Current policies subsidizing or accelerating deployment of photovoltaics (PV) are typically motivated by claims of environmental benefit, such as the reduction of CO2 emissions generated by the fossil-fuel fired power plants that PV is intended to displace. Existing practice is to assess these environmental benefits on a net life-cycle basis, where CO2 benefits occurring during use of the PV panels is found to exceed emissions generated during the PV manufacturing phase including materials extraction and manufacture of the PV panels prior to installation. However, this approach neglects to recognize that the environmental costs of CO2 release during manufacture are incurred early, while environmental benefits accrue later. Thus, where specific policy targets suggest meeting CO2 reduction targets established by a certain date, rapid PV deployment may have counter-intuitive, albeit temporary, undesired consequences. Thus, on a cumulative radiative forcing (CRF) basis, the environmental improvements attributable to PV might be realized much later than is currently understood. This phenomenon is particularly acute when PV manufacture occurs in areas using CO2 intensive energy sources (e.g., coal), but deployment occurs in areas with less CO2 intensive electricity sources (e.g., hydro). This thesis builds a dynamic Cumulative Radiative Forcing (CRF) model to examine the inter-temporal warming impacts of PV deployments in three locations: California, Wyoming and Arizona. The model includes the following factors that impact CRF: PV deployment rate, choice of PV technology, pace of PV technology improvements, and CO2 intensity in the electricity mix at manufacturing and deployment locations. Wyoming and California show the highest and lowest CRF benefits as they have the most and least CO2 intensive grids, respectively. CRF payback times are longer than CO2 payback times in all cases. Thin film, CdTe PV technologies have the lowest manufacturing CO2 emissions and therefore the shortest CRF payback times. This model can inform policies intended to fulfill time-sensitive CO2 mitigation goals while minimizing short term radiative forcing.

Water resource management is becoming increasingly burdened by uncertain and fluctuating conditions resulting from climate change and population growth which place increased demands on already strained resources. Innovative water management schemes are necessary to address the reality of available water supplies. One such approach is the substitution of trade in virtual water for the use of local water supplies. This study provides a review of existing work in the use of virtual water and water footprint methods. Virtual water trade has been shown to be a successful method for addressing water scarcity and decreasing overall water consumption by shifting high water consumptive processes to wetter regions. These results however assume that all water resource supplies are equivalent regardless of physical location and they do not tie directly to economic markets. In this study we introduce a new mathematical framework, Embedded Resource Accounting (ERA), which is a synthesis of several different analytical methods presently used to quantify and describe human interactions with the economy and the natural environment. We define the specifics of the ERA framework in a generic context for the analysis of embedded resource trade in a way that links directly with the economics of that trade. Acknowledging the cyclical nature of water and the abundance of actual water resources on Earth, this study addresses fresh water availability within a given region. That is to say, the quantities of fresh water supplies annually available at acceptable quality for anthropogenic uses. The results of this research provide useful tools for water resource managers and policy makers to inform decision making on, (1) reallocation of local available fresh water resources, and (2) strategic supplementation of those resources with outside fresh water resources via the import of virtual water.

