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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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DOE OSTI2026

Local Resource Assessment: Beetle-Killed Spruce in Alaska

This report synthesizes forest inventory and spatial data from federal and state sources to present a snapshot of beetle-killed spruce across Southcentral and Interior Alaska. This natural resource is under investigation for use in cellulose-based products, particularly building insulation. Research funded by the Department of Energy's ARPA-E program, has successfully developed insulation - Celium - using beetle-killed spruce combined with mycelium, the root network of fungi. The resulting insulation product can be manufactured locally and used across all Alaskan climate zones for residential, commercial, and shipping applications. Removing standing dead wood also contributes to wildfire risk reduction and mitigates associated public health impacts. This Local Resource Assessment, funded by the Denali Commission, contextualizes and reconciles unaligned forestry data sources, establishing a pathway to refined, replicable analysis and, ultimately, presenting estimates of beetle-killed spruce biomass to inform the potential scale and development of a Celium industry.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗
DOE OSTI2025

Using multiple high-resolution datasets to benchmark the energy exascale earth system model (E3SM) for renewable resource assessment

The United States is accelerating its shift toward a renewable energy system. However, renewable resources, which harness energy from the Earth system, are susceptible to both present-day climate variability and future climate change. For example, variations in regional climate can alter renewable energy production patterns and site viability. The use of high-resolution climate model projections can therefore facilitate and may be critical to long-term planning of renewable energy investments. However, climate models must first be validated for renewable resource assessment. This research employs multiple high-spatiotemporal-resolution datasets to assess the capability of the Department of Energy’s (DOE) Energy Exascale Earth System Model version 2 North American Regionally Refined Model (E3SMv2-NARRM) for predicting multi-year climatological values of solar and wind energy capacity factors in the continental U.S., with a focus on regional and seasonal variability. Present-day E3SMv2-NARRM simulations are compared with reported utility-scale production data obtained from the Energy Information Administration (EIA). In addition, E3SMv2-NARRM data are evaluated against non-climate benchmark models from the National Renewable Energy Laboratory, including the Wind Integration National Dataset Toolkit and the National Solar Radiation Database (NSRDB), as well as three wind energy datasets from PLUSWIND. Our analysis indicates that solar capacity factors from E3SM closely match those from the NSRDB dataset. However, both datasets tend to overestimate values by 10% in comparison to EIA data. Furthermore, biases in wind capacity factors within E3SM are notably pronounced in the West Coast regions, where the seasonal cycle diverges from EIA data.

Energy forecasting, Capacity factor, Renewable ene↗
DOE OSTI2022

Closed-Loop Pumped Storage Hydropower Resource Assessment for the United States. Final Report on HydroWIRES Project D1: Improving Hydropower and PSH Representations in Capacity Expansion Models

Pumped storage hydropower represents the bulk of the United States' current energy storage capacity: 23 gigawatts (GW) of the 24-GW national total (Denholm et al. 2021). This capacity was largely built between 1960 and 1990. PSH is a mature and proven method of energy storage with competitive round-trip efficiency and long life spans. These qualities make PSH a very attractive potential solution to energy storage needs, particularly for longer-duration storage (8 hours or more); such storage will be crucial to bridge gaps in electricity production as variable wind and solar production continue to comprise an ever-larger portion of the United States' energy portfolio (Cole et al. 2021; Frazier et al. 2021). However, it is unclear how much potential the United States has for the development of new PSH. No new large PSH has been constructed in the United States since the 1990s, and attempts to quantify technical potential capacity from PSH project applications to the Federal Energy Regulatory Commission (FERC) suffer from inconsistent site and cost evaluation methodologies and likely are not representative of all PSH opportunities. This study seeks to better under understand the technical potential for PSH development in the United States by developing a national-scale resource assessment for closed-loop PSH. Individual sites are not modeled in sufficient detail for project-level development, but they do provide valuable insights into potential resource areas across the United States, including the ability to provide estimates for a range of long-term development scenarios.

