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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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Comparing the OpenSolar Remote Shading Analysis Tool to On-Site Shading Measurements

OpenSolar is a free of charge application built for solar installers that creates a fully articulated 3D model of the site and performs remote shading analysis, in order to produce highly accurate designs and interactive, customizable proposals. Under the National Renewable Energy Laboratory (NREL) Commercialization Assistance Program (NCAP), NREL independently verified the accuracy of OpenSolar's remote analysis of solar access percentage values (SAVs) on an annual basis for locations in Los Angeles, CA, and Denver, CO. In aggregate, the results of the analysis show that Open Solar-calculated annual SAV measurements were statistically equivalent within ±2.63 SAVs for Los Angeles locations and ±2.69 SAVs for Denver locations compared to those of on-site measurements made with SunEye devices.

MATHEMATICS AND COMPUTING,SOLAR ENERGY↗

Degradation mechanisms and partial shading of glass-backsheet and double-glass photovoltaic modules in three climate zones determined by remote monitoring of time-series current–voltage and power datastreams

Degradation and partial shading impact the long-term reliability and power production of photovoltaic (PV) modules and power plants. Time-series power (P mp ) and current–voltage (I-V) curve datastreams from PV modules enable a remote diagnostic approach to quantify active degradation mechanisms and identify partial shading. We study three to nine years of these datastreams, including 3.6 million P mp I-V curves and 36 million values, from eight PV modules, four each of double-glass and glass-backsheet module architectures, located in three distinctly different Köppen-Geiger climate zones, to determine the module’s performance loss rates (PLR), identify active degradation mechanisms and power loss modes, along with partial shading by local objects. Considering both module architectures, PLR results indicate that the BSh climate zone is the most aggressive for module degradation, while the Alpine ET zone is the mildest climate. PLR of double-glass modules located in BWh and BSh climate zones are different due to the significantly greater uniform current loss (ΔP Isc ) for double-glass modules in BSh, at a 5% significance level. Power loss for four out of five modules located in the BWh and BSh climates are dominated by uniform current degradation. Statistical analysis of multistep I-V curves detects partial shading experienced by three studied modules with details of the shading profile, the shading Poynting vector diagram for the obstacle’s relative position, shading scenarios, and duration. Lastly, this work demonstrates how remote monitoring and diagnosis of P mp & I-V time-series of modules can provide quantitative operations and maintenance insights into system performance, degradation mechanisms, and shading.

14 SOLAR ENERGY↗

Computer Vision on Edge Devices for the Short Term Prediction of Cloud Cover

Edge Computing and IoT are important pieces of today's technological landscape. Here, we build a low-cost IoT sensor for sky imaging and program it using AWS GreenGrass, one of the leading IoT platforms. We demonstrate remote reprogramming of this device to load software that predicts sun shading events through the linear advection method, which is a baseline algorithm that can be used to benchmark algorithmic improvements in future work. Some future directions for sky imaging research are enumerated.

14 SOLAR ENERGY↗

Segmenting water and shadow regions within WorldView imagery using local binary patterns

Many shadow detection algorithms pertaining to remotely sensed imagery exist. Several of these algorithms exploit the spectral characteristics of shadows within imagery to identify shaded regions. However, these algorithms can have problems when water is also present within the imagery because water shares similar spectral characteristics with shadows. Many of these algorithms are applied to small image subsets instead of the image as a whole and frequently are applied to urban environments that require additional use of the normalized difference water index or other features to affect the removal of water from the shadow mask. This diversity of the image scene content coupled with the complexity and wide variety of environmental conditions that satellite imagery can acquire makes reliably separating shadow and water within larger images a complex problem. Thresholding various spectral indices to produce segmentation maps can be challenging when large, complex, and often imbalanced scenes are captured, which may require manual adjustment of algorithmic parameters for different image areas. Here, we present a methodology that makes use of the near-infrared channel using a watershed segmentation algorithm, local binary pattern measurements, and a support vector machine to classify shadow and water within a full WorldView scene. Results are promising with initial accuracies above 97% for both shadow and water.

