement methodology is implemented within the highway-corridor planning process. The research identified 12 performance measures, including measures of congestion, safety, alternative modes, and air quality, to address the goals and objectives in TxDOT’s strategic plan. The multiattribute utility theory (MAUT) decision-making approach was applied to quantify and normalize the selected performance measures and calculate sustainability index values for current and predicted future corridor conditions. This paper also presents the results from a pilot application of the methodology for a section of US-281 in San Antonio, Texas. The findings made it possible to identify specific performance measures and specific portions of the corridor that needed improvement to enhance the overall sustainability. This research provides a useful tool to assess the relative sustainability of transportation corridors now and in the future.

Greenhouse gas (GHG) accounting for individual cities in large metropolitan areas is confounded by spatial scale and boundary effects that impact the allocation of transportation fuels used for surface transport and airline travel. This paper expands on a demand-based methodology to spatially allocate transportation fuel use (surface and airline) among colocated cities in the United States that are part of a larger metropolitan area commutershed on the basis of demand for surface vehicle miles traveled (VMT) exerted by individual cities. By using travel demand models for metropolitan planning organizations, the demand method was first applied as part of the city of Denver’s GHG inventory in 2005 to develop a material flow analysis (MFA) of gasoline, diesel, and jet fuel consumption at the city scale. This paper reports on the application of the same method to six major metropolitan regions across the United States and a detailed analysis of all 27 cities within the larger Denver metro region. The analysis of six metropolitan areas in the United States demonstrated (1) the demand method produces VMT estimates allocated to cities across the commutershed that are similar (within 6%) to the boundary-limited polygon approach (linear correlation coefficient $R^2=0.82$; slope $m=0.98$); (2) airline travel allocation by vehicular trip count ratios to the regional airport from colocated cities produces results similar to regional airline travel allocation by population ratios (linear correlation coefficient $R^2=0.96$; slope $m=0.99$); and (3) the method is replicable with necessary data available from all cities in this study through their corresponding metropolitan planning organizations. In addition, the demand-VMT allocation method is found to be more responsive to future simulated mass transit growth. Further, the method is sensitive to local travel demand features of the individual cities, of which employment intensity was found to have the largest impact on per capita VMT allocated to a city. Within the Denver commutershed, daily VMT per capita estimates ranged from 13–129 km/capita/day (8–80 mi/capita/day) among the 27 communities, with a strong positive correlation with employment intensity (employment/capita; $R^2=0.97$) and employment density (employment/kilometer; $R^2=0.59$).

The writers describe the development of a set of carbon dioxide emissions estimates for highway travel by automobile, truck, bus, and other public transit vehicle movements within the nation’s 100 largest metropolitan areas in calendar year 2005. Considerable variability is found to exist across metropolitan areas when these greenhouse gas emissions are measured on a per capita and a per gross metropolitan product (GMP) basis. Least square and spatial error regression modeling show a relationship among emissions per capita and per GMP with truck traffic share, transit share, employment density, population dispersion within the metro area, and GMP per capita. As a result, many of the nation’s largest metropolitan areas tend to have lower ${\mathrm{CO}}_2$ emissions per capita and per GMP than smaller and more recently developed metro areas.