Sonoma County, CA is on an ambitious pathway to meeting stringent carbon emissions goals that are part of California Assembly Bill 32. At the county-level, climate planners are currently evaluating options to assist residents of the county in reducing their carbon footprint and also for saving money. The Sonoma County Energy Independence Program (SCEIP) is one such county-level measure that is currently underway. SCEIP is a revolving loan fund that eligible residents may utilize to install distributed solar energy on their property. The fund operates like a property tax assessment, except that it only remains for a period of 20 years rather than in perpetuity.

This analysis intends to estimate the potential countywide effect that the $100M SCEIP fund might achieve on the C02 and cost footprint for the residential building energy sector. A functional unit of one typical home in the county is selected for a 25 year analysis period. Outside source data for the lifecycle emissions generated by the production, installation and operations of a PV system are utilized. Recent home energy survey data for the region is also utilized to predict a “typical” system size and profile that might be funded by the SCEIP program. A marginal cost-benefit calculation is employed to determine what size solar system a typical resident might purchase, which drives the life cycle assessment of the functional unit. Next, the total number of homes that might be financed by the SCEIP bond is determined in order to forecast the potential totalized effect on the County’s lifecycle emissions and cost profile.

The final results are evaluated and it is determined that the analysis is likely conservative in its estimation of the effects of the SCEIP program. This is due to the fact that currently offered subsidies are not utilized in the marginal benefit calculation for the solar system but do exist, the efficiency of solar technology is increasing, and the cost of a system over its lifecycle is currently decreasing. The final results show that financing distributed solar energy systems using Sonoma County money is a viable option for helping to meet state mandated goals and should be further pursued.

This LCA used data from a previous LCA done by Chester and Horvath (2012) on the proposed California High Speed Rail, and furthered the LCA to look into potential changes that can be made to the proposed CAHSR to be more resilient to climate change. This LCA focused on the energy, cost, and GHG emissions associated with raising the track, adding fly ash to the concrete mixture in place of a percentage of cement, and running the HSR on solar electricity rather than the current electricity mix. Data was collected from a variety of sources including other LCAs, research studies, feasibility studies, and project information from companies, agencies, and researchers in order to determine what the cost, energy requirements, and associated GHG emissions would be for each of these changes. This data was then used to calculate results of cost, energy, and GHG emissions for the three different changes. The results show that the greatest source of cost is the raised track (Design/Construction Phase), and the greatest source of GHG emissions is the concrete (also Design/Construction Phase).

The Food-Energy-Water (FEW) nexus is the interaction and the interdependence of the food, energy and water systems. These interdependencies exist in all parts of the world yet little knowledge exists of the complexity within these interdependent systems. Using Arizona as a case study, systems-oriented frameworks are examined for their value in revealing the complexity of FEW nexus. Industrial Symbiosis, Life Cycle Assessment (LCA) and Urban Metabolism are examined. The Industrial Symbiosis presents the system as purely a technical one and looks only at technology and hard infrastructure.

The LCA framework takes a reductionist approach and tries to make the system manageable by setting boundary conditions. This allows the frameworks to analyze the soft infrastructure as well as the hard infrastructure. The LCA framework also helps determine potential impact. Urban Metabolism analyzes the interactions between the different infrastructures within the confines of the region and retains the complexity of the system. It is concluded that a combination of the frameworks may provide the most insight in revealing the complexity of nexus and guiding decision makers towards improving sustainability and resilience.

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.