13 HYDRO ENERGY↗
DOE OSTI2022

Improvement of aerosol optical depth data for localized solar resource assessment

Solar irradiance, especially for direct normal irradiance (DNI), is sensitive to the atmospheric aerosols, which can strongly extinguish DNI over areas with elevated aerosol loadings. The National Solar Radiation Database (NSRDB), developed by the National Renewable Energy Laboratory (NREL), uses AOD from MERRA-2 reanalysis and is further downscaled from 0.5° to 2-km based on elevation. However, the elevation-based downscaling may not accurately represent AOD, especially over the areas with large AOD gradients. This study examined whether the 1-km MODIS MAIAC satellite-retrieved AOD product can better represent the AOD distribution and be used to improve solar irradiance assessment. We focused on areas with relatively high AOD over North America (California, and New York City, US, and Mexico City in Mexico, in particular). The evaluation of MAIAC AOD and MERRA-2 AOD against ground-truth AERONET AOD shows that MAIAC AOD exhibits smaller RMSE by about 0.05 and higher correlation coefficient by 0.1-0.6 than MERRA-2 AOD. In addition, MERRA-2 AOD shows larger negative bias. The simulated DNI using MAIAC AOD (DNIMAIAC) and using MERRA-2 AOD (DNINSRDB) were evaluated with DNI observations. The results show the performance of DNIMAIAC is better than that of DNINSRDB with smaller RMSE by 0.5-1.5%, smaller positive mean bias by 0.8-3.1% and comparable correlation for the 3 sites analyzed. Overall, 1-km MAIAC AOD shows higher accuracy than 2-km elevation-based MERRA-2 AOD, leading to better performance of the simulated DNI using MAIAC AOD. Therefore, 1-km MAIAC AOD can be used to improve the accuracy of solar resource assessment.

14 SOLAR ENERGY↗
DOE OSTI2025

Oakridge Geothermal Resources Assessment

Through the Communities Local Energy Action Program (LEAP), NREL provided technical assistance to a coalition of stakeholders from Oakridge, Oregon. The coalition included community-based non-profit organizations, the city government, the local utility, and others. Technical assistance provides analysis and information to support Oakridge stakeholders with their goals to increase energy reliability and resilience in the community, while promoting economic development. The Geothermal Resource Assessment provides technical analysis related to the geothermal resource in the Oakridge area, possible technology applications, and information related to further geothermal exploration. Technical analysis includes a review of a previous geothermal study conducted for Oakridge, thermal modeling to estimate reservoir temperatures, and technoeconomic simulation of a combined heat and power application in the Oakridge area.

15 GEOTHERMAL ENERGY↗
DOE OSTI2021

Retrospective Analysis of Geothermal Mineral Recovery and Domestic Resource Assessment - References

This reference database in RIS format contains all of the references that were collected as part of our retrospective analysis of geothermal mineral recovery (REE and Li) activities and domestic resource assessment. The outputs detail the chemistry and molecular processes used in lithium recovery from geothermal brines. The articles included include information about the study including more information on geothermal brines and the technologies used for recovering lithium from geothermal brines.

15 GEOTHERMAL ENERGY↗
DOE OSTI2025

Evaluating the potential of short-term instrument deployment to improve distributed wind resource assessment

Distributed wind projects, which are connected at the distribution level of an electricity system or in off-grid applications to serve specific or local energy needs, often rely solely on wind resource models to establish wind speed and energy generation expectations. Historically, anemometer loan programs have provided an affordable avenue for more accurate onsite wind resource assessment, and the lowering cost of lidar systems has shown similar advantages for more recent assessments. While a full 12 months of onsite wind measurement is the standard for correcting model-based long-term wind speed estimates for utility-scale wind farms, the time and capital investment involved in gathering onsite measurements must be reconciled with the energy needs and funding opportunities that drive expedient deployment of distributed wind projects. Much literature exists to quantify the performance of correcting long-term wind speed estimates with 1 or more years of observational data, but few studies explore the impacts of correcting with months-long observational periods. This study aims to answer the question of how short you can go in terms of the observational time period needed to make impactful improvements to model-based long-term wind speed estimates. Three algorithms, multivariable linear regression, adaptive regression splines, and regression trees, are evaluated for their skill at correcting long-term wind resource estimates from the European Centre for Medium-Range Weather Forecasts Reanalysis version 5 (ERA5) using months-long periods of observational data from 66 locations across the US. On average, correction with even 1 month of observations provides significant improvement over the baseline ERA5 wind speed estimates and produces median bias magnitudes and relative errors within 0.22 m s −1 and 4 percentage points of the median bias magnitudes and relative errors achieved using the standard 12 months of data for correction. However, in cases when the shortest observational periods (1 to 2 months) used for correction are not well correlated with the overlapping ERA5 reference, the resultant long-term wind speed errors are worse than those produced using ERA5 without correction. Summer months, which are characterized by weaker relative wind speeds and standard deviations for most of the evaluation sites, tend to produce the worst results for long-term correction using months-long observations. The three tested algorithms perform similarly for long-term wind speed bias; however, regression trees perform notably worse than multivariable linear regression and adaptive regression splines in terms of correlation when using 6 months or less of observational data for correction. Translating the analysis to wind energy, median relative errors in the capacity factor are on average within 10 % using 1 month of training. If the observation period used for correction is not well correlated with the reference data, however, misrepresentation of the observed capacity factor can be substantial. The risk associated with poor correlation between the observed and reference datasets decreases with increasing training period length. In the worst-correlation scenarios, the median capacity factor relative errors from using 1, 3, and 6 months are within 47 %, 26 %, and 16 %, respectively.

