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This guidebook is a synthesis of existing reports and data to provide insights into the state of energy storage for renewable energy sources. This guide is for people who have or are interested in investing in renewable energy battery storage to power their homes, businesses, or community spaces. In it, we'll walk you through how the US electricity grid operates, how renewable energy generated by homes and buildings works alongside it, and how investing in battery storage for renewable energy can optimize resources and help protect communities against power outages. We'll also overview the different technologies available for storing renewable energy for future use and the partners, costs, and steps involved with installing an energy storage battery. Recent case studies from three sites in Minnesota, a state without fossil fuel reserves yet rich in renewable resources, illustrate how energy storage batteries help aid in the resilience of communities and the health of the planet by reducing reliance on fossil fuels. ; This guide is for people who have or are interested in investing in renewable energy batteries to power their homes, businesses, or community spaces. In it, we'll walk you through how the US electricity grid operates, how renewable energy generated by homes and buildings works alongside it, and how investing in battery storage for renewable energy can optimize resources and help protect communities against power outages. We'll also overview the different technologies available for storing renewable energy for future use and the partners, costs, and steps involved with installing an energy storage battery. Recent case studies from three sites in Minnesota, a state without fossil fuel reserves yet rich in renewable resources, illustrate how energy storage batteries help aid in the resilience of communities and the health of the planet by reducing reliance on fossil fuels. ; Funding for this project (ML2018 07b) was provided by the Minnesota Environment and Natural Resources Trust Fund as recommended by the Legislative-Citizen Commission on Minnesota Resources (LCCMR).

As probability elicitation becomes widely used, methods other than one-on-one interviews are being used to elicit expert probabilities. This paper considers biases that may arise when probabilities are elicited in an online or workbook setting. We develop a prescriptive model in which the elicited probability is a convex combination of the expert's underlying probability with elements of partition dependence and two anchors arising from responses to previous questions ("carryover" bias). Our model, applied to two data sets, allows us to estimate the amount of the various biases in a set of elicited probabilities from experts. We find that both the format of the questions—whether they appear on the same or separate pages/screens—and the ordering of the questions can affect the amount of bias. Our research addresses biases in the presence of multiple anchors and provides guidance on manipulating the availability of anchors. The results demonstrate the persistence of anchoring even with careful questionnaire design; thus, the proposed model-based methods are useful to suggest corrections for the resulting biases.

Decision analysis provides a robust framework for complex decisions related to environmental sustainability and conservation, including for energy and water, fisheries and wildlife management, agriculture, and climate change response. The complexities of these problems stem from their large scope and scale, which leads to multiple decision makers, stakeholders, rightsholders, and other entities with potentially competing objectives. These problems often are time limited (e.g., urgent action is required to prevent species' extinction), involve management interventions over long time scales and delayed responses to management (deep uncertainty), and are impeded by limited resources (funding, capacity, etc.). In this Special Issue on "Decision Analysis to Advance Environmental Sustainability," we present five case studies of applications of decision analysis to complex problems in environmental sustainability and conservation. These case studies incorporate multiple objectives related to ecological and environmental sustainability, economic and social concerns, and logistics of implementation. They showcase a wide range of tools and applications to these problems. We also provide suggestions for new avenues of research and application of decision analysis to problems of environmental sustainability and conservation, including how to incorporate other decision-making tools into decision analysis processes, how to broaden the reach of decision analysis to other sustainability problems, how to incorporate more stakeholders and rightsholders into the decision process, the potential to incorporate new technology into these processes, identifying more creative alternatives, how to secure more funding, ways to move from decision to action, and how to move beyond status quo to make big transitions necessary to achieve sustainability.

AbstractVisually communicating temperature and precipitation climate outlook graphics is challenging because it requires the viewer to be familiar with probabilities as well as to have the visual literacy to interpret geospatial forecast uncertainty. In addition, the visualization scientific literature has open questions on which visual design choices are the most effective at expressing the multidimensionality of uncertain forecasts, leaving designers with a lack of concrete guidance. Using a two-phase experimental setup, this study shows how recently developed visualization diagnostic guidelines can be used to iteratively diagnose, redesign, and test the understandability the U.S. National Oceanic and Atmospheric Administration (NOAA) Climate Prediction Center (CPC) climate outlooks. In the first phase, visualization diagnostic guidelines were used in conjunction with interviews and focus groups to identify understandability challenges of existing visual conventions in temperature and precipitation outlooks. Next, in a randomized control versus experimental treatment setup, several graphic modifications were produced and tested via an online survey of end users and the general public. Results show that, overall, end users exhibit a better understanding of outlooks, but some types of probabilistic color mapping are misunderstood by both end users and the general public, which was predicted by the diagnostic guidelines. Modifications lead to significant gains in end-user and general public understanding of climate outlooks, providing additional evidence for the utility of using control versus treatment testing informed by visualization diagnostics.