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DOE OSTI2020

Removing the Cloak of Secrecy from Legacy Cleanup at Los Alamos national Laboratory - 20395

With the establishment in 2018 of the Los Alamos Legacy Cleanup Contract, the Department of Energy's (DOE) Environmental Management Los Alamos Field Office (EM-LA) and its contractor Newport News Nuclear BWXT Los Alamos (N3B) embarked on an expansive program to engage a broad range of local and regional stakeholders in the decision-making process for cleanup of legacy wastes (pre-1999) at the Los Alamos National Laboratory (LANL). From the inception of LANL during the Manhattan Project until the issuance of the new cleanup contract, the site was managed by a single management and operations (M and O) contactor whose main focus was national security. Segmenting from laboratory operations a separate cleanup contract managed by DoE's Office of Environmental Management (EM) brought new opportunities for the cleanup of legacy waste. That change likewise has opened new opportunities for engaging the community on legacy cleanup decisions. The new legacy cleanup contract - an unclassified contract - emphasizes public outreach, marking a cultural shift in how stakeholders in Los Alamos and throughout northern New Mexico are engaged. Without the constraints of classified work, EM-LA and N3B have increased the level of transparency with the public regarding cleanup activities. EM-LA and N3B have crafted an approach that best meets the values, priorities and needs of the neighboring communities by adapting the model successfully employed at Rocky Flats. Through enhanced stakeholder involvement, EM-LA will implement decisions that have considered broad input and deliver a safe and efficient cleanup of the site. EM-LA and N3B began the expanded stakeholder outreach program in January 2019, leading up to four Environmental Management Cleanup Forums held in the summer of 2019. EM-LA and N3B are now in the process of initiating a series of meetings with various stakeholder groups to determine their 'values' as they relate to cleanup using a novel approach that elicits and records values. The entire process is documented, ensuring that should questions arise about how, when and why decisions were made, they can be easily addressed. In addition to other public meetings to present cleanup scenarios and solicit active public involvement in cleanup decisions, the EM-LA and N3B approach involves discussions with stakeholders who want to explore specific technical issues and cleanup discussions in depth. EM-LA and N3B are also evaluating and implementing a variety of communications tools to help ensure the engagement plan sets the gold standard for transparency in legacy cleanup and stakeholder involvement. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

IM3 Projected US Data Center Locations

IM3 Projected US Data Center Locations This dataset contains model projections of new data center facilities in the contiguous United States (CONUS) through 2035 using the CERF – Data Centers model. Data center locations are modeled across four data center electricity demand growth scenarios (low, moderate, high, higher) and five market gravity scenarios (0%, 25%, 50%, 75%, 100%). Projected locations are intended to be regional representations of feasible siting locations in the future to assess potential grid and water stress impacts. The data center load growth scenarios correspond with the rates outlined in EPRI (2024) and include 3.71%, 5%, 10%, and 15% annual growth of electricity demand for data centers from 2023 values in 37 states across the CONUS. Market gravity scenarios correspond to the relative importance of proximity to data center markets or high population areas compared to locational cost in the siting algorithm. 0% market gravity means that siting decisions were entirely determined by the locational cost in each feasible location. 100% market gravity means that only market proximity was considered when siting. Other scenarios have weight placed on both components where total weight always equals 100%. Locational cost is dependent on facility cooling type and corresponding electricity cost, taxes, and other factors. Facility cooling type is spatially determined where high water stress and/or areas with high summer wet bulb temperatures are assumed to operate with mechanical cooling for a higher fraction of the year rather than evaporative cooling. Feasible data center siting areas are based on geospatial suitability raster data developed with open-source information. The following areas are excluded from siting: Areas within 300 m of a federal airport runway Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory Protected Areas Database of the United States (PAD-US) areas Railroads, major roadways, and minor roadways Military areas and training grounds NLCD developed lands Areas >0.8 km (0.5 miles) from NLCD developed lands Because we use open-source information, proprietary information that can influence siting decisions such as individual tax agreements with cities, detailed fiber line connectivity, electric grid power capacity agreements, and others, are not currently accounted for in the modeling process. Using specific building locations and footprints in the dataset for local planning purposes is not advised. Technical Information Geospatial data is provided in geojson format using the Albers Equal Area Conic (ESRI:102003) coordinate reference system. The datasets contain the following parameters: id - unique identification number within given scenario file growth_scenario – data center demand growth scenario market_gravity_weight – market gravity weight scenario (%) region – name of region (i.e., US State) total_cost_million_usd – locational siting cost ($million) campus_size_square_ft – total land acquired for data center facility (square ft) data_center_it_power_mw – IT power of data center facility (MW) mechanical_cooling_frac – fraction of year when data center uses mechanical cooling system water_cooling_frac– fraction of year when data center uses evaporative cooling system cooling_energy_demand_mwh – total annual facility energy demand for cooling (MWh) cooling_water_demand_mgy – total annual facility water demand for cooling (MG) cooling_water_consumption_mgy – total annual facility water consumed (MG) normalized_locational_cost – normalized total locational cost score for location normalized_gravity_score – normalized market gravity score for location weighted_siting_score – total weighted siting score of locational cost and gravity score geometry – polygon geometry of facility Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4.0 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall (ORCID:0000000328077088)↗

