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DOE OSTI2022

Residential Energy Efficiency Design Guide for Tribal Lands

Homeowners and renters on tribal lands have historically faced a disproportionate energy burden compared to the United States as a whole. The Indian Health Service (IHS), which serves these communities, strives to meet aggressive energy performance goals when constructing their residential housing. Challenges common in rural locations can hinder progress toward those goals, such as availability of materials, access to specialized labor, and budget constraints. This guide is for architects and builders who aim to incorporate energy efficiency (EE) into their residential designs. This report presents commercially viable energy efficiency packages for a variety of locations and home inputs to help guide home builders in choosing improvements for energy performance. The intention is to provide a diverse set of packages that can be used during the design phase to achieve energy savings compared to a code minimum building design. By presenting a set of diverse options with similar expected energy savings and life-cycle costs, final decisions can be left up to the building designers who can better determine the appropriate package given local costs, materials, and labor availability. Although this guide was developed for IHS projects, it can be used to help designers and construction professionals better make cost-effective choices when a detailed, project-specific building energy analysis is not possible.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2024

Life Cycle Analysis of Natural Gas Extraction and Power Generation: U.S. 2020 Emissions Profile

This analysis expands upon previous life cycle analyses (LCAs) of natural gas systems performed by the National Energy Technology Laboratory (NETL). It provides a complete inventory of emissions to air and water, water consumption, and land use change. These environmental burdens are detailed for all supply chain steps from natural gas production through natural gas distribution. This package includes the report, the NETL Natural Gas Model, and appendices that include several Excel workbooks and a python script to provide transparent access to the calculations and resulting data.<p>To access the NETL Natural Gas Lifecycle model, visit https://doi.org/10.18141/2476250.</p><p>To access the 2020 Report Appendices, visit https://doi.org/10.18141/2438472.</p>

03 NATURAL GAS↗
DOE OSTI2025

Life Cycle Analysis of Natural Gas Extraction and Power Generation: U.S. 2020 Emissions Profile

This analysis expands upon previous life cycle analyses (LCAs) of natural gas systems performed by the National Energy Technology Laboratory (NETL). It provides a complete inventory of emissions to air and water, water consumption, and land use change. These environmental burdens are detailed for all supply chain steps from natural gas production through natural gas distribution. This package includes the report, the NETL Natural Gas Model, and appendices that include several Excel workbooks and a python script to provide transparent access to the calculations and resulting data. This is revision 1 of the 2024 study (published December 17, 2024 and updated on January 24, 2025) and corrects a modeling error in natural gas composition. See the errata on page 2 for more information.

03 NATURAL GAS↗
DOE OSTI2021

A hub and spoke approach to optimizing energy wheeling of renewable resources

The deployment of zero carbon renewable energy sources needs to increase significantly to support the goal of net zero greenhouse gas emissions by 2050. At the same time energy end use needs to decarbonize. This will change both energy supply and energy demand patterns, requiring the energy delivery infrastructure (grid-based transmission circuits) to become increasingly flexible to maintain security of supply everywhere and always. The integration of zero carbon renewable energy requires cross-border and cross energy system coupling and a fit-for-purpose design. Nowadays, energy systems are planned, designed and operated in silos with a strong national focus. However, large-scale offshore wind production needs to be transported to deep inland locations, across country borders. The increased peak generation capacity of renewable energy sources will, at times, significantly exceed demand (Matthew Langholtz, 2020). The traditional solution of continuously reinforcing and extending the electricity grid is not sustainable from a cost and societal perspective. This paper will, however, propose a deterministic approach on how networked (interconnected grid) Points of receipt (POR) to Points of Delivery (POD) can be optimized for wheeling renewable energy resources while minimizing energy cost with a hub and spoke approach. The statistical approach will be done via using existing daily energy market clearing prices, available transmission capacity and firm daily transmission prices in open access energy markets. Renewable energy targets, including specific offshore wind targets, need to be in line with the ramp-up as implied by the Paris Agreement. These targets are required to provide industry with a secure market outlook that allows them to build up supply chains accordingly. Optimizing wheeled energy paths from carbon neutral resources such as renewables make them not only cost competitive on the unit commitment stack, but also more accessible on the dispatch stack to other carbon heavy forms of generation such as coal and natural gas turbines (Matthew Langholtz, 2020). This correlates to maximizing renewable resource inertia (wind, solar, biomass) within an interconnected grid without having to consider additional expansion of resources via land purchases and de-forestation.

