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DOE OSTI2024

Trends, Insights, and Considerations for Agrivoltaics in the Northeast: Applying National Lessons Learned to the Case of Pennsylvania

There are unique challenges and opportunities at the nexus of agriculture and energy. This presentation will feature a social science overview of agrivoltaics, which is the practice of combining solar energy and agricultural production on the same land. Centering on recent research and commercial insights, this presentation will discuss the implications of lessons learned in the Northeast and highlight key considerations for future agrivoltaic R&D in Pennsylvania.

agriculture↗
DOE OSTI2024

Enhancing risk and crisis communication with computational methods: A systematic literature review

Abstract Recent developments in risk and crisis communication (RCC) research combine social science theory and data science tools to construct effective risk messages efficiently. However, current systematic literature reviews (SLRs) on RCC primarily focus on computationally assessing message efficacy as opposed to message efficiency. We conduct an SLR to highlight any current computational methods that improve message construction efficacy and efficiency. We found that most RCC research focuses on using theoretical frameworks and computational methods to analyze or classify message elements that improve efficacy. For improving message efficiency, computational and manual methods are only used in message classification. Specifying the computational methods used in message construction is sparse. We recommend that future RCC research apply computational methods toward improving efficacy and efficiency in message construction. By improving message construction efficacy and efficiency, RCC messaging would quickly warn and better inform affected communities impacted by current hazards. Such messaging has the potential to save as many lives as possible.

Mathematical Methods In Social Sciences↗
DOE OSTI2024

Wind Energy Accomplishments and Year-End Performance Report: Fiscal Year 2024

As the largest source of clean, renewable power generation in the United States and one of the fastest growing sources of new electricity supply, wind energy will play a large role in the nation's energy future. In Fiscal Year (FY) 2024, scientists, engineers, analysts, and support professionals at the U.S. Department of Energy's (DOE's) National Renewable Energy Laboratory (NREL) worked to accelerate the pace of innovation in wind energy science and technology, advance grid systems integration, and develop sustainable solutions to deployment challenges. Much of NREL's research, development, and deployment work aligns with addressing the Grand Challenges of Wind Energy. Beginning in 2019, DOE's Wind Energy Technologies Office partnered with the International Energy Agency to identify the barriers to greater wind energy deployment and related research gaps. The world's leading wind energy scientists and engineers identified five research areas as critical to advancing wind energy deployment: wind atmospheric science, wind turbine systems, wind plants and grid, environmental co-design, and social science. In FY 2024, NREL's accomplishments helped narrow the research gaps in these critical areas. This report provides details on those accomplishments.

accomplishments↗
DOE OSTI2021

Basic Research Needs for Communicating Basic Science

Basic science—also known as discovery or foundational research—is the fuel that powers our innovation ecosystem and the global economy. Despite this critical role, public awareness for how and where basic research is done, how it is funded, and its need for sustainable support over the long term is negligible. The ability to engage broader publics in awareness and understanding of basic science is paramount if we are to maintain the research enterprise that has transformed the modern world. Communicating how the federal government stewards taxpayer dollars for basic science is also incumbent on the agencies and scientists who use public dollars for their research. However, science communication is a complex activity that requires advanced planning, resources, and skill. Therefore, it is important to understand what we know about communicating basic science to the broader publics, as well as what we do not know, to be strategic and better equipped for effective, meaningful engagement. To identify and explore knowledge gaps in our understanding of basic science communication, the Science Public Engagement Partnership (SciPEP), a public-private partnership of the U.S. Department of Energy (DOE) Office of Science and The Kavli Foundation, carried out a two-part landscape analysis: literature surveys of social science scholarship and a basic research needs conference.

96 KNOWLEDGE MANAGEMENT AND PRESERVATION↗
DOE OSTI2020

Editorial: Achieving Water-Energy-Food Nexus Sustainability: A Science and Data Need or a Need for Integrated Public Policy?

