The decision theoretic life cycle assessment (DT-LCA) framework revolutionizes the way LCA is conducted by tightly coupling it with stakeholder decision-making through serious gaming. This will enable LCA to address important questions regarding how various human decision factors influence sustainability outcomes, and in turn, how sustainability outcomes influence decision-making. DT-LCA uses an immersive game-based approach to engage stakeholders in simplified but realistic decision scenarios. Unlike the deterministic LCA approach, DT-LCA simulates sustainability outcomes in an iterative, dynamic manner based upon actual decisions made by stakeholders during the game. It combines social experimenting, computer modeling, education, and outreach into one integrated framework. Particularly, this research uses DT-LCA to address the health, economic, and environmental aspects related to drinking water emergency planning and response. Decision factors including risk attitudes, interorganizational networks, and access to LCA results will be introduced into the game’s experimental design to investigate their influences on sustainability outcomes. 

This research seeks to develop understanding and knowledge of the resilience and sustainability of integrated centralized and decentralized water and energy systems under future demographic, climate, and technology scenarios. The project uses social science approaches to characterize individual preferences (utility functions) related to (de)centralization of water and energy infrastructure systems; a spatial agent-based model to develop spatially explicit adoption trajectories and patterns in accordance with utility functions and characteristics of the major metropolitan case study locations; and a system dynamics model that considers interactions among infrastructure systems, characterizes measures of resilience and sustainability, and feeds these back to the agent based model. Combined, they provide a robust capacity to consider the ways in which future development of energy and water resources can be more or less resilient, have fewer or greater environmental consequences, meet differential demands of human populations, and result in greater or lesser overall resource use. 

The research goal is to advance the understanding and integration of: 1) the trade-offs and dynamic behavior of dams in coupled social–ecological systems (SES); and 2) the ways in which SES and other knowledge are developed and used as knowledge systems (KS) to shape decision-making. Hydropower represents the largest source of clean energy in New England (NE). NE also has > 1,000 significant or high hazard dams, and 52 dams in ME, NH, and RI will require FERC relicensing in the next decade. This nexus offers a unique laboratory to develop and integrate new knowledge of dam-related SES dynamics with KS research to enhance science-based decision making.

This research aims to design, assess, and understand a novel and generalizable contest-based crowdsourcing scheme to engage the public in continuous yet random water quality monitoring activities at the consumer tap. The approach is intended to allow early response, risk management, and harm reduction in a public water quality crisis like Flint, MI. Two contests with different public recognition reward schemes, one that focuses on rewarding participants for the number of samples collected at different locations and another that focuses on rewarding participants for the number of new recruits to the program, were carried out in a testbed area. The experimental design of each contest includes online pre-contest surveys, sample collection by the participants, paper-based post-contest surveys and interviews, and centralized sample analysis at one lab facility. We used survey instruments to collect information regarding participants’ motivation, socioeconomic characteristics, and perceptions of the proposed scheme. The research facilitates identification and understanding of optimal program design features and demographic factors that influence outcomes related to data quality, use of science in decision-making, scientific literacy, and networking changes from contest-based crowdsourcing efforts.

As stormwater and its associated nutrients continue to impair our nation’s waterways, green infrastructure systems (GIs) are increasingly applied in urban and suburban communities as a sustainable remedy to combined sewer system overflows and controlling stormwater related pollutants from changing land uses and precipitation patterns. Although GIs have been widely studied for their life cycle impacts and benefits, most of these studies adopt a static approach which prevents that information from being scaled or transferred to different spatial and temporal settings. To overcome this limitation, this research combines system dynamics modeling with life cycle assessment to evaluate seven different GIs through both economic and environmental lenses. Evaluated impacts include cumulative energy demand, global warming potential, marine and freshwater eutrophication potentials, and life cycle costs. The base model was then expanded to assess different scenarios in terms of geographic locations, land uses, GI design sizes, and climate changes. Our results show these aforementioned factors have significant influences on GIs’ life cycle performances.