Mukherjee, Srijib↗
DOE OSTI2022

Basin and Range Investigation for Developing Geothermal Energy: Exploration Data

This data package includes exploration material from the Basin & Range Investigation for Developing Geothermal Energy [in Hidden Systems] project (BRIDGE), which is part of a broader initiative to advance the exploration of hidden geothermal resources in the Basin & Range Province of the western U.S. Data modalities include a helicopter-borne time-domain electromagnetic survey, magnetotellurics, 2-meter temperature measurements, ground-based gravity and legacy aeromagnetic surveys, geochemistry, geologic mapping, LiDAR analysis, 3D models, associated geospatial data, and a bibliography of existing data and references utilized in prospect characterization and conceptual modeling. Key files are in CSV, Geosoft, and Geotools formats. Please refer to READMEs for dataset-specific information. Where applicable, acquisition data and inversion models for a particular prospect or area of interest are organized separately. This BRIDGE data package is the product of a collaboration led by Sandia National Laboratories with partners from Geologica Geothermal Group, Inc., the U.S. Navy Geothermal Program Office, and consultants Steven Sewell (Australis Geoscience Ltd) and William Cumming (Cumming Geoscience). The project's areas of interest (AOIs) are based off priority areas of interest in the southwestern portion of the Nevada Play Fairway map, distribution across tectonic provinces, accessibility, and the project team's extensive experience in the region. AOIs cover about a dozen basins that include unexplored prospects, partially explored prospects, and some developed analogue resources that provide validation cases. Many unexplored and partially explored prospects are on U.S. Department of Defense (DoD) land, though adjacent lands are included as well.

15 GEOTHERMAL ENERGY↗
DOE OSTI2022

Introduction to Evolve Central Appalachia

The Evolve-CAPP project is developing and implementing strategies to enable the Central Appalachian basin to realize its full economic potential for producing high-value, non-fuel, carbon-ore (CO) products, rare earth elements (REE), and critical minerals (CM). The Basinal Assessment of CORE-CM Resources is a state-of-the-art geological model and comprehensive database that will be used to identify, locate, and quantify in-situ resources in the basin. Restrictive aspects of resource recovery, such as ownership and legal restrictions, are being considered in estimating recoverable resources. A gap analysis of missing or unavailable data that could not be fully integrated in the initial assessment due to budget, access, or other constraints during the assessment effort is planned. A characterization and data acquisition plan to fully characterize the basin’s CORE-CM potential will address gaps in data. The plan will be developed with input from project team members and relevant stakeholders, including land and mineral holding companies and coal operators, who maintain sampling programs as part of their normal operations.

Bishop, Richard↗
DOE OSTI2023

Land surface dynamics and meteorological forcings modulate land surface temperature characteristics

This study examines the effect of land cover, vegetation health, climatic forcings, elevation heat loads, and terrain characteristics (LVCET) on land surface temperature (LST) distribution over West Africa (WA). We employ fourteen machine-learning models, which preserve nonlinear relationships, to downscale LST and other predictands while preserving the geographical variability of WA. Our results showed that the random forest model performs best in downscaling predictands. This is important for the sub-region since it has limited access to mainframes to power multiplex machine-learning algorithms. In contrast to the northern regions, the southern regions consistently exhibit healthy vegetation. Also, areas with unhealthy vegetation coincide with hot LST clusters. The positive Normalized Difference Vegetation Index (NDVI) trends in the Sahel underscore rainfall recovery and subsequent Sahelian greening. The southwesterly winds cause the upwelling of cold waters, lowering LST in southern WA and highlighting the cooling influence of water bodies on LST. Identifying regions with elevated LST is paramount for prioritizing greening initiatives, and our study underscores the importance of considering LVCET factors in urban planning. Topographic slope-facing angles, heat loads, and diurnal anisotropic heat all contribute to variations in LST, emphasizing the need for a holistic approach when designing resilient and sustainable landscapes.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Root Foraging Alters Global Patterns of Ecosystem Legacy From Climate Perturbations

