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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4

Uncertain Pathways to a Future Safe Climate

Abstract Global climate change is often thought of as a steady and approximately predictable physical response to increasing forcings, which then requires commensurate adaptation. But adaptation has practical, cultural and biological limits, and climate change may pose unanticipated global hazards, sudden changes or other surprises–as may societal adaptation and mitigation responses. These poorly known factors could substantially affect the urgency of mitigation as well as adaptation decisions. We outline a strategy for better accommodating these challenges by making climate science more integrative, in order to identify and quantify known and novel physical risks including those arising from interactions with ecosystems and society. We need to do this even–or especially–when they are highly uncertain, and to explore risks and opportunities associated with mitigation and adaptation responses by engaging across disciplines. We argue that upcoming climate assessments need to be more risk‐aware, and suggest ways of achieving this. These strategies improve the chances of anticipating potential surprises and identifying and communicating “safe landing” pathways that meet UN Sustainable Development Goals and guide humanity toward a better future.

Sherwood, S. C.↗

Pathways to a net-zero-carbon water sector through energy-extracting wastewater technologies

The energy-consuming and carbon-intensive wastewater treatment plants could become significant energy producers and recycled organic and metallic material generators, thereby contributing to broad sustainable development goals, the circular economy, and the water-energy-sanitation-food-carbon nexus. This review provides an overview of the waste(water)-based energy-extracting technologies, their engineering performance, techno-economic feasibility, and environmental benefits. Here, we propose four crucial strategies to achieve net-zero carbon along with energy sufficiency in the water sector, including (1) improvement in process energy efficiency; (2) maximizing on-site renewable capacities and biogas upgrading; (3) harvesting energy from treated effluent; (4) a new paradigm for decentralized water-energy supply units.

54 ENVIRONMENTAL SCIENCES↗

Inappropriate antibiotic access practices at the community level in Eastern Ethiopia

Access to antibiotic medications is critical to achieving the Sustainable Development Goal for good health and well-being. However, non-prescribed and informal sources are implicated as the most common causes of inappropriate antibiotic access practices, resulting in untargeted therapy, which leads to antibiotic resistance. Hence, knowing antibiotic access practices at the community level is essential to target misuse sources. In this study, 2256 household representatives were surveyed between July and September 2023 to examine their antibiotic access practices. Of 1245 household members who received antibiotics, 45.6% did so inappropriately. Non-prescribed antibiotic access was more common among urban residents and individuals not enrolled in health insurance schemes. This means of antibiotic access was also more common among individuals concerned about distance, drug availability, and healthcare convenience at public facilities. In addition, women and rural individuals were more likely to get antibiotics from unauthorized sources. Unrestricted antibiotic dispensing practices in urban areas enabled their non-prescribed access, while unlicensed providers prevailed with this access practice in rural areas. In this regard, personal behaviors and healthcare-related gaps such as the lack of health insurance, inconvenience, and drug unavailability have led community members to seek antibiotics from unofficial and non-prescribed sources. Targeting the identified behavioral and institutional factors can enhance antibiotic access through prescriptions, hence reducing antibiotic resistance.

60 APPLIED LIFE SCIENCES↗

Assessing the future of global energy-for-water

This study incorporates the energy demands of water abstraction, treatment, distribution, and post-use (wastewater) treatment into the Global Change Assessment Model (GCAM), an integrated human-Earth systems model, and analyzes a range of scenarios that estimate the future evolution of this demand of energy. The study builds on prior research on the historical demands of energy-for-water, fitting these demands of energy into existing nation-level energy balances, where demands for energy-for-water have heretofore been aggregated with other energy use in the commercial and public services, industrial, agricultural, and/or electric power sectors. This development allows for improved projections of future energy demands in general, and in this study, allows for assessment of the energy implications of different scenarios of improvements in water access and water quality that are consistent with the Sustainable Development Goals. In our baseline scenario, energy-for-water approximately doubles from 2010 to 2050, and in the scenario with the greatest level of water access, standards for treatment of wastewater, and irrigation expansion, the consequent energy-for-water demands increase three-fold from 2010 to 2050. Note also that these increases do not consider future scarcity-driven increases in energy requirements per unit of water abstraction, treatment, and distribution.