47 OTHER INSTRUMENTATION↗

Vegetation clumping modulates global photosynthesis through adjusting canopy light environment

Abstract The spatial dispersion of photoelements within a vegetation canopy, quantified by the clumping index (CI), directly regulates the within‐canopy light environment and photosynthesis rate, but is not commonly implemented in terrestrial biosphere models to estimate the ecosystem carbon cycle. A few global CI products have been developed recently with remote sensing measurements, making it possible to examine the global impacts of CI. This study deployed CI in the radiative transfer scheme of the Community Land Model version 5 (CLM5) and used the revised CLM5 to quantitatively evaluate the extent to which CI can affect canopy absorbed radiation and gross primary production (GPP), and for the first time, considering the uncertainty and seasonal variation of CI with multiple remote sensing products. Compared to the results without considering the CI impact, the revised CLM5 estimated that sunlit canopy absorbed up to 9%–15% and 23%–34% less direct and diffuse radiation, respectively, while shaded canopy absorbed 3%–18% more diffuse radiation across different biome types. The CI impacts on canopy light conditions included changes in canopy light absorption, and sunlit–shaded leaf area fraction related to nitrogen distribution and thus the maximum rate of Rubisco carboxylase activity ( V cmax ), which together decreased photosynthesis in sunlit canopy by 5.9–7.2 PgC year −1 while enhanced photosynthesis by 6.9–8.2 PgC year −1 in shaded canopy. With higher light use efficiency of shaded leaves, shaded canopy increased photosynthesis compensated and exceeded the lost photosynthesis in sunlit canopy, resulting in 1.0 ± 0.12 PgC year −1 net increase in GPP. The uncertainty of GPP due to the different input CI datasets was much larger than that caused by CI seasonal variations, and was up to 50% of the magnitude of GPP interannual variations in the tropical regions. This study highlights the necessity of considering the impacts of CI and its uncertainty in terrestrial biosphere models.

59 BASIC BIOLOGICAL SCIENCES↗

CHESS 2025: Crown polygons and extracted reflectance for field sampling sites

This dataset contains (1) crown polygons for each tree, meadow, and shrub site sampled in the 2025 Colorado Headwaters Ecological Spectroscopy Study (CHESS) campaign (in geojson format, .geojson) and (2) extracted reflectance, uncertainty, and shade estimates for each crown polygon from the 2018 National Ecological Observatory Network (NEON) and 2025 CHESS campaigns. (in CSV format, .csv). Additional metadata are provided in a data dictionary describing column names and definitions (dd.csv), and in a file-level metadata file (flmd.csv). Crown polygons were manually delineated for each site in the 2025 campaign using a combination of field-collected GPS data (doi:10.15485/3022418), RGB (red, green, blue) and false color reflectance mosaics (doi:10.15485/3013535), and LiDAR-derived (Light Detection and Ranging) canopy height (CHM) and digital surface (DSM) models (DOI and citation to be added upon publication). Where there was misalignment between the spectrometer- and LiDAR-derived data products, polygons prioritized alignment with the spectrometer-derived data products. Polygons were delineated conservatively to only select pixels representative of vegetation samples collected in the field. Crown polygons for 2018 are published at (doi:10.15485/1618130) and were developed using the same protocol. For each polygon, all pixels from all flightlines were extracted where the pixel centroid was contained within the polygon. For each pixel, we extracted the surface reflectance, uncertainty, and shade estimates. Details on the extracted datasets are available at (doi:10.15485/3013527, doi:10.15485/3013535). CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgment: This research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004) and was funded by EMIT Extended Mission Phase E Science.

2018 NEON and 2025 CHESS Campaigns↗

Synergistic effects of climate warming and atmospheric nutrient deposition on the alpine lake ecosystem in the south-eastern Tibetan Plateau during the Anthropocene