The response of terrestrial ecosystems to climate perturbations typically persist longer than the timescale of the forcing, a phenomenon broadly referred to as legacy. Understanding the strength of legacy is critical for predicting ecosystem sensitivity to climate extremes and the extent that persistent changes in surface-atmosphere exchange might feedback onto climate. The cause of ecosystem legacy has been associated with myriad factors such as changes in aboveground biomass, however, few studies have tested how changes in the depth distribution of fine roots in response to perturbation might alter an ecosystem's recovery time. We explore this question using an Earth System Model that includes a dynamic root module where vegetation can forage for water and nutrients by altering their root profiles. The global simulations presented here show that in response to water stress events most ecosystems deepen their root profiles. In semi-arid ecosystems, this response expedites recovery (i.e., less legacy) relative to simulations without dynamics roots because access to deeper water pools after the initial event remains favorable. In wetter ecosystems, the development of deeper root profiles slows down the recovery timescale (i.e., more legacy) because the deeper root profile reduces access to nutrients and is thus unfavorable. Here, the simulations show that while the inclusion of dynamic roots might only minimally affect global patterns of Gross Primary Productivity and Evapotranspiration, the shift in root profile alters the timescale of recovery. Studies interested in the sustained response of land surfaces fluxes to climate disturbances should consider models that include dynamic root capability.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Data for: Patel et al. Carbon flux estimates are sensitive to data source: A comparison of field and lab temperature sensitivity data

This dataset contains data and code used for the paper "Carbon flux estimates are sensitive to data source: A comparison of field and lab temperature sensitivity data" [DOI COMING SOON]A large literature exists on mechanisms driving soil production of the greenhouse gases CO2 and CH4. Measurements of these gases’ fluxes are often performed using closed-chamber incubations in the laboratory or in situ, i.e., in the field. Although it is common knowledge that measurements obtained through field studies vs. laboratory incubations can diverge because of the vastly different conditions of these environments, few studies have systematically examined these patterns. It is crucial to understand the magnitude and reasons for any differences, as these data are used to parametrize and benchmark ecosystem- to global-scale models, which are then susceptible to the biases of the source data. Here, we specifically examine how greenhouse gas measurements may be influenced by whether the measurement/incubation was conducted in the field vs. laboratory, focusing on CO2 and CH4 measurements. We use Q10 of greenhouse gas flux (temperature sensitivity) for our analyses, because of the ubiquity of this metric in biological and Earth system sciences and its importance to many modeling frameworks. We predicted that laboratory measurements would be less variable, but also less representative of true field conditions. However, there was greater variability in the Q10 values calculated from lab-based measurements of CO2 fluxes, because lab experiments explore extremes rarely seen in situ, and reflect the physical and chemical disturbances occurring during sampling, transport, and incubation. Overall, respiration Q10 values were significantly greater in laboratory incubations (mean = 4.19) than field measurements (mean = 3.05), with strong influences of incubation temperature and climate region/biome. However, this was in part because field measurements typically represent total respiration (Rs), whereas lab incubations typically represent heterotrophic respiration (Rh), making direct comparisons difficult to interpret. Focusing only on Rh-derived Q10, these values showed almost identical distributions across laboratory (n = 1110) and field (n = 581) experiments, providing strong support for using the former as an experimental proxy for the latter, although we caution that geographic biases in the extant data make this conclusion tentative. Due to a smaller sample size of CH4 Q10 data, we were unable to perform a comparable robust analysis, but we expect similar interactions with soil temperature, moisture, and environmental/climatic variables. Our results here suggest the need for more concerted efforts to document and standardize these data, including sample and site metadata. This dataset contains a compressed (.zip) archive of the data and R scripts used for this manuscript. The dataset includes files in .csv format, which can be accessed and processed using MS Excel or R. This archive can also be accessed on GitHub at https://github.com/kaizadp/field_lab_q10 (DOI: 10.5281/zenodo.7106554).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Machine Learning Prediction of Tritium‐Helium Groundwater Ages in the Central Valley, California, USA

