Steven A. Conrad

This dataset provides survey responses generated among agricultural water users on Colorado's West Slope. The dataset characterizes these water users' demographics, farm and ranch characteristics, attitudes towards water conservation activities, and stated preferences for water conservation program or policy attributes. Survey responses were collected in 2023 and 2024 over the Internet using the Qualtrics survey platform and through distribution of paper surveys to addresses associated with agricultural lands in Colorado counties located west of the Continental Divide. The dataset consists of responses from 573 individuals self-identified as agricultural water users.

Light-duty passenger electric vehicle (EV) adoption is widely anticipated to translate into sustained and continued use, thereby playing a central role in decarbonizing transportation. However, poor experiences could influence EV owners to reduce or abandon EV ownership after adoption. This paper investigates post-adoption EV Disengagement by synthesizing literature on continued use, under-utilization, and discontinuance, with a focus on the role of charging infrastructure and user experience. The paper identifies behavioral, economic, and infrastructural factors that erode continued EV use, influencing under-utilization and, in some circumstances, complete discontinuance. This paper harmonizes continuance and technology use theories to propose a conceptual framework for EV Disengagement that models post-adoption behavior through initial enthusiasm, barrier encounter, and continued use decisions. The findings highlight how charging infrastructure reliability, perceived inconveniences, and unmet expectations undermine sustained EV use. The disengagement framework has implications for infrastructure planning, policy, and projections of the EV market and environmental impacts.

Urban systems management requires analysing complex textual documentation that necessitates coding and analysis to set requirements and evaluate built environment performance. This study contributes to the research of applying large language models (LLMs) to qualitative coding activities, aiming to reduce resources while maintaining comparable reliability performing like humans. Qualitative coding faces challenges such as resource limitations, bias and consistency between evaluators. We report the application of LLMs to deductively code 10 case documents for 17 common characteristics for the management of urban systems. We utilise whole‐text analysis and text‐chunk analysis to compare the processing of LLMs with human coding efforts using three OpenAI models. Results indicate that LLMs may perform similarly to human coders when initialised with specific deductive coding contexts. GPT‐4o, o1‐mini and GPT‐4o‐mini showed significant agreement with human raters when using a chunking method. The application of GPT‐4o and GPT‐4o‐mini as additional raters with humans showed statistically significant agreement, indicating that the analysis of textual documents benefits from LLMs addition. The novel contribution of this paper is the domain‐specific evaluation of a chunk‐based prompting approach for deductive coding in urban systems management, validating human–AI teaming performance.

This paper suggests a comprehensive life cycle assessment (LCA) framework for agrivoltaic systems - systems that integrate photovoltaic energy and agricultural production. Agrivoltaics proposes a solution that provides additional land for meeting renewable energy goals while supporting agricultural production and water and land use efficiency. This study contributes to the assessment of the dynamic life cycle improvements associated with agrivoltaics installations through applying the framework to a case study at Jack's Solar Garden in Boulder, Colorado. We utilize the ReCIPe midpoint hierarchist method and leverage data from existing OpenLCA databases to evaluate the environmental and economic impacts of co-located crop production and solar energy generation. The results highlight the potential for reduced land and water use, underscoring agrivoltaics' role in managing land conflicts and water scarce environments. However, challenges such as increased material demands, limited open-source data, and the need for tailored configurations remain. Our framework aims to guide researchers, producers, and policymakers in making informed decisions on the adoption of agrivoltaics.

This paper addresses the equity and justice issues that are directly related to agrivoltaics, largely through the lens of farmers and other rural stakeholders, but also to some extent through the eyes of commercial developers. Though clearly different in nature, both small-scale and utility-scale projects must address the equity and justice concerns of stakeholder communities in order to be successful. Further, while the ideas and principles discussed here are mostly U.S.-centric, they still apply to similar settings around the globe. The paper first reviews the concept of energy justice, drawing a distinction between justice and equity. It then moves on to the ways in which equity and justice are more specifically realized in agrivoltaics applications. Some of the main equity and justice issues are identified, particularly as they constitute barriers (real or perceived) that detract from more rapid adoption and deployment of agrivoltaics technology. In addition, the paper considers the differences in equity and justice associated with non-rural agrivoltaics applications; and it concludes with some general principles that should be followed to ensure the development and deployment of this emerging technology achieves overall success.

Energy and water systems are deeply interdependent yet organized and managed into separate sectors. Although technological innovations emerge at the intersection of energy and water, these sectors largely operate independently, despite their mutual importance. This persistent challenge is structural, as the sectors are organized and managed as separate systems. More can be done to integrate these sectors for mutual benefit and resilience. This paper provides an overview and a useful categorization of six research areas that bridge the water and energy sectors: integrated planning, integrated operations, data and analytics, policy and economics, hydropower and marine energy, and resilience. The authors lead the IEEE Power & Energy Society Task Force on Water-Power Systems (WPS), which represents an international and rapidly growing collaboration across both energy and water sectors to find common areas of cooperation and innovation. Through the collective efforts of this Task Force, a comprehensive roadmap on water power systems integration was issued in 2023. The paper presents evidence that coordinated efforts in data analytics, policy, and economic interventions can significantly advance hydropower, marine energy, and energy storage technologies, ultimately enhancing the resilience and efficiency of both water and power infrastructures.