17 WIND ENERGY↗
DOE OSTI2022

Evaluation of obstacle modelling approaches for resource assessment and small wind turbine siting: case study in the northern Netherlands

Abstract. Growth in adoption of distributed wind turbines for energy generation is significantly impacted by challenges associated with siting and accurate estimation of the wind resource. Small turbines, at hub heights of 40 m or less, are greatly impacted by terrestrial obstacles such as built structures and vegetation that can cause complex wake effects. While some progress in high-fidelity complex fluid dynamics (CFD) models has increased the potential accuracy for modelling the impacts of obstacles on turbulent wind flow, these models are too computationally expensive for practical siting and resource assessment applications. To understand the efficacy of available models in situ, this study evaluates classic and commonly used methods alongside new state-of-the-art lower-order models derived from CFD simulations and machine learning approaches. This evaluation is conducted using a subset of an extensive original dataset of measurements from more than 300 operational wind turbines in the northern Netherlands. The results show that data-driven methods (e.g. machine learning and statistical modelling) are most effective at predicting production at real sites with an average error in annual energy production of 2.5 %. When sufficient data may not be available de novo to support these data-driven approaches, models derived from high-fidelity simulations show promise and reliably outperform classic methods. On average these models have 6.3 %–11.5 % error compared with 26 % for classic methods and 27 % baseline error for reanalysis data without obstacle correction. While more performant on average, these methods are also sensitive to the quality of obstacle descriptions and reanalysis inputs.

17 WIND ENERGY↗
DOE OSTI2021

Addendum to water resource assessment in the New Mexico Permian Basin

There are an estimated 48,745 wells producing oil or gas in New Mexico as of August 8, 2020 and with advances in drilling and oil recovery technology the use of hydraulic fracturing has become more commonplace. With a typical well requiring 1.5 to 16 million gallons of water, there is an increased demand for water in the Permian Basin and concern over the regions ability to meet this demand. This report is an addendum to the 2018 report Water Resource Assessment in the New Mexico Permian Basin (SAND2018-12018) to monitor baseline water level and chemistry data established in the original report. Results from this addendum can be used to further understand regional water supply and demands and aid in the BLMs mission of sustainably meeting the needs of water users while protecting human and environmental health.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Organic Waste Resource Assessment for the Detroit Region

This study summarizes major sources of organic wastes in the Detroit region to (1) characterize target feedstock magnitudes and distribution in support of techno-economic analysis (TEA), and (2) guide the design of blended feedstock conversion experiments using hydrothermal liquefaction (HTL). Feedstocks considered in this review include municipal wastewater sludge solids (untreated) and scum; bulk municipal solid waste (MSW); the organic fraction of municipal solid waste (OF-MSW); residential food waste, non-residential food waste including institutional, industrial, and commercial (IIC) sources; confined animal manures (i.e., lactating dairy, feedlot beef, and market swine); waste fats, oils and greases (FOG); agricultural residues; forest residues. The scope of the investigation was limited to existing modeled or publicly available reporting datasets. Bulk MSW data were only collected for context and to generate estimates of OF-MSW by waste type and should not be included in total organic waste estimates. Because the TEA analysis boundary was not defined prior to conducting the resource assessment, the data are summarized within six spatial contexts (boundaries), including (1) city of Detroit (census); (2) Great Lakes Water Authority (GLWA) service area; “Tri-county” urban area (census); “Metro” Detroit-Warren-Dearborn Metropolitan Statistical Area (MSA) (census); Detroit-Warren-Ann Arbor Combined Statistical Area (CSA) (census); and the Michigan Councils of Government (COG) Region-1. All of the spatial contexts are entirely within the State of Michigan, and some overlap one another. A broader context could be developed to include data from surrounding states or Canada.