Abstract Groundwater ages provides insight into recharge rates, flow velocities, and vulnerability to contaminants. The ability to predict groundwater ages based on more accessible parameters via Machine Learning (ML) would advance our ability to guide sustainable management of groundwater resources. In this study, ML models were trained and tested on a large data set of tritium concentrations and tritium‐helium groundwater ages from the California Central Valley, a large groundwater basin with complex land use, irrigation, and water management practices. The ML models were trained on 63 features, including location, well construction information, landscape characteristics, and climate variables, water chemistry, and stable isotopes. The Bagging regressor method can accurately classify (F1‐score = 0.91) groundwater samples as either modern or pre‐modern whereas the accuracy of the ML prediction of continuous tritium‐helium groundwater ages is limited and explains only of the variability in this data set. In general, ML groundwater age prediction relies mostly on features related to (a) the source of groundwater recharge, (b) contaminant history, (c) aquifer materials, (d) well construction, and (e) geochemical reactions along flow paths.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Thermal, RGB, and Multispectral Unexploded Ordnance Data Collection

As of May 1, 2026 Landmine contamination affects 58 countries and many hundreds of thousands of km² of land. For example, the National Mine Action Program Demining Ukraine reporting that up to 144,000 km² of territory are potentially contaminated and require survey and clearance (National Mine Action Program “Demining Ukraine,” n.d.) alone. This contamination includes mines and other explosive remnants of war and continues to constrain civilian access, agricultural use, infrastructure recovery, and broader socioeconomic activity (International Campaign to Ban Landmines–Cluster Munition Coalition [ICBL-CMC], 2024; Mine Action Review, 2024). Current response activities rely on established mine-action approaches including non-technical survey, technical survey, clearance, and explosive ordnance disposal, consistent with international mine-action terminology and operational practice (United Nations Mine Action Service [UNMAS], 2024; Geneva International Centre for Humanitarian Demining [GICHD], 2023). In this context, UAV-based sensing, including UAV-mounted thermal imaging, may provide a useful supplementary capability by supporting faster, safer detection and mapping of suspect hazards prior to ground intervention (Smiljanic, 2022).