The benefits of addressing the water, energy, and food sectors in an integrated manner is gaining significant recognition. An integrated approach can provide improved resource use efficiencies, more coherent environmental policies, and an overall strategy for achieving sustainability in the three sectors, as outlined in the United Nations Sustainable Development Goals (SDG) 2 (Food), 6 (Water), and 7 (Energy). Societies are concerned with ensuring food security, avoiding wars over water, and creating opportunity by ensuring access to energy. To be effective, however, this approach needs to be adopted at all levels of societies including government, private and civil society and reinforced by management and planning methods. This special issue identifies different approaches that are either being conceptualized or tested to support the Water-Energy-Food (WEF) Nexus approach. The articles contribute to answering the question, “Is achieving Water-Energy-Food (WEF) Nexus Sustainability a science and data need or an integrated public policy need?” In either case, both natural and social sciences will need to combine to support science issues or integrated policy issues. The papers explore the ways in which science, data, and policy development could help to define integrative principles and policies for the three sectors. This approach could expand beyond the water, energy, and food sectors to include health, environment, trade, commerce, and international assistance thereby providing broad support to the SDGs. Moreover, this issue demonstrates that data combined with new technologies (tools and models) can support better decision-making when adopted by governments and the sectors.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

A Framework for Effective Science Communication and Outreach Strategies and Dissemination of Research Findings for Marine Energy Projects

Marine energy is an emerging renewable energy industry with the potential to produce 2300 terawatt-hours per year from resources within the United States. As development and testing of marine energy devices advance, regulatory and permitting decision-makers are concerned about the uncertainty surrounding the potential environmental effects resulting from the introduction of these novel devices in coastal and riverine environments. The Triton Initiative researches and provides recommendations for environmental monitoring technologies and methods to inform industry stakeholders with the data necessary to permit the testing of marine energy systems. Effective dissemination of the research findings is essential for improving the accessibility of data to stakeholders who may use the results to inform policy decisions, yet few frameworks for conducting science communications for marine energy projects exist. In this paper, we present tools, channels, and tactics for developing a science communication framework for marine energy projects, or similar areas of study, using the Triton Initiative’s pilot science communication program as a case study. By leveraging existing bodies of work in disciplines such as communications theory, marketing, public relations, and social science, the presented framework includes audience identification and analysis; channel development, including a website, blog, newsletter, social media, and webinars and presentations; and metrics for determining success. Outcomes from one year of Triton’s case study are presented, including the most effective tactics and lessons learned.

communication framework↗
DOE OSTI2023

Tackling Grand Challenges in Wind Energy through a Socio-Technical Perspective

Wind power has an important role to play in tackling climate change. Key challenges in wind energy science and innovation must be overcome to increase the penetration and capability of this technology. However, the success of these efforts heavily depends on how society engages with the development of wind power infrastructure. Consequently, grand challenges exist in both technical and social domains, yet little research has made substantial efforts in connecting them. Here we review the social science and humanities literature on wind energy to illustrate the social dimensions of previously identified technical challenges. We suggest that a socio-technical lens enables an interdisciplinary approach to overcome the prevalent tendency of silo thinking in wind energy research and use it to explore socio-technical grand challenges related to the design, planning, development, operational and end-of-life phases of wind energy. Finally, we provide an outlook for research, practice and innovation, including an interdisciplinary and socio-technical research agenda for wind energy science, renewable energy developments and science policy in general.

end-of-life↗
DOE OSTI2021

Psychosocial drivers of land management behaviour: How threats, norms, and context influence deforestation intentions

Understanding how private landholders make deforestation decisions is of paramount importance for conservation. Behavioural frameworks from the social sciences have a lot to offer researchers and practitioners, yet these insights remain underutilised in describing what drives landholders' deforestation intentions under important political, social, and management contexts. Using survey data of private landholders in Queensland, Australia, we compare the ability of two popular behavioural models to predict future deforestation intentions, and propose a more integrated behavioural model of deforestation intentions. We found that the integrated model outperformed other models, revealing the importance of threat perceptions, attitudes, and social norms for predicting landholders' deforestation intentions. Social capital, policy uncertainty, and years of experience are important contextual moderators of these psychological factors. Here, we conclude with recommendations for promoting behaviour change in this deforestation hotspot and highlight how others can adopt similar approaches to illuminate more proximate drivers of environmental behaviours in other contexts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Roadmap for the future of extreme wildfire events