DOE OSTI2026

IM3 Projected US Data Center Locations

IM3 Projected US Data Center Locations This dataset contains model projections of new data center facilities in the contiguous United States (CONUS) through 2035 using the CERF – Data Centers model. Data center locations are modeled across four data center electricity demand growth scenarios (low, moderate, high, higher) and five market gravity scenarios (0%, 25%, 50%, 75%, 100%). Projected locations are intended to be regional representations of feasible siting locations in the future to assess potential grid and water stress impacts. The data center load growth scenarios correspond with the rates outlined in EPRI (2024) and include 3.71%, 5%, 10%, and 15% annual growth of electricity demand for data centers from 2023 values in 37 states across the CONUS. Market gravity scenarios correspond to the relative importance of proximity to data center markets or high population areas compared to locational cost in the siting algorithm. 0% market gravity means that siting decisions were entirely determined by the locational cost in each feasible location. 100% market gravity means that only market proximity was considered when siting. Other scenarios have weight placed on both components where total weight always equals 100%. Locational cost is dependent on facility cooling type and corresponding electricity cost, taxes, and other factors. Facility cooling type is spatially determined where high water stress and/or areas with high summer wet bulb temperatures are assumed to operate with mechanical cooling for a higher fraction of the year rather than evaporative cooling. Feasible data center siting areas are based on geospatial suitability raster data developed with open-source information. The following areas are excluded from siting: Areas within 300 m of a federal airport runway or within an airport area boundary Waterbodies Areas with slope >16% Areas susceptible to sinkholes High coastal or inland flood risk areas Local, state, and federal parks, leisure areas, and cemeteries Areas >2 km away from electric substations Areas >5 km away from a municipal water supplier service area Areas >2 km away from high-speed fiber provider service territory USGS Protected Areas Database of the United States (PAD-US) GAP status 1, 2, or 3 areas US National Parks Wetlands USFWS critical habitats BIA land areas Railroads, major roadways, and minor roadways Military areas and training grounds NLCD developed lands Areas >0.8 km (0.5 miles) from NLCD developed lands Because we use open-source information, proprietary information that can influence siting decisions such as individual tax agreements with cities, detailed fiber line connectivity, electric grid power capacity agreements, and others, are not currently accounted for in the modeling process. Using specific building locations and footprints in the dataset for local planning purposes is not advised. Technical Information Geospatial data is provided in geojson format using the Albers Equal Area Conic (ESRI:102003) coordinate reference system. The datasets contain the following parameters: id - unique identification number within given scenario file growth_scenario – data center demand growth scenario market_gravity_weight – market gravity weight scenario (%) region – name of region (i.e., US State) total_cost_million_usd – locational siting cost ($million) campus_size_square_ft – total land acquired for data center facility (square ft) data_center_it_power_mw – IT power of data center facility (MW) mechanical_cooling_frac – fraction of year when data center uses mechanical cooling system water_cooling_frac– fraction of year when data center uses evaporative cooling system cooling_energy_demand_mwh – total annual facility energy demand for cooling (MWh) cooling_water_demand_mgy – total annual facility water demand for cooling (MG) cooling_water_consumption_mgy – total annual facility water consumed (MG) normalized_locational_cost – normalized total locational cost score for location normalized_gravity_score – normalized market gravity score for location weighted_siting_score – total weighted siting score of locational cost and gravity score geometry – polygon geometry of facility Acknowledgment IM3 is a multi-institutional effort led by Pacific Northwest National Laboratory and supported by the U.S. Department of Energy's Office of Science as part of research in MultiSector Dynamics, Earth and Environmental Systems Modeling Program. License This data is made available under a CCBY4.0 License Disclaimer This material was prepared as an account of work sponsored by an agency of the United States Government. Neither the United States Government nor the United States Department of Energy, nor the Contractor, nor any or their employees, nor any jurisdiction or organization that has cooperated in the development of these materials, makes any warranty, express or implied, or assumes any legal liability or responsibility for the accuracy, completeness, or usefulness or any information, apparatus, product, software, or process disclosed, or represents that its use would not infringe privately owned rights. Reference herein to any specific commercial product, process, or service by trade name, trademark, manufacturer, or otherwise does not necessarily constitute or imply its endorsement, recommendation, or favoring by the United States Government or any agency thereof, or Battelle Memorial Institute. The views and opinions of authors expressed herein do not necessarily state or reflect those of the United States Government or any agency thereof. PACIFIC NORTHWEST NATIONAL LABORATORYoperated byBATTELLEfor theUNITED STATES DEPARTMENT OF ENERGYunder Contract DE-AC05-76RL01830

