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Decision support tools (DSTs) are a means to facilitate science-based conservation planning. Technical advancements in conservation science, the pragmatic needs of conservation planning, and government support for collaborative initiatives such as the Conservation Effects Assessment Project (CEAP), have contributed to evaluation and development of both existing and new DSTs. Much of current scholarship on DSTs, however, focuses on their uptake by farmers and their crop advisors. Limited, to almost no, attention has been paid to the education and training needs of conservation agency staff—the primary users of these tools. To address this knowledge gap, we conducted an online survey of staff in conservation agencies that are located in counties that either currently include or included a CEAP Watershed Assessment Study site. We found that agency staff did not use all DSTs, and not all DSTs we surveyed were equally popular with respect to their usage and awareness. The desired technical roles of DSTs included conservation targeting, watershed assessment and planning, and quantifying environmental and financial benefits of conservation practices. The desired stakeholder engagement roles of DSTs included facilitating engagement with watershed stakeholders, educating farmers about areas of concern in the watershed, and facilitating engagement with farmers one-on-one and in a group setting. By applying the Reasoned Action Approach framework, we found that DST users and nonusers are not only differently skilled, but also perceive barriers related to learning about and using DSTs differently. Taken together, our findings suggest the need for future research on establishing a deeper understanding of conservation agency staffs9 skills, attitudes, perceived norms, behavioral limitations, and intentions toward using DSTs, in order to refine future training and education to better meet needs.

Summary In the ongoing debate about the climate benefits of fuel switching from coal to natural gas for power generation, the metrics used to model climate impacts may be important. In this article, we evaluate the life cycle greenhouse gas emissions of coal and natural gas used in new, advanced power plants using a broad set of available climate metrics in order to test for the robustness of results. Climate metrics included in the article are global warming potential, global temperature change potential, technology warming potential, and cumulative radiative forcing. We also used the Model for the Assessment of Greenhouse-gas Induced Climate Change (MAGICC) climate-change model to validate the results. We find that all climate metrics suggest a natural gas combined cycle plant offers life cycle climate benefits over 100 years compared to a pulverized coal plant, even if the life cycle methane leakage rate for natural gas reaches 5%. Over shorter time frames (i.e., 20 years), plants using natural gas with a 4% leakage rate have similar climate impacts as those using coal, but are no worse than coal. If carbon capture and sequestration becomes available for both types of power plants, natural gas still offers climate benefits over coal as long as the life cycle methane leakage rate remains below 2%. These results are consistent across climate metrics and the MAGICC model over a 100-year time frame. Although it is not clear whether any of these metrics are better than the others, the choice of metric can inform decisions based on different societal values. For example, whereas annual temperature change reported may be a more relevant metric to evaluate the human health effects of increased heat, the cumulative temperature change may be more relevant to evaluate climate impacts, such as sea-level rise, that will result from the cumulative warming.

Summary Potable residential water efficiency and reuse technologies have seen increasing adoption in recent years and have been estimated to reduce demands by up to 50%. In this work, we used an engineering economic model to estimate the technically feasible levelized cost of water provided by seven above-code water efficiency (i.e., beyond that required by building code) and reuse technologies within the Lower Colorado River Authority (LCRA) in central Texas. Unlike other demand-side studies of residential water use, we model uncertainty and variation in technology adoption cost and performance; include reuse technologies; and differentiate between new construction and retrofits. We developed a conservation supply curve to compare the levelized cost of efficiency and reuse technologies with conventional supply-side water management strategies. We estimate that efficiency and reuse in the residential sector can meet 85% of 50-year projected needs (the difference between projected demand and estimated supplies) for the LCRA service area. We also estimate lower levelized costs for immediate retrofits of most technologies, promoting incentives for early technology adoption. However, efficiency and reuse technology performance demonstrates considerable uncertainty and variability. The fraction of demands met by demand-side strategies range from around 60% to 100%. Occupancy drives much of the variability because it significantly affects demand. These results promote designing incentives for adoption of water efficiency and reuse technologies based upon use. We find that water-efficient showerheads and bathroom faucet aerators perform well over a variety of assumptions, indicating that these technologies should be a priority for municipalities seeking water demand reductions.

