Achieving Realistic Energy and Greenhouse Gas Emission Reductions in U.S. Cities

In recognizing that energy markets and greenhouse gas emissions are significantly influences by local factors, this research examines opportunities for achieving realistic energy greenhouse gas emissions from U.S. cities through provisions of more sustainable infrastructure. Greenhouse gas reduction opportunities are examined through the lens of a public program administrator charged with reducing emissions given realistic financial constraints and authority over emissions reductions and energy use. Opportunities are evaluated with respect to traditional public policy metrics, such as benefit-cost analysis, net benefit analysis, and cost-effectiveness.;Section 2 summarizes current practices used to estimate greenhouse gas emissions from communities. I identify improved and alternative emissions inventory techniques such as disaggregating the sectors reported, reporting inventory uncertainty, and aligning inventories with local organizations that could facilitate emissions mitigation. The potential advantages and challenges of supplementing inventories with comparative benchmarks are also discussed. Finally, I highlight the need to integrate growth (population and economic) and business as usual implications (such as changes to electricity supply grids) into climate action planning. I demonstrate how these techniques could improve decision making when planning reductions, help communities set meaningful emission reduction targets, and facilitate CAP implementation and progress monitoring.;Section 3 evaluates the costs and benefits of building energy efficiency are estimated as a means of reducing greenhouse gas emissions in Pittsburgh, PA and Austin, TX. Two policy objectives were evaluated: maximize GHG reductions given initial budget constraints or maximize social savings given target GHG reductions. This approach explicitly evaluates the trade-offs between three primary and often conflicting program design parameters: initial capital constraints, social savings, and GHG reductions. Results suggest uncertainty in local stocks, demands, and efficiency significantly impacts anticipated outcomes. Annual greenhouse gas reductions of 1 ton CO2 eq/capita/yr in Pittsburgh could cost near nothing or over ;Section 4 evaluates the life cycle assessment costs and benefits of the widespread retrofit of green roofs in a typical urban mixed-use neighborhood. Shadow-cost analysis was used to evaluate the cost-effectiveness of green roofs' many benefits. Results suggest green roofs are currently not cost effective on a private cost basis, but multi-family and commercial building green roofs are competitive when social benefits are included. Multifamily and commercial green roofs are also competitive alternatives for reducing greenhouse gases and storm water run-off. However, green roofs are not competitive energy conservation techniques. GHG impacts are dominated by the material production and use phases. Energy impacts are dominated by the use phase, with urban heat island (UHI) impacts being an order of magnitude higher than direct building impacts. Results highlight the importance of clarifying sustainable infrastructure costs and benefits across many public and private organizations (e.g., private building owners, storm water agencies, efficiency stakeholders, and roofing contractors) to identify appropriate incentives and effective program design strategies.;Section 5 synthesizes the work and provides guidance for local and state sustainability program administrators. Section 5 highlights the unrealized social benefits associated with sustainability and reflects upon the role of local and state governments in overcoming barriers to achieving more sustainable infrastructure. Section 5 encourages program administrators to consider their local markets for sustainability as influences by resource pricing, weather, infrastructure condition, jurisdiction, and other factors. The differences between sustainability programming and traditional municipal programming are highlighted, namely that sustainability programming often requires self-selection for participation and is subject to new sources of uncertain regarding user behavior, technology breadth and change, and the scope of costs and benefits. These characteristic issues of sustainable infrastructure opportunities provide new challenges to program administrators, requiring new paradigms and support resources. (Abstract shortened by UMI.)...