Mongird, Kendall (ORCID:0000000328077088)↗

DOE OSTI2023

SolarAPP+ Performance Review (2022 Data)

The Solar Automated Permit Processing Plus (SolarAPP+) platform is an online portal to facilitate and expedite rooftop solar photovoltaic (PV) permitting processes. SolarAPP+ allows PV contractors to upload system specifications, have those specifications automatically reviewed for code compliance, and receive instant approval for code-compliant systems. SolarAPP+ also provides inspection checklists to verify installation practices and adherence to approved designs. SolarAPP+ is available to authorities having jurisdiction (AHJs) at no cost. This report is part of an ongoing series of reviews of SolarAPP+ performance. Consistent with previous performance reviews, we summarize SolarAPP+ adoption trends to date and compare various metrics for PV systems permitted through SolarAPP+ versus systems permitted through conventional AHJ permitting processes. As of the end of 2022, the National Renewable Energy Laboratory (NREL) had contacted over 1,500 AHJs with significant solar permitting volume regarding SolarAPP+. Of those, 607 AHJs had at least expressed interest in the platform. 16 AHJs had begun piloting the platform and 15 of these had publicly launched the platform by the end of 2022. In 2022, 206 installers submitted 11,092 permits through the SolarAPP+ platform, including 708 permits for solar+storage systems. SolarAPP+ permits accounted for around 37% of all permits issued in participating AHJs. We compare permitting timelines through SolarAPP+ to traditional AHJ permitting processes to assess the platform's performance. Consistent with previous SolarAPP+ performance reviews, we find that permitting timelines are significantly shorter for SolarAPP+ projects. Based on median timelines, a typical SolarAPP+ project is permitted and inspected 8 business days sooner than traditional projects. We estimate that automatic SolarAPP+ permitting saved between 3,500 and 13,900 hours of AHJ staff time in 2022. Finally, we find evidence that SolarAPP+ may improve inspection outcomes, with SolarAPP+ projects failing inspections about 28% less frequently than traditional projects.

14 SOLAR ENERGY↗

DOE OSTI2020

Implications of End Points on Remediation - 20476

The Port Hope Area Initiative (PHAI) is a federal environmental clean-up program. Its mandate is the remediation and local, long-term, safe management of approximately 1.7 million cubic metres of historic low-level radioactive waste in the adjacent communities of Port Hope and Port Granby in Southern Ontario, Canada. The PHAI is being undertaken by Canadian Nuclear Laboratories (CNL), on behalf of Atomic Energy of Canada Limited, a federal Crown corporation. It is currently one of the largest environmental remediation projects in Canada. The safety of workers, the public and the environment while delivering the PHAI compliantly, on time and within budget is CNL's number one priority. The PHAI is being implemented as two projects - the Port Hope Project and the Port Granby Project. The Port Hope Project is the larger of the two and includes the cleanup of approximately 1.2 million cubic metres of historic waste. The Port Hope Project includes a unique and important component - the remediation of approximately 1,200 private residences and businesses to include both interior and exterior verification of soil and surface-contaminated objects. Planning and consultation for the PHAI clean-up criteria and remediation verification standard operating procedures (RVSOP) were initiated in the early 2000's. The criteria were developed through a cooperative effort involving the PHAI, scientific specialists, federal and provincial government agencies, peer reviewers, the municipalities and members of the public. Subsequent verification procedures which detail the unique systematic methods to verify compliance with the clean-up criteria were developed by CNL in consultation with federal regulators and relevant stakeholders. Now, specifically with the Port Hope Small-Scale Sites project having been underway for a year and approximately 38 properties in some stage of remediation, it has become increasingly evident that the practical application of the clean-up criteria and RVSOP methodology is posing unique challenges that are having direct impact on project execution. The current RVSOP approach is based on discrete sample verification not allowing failure of any one sample. When implemented in the field, particularly at the Small-Scale Sites, it leads to a much more extensive excavation than what was accounted for in the original design, the implications of which are substantial delays in project progress and much more significant impact on the individual properties than originally anticipated. This paper will examine the evolution of PHAI clean-up criteria, subsequent RVSOP methodology and its impact on current project execution and the justification for exploring potential revisions to methods of remediation verification. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Middlesex South FUSRAP Site: Collaboration Towards Beneficial Reuse - 20338