Background Extreme wildfire events (EWEs) represent a growing threat globally, posing substantial risks to ecosystems, human communities, and infrastructure. Despite increased recognition of their ecological, social, and economic significance, current definitions of EWEs vary widely, reflecting disciplinary biases and regional contexts. This article emerges from an interdisciplinary workshop convened to reassess and refine the definition of EWEs, examine their impacts across ecological and social dimensions, and identify critical knowledge gaps impeding our understanding of these infrequent but important events. Results Our synthesis highlights significant limitations with existing definitions, particularly their reliance on subjective thresholds and their emphasis on extreme fire behavior alone. EWEs encompass a spectrum of complex, multi-dimensional phenomena that extend beyond immediate biophysical characteristics to include cumulative social, economic, and ecological impacts. These impacts often manifest over extended timeframes and include hazardous environmental contamination, severe geomorphic disturbances, ecosystem transformations, and unintended consequences of post-fire management actions. Current wildfire modeling frameworks inadequately capture these compounding factors, particularly the interactions among social systems, ecological conditions, and extreme fire behavior. To overcome these issues, we advocate for an interdisciplinary and context-sensitive approach to defining and studying EWEs. This revised definition emphasizes wildfires exhibiting anomalies in fire behavior, ecological outcomes, or social impacts relative to historically observed baselines, accommodating variability across different geographic regions and ecological settings. Conclusions Adopting an interdisciplinary framework that integrates biophysical and social sciences will enhance the predictive capability of wildfire models and improve resilience planning and response strategies. Filling identified knowledge gaps—such as limited high-quality empirical fire behavior data and insufficient integration of social dynamics into modeling—will better prepare communities and ecosystems to cope with and adapt to EWEs. This inclusive approach underscores the necessity for collaboration across disciplines and sectors, essential to managing extreme wildfires in an era of increasing climatic and ecological uncertainty.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Of Actors, Cities and Energy Systems: Advancing the Transformative Potential of Urban Electrification

The electrification of transportation and the integration of electric vehicles (EVs) with buildings connected to clean grids has been touted as one of the key solutions to the global decarbonization challenge. Cities are on the frontlines of current and future electrification, as they depend on and drive electricity generation, distribution, and use. City actors also occupy a central role in the actions to enable electrification to support energy transitions in efficient, equitable, environmentally sound, and resilient ways. Currently, however, research and development on the interactions between actors, cities and energy systems is predominantly conducted in disciplinary siloes. This topical review analyzes the transformational potential of urban electrification. It focuses on efforts to electrify transportation and integrate EVs with buildings connected to a clean grid. We find that actions in these area are driving change; they are adopted by wealthier populations and on an experimental basis by specific communities. Their larger-scale growth is constrained by institutional, behavioral, and infrastructural factors. We also find that existing siloed disciplinary approaches are often incompatible with advancing holistic research. To achieve that, divergent communities of scholars need to come together to integrate their research and create broader perspectives. Through incorporation of the social sciences, these perspectives need to consider the societal limits and potentials brought to bear by human behavior and decision making. Only then can urban electrification be understood as the empirically rich and socially complex topic that it is. And only with this understanding will innovations and smart policy actions be able to tap into the transformational potential of urban electrification.

cities↗
DOE OSTI2022

Addressing Uncertainty in MultiSector Dynamics Research

MultiSector Dynamics (MSD) research explores the dynamics and co-evolutionary pathways of human and Earth systems and the emerging interdependent sectors of energy, water, agriculture, and transportation among others. The interactions between these sectors are central to MSD science, as they capture how processes and feedbacks across Earth, environmental, infrastructure, and societal systems shape transitions, socioeconomic risks, and the provision of services. By definition, MSD research requires deep integration across diverse scientific disciplines, ranging from the natural to the social sciences and engineering. All these disciplines apply a variety of numerical simulation models to study and understand their underlying systems of focus. The utility of these models hinges on the fidelity with which they represent the real systems and their ability to produce novel insights about systems and their interactions. The coupled human-natural systems typically represented are shaped by a multitude of interdependent human and natural processes which, when modeled, translate to highly complex, non-linear, interacting behaviors. This ever-increasing complexity massively expands the uncertainty space of a model and can be found in model inputs, processes and parameters. This is further amplified when several models are combined to answer multisectoral questions, as additional uncertainty regarding coupling relationships and interactions is introduced.