45 MILITARY TECHNOLOGY, WEAPONRY, AND NATIONAL DEF↗
DOE OSTI2023

Rapid remodeling of the soil lipidome in response to a drying-rewetting event

Abstract Background Microbiomes contribute to multiple ecosystem services by transforming organic matter in the soil. Extreme shifts in the environment, such as drying-rewetting cycles during drought, can impact the microbial metabolism of organic matter by altering microbial physiology and function. These physiological responses are mediated in part by lipids that are responsible for regulating interactions between cells and the environment. Despite this critical role in regulating the microbial response to stress, little is known about microbial lipids and metabolites in the soil or how they influence phenotypes that are expressed under drying-rewetting cycles. To address this knowledge gap, we conducted a soil incubation experiment to simulate soil drying during a summer drought of an arid grassland, then measured the response of the soil lipidome and metabolome during the first 3 h after wet-up. Results Reduced nutrient access during soil drying incurred a replacement of membrane phospholipids, resulting in a diminished abundance of multiple phosphorus-rich membrane lipids. The hot and dry conditions increased the prevalence of sphingolipids and lipids containing long-chain polyunsaturated fatty acids, both of which are associated with heat and osmotic stress-mitigating properties in fungi. This novel finding suggests that lipids commonly present in eukaryotes such as fungi may play a significant role in supporting community resilience displayed by arid land soil microbiomes during drought. As early as 10 min after rewetting dry soil, distinct changes were observed in several lipids that had bacterial signatures including a rapid increase in the abundance of glycerophospholipids with saturated and short fatty acid chains, prototypical of bacterial membrane lipids. Polar metabolites including disaccharides, nucleic acids, organic acids, inositols, and amino acids also increased in abundance upon rewetting. This rapid metabolic reactivation and growth after rewetting coincided with an increase in the relative abundance of firmicutes, suggesting that members of this phylum were positively impacted by rewetting. Conclusions Our study revealed specific changes in lipids and metabolites that are indicative of stress adaptation, substrate use, and cellular recovery during soil drying and subsequent rewetting. The drought-induced nutrient limitation was reflected in the lipidome and polar metabolome, both of which rapidly shifted (within hours) upon rewet. Reduced nutrient access in dry soil caused the replacement of glycerophospholipids with phosphorus-free lipids and impeded resource-expensive osmolyte accumulation. Elevated levels of ceramides and lipids with long-chain polyunsaturated fatty acids in dry soil suggest that lipids likely play an important role in the drought tolerance of microbial taxa capable of synthesizing these lipids. An increasing abundance of bacterial glycerophospholipids and triacylglycerols with fatty acids typical of bacteria and polar metabolites suggest a metabolic recovery in representative bacteria once the environmental conditions are conducive for growth. These results underscore the importance of the soil lipidome as a robust indicator of microbial community responses, especially at the short time scales of cell-environment reactions.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2025

The Marchantia polymorpha pangenome reveals ancient mechanisms of plant adaptation to the environment

Plant adaptation to terrestrial life started 450 million years ago and has played a major role in the evolution of life on Earth. The genetic mechanisms allowing this adaptation to a diversity of terrestrial constraints have been mostly studied by focusing on flowering plants. Here, we gathered a collection of 133 accessions of the model bryophyte Marchantia polymorpha and studied its intraspecific diversity using selection signature analyses, a genome-environment association study and a pangenome. We identified adaptive features, such as peroxidases or nucleotide-binding and leucine-rich repeats (NLRs), also observed in flowering plants, likely inherited from the first land plants. The M. polymorpha pangenome also harbors lineage-specific accessory genes absent from seed plants. We conclude that different land plant lineages still share many elements from the genetic toolkit evolved by their most recent common ancestor to adapt to the terrestrial habitat, refined by lineage-specific polymorphisms and gene family evolution.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2020

GCAM-Demeter-LU

This GCAM-Demeter-LU is made available under the Open Data Commons Attribution License:http://opendatacommons.org/licenses/by/1.0/. The dataset includes the projected global gridded land cover (excluding the Antarctic) for the period of 2015-2100 at 0.05-degree resolution and 5-year time step under fifteen SSP-RCP scenarios driven by five GCMs (i.e., gfdl, hadgem, ipsl, miroc, and noresm), using the Global Change Analysis Model (GCAM) and a geospatial downscaling model (Demeter). The data has been stored in self-describing NetCDF format. The dataset also includes the mean and standard deviation of the results driven by the five GCMs. More specifically, the data in each year includes grid-explicit fraction (in percent) of each of the 32 plant functional types that are widely used in current Earth system models. The NetCDF files are named as “GCAM_Demeter_LU_SSP_RCP_Model_Year.nc”, where “SSP” and “RCP” denote the SSP and RCP scenarios, including 'ssp1_rcp26', 'ssp1_rcp45', 'ssp1_rcp60', 'ssp2_rcp26', 'ssp2_rcp45', 'ssp2_rcp60', 'ssp3_rcp45', 'ssp3_rcp60', 'ssp4_rcp26', 'ssp4_rcp45', 'ssp4_rcp60', 'ssp5_rcp26', 'ssp5_rcp45', 'ssp5_rcp60', and 'ssp5_rcp85'. “Year” denotes the year of the land use data, and “GCM” denotes the source driving forcing data from five global climate models (gfdl, hadgem, ipsl, miroc, and noresm), or the mean (“modelmean”) and the standard deviation (“modelstd”) of the results from the five GCMs.See https://github.com/JGCRI/chen_et_al_2020a for details on how to reproduce this data. Rights and permissions Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver http://creativecommons.org/publicdomain/zero/1.0/ applies to the metadata files associated with this article