The US Department of Energy (DOE) Office of Legacy Management (LM) manages DoE's post-closure responsibilities and ensures the future protection of human health and the environment with respect to sites that have no continuing DOE mission after undergoing remediation. LM's beneficial reuse program promotes the LM strategic goal to sustainably manage and optimize use of public lands. The beneficial reuse program aims to repurpose former contaminated sites to restore the environment, protect the public health, revitalize communities, and spur economic growth. Benefits from the reuse of a site may increase the local tax base, facilitate job growth, utilize existing infrastructure, and enhance or protect natural resources. Beneficial reuse also promotes protectiveness by ensuring activities are compatible with long-term maintenance and protection of public health and the environment, as well as by retaining good stewardship of natural resources. LM actively participates in promoting the economic development vision of the surrounding communities by collaborating with local communities to promote regional or municipal initiatives. The Borough of Middlesex, New Jersey, has prepared the Lincoln Boulevard Redevelopment Plan, which will reinvent a once-viable downtown and enhance the quality of life for the community. The Middlesex South, New Jersey, Formerly Utilized Sites Remedial Action Program (FUSRAP) site lies within the boundaries of this redevelopment area. In support of this development plan, the Borough is interested in acquiring the site for its Department of Public Works and to increase street access in the future commercial district to be built near adjacent properties. The opportunity to put the FUSRAP site into productive use aligns with LM's mission and strategic goals. In support of beneficial reuse activities, DOE can dispose of excess real property using several mechanisms. The two disposal options applicable to the Middlesex south site include (1) utilizing the US General Services Administration (GSA) or (2) using the Title 10 Code of Federal Regulations Section 770, 'Transfer of Real Property at Defense Nuclear Facilities for Economic Development' (known as a '770 transfer') process. Using the 770 transfer requires economic development as the primary driver, and a specific redevelopment proposal must be submitted. If there is no interest in specific economic development, the GSA option becomes the default mechanism for disposal of the property. In the case of the Middlesex south site, the 770 transfer process is being utilized and the Borough has submitted its economic development proposal to LM. Although LM is encouraged by the opportunity to put the site into productive use, the Middlesex south site is currently on the US Environmental Protection Agency (EPA) National Priorities List and remediation is being performed by the US Army Corp of Engineers (USACE) under the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA). Consequently, any property transfer must meet the requirements under CERCLA Section 120(h), 'Property Transferred by Federal Agencies.' As the groundwater remedy will not be in place for several years, approval would be required from the US EPA administrator and the governor of the state of New Jersey to perform an early transfer of the site (before all response actions have been completed). The time frame for these approvals to occur under the normal process conflicts with the proposed redevelopment schedule; therefore, various options for expedited sale, transfer, or lease of portions of the site to the Borough were evaluated. The subsequent decision on a mutually beneficial path forward was the result of a collaborative effort between LM, USACE, the Borough and its redevelopment team, EPA, and the New Jersey Department of Environmental Protection. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Consequence Analysis of Residual Water in a Storage Canister - 20484