54 ENVIRONMENTAL SCIENCES↗

Deep Learning Scene Classification Experiments in Automatic Detection of Slums on Planetscope Imagery

Population growth is increasingly happening in slum settlements of the large urban centers in the Global South. The term "slum" encompasses a wide range of communities, located mostly in underserved areas, and often exhibiting distinct structural and functional informalities with a relatively high concentration of marginalized populations. To address the issues confronting slums for effective planning and development, including the realistic estimation of the resident population, identifying them accurately is fundamental. Given the disagreements over a universal definition, diverse characteristic features, and socio-political limitations, global detection of slums is a veritable challenge. In this paper, we present experiments in slum detection using a scene classification algorithm and 3-meter spatial resolution satellite imagery. We train and evaluate the model for slum detection in Mumbai, India for the year 2023 and test the temporal generalization of the trained model on Mumbai in 2020 and 2018. In addition, we explore the pathways toward geographic generalization to Kolkata and Delhi (India). We discuss several limitations in the workflow and model, situate our findings in the existing literature, and suggest improvements and alternatives. With this, we establish baseline methods and experiments as a first step towards developing an image-based global slum detection framework and algorithm. This work adds to the community discussion on methods, data challenges, and open questions related to the detection of slums globally. With this research, we hope to improve our understanding of human settlements, especially in critical areas, improve population estimates, and help measure progress towards the sustainable development goals.

Arndt, Jacob↗

Quantitative approaches for including equity in risk and resilience infrastructure planning analyses

Risk and resilience assessments for critical infrastructure focus on myriad objectives, from natural hazard evaluations to optimizing investments. Although research has started to characterize externalities associated with current or possible future states, incorporation of equity priorities at project inception is increasingly being recognized as critical for planning related activities. However, there is no standard methodology that guides development of equity-informed quantitative approaches for infrastructure planning activities. Here, to address this gap, we introduce a logic model that can be tailored to capture nuances about specific geographies and community priorities, effectively incorporating them into different mathematical approaches for quantitative risk assessments. Specifically, the logic model uses a graded, iterative approach to clarify specific equity objectives as well as inform the development of equations being used to support analysis. We demonstrate the utility of this framework using case studies spanning aviation fuel, produced water, and microgrid electricity infrastructures. For each case study, the use of the logic model helps clarify the ways that local priorities and infrastructure needs are used to drive the types of data and quantitative methodologies used in the respective analyses. The explicit consideration of methodological limitations (e.g., data mismatches) and stakeholder engagements serves to increase the transparency of the associated findings as well as effectively integrate community nuances (e.g., ownership of assets) into infrastructure assessments. Such integration will become increasingly important to ensure that planning activities (which occur throughout the lifecycle of the infrastructure projects) lead to long-lasting solutions to meet both energy and sustainable development goals for communities.

community-based↗

Fragile Earth: AI for Climate Mitigation, Adaptation, and Environmental Justice

The Fragile EarthWorkshop is a recurring event that gathers the research community to find and explore howdata science can measure and progress climate and social issues, following the framework of the United Nations Sustainable Development Goals (SDGs).Fragile Earth 2022: AI for Climate Mitigation, Adaptation, and Environmental Justice is a workshop taking place as part of the ACM's KDD 2022 Conference on research in knowledge discovery and data mining and their applications. The dates for the Conference are August 14-18, 2022.