IM3, Uncertainty and Sensitivity Analysis, multise↗
DOE OSTI2020

Post Conference Activities for the NCSE 2019 Annual Conference: Sustainable Infrastructure & Resilience

The National Council for Science and the Environment (NCSE) held its 19th Annual Conference from January 7-10, 2019. The NCSE 2019 Annual Conference: Sustainable Infrastructure & Resilience explored how systems thinking that includes tools, data, and synthesis effectively supports the increasingly urgent need to advance a more resilient, sustainable society. Nearly 600 participants from a range of scientific disciplines and sectors including natural and social science, humanities, engineering, government, business, and civil society attended the conference. Post-conference activities planned through this project were planned to extend the impact of the Annual Conference and were made possible through support from the Department of Energy. These efforts included: 1) developing and producing a research pilot on Energy Systems and Resilient Infrastructure, which advances research focused on the better alignment of education and workforce needs with respect to energy resilience; 2) facilitating dialogue and in-person convenings with the Energy Education Community of Practice across the broader NCSE research community; and 3) designing and hosting a webinar series focused on the role of science in infrastructure and resilience. This report summarizes the outcomes of the proposed activities and additional work made possible by support from the Department of Energy.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Explaining and predicting human behavior and social dynamics in simulated virtual worlds: reproducibility, generalizability, and robustness of causal discovery methods

Ground Truth program was designed to evaluate social science modeling approaches using simulation test beds with ground truth intentionally and systematically embedded to understand and model complex Human Domain systems and their dynamics Lazer et al. (Science 369:1060–1062, 2020). Our multidisciplinary team of data scientists, statisticians, experts in Artificial Intelligence (AI) and visual analytics had a unique role on the program to investigate accuracy, reproducibility, generalizability, and robustness of the state-of-the-art (SOTA) causal structure learning approaches applied to fully observed and sampled simulated data across virtual worlds. In addition, we analyzed the feasibility of using machine learning models to predict future social behavior with and without causal knowledge explicitly embedded. In this paper, we first present our causal modeling approach to discover the causal structure of four virtual worlds produced by the simulation teams—Urban Life, Financial Governance, Disaster and Geopolitical Conflict. Our approach adapts the state-of-the-art causal discovery (including ensemble models), machine learning, data analytics, and visualization techniques to allow a human-machine team to reverse-engineer the true causal relations from sampled and fully observed data. We next present our reproducibility analysis of two research methods team’s performance using a range of causal discovery models applied to both sampled and fully observed data, and analyze their effectiveness and limitations. We further investigate the generalizability and robustness to sampling of the SOTA causal discovery approaches on additional simulated datasets with known ground truth. Our results reveal the limitations of existing causal modeling approaches when applied to large-scale, noisy, high-dimensional data with unobserved variables and unknown relationships between them. We show that the SOTA causal models explored in our experiments are not designed to take advantage from vasts amounts of data and have difficulty recovering ground truth when latent confounders are present; they do not generalize well across simulation scenarios and are not robust to sampling; they are vulnerable to data and modeling assumptions, and therefore, the results are hard to reproduce. Finally, when we outline lessons learned and provide recommendations to improve models for causal discovery and prediction of human social behavior from observational data, we highlight the importance of learning data to knowledge representations or transformations to improve causal discovery and describe the benefit of causal feature selection for predictive and prescriptive modeling.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2021

Position Papers for the ASCR Workshop on the Science of Scientific-Software Development and Use

Software is an increasingly important component in the pursuit of scientific discovery. Both its development and use are essential activities for many scientific teams. At the same time, very little scientific study has been conducted to understand, characterize, and improve the development and use of software for science. Computational science teams have diversified over time to include contributions from domain scientists who provide expertise in scientific and engineering disciplines, applied mathematicians and computer scientists who provide optimal algorithms and data structures, and software and data engineers who provide methodologies and tools adapted and adopted from other software domains. These diverse contributions have enabled tremendous advances in the pursuit of scientific discovery, even as models, computer architectures, and software environments have become more complicated. With this increasing diversity, we believe the next opportunity for qualitative improvement comes from applying the scientific method to understanding, characterizing, and improving how scientific software is developed and used. We believe that this pursuit requires expertise from computational scientists themselves, and from the cognitive and social sciences as well as the software engineering research community. As we look to increase the productivity and sustainability of the scientific-software-development-and-use cycle, a more systematic application of the scientific method to understand processes for software development and use will be a valuable tool to guide future work and result in more usable and sustainable software. This workshop will bring together computer scientists, software engineering researchers, computational scientists, applied mathematicians, social scientists, cognitive scientists, and others, to explore how we can conduct such systematic investigations, what can be learned, and how doing so will benefit the scientific enterprise. The workshop will be structured around a set of breakout sessions, with every attendee expected to participate actively in the discussions. Afterward, workshop attendees — from DOE, industry, and academia — will produce a report for ASCR that summarizes the findings of the workshop.