Recent observations from projects sponsored under the DOE-Nuclear Energy Spent Fuel and Waste Disposition campaign show that residual free water, well above the 0.4 gm-moles that correspond to a 3 torr rebound pressure after a 30-minute hold following prototypic drying, may remain within SNF canisters used for long-term dry storage. Specifically, experimental observations in an Integrated Research Project showed subzero temperatures and a local pocket of frozen water in a mockup fuel assembly subjected to an industry practiced drying process. In gas sampling and analysis from the High Burnup (HBU) Demonstration project, using a fully loaded and dried SNF canister, indicated presence of 100 g of residual water had remained in the canister. The effects of residual water in terms of potential adverse impacts on the condition of the SNF and the canister internals during long-term dry storage has been rigorously evaluated to address inadvertent residual water contents. The impact of residual water on the fuel and canister internals, with a focus on the oxidation of the cladding and of postulated exposed (breached-clad) fuel, were evaluated using an integrated set of time-dependent environmental conditions with semi-empirical materials oxidation models. An 'integration model,' with coupled sub-models, developed and previously used by the Center for Nuclear Waste Regulatory Analysis (CNWRA), was applied and expanded with improved sub-models for water radiolysis, and for cladding and fuel oxidations. Cladding oxidation models for various alloys were developed using the rate constants for various cladding alloys in the dry storage temperature range. A burnup-dependent fuel oxidation model was developed; it accounted for inhibition effect of fission products on fuel oxidation rates. The potential for extension of the initial breach flaw (1 mm hole) was evaluated by two separate mechanics criteria. In the first case, a critical cladding strain criterion was used. In the second case, a critical stress intensity was used to evaluate stability of a planar axial flaw postulate. A failure condition exists when a sufficient amount of fuel oxidation (at the postulated breached-clad location) causes fuel pellet swelling to load the cladding to meet a mechanics criterion for flaw extension. The integration model's results provide the following insights. The radiolysis-generated oxygen is consumed with a partitioning between the cladding and the fuel. The extent of cladding oxidation is no more than 2 μm additional consumption of the cladding metal even with 10 moles of residual water, indicating that changes in cladding conditions due to water are expected to be negligible. The conditions for cladding failure (breach opening size extension) directly correlates with the extent of fuel oxidation. Fuel oxidation significant to extend the breach could occur even with 5.5 moles of residual water. The results indicate that fuel oxidation vis-a-vis cladding oxidation is more likely under a higher radiation field, i.e., when radiolytic decomposition of the residual water occurs in few years compared to several decades, and that the conditions to cause failure are increased with fuel and cladding temperatures approaching the peak storage temperature limit of 400 deg. C. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Analysis of fast-ion losses measured in MAST-U via infrared thermography and a Fast Ion Loss Detector

Fast-ion losses need to be monitored to avoid damage to plasma facing components. In existing experimental devices, the scintillator-based fast-ion loss detector (FILD) is the most advanced diagnostic for measuring fast-ion losses. However, FILDs provide only local information about the losses. Infrared (IR) thermography can be used as a complementary tool for more global monitoring of the deposition of fast-ion losses on the wall, at the expense of no velocity-space resolution. IR cameras measure the temperature of the plasma facing components. This measurement, determined by a combined effect of the thermal plasma, radiation, neutrons and fast-ion losses, can be decomposed to infer the fast-ion load on the tokamak wall. In this manuscript, a workflow to estimate fast-ion losses via IR thermography is applied to the MAST-U spherical tokamak, using a 1D approximation to extract the experimental heat flux on the FILD front face from IR data. To numerically estimate the different contributions to this total heat flux, the field-line tracing environment SMITER is used to calculate the thermal plasma contribution, the orbit-following Monte-Carlo code ASCOT to estimate the fast-ion losses, and bolometry measurements for the radiation. To validate the workflow, two discharges, L-mode plasmas with low MHD activity, were executed using on and off-axis beams, respectively. The experimentally and numerically estimated heat flux are of the same order of magnitude for the on-axis heated scenario, with a strong dependence of the estimated fast-ion losses contribution on the fit to the kinetic profiles used as input. This is also true for the off-axis heated scenario, where the total numerically estimated heat flux is 2.1 or 1.3 times higher than the maximum experimentally estimated heat flux, depending on the ASCOT input used.

FILD↗

DOE OSTI2020

Contaminant Transport Modeling for Technology Evaluation and Long-Term Monitoring in the Tims Branch Testbed, SC - 20343