Abe, Naoki↗

Global Precipitation Experiment—A New World Climate Research Programme Lighthouse Activity

The future state of the global water cycle and the prediction of freshwater availability for humans around the world remain among the challenges of climate research and are relevant to several United Nations Sustainable Development Goals. The Global Precipitation Experiment (GPEX) takes on the challenge of improving the prediction of precipitation quantity, phase, timing, and intensity, characteristics that are products of a complex integrated system. It will achieve this by leveraging existing World Climate Research Programme (WCRP) activities and community capabilities in satellite, surface-based, and airborne observations, modeling, and experimental research and by conducting new and focused activities. It was launched in October 2023 as a WCRP Lighthouse Activity. Here, we present an overview of the GPEX Science Plan that articulates the primary science questions related to precipitation measurements, process understanding, model performance and improvements, and plans for capacity development. The central phase of GPEX is the WCRP Years of Precipitation for 2–3 years with coordinated global field campaigns focusing on different storm types (atmospheric rivers, mesoscale convective systems, monsoons, and tropical cyclones, among others) over different regions and seasons. Activities are planned over the three phases (before, during, and after the Years of Precipitation) spanning a decade. These include gridded data evaluation and development, advanced modeling, enhanced understanding of processes critical to precipitation, multiscale prediction of precipitation events across scales, and capacity development. These activities will be further developed as part of the GPEX Implementation Plan.

Climate change↗

Advancing representations of equity and justice in climate mitigation futures

THIS PAPER WAS PRIMARILY COMPLETED PRIOR TO THE AUTHOR JOINING PNNL AND NO DOE FUNDING WAS USED FOR THIS PAPER. In this work, we review how equity and justice issues in global climate mitigation scenarios are addressed within Integrated Assessment Models (IAMs) and propose a new research agenda to strengthen their integration in model development and application. We begin by examining prominent concerns at the science-policy interface. We introduce a typology of equity and justice limitations in climate mitigation scenarios, distinguishing among structural, methodological, and epistemological biases that shape what integrated assessment models can reveal at policy-relevant scales. Reflecting on these concerns, we propose a research agenda that describes new avenues of work and draws together distinct emerging initiatives. This agenda is based on the feasibility and depth of required interventions, from incremental improvements to structural reforms and alternative participatory approaches. Drawing on reflexive insights from integrated assessment practitioners, it addresses the operational challenges of translating justice concepts into metrics, including risks of reductionism, tokenism, and narrow definitions. Underlying this research agenda is a recognition that modeling communities must engage more critically with implicit assumptions in model design and use that have equity and justice implications. Achieving equitable climate futures will require transformative actions that integrate diverse justice concerns, advance sustainable development goals, and confront systemic inequities across both human and ecological dimensions. Although models will never capture all these aspects, they can be significantly enhanced to support more informed discussion and practical application. Our contribution proposes a way forward to achieving this goal.

Pachauri, Shonali↗

Increasing Access to Grid-Tied Distributed Photovoltaics for Low-Income Populations: Considerations for Developing Countries

Governments around the world are under immense pressure to promote inclusive economic growth, reduce budget deficits, and promote sustainable development goals. Such goals may potentially be addressed through public policy approaches to encourage the use of distributed photovoltaic (DPV) systems in developing countries, particularly among low-income electricity customers. At the same time, low-income customers face numerous barriers to DPV deployment including a lack of access to capital and financing, a lack of awareness about the technology, lack of homeownership, and distorted price signals via lower retail tariffs. As a result of these factors, among others, they are often the least likely customers in developed and developing countries alike to deploy solar. However, under the right set of conditions, low-income grid tied DPV programs can offer beneficial outcomes for governments, customers, utilities, and the environment. This brief informs decision makers in developing countries as they explore ways to promote equitable access to solar energy in their communities.

14 SOLAR ENERGY↗

Climate Change 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change, Chapter 11

The AR5 was published in 2014. The Paris Agreement and the 17 Sustainable Development Goals (SDGs) were adopted in 2015. An increasing number of countries have since announced ambitions to be carbon neutral by 2045–2060. The COVID-19 pandemic shocked the global economy in 2020 and motivated economic stimulus with demands for green recovery and concerns for economic security. All this has created a new context and a growing recognition that all industry, including the energy and emissions intensive industries, need to reach net zero GHG emissions. There is an ongoing mind shift around the opportunities to do so, with electrification and hydrogen emerging among key mitigation options as a result of renewable electricity costs falling rapidly. On the demand side there has been renewed attention to end-use demand, material efficiency, and more and better-quality recycling measures. This chapter takes its starting point in this new context and emphasizes the need for deploying innovative processes and practices in order to limit the global warming to 1.5°C or 2°C (IPCC 2018a).