09 BIOMASS FUELS↗
DOE OSTI2026

Stochastic Thermo-Hydro Modeling and Neural Network Surrogate Development for Thermal Resource Assessment of the Galleries-to-Calories Geobattery

The Galleries-to-Calories Geobattery concept explores the use of abandoned coal mine workings for large-scale thermal energy transport and storage. The system involves injecting waste heat from a supercomputing facility into flooded mine galleries, where groundwater flow can store and transport thermal energy for potential recovery in downgradient district heating and cooling applications. To evaluate the feasibility and performance of the Geobattery under geological and operational uncertainty, we developed a suite of stochastic thermo-hydrological (TH) simulations using Monte Carlo sampling of key uncertain parameters (e.g., permeability, porosity, thermal conductivity, specific heat capacity) and operating conditions (e.g., injection rate, injection temperature). Results identified injection rate and temperature as the most influential parameters governing thermal front propagation, while the geometry of the room-and-pillar structure played a critical role in directing the extent and orientation of thermal advancement. Optimal combinations of material properties for maximizing heat recovery were also determined. To address the high computational cost of coupled-process stochastic modeling, we trained a neural network surrogate model on 24,000 physics-based realizations, achieving an R² > 0.99 and MAE < 0.1 for temperature predictions at monitoring locations. This surrogate enabled an additional 100,000 realizations for global sensitivity analysis and probabilistic thermal resource assessment. The integrated stochastic physics–surrogate modeling framework offers a computationally efficient tool for quantifying uncertainty, identifying key drivers, and informing early-stage design decisions for Geobattery systems.

15 - GEOTHERMAL ENERGY↗
DOE OSTI2026

Technology Impact and Resource Assessment of Existing and Planned U.S. Biofuel Production: Life Cycle Water Consumption, Water Stress, Land Use, and Criteria Air Pollutants

Biofuels have the potential to strengthen the U.S. energy supply, enhance energy security, and promote economic development. As the United States continues to expand biofuel production, quantifying resource requirements and location-specific constraints is crucial for planning, siting, and technology development to support long-term viability. Accordingly, this work assesses the life cycle resource consumption (water consumption, and land use), water stress and criteria air pollutants associated with expanded U.S. biofuel production over the 2020–2035 period, based on producers’ plans. We perform a bottom-up technology impact assessment and resource assessment by integrating facility-level production statistics with Argonne’s Research and Development (R&D) GREET model and county-level water-stress characterization factors from Available Water Remaining for the United States (AWARE-US) model. Results suggest that by 2035, biofuels could meaningfully contribute to U.S. energy demand, driven primarily by first-generation and waste-based feedstocks with plans for substantial capacity expansion, although cellulosic and e-fuel technologies remain limited. However, growth must be managed to minimize impacts on water resources and land use. These impacts vary by fuel type and facility location, specifically, projected expansion increases water consumption and can elevate water-stress impacts in certain regions like Nebraska, Kansas, Colorado, Idaho, California and North Texas. Direct land use also increases overall, particularly for first-generation feedstocks such as corn and soybeans. These findings underscore the need for continued technological improvements and innovative strategies to manage resource demands as the industry scales and to support complementary deployment within the evolving U.S. energy system.

09 BIOMASS FUELS↗
DOE OSTI2022

Evolving Metrics for Resource Adequacy Assessment

Resource adequacy analysis quantifies the likelihood of capacity shortfall on a power system in a probabilistic manner. Using a combination of statistical techniques and power system fundamentals, the analysis typically evaluates hundreds or thousands of stochastic random samples (replications) of varying load, generator outages, variable renewable energy availability, and other aspects of power system uncertainty. In this range of uncertainty, there are - at times - periods where the power system's available resources are insufficient to meet system demand, referred to as a shortfall event. Today's power systems' rapidly evolving generation mix is changing the types of data needed by system planners and regulators, which can often render traditional resource adequacy metrics insufficient for ensuring resource adequacy for tomorrow's grid. In this paper we provide a critical assessment of traditional measures of shortfall risk in power systems, discussing their shortcomings and how they compare to metrics used in other domains. From this analysis we propose four steps forward for improving power system resource adequacy risk metrics in the future.