Studies conducted at U.S. DOE sites have shown the presence of heavy metals, radionuclides, and volatile organic compounds in surface water, groundwater, and soil as a result of nuclear activity in the Cold War era. Since the 1990's, innovative cleanup methods have been implemented in the Tims Branch watershed at Savannah River Site (SRS) to limit the contaminant flux to the stream that have reduced the contaminant concentrations to acceptable regulatory levels in the dissolved phase. A tin-based treatment which effectively eliminated all local anthropogenic mercury inputs to this ecosystem resulted in a known step function addition of inert tin oxide particles which now serve as a potential tracer for sedimentation and particle transport processes in the stream. The long-term effectiveness of this and other remediation techniques and the potential for remobilization of adsorbed contaminant in sediment during extreme hydrologic conditions however remains unclear. It is therefore important to understand not only the fate and transport of dissolved contaminants, but also the movement of sediment and the relevant interactions with dissolved contaminant. To narrow this knowledge gap, a study is being conducted using the Tims Branch watershed as a stream-scale ecosystem test-bed to identify the primary transport processes of major contaminants of concern (such as mercury, nickel and uranium) with an emphasis on interactions with sediment transport. This involves the development of a fully distributed hydrologic watershed model of the Tims Branch watershed to predict streamflow under extreme weather conditions, as well as the development of a comprehensive contaminant transport model that can properly account for coupled contaminant and sediment transport. Review of relevant research reports and peer-reviewed journals revealed that aside from advection-dispersion transport of dissolved contaminants, adsorption and desorption with suspended solids and bed sediment also play an important role in the transport of those contaminants of concern. To develop the fully distributed hydrologic watershed model, the MIKE SHE 2-dimensional (2D) land surface/3D groundwater model that simulates surface/subsurface hydrologic processes (such as overland flow, evapotranspiration, and infiltration) was coupled with a 1D streamflow model that accounts for stream water hydraulics (such as hydraulic structures, cross-sections, and network). To model contaminant transport, the MIKE 11 streamflow component was coupled with the MIKE 11 AD module that simulates solute transport through advection and dispersion, and MIKE ECO Lab module that accounts for both sediment transport and interactions with dissolved contaminant. At this stage, the development and optimization of the fully distributed hydrologic model has been completed, achieving satisfactory statistical results between observed and predicted discharge as indicated by a root mean square error (RMSE) of 0.039 cms and a Nash-Sutcliffe efficiency coefficient (NSE) of 0.764. The ongoing development of the contaminant transport model has also yielded realistic results from preliminary tests. Results from this study are a key to evaluating the effectiveness of tin (II)-based mercury treatment of wetlands at the SRS site, and are also relevant to evaluating the potential of using this type of novel remediation technology in other mercury-contaminated stream systems. Knowledge acquired from this research will also support interpretation of historical data on the trends of contaminant concentration distribution in Tims Branch, particularly considering the effect of extreme hydrological events on the stream flow and pollutant transport. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2020

Analysis of Exposure during Transportation of Waste to the Nevada National Security Site (NNSS) - 20445

Safety is a priority for the U.S. Department of Energy (DOE) Environmental Management (EM) Nevada Program. This commitment to safety is integrated into requirements and work procedures at DOE sites across the U.S. that generate low-level radioactive waste, mixed low-level radioactive waste, and classified waste that is transported to the Nevada National Security Site (NNSS) for permanent disposal. Generators of this waste are responsible for ensuring it is packaged and transported in a safe and compliant manner. These generators and their contracted commercial carriers must comply with U.S. Department of Transportation (DOT) regulations; the Nevada National Security Site Waste Acceptance Criteria (NNSSWAC); and other applicable federal, state, and local regulations and requirements. This includes packaging and shipping the waste to meet DOT regulatory radiation dose limits to ensure public safety during transportation. NNSS waste generators have a solid safety record for complying with these stringent regulations as demonstrated by the fact that no shipments exceeding DOT dose rate limits were received at the NNSS Area 5 Radioactive Waste Management Complex (RWMC) during FY 2014 through FY 2018. A 2005 study conducted by the Desert Research Institute validated shipments to the NNSS comply with DOT radiation dose limits. In response to recent Nevada stakeholder requests for an updated study, an analysis was conducted to verify and provide evidence that the public continues to be safe from exposure to radioactive waste shipment to the NNSS. Radiation exposure from radioactive waste shipments in transit to the NNSS was evaluated. Three studies were performed: 1. Confirm compliance of waste shipments to the DOT radiation limits using dose rate surveys taken at the generator site and at the disposal site. 2. Estimate the dose to the public from waste shipments using the dosimetry results for disposal site personnel by comparing time of exposure for various individuals/scenarios. 3. Estimate the truck driver dose using the receipt dose rate surveys and time of exposure, and from dosimetry results. Study 1 confirmed compliance with the DOT dose rate limits for a sample of waste shipments (123 of 1,038) received during fiscal year (FY) 2017. Study 2 showed that the average annual radiation equivalent dose for disposal site personnel during FY 2017 was approximately 6.7% [0.415 mSv (41.5 millirem)] of the annual average dose that a person living in the U.S. receives from all sources [6.2 mSv (620 mrem)]. Maximum dose to a member of the public, a person resting/sleeping in an adjacent truck at a rest area to a waste shipment, was 0.0166 mSv (1.66 mrem), which is less than the dose received from a person taking a round trip from the east coast to the west coast of the continental U.S. on an airplane [0.07 mSv (7 mrem) per round trip]. Study 3 showed that the truck driver who made the most shipments of radioactive waste to the NNSS, who drove the most hours (estimated time of exposure 2,520 hours), during FY 2017 had a total dose of 0.15 mSv (15 mrem), which was obtained from their personal dosimeter. The annual dose recorded for disposal site personnel, the dose estimates for the public, and the truck driver dose were all a small percentage of the average radiation dose a person receives from all sources (e.g., background and medical radiation). At these levels, risk should only be described qualitatively. Radiation exposure from radioactive waste shipments to the NNSS were shown to be compliant with the DOT dose rate limits, safe, and very low (i.e., within background levels). (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Low- n stability and plasma response to RMP in various STEP scenarios