Alpine lakes on the Tibetan Plateau are highly sensitive to global change and have been recognized as the sentinel of climate warming. However, anthropogenic impacts in populated area are migrating to these remote areas via transporting particulate nutrients by atmospheric deposition. Whether warming and nutrient deposition would impose additive or synergistic effects on the lake ecosystem remains largely unknown. Here, we present multi-proxy (sediment pigment and geochemistry) records during the past two centuries at the Cuoqia Lake in the southeast Tibetan Plateau. We found that the lake exhibited rapid ecological changes since 1980 AD characterized by an increase in primary productivity due to algal proliferation, with more rapid growth of green algae and diatoms. These findings are in concert with many other lakes (e.g., Moon Lake and Shade Co) in the same area, suggesting a consistent pattern of ecosystem evolution at the region scale. Statistical analyses suggested that nutrient deposition and climate warming were strongly associated with the variations in primary productivity and algae composition, exerting both individual and interactive effects. In addition, scenario analyses with a well-established process-based ecosystem model further revealed that the two factors not only individually, but also synergistically promoted the algal proliferation and community succession. Such synergy is evident in that the effect of lake warming would be more pronounced under higher nutrient deposition scenario, which is potentially due to higher temperature-driven mineralization in warmer conditions, and higher efficiency of nutrient utilization under enhanced light availability attributing to declining ice thickness and duration in cold seasons. Overall, our study proposes the existence and quantifies the synergistic impacts of climate warming and anthropogenic activities in driving the ecological changes in remote alpine lakes on the Tibetan Plateau. The lake ecological consequences driven by individual factor would be worsen by such synergy, so that we cannot predict the lake ecosystem trajectory in the future based on each factor separately, and more efforts than previously expected would be needed for the lake restoration and management.

Zhang, Can↗

Bridging gaps in permafrost-shrub understanding

Permafrost, permanently frozen ground which underlies much of the Arctic and sub-Arctic, is influenced by deciduous shrubs, yet our understanding of permafrost-shrub interactions is limited. This is largely due to a lack of widespread, long-term, high-quality observations across Arctic and sub-Arctic systems, which are difficult to study due to their remote locations. Shrubs are rapidly expanding in many areas of Arctic tundra and can either amplify or inhibit permafrost thaw, making it crucial that we can understand and predict permafrost-shrub interactions. As we have limited time and resources to make observations, we must design our field campaigns to be as impactful as possible. Below we outline the current state of knowledge and give suggestions about how we can maximize our fieldwork’s impact. From field studies conducted around the Arctic, we know that shrubs generally have a cooling effect on permafrost in the summer, largely caused by the shrub canopy shading the soil. However, summertime cooling can be counteracted by a warming effect in winter, caused by the trapping of blowing snow by shrubs, which leads to increased snow depths. In addition to these commonly observed effects, both observations and models show that other local factors such as climate, soil, snow, and disturbances can interact to cause contrasting dominant effects on permafrost temperatures. For example, shrubs that protrude through the snowpack have been observed to cool permafrost in winter via thermal bridging between the air above the snow and the soil below. However, at other research sites, protruding shrubs lower the surface albedo and cause earlier snowmelt in spring, amplifying permafrost thaw by exposing the soil to thawing earlier. Protruding shrubs have also been observed to induce snow melt in autumn, creating ice layers at the snow surface that prevent further snow accumulation and eliminate the ability of shrubs to trap blowing snow, thereby reducing the winter warming effect. While we understand the physical processes that lead to these effects, we cannot explain why we observe different effects between sites.

54 ENVIRONMENTAL SCIENCES↗

Custom surface reflectance, shade mask, and equivalent water thickness maps for the Colorado Headwaters Ecological Spectroscopy Study (2025)

This dataset contains land surface reflectance estimates and additional derived products generated from NEON Imaging Spectrometer (NIS) data collected in the Upper Gunnison river basin during June and July of 2025. Data was collected over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). These products were derived from radiance and LiDAR data collected by the NEON Airborne Observation Platform (AOP) campaign funded by the Colorado Headwaters Ecological Spectroscopy Study (CHESS) (doi:10.15485/3017965). Products include per-pixel surface reflectance (rfl) and reflectance uncertainty (rfl_unc), observational data (obs), canopy equivalent water thickness (ewt), and shade masks. Atmospheric correction was performed per flightline using the ISOFIT (Imaging Spectrometer Optimal FITting) optimal estimation framework to estimate surface reflectance and the associated per-band reflectance uncertainty. Reflectance retrievals achieved a mean absolute error of 1.5% across diverse validation surfaces (see validation report.pdf). Equivalent water thickness was calculated from surface reflectance using the Beer–Lambert absorption of liquid water. Shade masks were generated based on the geometry between the sun angle, ground surface, and sensor at the time of flight. Data products are provided per-flightline and as mosaics for each domain. Flightline data products are provided as ENVI-formatted binary files (rfl, rfl_unc, ewt) and GeoTIFFs (shade). Reflectance and uncertainty mosaics are provided as tiled NetCDFs, while all other mosaicked products are provided as cloud-optimized GeoTIFFs. These formats are supported by common geospatial software (e.g., QGIS, ArcGIS, ENVI) and programmatic libraries in Python (e.g., rasterio, xarray, spectral, netCDF4) and R (e.g., terra, ncdf4). Processing workflows were designed to be equivalent to those used to generate the 2018 CHESS campaign airborne imaging spectroscopy data products (doi:10.15485/3013527). All outputs were co-registered to a common spatial grid to support time series analyses. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgment: Data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). Computational research was carried out at the Jet Propulsion Laboratory, California Institute of Technology, under a contract with the National Aeronautics and Space Administration (80NM0018D0004) and was funded by EMIT Extended Mission Phase E Science.