54 ENVIRONMENTAL SCIENCES↗

Citizen-Led Community Innovation for Food Energy Water Nexus Resilience

Food-energy-water (FEW) resources are necessary for the function of multiple socio-natural systems. Understanding the synergies and trade-offs in the FEW nexus, and how these interconnections impact earth’s systems, is critical to ensure adequate access to these resources in the future; an essential component for achieving the Sustainable Development Goals (Scanlon et al., 2017). Although, over the last decade, the identification of FEW nexus complexities has increased at a global (IPCC, 2018; D’Orodico et al., 2018), national (Lant et al., 2019), and city scale (Rushforth and Ruddell, 2018), these findings are yet to be adequately translated into ‘on the ground’ action due a lack of technical and political capacity (Weitz et al., 2017). Specifically, local FEW systems have been overlooked in these analyses (Scanlon et al., 2017; Lant et al., 2019), thus leaving small and medium towns vulnerable due to a lack of data and inadequate FEW system management. Building on three years of field-tested FEW nexus research in the Ruddell Lab, we argue that participatory citizen science projects, such as our FEWSION for Community Resilience initiative, can bridge the data-policy gaps that exist within local FEW system management by: 1) providing last mile data on the FEW system, and 2) translating local data into evidence-based solutions at a grassroots level. Thus, we present a broadly applicable framework and call to action for local scale participatory citizen science to solve complex FEW nexus issues at a local, regional, and national scale.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Bioprospecting Trichoderma: A Systematic Roadmap to Screen Genomes and Natural Products for Biocontrol Applications

Natural products derived from microbes are crucial innovations that would help in reaching sustainability development goals worldwide while achieving bioeconomic growth. Trichoderma species are well-studied model fungal organisms used for their biocontrol properties with great potential to alleviate the use of agrochemicals in agriculture. However, identifying and characterizing effective natural products in novel species or strains as biological control products remains a meticulous process with many known challenges to be navigated. Integration of recent advancements in various “omics” technologies, next generation biodesign, machine learning, and artificial intelligence approaches could greatly advance bioprospecting goals. Herein, we propose a roadmap for assessing the potential impact of already known or newly discovered Trichoderma species for biocontrol applications. By screening publicly available Trichoderma genome sequences, we first highlight the prevalence of putative biosynthetic gene clusters and antimicrobial peptides among genomes as an initial step toward predicting which organisms could increase the diversity of natural products. Next, we discuss high-throughput methods for screening organisms to discover and characterize natural products and how these findings impact both fundamental and applied research fields.

59 BASIC BIOLOGICAL SCIENCES↗

Optimal Electrification Using Renewable Energies: Microgrid Installation Model with Combined Mixture k-Means Clustering Algorithm, Mixed Integer Linear Programming, and Onsset Method