The low-n (n is the toroidal mode number) magnetohydrodynamic (MHD) stability and plasma response are numerically investigated for various scenarios designed for STEP, that are relevant for the H-mode pedestal analysis. Control of the edge-localized modes (ELMs) with externally applied resonant magnetic perturbations (RMPs) is considered. Optimization of the ELM control coil current configuration, based on the computed plasma MHD response and well-established figures of merit validated on present-day experiments, finds reasonable robustness of a fixed coil phasing (for a given n-number) to control ELMs in all five STEP plasmas considered. Based on certain semi-empirical criteria, the required coil current to achieve ELM suppression is estimated to be about 10–20 kAt with the n = 1 or 2 RMP configuration and about 100–200 kAt for the n = 4 RMP. Systematic linear stability calculations are used to map out stability windows for the low-n kink-peeling modes, in terms of the ideal-wall location and variation of the edge safety factor q 95 with respect to the target design. The kink-peeling stability boundary is found to be generally sensitive to the q 95 variation, which has implications for achieving the quiescent H-mode regime in STEP. Full toroidal quasilinear initial-value simulations for these STEP plasmas find that generation of the edge-harmonic oscillations (EHOs) depends sensitively on the plasma scenario, the initial linear stability of the kink-peeling modes, the initial plasma toroidal flow and q 95 . In general, it is easier (more robust) to access the EHO-regime for two of the cases considered with smaller plasma volume and higher on-axis safety factor. Finally, quasilinear simulations find robust density pumpout due to applied RMPs in these STEP plasmas, but the effect on the plasma toroidal flow varies among different cases.

EHO↗

DOE OSTI2025

Continuous snow depth and temperature measurements from dense network of above-ground distributed temperature profiling systems from 2021-09-23 to 2024-08-23, Seward Peninsula, Alaska