2018 NEON and 2025 CHESS Campaigns↗

Point Cloud Based Mapping of Understory Shrub Fuel Distribution, Estimation of Fuel Consumption and Relationship to Pyrolysis Gas Emissions on Experimental Prescribed Burns

Forest fires spread via production and combustion of pyrolysis gases in the understory. The goal of the present paper is to understand the spatial location, distribution, and fraction (relative to the overstory) of understory plants, in this case, sparkleberry shrub, namely its degree of understory consumption upon burn, and to search for correlations between the degree of shrub consumption to the composition of emitted pyrolysis gases. Data were collected in situ at seven small experimental prescribed burns at Ft. Jackson, an army base in South Carolina, USA. Using airborne laser scanning (ALS) to map overstory tree crowns and terrestrial laser scanning (TLS) to characterize understory shrub fuel density, both pre- and postburn estimates of sparkleberry coverage were obtained. Sparkleberry clump polygons were manually digitized from a UAV-derived orthoimage of the understory and intersected with the TLS point cloud-derived rasters of pre- and postburn shrub fuel bulk density; these were compared in relation to overstory crown cover as well as to ground truth. Shrub fuel consumption was estimated from the digitized images; sparkleberry clump distributions were generally found to not correlate well to the overstory tree crowns, suggesting it is shade-tolerant. Moreover, no relationship was found between the magnitude of the fuel consumption and the chemical composition of pyrolysis gases, even though mixing ratios of 25 individual gases were measured.

54 ENVIRONMENTAL SCIENCES↗

We Must Stop Fossil Fuel Emissions to Protect Permafrost Ecosystems

Climate change is an existential threat to the vast global permafrost domain. The diverse human cultures, ecological communities, and biogeochemical cycles of this tenth of the planet depend on the persistence of frozen conditions. The complexity, immensity, and remoteness of permafrost ecosystems make it difficult to grasp how quickly things are changing and what can be done about it. Here, we summarize terrestrial and marine changes in the permafrost domain with an eye toward global policy. While many questions remain, we know that continued fossil fuel burning is incompatible with the continued existence of the permafrost domain as we know it. If we fail to protect permafrost ecosystems, the consequences for human rights, biosphere integrity, and global climate will be severe. The policy implications are clear: the faster we reduce human emissions and draw down atmospheric CO 2 , the more of the permafrost domain we can save. Emissions reduction targets must be strengthened and accompanied by support for local peoples to protect intact ecological communities and natural carbon sinks within the permafrost domain. Some proposed geoengineering interventions such as solar shading, surface albedo modification, and vegetation manipulations are unproven and may exacerbate environmental injustice without providing lasting protection. Conversely, astounding advances in renewable energy have reopened viable pathways to halve human greenhouse gas emissions by 2030 and effectively stop them well before 2050. We call on leaders, corporations, researchers, and citizens everywhere to acknowledge the global importance of the permafrost domain and work towards climate restoration and empowerment of Indigenous and immigrant communities in these regions.