ENERGY PLANNING, POLICY, AND ECONOMY,POWER TRANSMI↗
DOE OSTI2023

Beyond Expected Values Evolving Metrics for Resource Adequacy Assessment

Resource adequacy analysis quantifies the likelihood of capacity shortfall on a power system in a probabilistic manner. Using a combination of statistical techniques and power system fundamentals, the analysis typically evaluates hundreds or thousands of stochastic random samples (replications) of varying load, generator outages, variable renewable energy availability, and other aspects of power system uncertainty. In this range of uncertainty, there are - at times - periods where the power system's available resources are insufficient to meet system demand, referred to as a shortfall event. Today's power systems' rapidly evolving generation mix is changing the types of data needed by system planners and regulators, which can often render traditional resource adequacy metrics insufficient for ensuring resource adequacy for tomorrow's grid. In this paper we provide a critical assessment of traditional measures of shortfall risk in power systems, discussing their shortcomings and how they compare to metrics used in other domains. From this analysis we propose four steps forward for improving power system resource adequacy risk metrics in the future.

ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

Resource Assessment for Hydrogen Production

This analysis was conducted in support of the U.S. Department of Energy's H2@Scale initiative, and this report examines the resources required to meet demand for an additional 10 million metric tonnes (MMT) of hydrogen in 2040. The technical potential of hydrogen production from fossil, nuclear, and renewable energy resources is presented. Updated maps describe the geographical distribution of hydrogen production potential from renewable energy resources. The results conclude that the technical resource availability of domestic energy resources is sufficient to meet an additional 10 MMT of hydrogen demand in 2040, without placing significant pressure on existing resources. While this level of hydrogen demand could result in a significant increase in renewable energy consumption, in particular, the technical potential of each resource is estimated to be sufficient to meet the demand. Future research, to enable the large-scale integration of hydrogen in the U.S. energy and other sectors, will include analyzing the geographic distribution of resources in relation to hydrogen demand for a variety of applications. Additional techno-economic analysis is also needed to understand the economic potential of hydrogen in other industries, beyond transportation; such analysis is currently being undertaken by a multi-lab project initiated by DOE in 2016. Finally, information from techno-economic analyses should be used to continually update and inform R&D targets for energy production, hydrogen production, and hydrogen utilization technologies.

08 HYDROGEN↗
DOE OSTI2020

Sensitive Resources Assessment and Forest Analysis for the Proposed Versatile Test Reactor, Oak Ridge, Tennessee

The US Department of Energy’s (DOE’s) Oak Ridge National Laboratory (ORNL) is a leading institution in advanced materials, supercomputing, neutrons, and nuclear science. As a research laboratory managed by UT-Battelle, LLC for DOE, ORNL has national priorities in energy, security, and scientific discovery that necessitate facility improvements and expansions. DOE is also committed to environmental stewardship. The laboratory is located on the ~32,000-acre (~13,000-ha) Oak Ridge Reservation (ORR), much of which is categorized as a National Environmental Research Park (NERP) and a state Wildlife Management Area. DOE works with the Tennessee Wildlife Resources Agency (TWRA), Tennessee Department of Environment and Conservation (TDEC), US Fish and Wildlife Service (USFWS), US Department of Agriculture, and other agencies to serve as an effective steward of the ORR. Accordingly, project managers must conform to environmental regulations, agreements, and policies at the federal, state, and institutional levels. Per 40 CFR (Code of Federal Regulations) 1508.14, potential effects on research and science education also represent potential effects of federal actions on the NERP, and impacts on, e.g., deer harvest, must be considered on the Oak Ridge Wildlife Management Area when other aspects of the human environment are affected. The United States currently has no fast neutron testing capability to support advanced nuclear research and development. The proposed Versatile Test Reactor (VTR) will take advantage of current investments by the US government and private industry in nuclear reactors to expedite the design and construction process, using proven technology to create a world-class scientific infrastructure. The VTR will take advantage of fast neutrons provided by this proven technology, along with a capability to rapidly insert, conduct, and remove state-of-the-art experiments. An advantage of the VTR is that it can support future innovations in experimental capabilities without modifying the facility. The VTR will support progress in a variety of science and technology areas, including testing and qualification of advanced reactor fuels; testing and qualification of innovative structural materials; testing of innovative components and instruments; validation of advanced modeling and simulation tools; and versatility for future technical missions. Through proven technology, the VTR can take advantage of existing reactor designs and operating experience to reduce the risk, cost, and time for design and construction. The top available resources of DOE laboratories, industry, and universities will be used to expedite reactor design and construction toward developing the scientific infrastructure that affords a strong testing capability that can be sustained over many years. This report summarizes current knowledge of natural and cultural resources primarily within the VTR construction area. At the time of this report, the proposed VTR site design includes a construction area of ~150.4 acres (~69.9 ha), which contains an ~51.3-acre (~20.8-ha) operations area, located within forested natural areas of the ORR. The primary goal of the work presented here was to evaluate potential effects on sensitive resources that might result from development and construction activities associated with VTR. In addition to on-the-ground surveys during spring and summer 2020 by the ORNL Natural Resources Management Program and Aquatic Ecology Group staff, this report makes use of historical (pre-1995) and contemporary (1995 to present) data from additional confirmed sources (e.g., TDEC). Likewise, forest conditions were compiled from a 2011 forest inventory and supplemented with limited ground observations in 2020. The individuals who obtained and compiled the data presented here are familiar with and routinely assess sensitive resources on the ORR. Anyone who references this report must consider that the timing of surveys did not permit a complete delineation of the resources that will be affected. If the VTR project proceeds, additional surveys will be required to account for the seasonal patterns of various threatened and endangered species. Data deficiencies and potential resources that likely went undetected are indicated where possible. Accordingly, this report should facilitate more environmentally sound decisions during planning and 2 development of the VTR site, provide a foundation for further assessment of sensitive and cultural resources, and help project managers better address regulatory guidance and DOE policies on sustainable development in compliance with, for example, the US Endangered Species Act (ESA), Migratory Bird Treaty Act (MBTA), Tennessee Rare Plant Protection and Conservation Act of 1985, Tennessee Nongame and Endangered or Threatened Wildlife Species Conservation Act of 1974, several federal and state regulations regarding aquatic resource protection, and site-specific policies as outlined in various ORR management plans developed by ORNL and TWRA for DOE.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗
DOE OSTI2020

