Sustainable mobility policy for long-distance transportation services should consider emerging automobiles and aircraft as well as infrastructure and supply chain life-cycle effects in the assessment of new high-speed rail systems. Using the California corridor, future automobiles, high-speed rail and aircraft long-distance travel are evaluated, considering emerging fuel-efficient vehicles, new train designs and the possibility that the region will meet renewable electricity goals. An attributional per passenger-kilometer-traveled life-cycle inventory is first developed including vehicle, infrastructure and energy production components. A consequential life-cycle impact assessment is then established to evaluate existing infrastructure expansion against the construction of a new high-speed rail system. The results show that when using the life-cycle assessment framework, greenhouse gas footprints increase significantly and human health and environmental damage potentials may be dominated by indirect and supply chain components. The environmental payback is most sensitive to the number of automobile trips shifted to high-speed rail, and for greenhouse gases is likely to occur in 20–30 years. A high-speed rail system that is deployed with state-of-the-art trains, electricity that has met renewable goals, and in a configuration that endorses high ridership will provide significant environmental benefits over existing modes. Opportunities exist for reducing the long-distance transportation footprint by incentivizing large automobile trip shifts, meeting clean electricity goals and reducing material production effects.

Meaningful sustainable consumption patterns require informed consumers who understand the actual impact of their actions on a quantitative and tangible basis. Life cycle assessment (LCA) is a tool well suited to achieving this goal, but has only been superficially applied to the analysis of plant-based diets. This analysis looks at a common component of plant-based meat alternatives: a wheat-based protein known as seitan, which is a common substitute for beef. A comparative consequential analysis shows the overall change in environmental impact when 1000 servings of seitan displace 1000 servings of beef. The functional unit for comparison is one serving of seitan or one serving of beef and the system boundaries include production but not distribution, consumption or disposal. Life cycles are created for seitan and beef in the LCA modeling software SimaPro and an analysis is run using the Eco-indicator 99 methodology. The beef life cycle is created using complete existing LCA data, while the seitan life cycle is created using LCA data for constituent materials and processes.

Findings indicate that beef is much more environmentally impactful than seitan, but the largest difference is found in land use change. Significant data quality and uncertainty issues exist due to the data being incomplete or not representative for US processes and the use of proxy processes to estimate industrial processing. This analysis is still useful as a screening tool to show rough differences in impact. It is noted that despite seitan having a lower environmental impact than beef, increasing seitan production will probably have the effect of increasing overall environmental impacts, as beef production is not likely to decrease as a result. Massive changes in consumer purchase patterns are required before reductions in impact can be expected. Recommendations for future work include expanding system boundaries and obtaining industry specific data for seitan production.

With potential for automobiles to cause air pollution and greenhouse gas emissions relative to other modes, there is concern that automobiles accessing or egressing public transportation may significantly increase human and environmental impacts from door-to-door transit trips. Yet little rigorous work has been developed that quantitatively assesses the effects of transit access or egress by automobiles.

This research evaluates the life-cycle impacts of first and last mile trips on multimodal transit. A case study of transit and automobile travel in the greater Los Angeles region is developed. First and last mile automobile trips were found to increase multimodal transit trip emissions, mitigating potential impact reductions from transit usage. In some cases, a multimodal transit trips with automobile access or egress may be higher than a competing automobile trip.

In the near-term, automobile access or egress in some Los Angeles transit systems may account for up to 66% of multimodal greenhouse gas trip emissions, and as much as 75% of multimodal air quality impacts. Fossil fuel energy generation and combustion, low vehicle occupancies, and longer trip distances contribute most to increased multimodal trip impacts. Spatial supply chain analysis indicates that life-cycle air quality impacts may occur largely locally (in Los Angeles) or largely remotely (elsewhere) depending on the propulsion method and location of upstream life-cycle processes. Reducing 10% of transit system greenhouse emissions requires a shift of 23% to 50% of automobile access or egress trips to a zero emissions mode.