54 ENVIRONMENTAL SCIENCES↗

CHESS 2025: Spectrometer orthorectified at-sensor radiance from NEON AOP imaging spectroscopy surveys

This dataset provides Level 1 (L1) orthorectified at-sensor radiance derived from measurements collected by the Imaging Spectrometer-1 (NIS-1) onboard the NEON (National Ecological Observatory Network) Airborne Observation Platform (AOP) for the 2025 Colorado Headwaters Ecological Spectroscopy Study (CHESS). NIS-1 captures light reflected from the Earth’s surface in 426 discrete wavelength bands as raw digital numbers (DNs; Level 0). These data are then calibrated to physical units (uW/cm²·sr·nm) following the processing steps described in the NEON Imaging Spectrometer Level 1B Calibrated Radiance Algorithm Theoretical Basis Document (ATBD; Gallery 2022). The data delivered here are the primary inputs for the surface reflectance product in “Custom surface reflectance, shade masks, and equivalent water thickness maps for the Colorado Headwaters Ecological Spectroscopy Study” (Carroll et al. 2026). For intertemporal comparison, the radiance data here are most directly relatable to the v2 radiance data in “NEON AOP Imaging Spectroscopy Survey of Upper East River Colorado Watersheds: Raw-Space Radiance and Observational Variable Dataset” (Goulden et al. 2018), to which the same processing methodology was applied. Together, the radiance and reflectance data enable users to exploit the unique reflection signatures of different surface objects for land cover classification, foliar trait mapping, plant vigor assessment, water content estimation, trace-element identification, and other scientific applications. The data were acquired over three study domains in the Upper Gunnison river basin: the upper East River watershed (CRBU); Almont Triangle and Taylor Canyon (ALMO); and Upper Taylor River watershed (UPTA) between 2025-06-13 and 2025-07-15. Within each domain, data are delivered by flightline as orthorectified and calibrated hyperspectral rasters in Hierarchical Data Format version 5 (HDF5) format, with radiance values provided in uW/cm²·sr·nm on a fixed, uniform Universal Transverse Mercator (UTM) grid at 1 meter spatial resolution. The radiance rasters include all 426 NIS-1 spectral bands, along with associated quality-assurance (QA) and diagnostic and ancillary layers needed for atmospheric correction workflows. Orthorectified radiance is produced from pushbroom spectrometer observations by applying NEON’s radiometric calibration (including bad pixel masking, dark subtract, dark pedestal shift correction, electronic panel ghost correction, grating ghost correction, deblur correction and flat-fielding) and spectral calibration (using spectral response function band centers and full-width at half-maximum intensity), followed by geolocation and regridding to the fixed grid. CHESS Project Description: The Colorado Headwaters Ecological Spectroscopy Study (CHESS) comprised a multi-week airborne remote sensing and field observation campaign in the Upper Gunnison Basin, Colorado, conducted in June and July of 2025. Airborne remote sensing was conducted by the National Ecological Observatory Network Airborne Observation Platform (NEON AOP), concurrent with a field campaign run by the Rocky Mountain Biological Laboratory (RMBL), the Lawrence Berkeley National Laboratory (LBNL) and SLAC National Accelerator Laboratory Watershed Function Science Focus Area (SFA), and NASA-JPL (Jet Propulsion Laboratory) Earth Surface Mineral Dust Source Investigation (EMIT) program. Between June 10 and July 18, 2025, the NEON AOP flight team collected high-resolution aerial imaging spectroscopy and Light Detection and Ranging (LiDAR) data over three domains: the Upper East River (CRBU), Almont Triangle (ALMO), and the Upper Taylor Basin (UPTA). In coordination with the flights, a field campaign acquired ground-truth observations, including observations of vegetation composition, foliar traits, forest demography, and subsurface properties in 18 core sampling areas within the domains. Additional surface water observations were taken at over 380 point locations. All CHESS campaign datasets can be found within the CHESS ESS-DIVE data portal: https://data.ess-dive.lbl.gov/portals/chess. Funding Acknowledgement: Field and remote-sensing data acquisition was performed under a grant from the National Aeronautics and Space Administration (80NSSC24K1005). This work was also supported by the Watershed Function Science Focus Area at Lawrence Berkeley National Laboratory funded by the US Department of Energy, Office of Science, Biological and Environmental Research under Contract No. DE-AC02-05CH11231.

2018 NEON and 2025 CHESS Campaigns↗

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↗