42 ENGINEERING↗
DOE OSTI2026

The UCAR Africa Initiative: Recent insights, challenges, and opportunities to foster collaborative research for environmental sustainability

Africa is increasingly being exposed to the negative impacts of climate and environmental change, while having less capacity to respond compared to other continents. The vulnerability partially results from unprecedented demographic growth, urbanization, and industrialization. However, the continent has still largely been underserved by the broader Earth System Science (ESS) community, as evidenced by the limited amount of ESS data and research that cover Africa compared to other areas of the world. Here we present the recent University Corporation for Atmospheric Research (UCAR) Africa Initiative that aims to enhance environmental sustainability in Africa by fostering international collaborative research partnerships co-led by African scientists. Specifically, we outline urgent challenges and opportunities identified through an international workshop in six areas of ESS namely (1) air quality and health, (2) weather, (3) climate, (4) land and water, (5) social science perspectives, and (6) developing equitable collaboration and sustainable infrastructure. We highlight examples of successful partnerships and conclude with recommendations to advance collaborative, actionable ESS research that addresses Africa’s critical environmental challenges.

African weather and land variability↗
DOE OSTI2023

Think before you throw! An analysis of behavioral interventions targeting PET bottle recycling in the United States

The United States generates 42 Mt of plastic waste each year and is one of the biggest contributors to ocean plastic waste. Consequently, plastic has become synonymous with the linear economy, and many scholars are studying and proposing circular economy solutions to mitigate plastic pollution. Recycling has received much attention from both social sciences and engineering as a circular economy strategy, but no study has yet quantified how behavioral interventions could asymmetrically affect different populations. Here, this study combines agent-based modeling, material flow analysis, system dynamics, and life cycle assessment to assess the effect of four behavioral interventions on the collection rates of polyethylene terephthalate bottle waste, displaced virgin plastic manufacturing, and avoided greenhouse gas (GHG) emissions. Results show that, while behavioral interventions would require about 300–900 GJ of additional energy at end-of-life due to improved collection rates, they would avoid about 500–700 thousand metric tons of GHG emissions. Results also illustrate the importance of habits in disposal behaviors and show that different forms of interventions can be better adapted to particular social contexts than others. While the circular economy and its application to plastic waste should certainly not be restricted to recycling, this study demonstrates that improved collection rates and recycling technologies can contribute to reducing the amount of plastic waste polluting our oceans.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2021

Who is marginalized in energy justice? Amplifying community leader perspectives of energy transitions in Ghana

There is a divide in energy access studies, between technologically-focused modeling papers in engineering and economics, and energy justice frameworks and principles grounded in social sciences. Quantitative computational models are necessary when analyzing energy, and more specifically electricity, systems, as they are technologically-complex systems that can diverge from intuitive patterns. To assure energy justice, these models must be reflective of, and informative to, a wide range of stakeholders, including households and communities alongside utilities, governments, and others. Yet, moving from a qualitative understanding of preferences to quantitative modeling is challenging. In this perspective piece, we pilot the use of the value-focused thinking framework to inform stakeholder engagement. The result is a strategic objective hierarchy that highlights the tradeoffs and the social, economic and technological factors that need to be measured in models. We apply the process in Ghana, using a survey, stakeholder workshops, and follow-up interviews to uncover key tradeoffs and stakeholder-derived objectives. We discuss three key areas that have been rarely, if ever, well-represented in energy models: (1) the relationship between the dynamics of electricity end-use and the technology and economic structure of the system; (2) explicit tradeoffs between electricity access, cost, and reliability as defined by stakeholders; and (3) the definition of new objectives, such as minimizing hazards related to theft. We conclude that this model of engagement provides an opportunity to tie together rigorous qualitative analysis and stakeholder engagement with crucial quantitative models of the electricity system.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