99 GENERAL AND MISCELLANEOUS↗
DOE OSTI2022

SpaceNet 8 - The Detection of Flooded Roads and Buildings

The frequency and intensity of natural disasters (i.e. wildfires, storms, floods) has increased over recent decades. Extreme weather can often be linked to climate change, and human population expansion and urbanization have led to a growing risk. In particular floods due to large amounts of rainfall are of rising severity and are causing loss of life, destruction of buildings and infrastructure, erosion of arable land, and environmental hazards around the world. Expanding urbanization along rivers and creeks often includes opening flood plains for building construction and river straightening and dredging speeding up the flow of water. In a flood event, rapid response is essential which requires knowledge which buildings are susceptible to flooding and which roads are still accessible. To this aim, SpaceNet 8 is the first remote sensing machine learning training dataset combining building footprint detection, road network extraction, and flood detection covering 850km 2, including 32k buildings and 1,300km roads of which 13% and 15% are flooded, respectively.

Arndt, Jacob↗
DOE OSTI2023

Clean Energy Technology Applications on US Mine Land: Technical Analysis

As the United States transitions toward a clean energy economy, an opportunity exists for redeveloping the more than 17,000 mine land sites located across the nation with clean energy technologies, which have a combined potential for generating more than 85 GW of clean electricity. This report provides an overview of the potential of demonstrating and deploying clean energy projects on current and former mine land. Clean energy project refers to a project that demonstrates one or more of the following technologies: solar; microgrids; geothermal; direct air capture; fossil-fueled electricity generation with carbon capture, utilization, and sequestration; energy storage, including pumped storage hydropower and compressed air energy storage; and advanced nuclear technologies. The report discusses the following technologies and their potential for creating jobs and generating tax revenue that would result in direct and indirect benefits to the local economy: Solar photovoltaics (PV) is being developed on current and former mine land in various parts of the world, including the United States. This approach is attractive because it requires limited infrastructure investment and would utilize the bare surfaces of mines and tailing ponds. Solar resource availability may be greater in the southern regions, including the Interior and Appalachian Basins and the southwestern United States. However, since some mine land sites include areas of significant change in elevation, the deployment of PV on mine land may require sophisticated planning to account for shading and irradiance, or may require regrading of the areas. PV does not create significant environmental risks and generally does not face public resistance; Geothermal systems are often spatially and genetically associated with ore deposits, and in some cases, they have been discovered while in search for epithermal mineral resources. Numerous diverse geothermal applications have been employed at mine land around the world, including power generation, mineral extraction from geothermal brines, process heating, direct use for other mining operations, and direct use for non-mining operations and subsurface energy storage, including geothermal heat pumps. Case studies highlighting these applications provide key lessons relating to identifying drivers and barriers to geothermal resource deployment and can be used to create screening tools for identifying the types and locations of mine land most amenable to utilizing geothermal resources; Carbon capture, utilization, and sequestration technologies include direct air capture (DAC) and enhanced weathering. DAC technologies include air contactors, regeneration systems, and CO 2 compression systems. Captured CO 2 can be converted to valuable feedstocks or possibly injected into abandoned subsurface mines where it would be absorbed by alkaline rock waste and mine tailings or by the porous minerals along the walls of the mine. DAC systems can be coupled with energy sources such as wind, solar, grid, or geothermal. Many DAC systems require a source of water or steam; however, some are expected to be net producers of water. Local impacts of DAC systems are expected to be low, and are related to land footprint, material disposal, and upstream impacts of energy and material production; Compressed air energy storage is an established energy storage technology in salt caverns. It has the potential for implementation in underground mines by pressurizing and storing a large amount of air using electrical compressors when excess electricity is available. When a need for discharge emerges, the air is used to spin turbines and produce the necessary volume of electricity. Abandoned or unused mine openings, including shafts, adits, access tunnels, and mined workings of any orientation, offer potential for vast amounts of compressed air energy storage if the site characteristics meet operational requirements; Pumped hydropower storage can be implemented in surface and subsurface mines. In surface mine applications, both reservoirs may be located in a mine pit or artificial reservoirs made of excavated materials. In subsurface mines, the lower reservoir may be implemented by waterproofing and flooding mine shafts and tunnels. The water is then pumped from the lower reservoir to the upper reservoir during periods of low load and high production, and it is discharged through the turbines during periods of peak demand. The potential environmental damages associated with acidity of mine water or the presence of toxic chemicals incentivizes the development of closed-loop technologies, in which water circulates inside the pumped hydropower facility without being discharged into the external water basins; Advanced nuclear energy technologies include small modular reactors, which can be deployed locally to produce electricity and heat. Such units require seismic stability and a supply of cooling water, but population constraints may exist in some areas. Therefore, remote mine land could represent an optimal location for siting advanced nuclear energy technologies.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2022