Natural Resources Assessment for the SNS Second Target Station, Oak Ridge, Tennessee

The US Department of Energy’s Oak Ridge National Laboratory (ORNL) is a leading institution in advanced materials, supercomputing, neutrons, and nuclear science. As a research laboratory managed by UT-Battelle, LLC for DOE, ORNL has national priorities in energy, security, and scientific discovery that necessitate facility improvements and expansions. DOE is also committed to environmental stewardship. The laboratory is located on the ~32,000-acre Oak Ridge Reservation (ORR), much of which is categorized as a National Environmental Research Park and a state Wildlife Management Area. DOE works with the Tennessee Wildlife Resources Agency (TWRA), Tennessee Department of Environment and Conservation (TDEC), US Fish and Wildlife Service (USFWS), US Department of Agriculture, and other agencies to serve as an effective steward of the ORR. Accordingly, project managers must conform to environmental regulations, agreements, and policies at the federal, state, and institutional levels. Per 40 CFR (Code of Federal Regulations) 1508.14, potential effects on research and science education on the National Environmental Research Park represent potential impacts of federal actions. Moreover, federal actions that affect the quantity and quality of hunting opportunities and deer reduction harvest on the Oak Ridge Wildlife Management Area must be considered whenever other aspects of the human environment (as defined by NEPA) are affected. The Spallation Neutron Source (SNS) is a premiere facility at ORNL that provides advanced capabilities in neutron scattering to promote new discoveries and research opportunities in material sciences, physics, chemistry, biological sciences, and others. A conceptual design for a Second Target Station (STS) has been in consideration for several years. The STS is intended to complement and enhance existing ORNL capabilities, notably research and exploration of complex materials. The proposed STS will involve development of existing natural areas on the ORR, which might contain sensitive resources that require mitigation or avoidance in accordance with existing policies and regulation. This report summarizes current knowledge of natural and cultural resources within the STS project area. At the time of this report, the proposed STS project consisted of an operations area comprising 55.4 acres (22.4 ha) and a total review area for potential construction comprising ~224 acres (90.6 ha). The review area is located primarily within forested natural areas of the ORR with minor development in the form of power-line rights-of-way and secondary/graveled roads (Figure 1). The primary goal was to evaluate potential effects on sensitive resources that might result from development of the STS. In addition to onthe-ground surveys during summer 2009 and fall 2019 to summer 2020 by ORNL Natural Resources Management Program and Aquatic Ecology Group staff, this report makes use of historical (pre-1995) and contemporary (1995 to present) data from additional confirmed sources (e.g., TDEC). Likewise, forest conditions were compiled primarily from a 2013 forest inventory effort for Forest Management Compartment 17 and supplemented with limited ground observations in 2019. The individuals who obtained and compiled the data that are presented here are familiar with and routinely assess sensitive resources on the ORR.

54 ENVIRONMENTAL SCIENCES↗