Most thermoelectric power plants in the United States (U.S.) rely on fresh water for cooling, resulting in significant water consumption. An understanding of the regional and seasonal water stress impact of such water consumption is needed. In this study, we used a U.S. county-level water stress index, Available Water Remaining for the United States (AWARE-US), with facility-level thermoelectric power generation water consumption data, to quantify the regional and seasonal water stress impact of U.S. thermoelectric power plants. Water stress impact was evaluated as water-scarcity footprint (WSF) using monthly AWARE-US data. Results show that most thermoelectric power plants in the United States that use fresh water are in water-abundant regions. Our findings also show that a small fraction of the U.S. thermoelectric generation facilities (13% by power) located in water stressed regions contribute the most water stress impact (88% of the total WSF) caused by thermoelectric power generation in the U.S. Even if fresh water is abundant on an annual basis, many power plants are in counties with seasonal water shortages. Of the 401 counties with thermoelectric power plants using fresh water for cooling, 80 counties in February and 160 counties in August had fresh water withdrawal requirements that exceeded the sustainable fresh water available (availability minus demand or AMD) in that region. This means that 27% and 46% of power generation facilities have difficulty securing sustainable fresh water in February and August, respectively. This study is intended to support water consumption management in existing power plants and guide the deployment of future power plants to mitigate water stress impact.

Understanding opportunities for carbon capture and storage (CCS) across sectors is important for choosing among greenhouse gas mitigation strategies. This study explores the cradle-to-gate life cycle environmental impacts of amine solvent based carbon capture systems on U.S. ammonia production, petroleum refineries, supercritical and subcritical pulverized coal power plants, and natural gas combined cycle plants. We use publicly available data to create comprehensive life cycle inventories for petroleum refining and ammonia production for 2014. We use these processes and additional modeled carbon capture processes to compare carbon capture on ammonia production and petroleum refining to inventories for coal and natural gas fired electricity with carbon capture. This analysis found that particulate matter formation potential, eutrophication potential, and water consumption increase in all sectors as a result of installation and operation of CCS technologies per kg CO2e abated, while the effect on acidification potential and particulate mater formation potential is mixed. The differences in tradeoffs among systems are driven primarily by three factors: the combustion emissions from fuel used to operate the capture unit, the upstream supply chain to obtain that fuel, and the relative impact of the carbon capture unit on baseline flue gas emissions (i.e. possible co-benefits from capture).

Residential electricity users need more detail than monthly bills to reduce consumption. With the emergence of technologies that provide detailed usage estimates for energy consumption, two questions arise. First, how many different energy-consuming appliances contribute to household electricity load, and secondly which appliances? Using national average penetration rates, the Residential Energy Consumption Survey (RECS), estimates that 42 unique appliances account for 93% of electricity consumption, while 12 appliances account for 80% of average household electric load. A typical scenario is developed from national and regional penetration rates and find that eight appliances are responsible for 80% of a household's electric load in the United States. Four household scenarios are developed: a house that uses electric appliances, gas appliances, the average household, and typical household. It is concluded that RECS cannot be used as a representative household as it overestimates the number of appliances that contribute to a household electric load. The number of significant appliances is affected by appliance ownership and use, which is more variable between homes than between census divisions. These results can be used to design and maximize the value of residential energy information and management systems.

AS greenhouse gas emissions from human activities continue to increase; it has become clear that our current trajectory is not sustainable. It is also apparent that current state, national, and international policies individually are not sufficient to meet the greenhouse gas emissions reductions recommended by the Intergovernmental Panel on Climate Change (IPCC). The fourth assessment report by the IPCC calls for greenhouse gas emissions rates that are 50%–80% of those experienced in year 2000 in order to stabilize atmospheric carbon dioxide levels [1]. It is my hypothesis that from a life cycle perspective, one vitally important factor that has the potential to reduce greenhouse gas emissions more rapidly than the integration of renewable and low carbon energy sources into our energy production mix is energy efficiency improvements by industrial, commercial, and residential consumers. Further research using life cycle assessment models illustrates the effectiveness of well constructed policy that stimulates real energy efficiency improvements as part of a long term comprehensive plan to reduce greenhouse gas emissions. It is also used to determine whether policies that encourage energy efficiency improvements, for example mandatory carbon labels for products, are more or less effective at meeting greenhouse gas reductions in both the short term and long term future than other popular current or potential policies and technologies such as low-carbon fuel and renewable energy mandates.