Public transportation systems are often part of strategies to reduce urban environmental impacts from passenger transportation, yet comprehensive energy and environmental life-cycle measures, including upfront infrastructure effects and indirect and supply chain processes, are rarely considered. Using the new bus rapid transit and light rail lines in Los Angeles, near-term and long-term life-cycle impact assessments are developed, including consideration of reduced automobile travel. Energy consumption and emissions of greenhouse gases and criteria pollutants are assessed, as well the potential for smog and respiratory impacts.

Results show that life-cycle infrastructure, vehicle, and energy production components significantly increase the footprint of each mode (by 48–100% for energy and greenhouse gases, and up to 6200% for environmental impacts), and emerging technologies and renewable electricity standards will significantly reduce impacts. Life-cycle results are identified as either local (in Los Angeles) or remote, and show how the decision to build and operate a transit system in a city produces environmental impacts far outside of geopolitical boundaries. Ensuring shifts of between 20–30% of transit riders from automobiles will result in passenger transportation greenhouse gas reductions for the city, and the larger the shift, the quicker the payback, which should be considered for time-specific environmental goals.

Public transit systems are often accepted as energy and environmental improvements to automobile travel, however, few life cycle assessments exist to understand the effects of implementation of transit policy decisions. To better inform decision-makers, this project evaluates the decision to construct and operate public transportation systems and the expected energy and environmental benefits over continued automobile use. The public transit systems are selected based on screening criteria. Initial screening included advanced implementation (5 to 10 years so change in ridership could be observed), similar geographic regions to ensure consistency of analysis parameters, common transit agencies or authorities to ensure a consistent management culture, and modes reflecting large infrastructure investments to provide an opportunity for robust life cycle assessment of large impact components. An in-depth screening process including consideration of data availability, project age, energy consumption, infrastructure information, access and egress information, and socio-demographic characteristics was used as the second filter. The results of this selection process led to Los Angeles Metro’s Orange and Gold lines.

In this study, the life cycle assessment framework is used to evaluate energy inputs and emissions of greenhouse gases, particulate matter (10 and 2.5 microns), sulfur dioxide, nitrogen oxides, volatile organic compounds, and carbon monoxide. For the Orange line, Gold line, and competing automobile trip, an analysis system boundary that includes vehicle, infrastructure, and energy production components is specified. Life cycle energy use and emissions inventories are developed for each mode considering direct (vehicle operation), ancillary (non-vehicle operation including vehicle maintenance, infrastructure construction, infrastructure operation, etc.), and supply chain processes and services. In addition to greenhouse gas emissions, the inventories are linked to their potential for respiratory impacts and smog formation, and the time it takes to payback in the lifetime of each transit system.

Results show that for energy use and greenhouse gas emissions, the inclusion of life cycle components increases the footprint between 42% and 91% from vehicle propulsion exclusively. Conventional air emissions show much more dramatic increases highlighting the effectiveness of “tailpipe” environmental policy. Within the life cycle, vehicle operation is often small compared to other components. Particulate matter emissions increase between 270% and 5400%. Sulfur dioxide emissions increase by several orders of magnitude for the on road modes due to electricity use throughout the life cycle. NOx emissions increase between 31% and 760% due to supply chain truck and rail transport. VOC emissions increase due to infrastructure material production and placement by 420% and 1500%. CO emissions increase by between 20% and 320%. The dominating contributions from life cycle components show that the decision to build an infrastructure and operate a transportation mode in Los Angeles has impacts far outside of the city and region. Life cycle results are initially compared at each system’s average occupancy and a breakeven analysis is performed to compare the range at which modes are energy and environmentally competitive.

The results show that including a broad suite of energy and environmental indicators produces potential tradeoffs that are critical to decision makers. While the Orange and Gold line require less energy and produce fewer greenhouse gas emissions per passenger mile traveled than the automobile, this ordering is not necessarily the case for the conventional air emissions. It is possible that a policy that focuses on one pollutant may increase another, highlighting the need for a broad set of indicators and life cycle thinking when making transportation infrastructure decisions.

Recent climatic trends show more flooding and extreme heat events and in the future transportation infrastructure may be susceptible to more frequent and intense environmental perturbations. Our transportation systems have largely been designed to withstand historical weather events, for example, floods that occur at an intensity that is experienced once every 100 years, and there is evidence that these events are expected become more frequent. There are increasing efforts to better understand the impacts of climate change on transportation infrastructure. An abundance of new research is emerging to study various aspects of climate change on transportation systems. Much of this research is focused on roadway networks and reliable automobile travel. We explore how flooding and extreme heat might impact passenger rail systems in the Northeast and Southwest U.S.

There is increasing evidence that vehicle travel in developed countries may have peaked, contradicting many historical travel demand forecasts. The underlying causes of this peaking are still under debate and there has been a mobilization of research, largely focused at national scales, to study the explanatory drivers. There is, however, a dearth of research focused at the metropolitan scale where transportation policy and planning are frequently decided.

Using Los Angeles County, California, as a case study, we investigate the Peak Car theory and whether social, economic, and technical factors, including roadways that have become saturated at times, may be contributing to changes in travel behavior. After peaking in 2002, vehicle travel in Los Angeles County declined by 3.4 billion (or 4.1%) by 2010. The effects of changing fuel prices, fuel economy, population growth, increased utilization of alternate transportation modes, changes in driver demographics, income, and freight are first assessed. It is possible, and likely, that these factors alone explain the reduction in travel. However, the growth in congestion raises questions of how a constricting supply of roadway network capacity may contribute to travel behavior changes.

There have been no studies that have directly assessed how the maturing supply of infrastructure coupled with increasing demand affect travel behavior. We explore regional and urban factors in Los Angeles to provide insight into the drivers of Peak Car at city scales where the majority of travel occurs. The results show that a majority of the decline in VMT in Los Angeles can be attributed the rising fuel prices during the 2000s. While overall roadway network capacity is not yet a limiting factor for vehicle travel there is some evidence that suggests that congestion along certain corridors may be shifting some automobile travel to alternatives. The results also suggest that the relative impact of any factor on travel demand is likely to vary from one locale to another and Peak Car analysis across large geographic areas obscures the nuisances of travel behavior at a local scale.