Cities around the globe struggle with socio-economic disparities, resource inefficiency, environmental contamination, and quality-of-life challenges. Technological innovation, as one prominent approach to problem solving, promises to address these challenges; yet, introducing new technologies, such as nanotechnology, into society and cities has often resulted in negative consequences. Recent research has conceptually linked anticipatory governance and sustainability science: to understand the role of technology in complex problems our societies face; to anticipate negative consequences of technological innovation; and to promote long-term oriented and responsible governance of technologies. This dissertation advances this link conceptually and empirically, focusing on nanotechnology and urban sustainability challenges. The guiding question for this dissertation research is: How can nanotechnology be innovated and governed in responsible ways and with sustainable outcomes? The dissertation: analyzes the nanotechnology innovation process from an actor- and activities-oriented perspective (Chapter 2); assesses this innovation process from a comprehensive perspective on sustainable governance (Chapter 3); constructs a small set of future scenarios to consider future implications of different nanotechnology governance models (Chapter 4); and appraises the amenability of sustainability problems to nanotechnological interventions (Chapter 5). The four studies are based on data collected through literature review, document analysis, participant observation, interviews, workshops, and walking audits, as part of process analysis, scenario construction, and technology assessment. Research was conducted in collaboration with representatives from industry, government agencies, and civic organizations. The empirical parts of the four studies focus on Metropolitan Phoenix. Findings suggest that: predefined mandates and economic goals dominate the nanotechnology innovation process; normative responsibilities identified by risk governance, sustainability-oriented governance, and anticipatory governance are infrequently considered in the nanotechnology innovation process; different governance models will have major impacts on the role and effects of nanotechnology in cities in the future; and nanotechnologies, currently, do not effectively address the root causes of urban sustainability challenges and require complementary solution approaches. This dissertation contributes to the concepts of anticipatory governance and sustainability science on how to constructively guide nanotechnological innovation in order to harvest its positive potential and safeguard against negative consequences.

Life cycle assessment (LCA) is a powerful framework for environmental decision making because the broad boundaries called for prevent shifting of burden from one life-cycle phase to another. Numerous experts and policy setting organizations call for the application of LCA to developing nanotechnologies. Early application of LCA to nanotechnology may identify environmentally problematic processes and supply chain components before large investments contribute to technology lock in, and thereby promote integration of environmental concerns into technology development and scale-up (enviro-technical integration). However, application of LCA to nanotechnology is problematic due to limitations in LCA methods (e.g., reliance on data from existing industries at scale, ambiguity regarding proper boundary selection), and because social drivers of technology development and environmental preservation are not identified in LCA. This thesis proposes two methodological advances that augment current capabilities of LCA by incorporating knowledge from technical and social domains. Specifically, this thesis advances the capacity for LCA to yield enviro-technical integration through inclusion of scenario development, thermodynamic modeling, and use-phase performance bounding to overcome the paucity of data describing emerging nanotechnologies. With regard to socio-technical integration, this thesis demonstrates that social values are implicit in LCA, and explores the extent to which these values impact LCA practice and results. There are numerous paths of entry through which social values are contained in LCA, for example functional unit selection, impact category selection, and system boundary definition - decisions which embody particular values and determine LCA results. Explicit identification of how social values are embedded in LCA promotes integration of social and environmental concerns into technology development (socio-enviro-technical integration), and may contribute to the development of socially-responsive and environmentally preferable nanotechnologies. In this way, tailoring LCA to promote socio-enviro-technical integration is a tangible and meaningful step towards responsible innovation processes.

Life Cycle Assessment (LCA) quantifies environmental impacts of products in raw material extraction, processing, manufacturing, distribution, use and final disposal. The findings of an LCA can be used to improve industry practices, to aid in product development, and guide public policy. Unfortunately, existing approaches to LCA are unreliable in the cases of emerging technologies, where data is unavailable and rapid technological advances outstrip environmental knowledge. Previous studies have demonstrated several shortcomings to existing practices, including the masking of environmental impacts, the difficulty of selecting appropriate weight sets for multi-stakeholder problems, and difficulties in exploration of variability and uncertainty. In particular, there is an acute need for decision-driven interpretation methods that can guide decision makers towards making balanced, environmentally sound decisions in instances of high uncertainty. We propose the first major methodological innovation in LCA since early establishment of LCA as the analytical perspective of choice in problems of environmental management. We propose to couple stochastic multi-criteria decision analytic tools with existing approaches to inventory building and characterization to create a robust approach to comparative technology assessment in the context of high uncertainty, rapid technological change, and evolving stakeholder values. Namely, this study introduces a novel method known as Stochastic Multi-attribute Analysis for Life Cycle Impact Assessment (SMAA-LCIA) that uses internal normalization by means of outranking and exploration of feasible weight spaces.