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1. Exploring equality and sustainability trade-offs of energy transition outcomes in the United States in 2050

   https://doi.org/10.1016/j.apenergy.2024.123376  

   Goforth, Teagan; Nock, Destenie; Brown, Maxwell; Ghosh, Tapajyoti; Lamers, Patrick (August 2024, Applied Energy)

   With increasing focus on equitable and just energy transition, it is critical to understand the trade-offs of different decarbonization outcomes across economic, environmental, and social sustainability criteria. In this analysis, we use a multi-criteria decision analysis to quantify sustainability outcomes across 32 decarbonization outcomes in 2050 in the U.S. The economic sustainability criteria we use are system cost, national average retail rate, and electricity system employment. The environmental sustainability criteria we use are life cycle greenhouse gas emissions, life cycle water depletion, life cycle land transformation, and air pollution fatalities. The social sustainability (distributional impacts) criteria we use are retail rate equality across states, electricity employment equality across low-income households, and air pollution disparities across census tracts. We evaluate performance across these criteria under eleven different stakeholder preference scenarios. We find that decarbonization policies with indefinitely extended tax credits have the highest sustainability score under equal criteria weighting, with greater investments in renewable energy technologies, and result in better environmental, system cost, job, and air pollution disparities compared to mid-case scenarios, that only include current policies and CO2 reduction targets. We also see that our multi-criteria decision analysis identifies decarbonization outcomes that would not have been identified as optimal under a single objective, which highlights the importance of trade-off analyses to understand decarbonization outcomes more holistically. 

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2. An ecosystem-based natural capital evaluation framework that combines environmental and socio-economic implications of offshore renewable energy developments

   https://doi.org/10.1088/2516-1083/ac702a  

   Trifonova, Neda; Scott, Beth; Griffin, Robert; Pennock, Shona; Jeffrey, Henry (June 2022, Progress in Energy)

   Abstract There is about to be an abrupt step-change in the use of coastal seas around the globe, specifically by the addition of large-scale offshore renewable energy (ORE) developments to combat climate change. Developing this sustainable energy supply will require trade-offs between both direct and indirect environmental effects, as well as spatial conflicts with marine uses like shipping, fishing, and recreation. However, the nexus between drivers, such as changes in the bio-physical environment from the introduction of structures and extraction of energy, and the consequent impacts on ecosystem services delivery and natural capital assets is poorly understood and rarely considered through a whole ecosystem perspective. Future marine planning needs to assess these changes as part of national policy level assessments but also to inform practitioners about the benefits and trade-offs between different uses of natural resources when making decisions to balance environmental and energy sustainability and socio-economic impacts. To address this shortfall, we propose an ecosystem-based natural capital evaluation framework that builds on a dynamic Bayesian modelling approach which accounts for the multiplicity of interactions between physical (e.g. bottom temperature), biological (e.g. net primary production) indicators and anthropogenic marine use (i.e. fishing) and their changes across space and over time. The proposed assessment framework measures ecosystem change, changes in ecosystem goods and services and changes in socio-economic value in response to ORE deployment scenarios as well as climate change, to provide objective information for decision processes seeking to integrate new uses into our marine ecosystems. Such a framework has the potential of exploring the likely outcomes in the same metrics (both ecological and socio-economic) from alternative management and climate scenarios, such that objective judgements and decisions can be made, as to how to balance the benefits and trade-offs between a range of marine uses to deliver long-term environmental sustainability, economic benefits, and social welfare. 

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3. Towards Designing Unbiased Replication Studies in Information Visualization

   https://doi.org/10.1109/BELIV.2018.8634261  

   Sukumar, Poorna Talkad; Metoyer, Ronald (October 2018, 2018 IEEE Evaluation and Beyond-Methodological Approaches for Visualization (BELIV))

   null (Ed.)

   Experimenter bias and expectancy effects have been well studied in the social sciences and even in human-computer interaction. They refer to the nonideal study-design choices made by experimenters which can unfairly influence the outcomes of their studies. While these biases need to be considered when designing any empirical study, they can be particularly significant in the context of replication studies which can stray from the studies being replicated in only a few admissible ways. Although there are general guidelines for making valid, unbiased choices in each of the several steps in experimental design, making such choices when conducting replication studies has not been well explored. We reviewed 16 replication studies in information visualization published in four top venues between 2008 to present to characterize how the study designs of the replication studies differed from those of the studies they replicated. We present our characterization categories which include the prevalence of crowdsourcing, and the commonly-found replication types and study-design differences. We draw guidelines based on these categories towards helping researchers make meaningful and unbiased decisions when designing replication studies. Our paper presents the first steps in gaining a larger understanding of this topic and contributes to the ongoing efforts of encouraging researchers to conduct and publish more replication studies in information visualization. 

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4. Developing a Data Quality Evaluation Framework for Sewer Inspection Data

   https://doi.org/10.3390/w15112043  

   Khaleghian, Hossein; Shan, Yongwei (June 2023, Water)

   The increasing amount of data and the growing use of them in the information era have raised questions about the quality of data and its impact on the decision-making process. Currently, the importance of high-quality data is widely recognized by researchers and decision-makers. Sewer inspection data have been collected for over three decades, but the reliability of the data was questionable. It was estimated that between 25% and 50% of sewer inspection data is not usable due to data quality problems. In order to address reliability problems, a data quality evaluation framework is developed. Data quality evaluation is a multi-dimensional concept that includes both subjective perceptions and objective measurements. Five data quality metrics were defined to assess different quality dimensions of the sewer inspection data, including Accuracy, Consistency, Completeness, Uniqueness, and Validity. These data quality metrics were calculated for the collected sewer inspection data, and it was found that consistency and uniqueness are the major problems based on the current practices with sewer pipeline inspection. This paper contributes to the overall body of knowledge by providing a robust data quality evaluation framework for sewer system data for the first time, which will result in quality data for sewer asset management. 

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5. Assessing the Potential of Urban Ecology Research to Inform Municipal Sustainability Practices

   Small, G.; Simeon, M.; Shrestha, P.; Dahmus, M.; Amel, E. (January 2019, Cities and the environment)

   Cities are increasingly making decisions related to sustainability, and information from the field of urban ecology may be useful in informing these decisions. However, the potential utility of this information may not translate into it actually being used. We surveyed municipal sustainability staff through the Minnesota GreenStep Cities program documenting their information needs and information sources, and used these results to identify the frequency with which urban ecologists are publishing studies of potential relevance to practitioners. We also quantified funded awards from the U.S. National Science Foundation in urban ecology that explicitly describe active partnerships with city policy makers. Our results show that urban ecologists are increasingly generating information of potential relevance to city sustainability efforts, with rapid increases in the number of articles published and grants funded on areas identified as key information needs. Our results also suggest that the transmission of information from academic urban ecologists to practitioners occurs mostly through indirect pathways, as municipal sustainability staff reported relying heavily on general web searches and government agency websites to find information. We found evidence of an increasing frequency of active collaborations between urban ecologists and policy makers from NSF grant abstracts. Our findings are consistent with previous findings that traditional models of passive communication to practitioners through academic journals results in a low efficiency of use of this knowledge, but that the potential for urban ecologists to help inform municipal sustainability initiatives through active collaborations with practitioners is great. 

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