Optimal planning and design of microgrids are priorities in the electrification of off-grid areas. Indeed, in one of the Sustainable Development Goals (SDG 7), the UN recommends universal access to electricity for all at the lowest cost. Several optimization methods with different strategies have been proposed in the literature as ways to achieve this goal. This paper proposes a microgrid installation and planning model based on a combination of several techniques. The programming language Python 3.10 was used in conjunction with machine learning techniques such as unsupervised learning based on K-means clustering and deterministic optimization methods based on mixed linear programming. These methods were complemented by the open-source spatial method for optimal electrification planning: onsset. Four levels of study were carried out. The first level consisted of simulating the model obtained with a cluster, which is considered based on the elbow and k-means clustering method as a case study. The second level involved sizing the microgrid with a capacity of 40 kW and optimizing all the resources available on site. The example of the different resources in the Togo case was considered. At the third level, the work consisted of proposing an optimal connection model for the microgrid based on voltage stability constraints and considering, above all, the capacity limit of the source substation. Finally, the fourth level involved a planning study of electrification strategies based mainly on microgrids according to the study scenario. The results of the first level of study enabled us to obtain an optimal location for the centroid of the cluster under consideration, according to the different load positions of this cluster. Then, the results of the second level of study were used to highlight the optimal resources obtained and proposed by the optimization model formulated based on the various technology costs, such as investment, maintenance, and operating costs, which were based on the technical limits of the various technologies. In these results, solar systems account for 80% of the maximum load considered, compared to 7.5% for wind systems and 12.5% for battery systems. Next, an optimal microgrid connection model was proposed based on the constraints of a voltage stability limit estimated to be 10% of the maximum voltage drop. The results obtained for the third level of study enabled us to present selective results for load nodes in relation to the source station node. Finally, the last results made it possible to plan electrification using different network technologies and systems in the short and long term. The case study of Togo was taken into account. The various results obtained from the different techniques provide the necessary leads for a feasibility study for optimal electrification of off-grid areas using microgrid systems.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Unveiling the Occupational Exposure to Microbial Contamination in Conservation–Restoration Settings

Assuring a proper environment for the fulfillment of professional activities is one of the Sustainable Development Goals and is contemplated in the One Health approach assumed by the World Health Organization. This particular study is applied to an often neglected sector of our society—the conservators/restorers—despite the many health issues reported by these professionals. Three different specialties (textiles, paintings and wood sculpture) and locations were selected for evaluation by placement of electrostatic dust cloths. After treatment of the samples, bacterial and fungal contamination were assessed, as well as mycotoxin determination, the presence of azole-resistant strains and cytotoxicity of the microorganisms encountered. Bacteria were only present in one of medias used and showed relatively low numbers. The highest level of contamination by fungi was identified in one of the textiles settings. The textile area also showed the highest variability for fungi. Aspergillus sp. are one indicator of possible environmental issues, and A. sections Fumigati and Circumdati were particularly relevant in two of the settings and identified in all of them. No mycotoxins were detected and the large majority of the fungi identified were non-cytotoxic. Overall, these can be considered low-contaminated environments but attention should be given to the Aspergillus sp. contamination. Additional studies are needed not only to make these results more robust, but also to test if the environmental sampling alone is the best approach in a setting where there is very little movement and dust displacement and where professionals are in very close proximity to the artefacts being treated, which may suggest the existence of a micro-atmosphere worth evaluating and comparing to the obtained results.

Viegas, Carla (ORCID:0000000215456479)↗

Policy Brief: Integrated Nexus Policies for Sustainable and Resilient Energy, Water, and Food Systems

Population growth, climate change, and resource depletion put food and water security and energy supply at risk. Sustainable and resilient water, food, and energy systems are crucial to meet Sustainable Development Goals (SDGs) and increase resilience to global health crises such as the COVID-19 pandemic. This policy brief describes the challenges and presents proposals regarding synergies in the land, water, and energy nexus to maximize net environmental, health, and social benefits. First, this brief focuses on water desalination, where the nexus approach helps to balance the full cost, including externalities, of desalinated water, and its socio-economic benefits. Second, this policy brief highlights nutrition-sensitive food policies that improve health and contribute to the preservation of natural resources. Finally, this brief presents challenges and opportunities for developing renewable energy.

energy↗

Circular Economy in Photovoltaics

The photovoltaic (PV) industry is advancing towards a circular economy (CE), emphasizing the crucial role of sustainability in PV technology. This progression entails adopting practices that extend the lifespan of PV modules, motivated by a commitment to CE principles and alignment with the United Nations Sustainable Development Goals. Tackling the challenges to achieve circularity is essential. Moreover, the goals of IEA-PVPS Task 12 are to enhance the environmental profile of PV electricity, highlighting the industry's dedication to the environmental, economic, and policy dimensions of CE.

circularity↗