A corresponding peer-reviewed journal publication is available here:
Greenhouse Gas and Air Quality Effects of Auto First-Last Mile Use With Transit, Christopher Hoehne and Mikhail Chester, 2017, Transportation Research Part D, 53, pp. 306-320,

Mitigation of urban heat islands has become a goal for research and policy as urban environmental heat is a rapidly growing concern. Urban regions such as Phoenix, AZ are facing projected warming as urban populations grow and global climates warm (McCarthy et al. 2010), and severe urban heat can even lead to human mortality and morbidity (Berko et al. 2014). Increased urban heat may also have social and economic consequences such as by discouraging physical activity, reducing outdoor accessibility, and decreasing economic output (Stamatakis et al. 2013; Karner et al. 2015; Obradovich & Fowler 2017; Kjellstrom et al. 2009). Urban heat islands have been well documented in academic literature (Oke 1982; Arnfield 2003), and anthropogenic waste heat is often a major factor. The American Meteorological Society (2012) has said that anthropogenic waste heat may contribute “15 – 50 W/m2 to the local heat balance, and several hundred W/m2 in the center of large cities in cold climates and industrial areas.”

Anthropogenic waste heat from urban vehicle travel may be a notable contributor to the urban heat balance and the urban heat island effect, but little research has quantified and explored how changes in vehicle travel may influence local climates. Even with recent rapid improvements to engine efficiencies, modern automobiles still convert small amounts of fuel to useful energy. Typically, around two-thirds of energy from fuel in internal combustion engine vehicles is lost as waste heat through exhaust and coolant (Hsiao et al. 2010; Yu & Chau 2009; Saidur et al. 2009; Endo et al. 2007), and as much as 80% of fuel energy can be lost to waste heat under poor conditions (Orr et al. 2016). In addition, combustion of fuel generates water vapor and air pollution which may also affect the urban climate. Figure 1 displays where a typical combustion engine’s fuel energy is used and lost. There has been little research that quantifies the influence of vehicle travel on urban anthropogenic waste heat. According to Sailor and Lu (2004), most cities have peak anthropogenic waste heat values between 30 and 60 W m-2 (averaged across city) and heating from vehicles could make up as much as 62% of the total in summer months. Additionally, they found that vehicle waste heat could account for up to 300 W m-2 during rush hours over freeways. In another study, Hart & Sailor (2009) used in situ measurements in Portland, OR to evaluate spatial variability of air temperatures on urban roadways. They found that air masses near major roadways are some of the warmest in the region. Although some of the warming is attributed to pavement characteristics (imperviousness, low albedo), an average increase of 1.3 C was observed on weekdays relative to weekends along roadways. The authors offer increased weekday traffic density and building use as the likely contributors to this discrepancy. These previous studies indicates that vehicle related waste heat could be an important consideration in the urban energy balance. If significant, there may exist viable strategies to reduce anthropogenic waste heat from urban vehicle travel by increasing the fleet fuel economy and shifting to electric vehicles. This could offer cooling in urban areas around roadways were pedestrians are often found. Figure 2 visually demonstrates waste heat from vehicles (including an electric vehicle) in two thermal images.

As technologies rapidly progress, there is growing evidence that our civil infrastructure do not have the capacity to adaptively and reliably deliver services in the face of rapid changes in demand, conditions of service, and environmental conditions. Infrastructure are facing multiple challenges including inflexible physical assets, unstable and insufficient funding, maturation, utilization, increasing interdependencies, climate change, social and environmental awareness, changes in coupled technology systems, lack of transdisciplinary expertise, geopolitical security, and wicked complexity. These challenges are interrelated and several produce non-stationary effects. Successful infrastructure in the twenty-first century will need to be flexible and agile. Drawing from other industries, we provide recommendations for competencies to realize flexibility and agility: roadmapping, focus on software over hardware, resilience-based thinking, compatibility, connectivity, and modularity of components, organic and change-oriented management, and transdisciplinary education. First, we will need to understand how non-technical and technical forces interact to lock in infrastructure, and create path dependencies.

This report has been advanced to a peer-reviewed journal publication:
Mikhail Chester and Braden Allenby, 2008, Toward adaptive infrastructure: flexibility and agility in a non-stationarity age, Sustainable and Resilient Infrastructure, pp. 1-19, DOI: 10.1080/23789689.2017.1416846.