Controlled-Environment Agriculture and the Geography of Food, Energy and Water Resilience in the United States

USDA guidelines call for an increase in fruit and vegetable consumption in U.S. households to promote healthier diets. Access to fresh fruits and vegetables are especially lacking in food deserts and food swamps (characterized by a prevalence of food that is highly processed and lacking in nutritional value). Adoption of the recommended healthy diet, which more than doubles the consumption of fruits and vegetables, would have a wide variety of health benefits and would reduce the land footprint of U.S diets. However, adopting a healthy diet would increase phosphate and nitrogen impacts associated with fertilizers and pesticides and would significantly increase freshwater consumption and energy use because of the resource intensity of field cultivation of fruits and vegetables. The majority of these crops are grown in just a few states, including California and Arizona, which are increasingly impacted by climate change. In addition, rural communities are rapidly becoming food deserts, while food produced in these areas is transported long distances to market. In recent years, highly intensified controlled environment (CE) agricultural systems, (i.e., vertical farming) have been developed to provide fresh food closer to consumers. Fruits and vegetables, many of which are amenable to CE culture, occupy a uniquely impactful segment of the food supply-chain, including their value in improving nutrition for vulnerable communities. The objective of this work is to elucidate the location dependency of the energy and water impacts of adoption of distributed CE farming for an important portion of the food system.

controlled environment agriculture↗
DOE OSTI2021

Spatially-Explicit Prediction of Capacity Density Advances Geographic Characterization of Wind Power Technical Potential

Mounting interest in ambitious clean energy goals is exposing critical gaps in our understanding of onshore wind power potential. Conventional approaches to evaluating wind power technical potential at the national scale rely on coarse geographic representations of land area requirements for wind power. These methods overlook sizable spatial variation in real-world capacity densities (i.e., nameplate power capacity per unit area) and assume that potential installation densities are uniform across space. Here, we propose a data-driven approach to overcome persistent challenges in characterizing localized deployment potentials over broad extents. We use machine learning to develop predictive relationships between observed capacity densities and geospatial variables. The model is validated against a comprehensive data set of United States (U.S.) wind facilities and subjected to interrogation techniques to reveal that key explanatory features behind geographic variation of capacity density are related to wind resource as well as urban accessibility and forest cover. We demonstrate application of the model by producing a high-resolution (2 km × 2 km) national map of capacity density for use in technical potential assessments for the United States. Our findings illustrate that this methodology offers meaningful improvements in the characterization of spatial aspects of technical potential, which are increasingly critical to draw reliable and actionable planning and research insights from renewable energy scenarios.

17 WIND ENERGY↗