The dataset contains temperature measurements from distributed temperature profiling (DTP) systems (Dafflon et al., 2022; Wielandt et al., 2022; Wang et al., 2024a; Fiolleau et al., 2024) deployed vertically above the ground surface at a large number of locations from 2021 to 2024. The research is designed to improve understanding of the local heterogeneity in snow depth and snow thermal insulation dynamics, as well as their interactions in a discontinuous permafrost region (Wang et al., 2025). The DTP systems were deployed at 96 locations in a watershed along the Nome-Teller road at mile marker 27 (T27) and at 54 locations on a hillslope along the Kougarok road at mile marker 64 (K64) in the Seward Peninsula, Alaska. The probe location information is stored in Probe_locations_T27.csv and Probe_locations_K64.csv. Temperature measurements were recorded at 15-minute intervals using high-precision digital sensors (accuracy: ±0.1°C, resolution: 0.0078°C). The temperature probes, either 1.4 m or 1.6 m long, contain sensors spaced every 5 cm or 10 cm along their length. The temperature data are stored in compressed files following the format: DTP_snow_air_temperature_(site)_(start)_(end).zip, where site is either T27 or K64, and start and end represent the time series period. Within each ZIP file, individual CSV files are named by probe ID and contain temperature records at different heights above the ground surface.This dataset also includes derived snow depth time series over three snow seasons, estimated from temperature measurements. Snow depth was estimated by identifying the consecutive sensor pair that exhibited the largest drop in high-frequency temperature fluctuations (detailed in the methods). These data are stored in: Snow_depths_flags_(site)_(start)_(end).csv, which includes snow depth time series and corresponding quality flags (defined in the methods) from different probes. Additionally, the dataset includes derived metrics and supporting measurements at selected locations over two snow seasons, contributing to the manuscript of Wang et al., 2025. These locations were chosen based on the availability of high-quality snow depth time series during both seasons. The additional data include: (1) Air temperature proxies measured from the top sensors on the pole when they were not buried by snow, stored in Air_temperature_proxies_(site)_(start)_(end).csv (2) Ground interface temperature, recorded at 3 cm above the ground, stored in Ground_interface_temperature_(site)_(start)_(end).csv (3) Site characteristics, including vegetation height, elevation, and the topographic position index (TPI) within a 50 m radius, stored in Selected_probe_locations_gps_vegheight_tpi_elevation_(site).csv. These metrics were derived from 1 m resolution summer LiDAR-based digital elevation models and digital surface models from Singhania et al., 2023, DOI:10.5440/1832016. Metadata files include data descriptions (_dd.csv) for tabular data. All included files are listed and described in xxxx_flmd.csv.This dataset is an updated version of a previous archive (Wang et al., 2024b, DOI: 10.15485/2475020), incorporating multiple seasons and improved snow depth estimation. Please note that due to large amount of information present in this dataset, many specificities associated with the acquisition of snow temperature, air temperature proxy and estimation of snow depth, and the future archiving of additional datasets on the soil temperature, thaw depth and soil characteristics at these locations, the author would welcome being contacted by people planning to use this dataset.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research.The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska.Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

Overview of the MAST Upgrade physics programme: testing novel concepts at low aspect ratio to inform future devices

The research programme performed on the Mega Amp Spherical Tokamak (MAST) Upgrade experiment has made significant advances in developing the physics understanding of low aspect ratio tokamaks in support of the operation of ITER and design of fusion powerplants. High performance plasma scenarios have been developed to facilitate a broad programme of experiments, in which confinement is constrained by the presence of m/n = 2/1 modes that cause substantial losses of fast ions. The onset of these modes coincides with the q = 2 surface residing in a local minimum in the toroidal current density profile. The maximum electron temperature at the pedestal top, T e,ped is limited with gas fuelling to ∼350 eV to maintain regular ELMs; higher T e,ped results in a transition to a non-stationary ELM-free regime. The operational space of spherical tokamaks has been expanded into small and ELM-free regimes. Strong shaping of the last closed flux surface can induce a transition from large to small ELMs, and ELM suppression with resonant magnetic perturbations has been observed for the first time in a low aspect ratio tokamak. Negative triangularity shaping has induced a transition from ELMy H-mode to a high-performance L-mode regime for the first time in a low aspect ratio tokamak. In studies of fast ion confinement, losses of fast particles due to Global Alfvén Eigenmodes have been identified. Interactions between fast ions generated by off-axis neutral beam injection and thermal neutrals can result in significant losses of fast ions. Experiments with on- and off-axis neutral beam injection exhibit a flux pumping mechanism, where the central safety factor is held to ∼1 in the absence of sawteeth. In studies of pedestal physics, it has been found that elevated main chamber neutral pressures result in an increase in the electron density and reduction in the temperature at the pedestal top. Advances in understanding plasma exhaust include the integration of a high-performance plasma core with detached outer divertors in the X-point target configuration. A newly commissioned lower divertor cryopump reduces the lower divertor neutral pressure by up to 50%, with minimal effect on the main chamber or upper divertor. New measurements and SOLPS-ITER simulations emphasise the importance of plasma–neutral interactions on divertor detachment in the conditions accessible in experiments. Real-time control of the ionisation front location in both divertor chambers independently has been demonstrated in double null experiments, enabled by the tightly baffled divertor chambers.

MAST Upgrade↗

DOE OSTI2020

Potential Advantages to Employing an Onsite Laboratory at FUSRAP Sites Contaminated with Radionuclides and Metals - 20353

Various factors that support an evaluation of the relative costs, advantages and disadvantages of utilizing an onsite laboratory or an offsite laboratory for remediation of Formerly Utilized Sites Remedial Action Program (FUSRAP) sites contaminated with radionuclides and metals are presented. In terms of how much more quickly an onsite laboratory provides results versus an offsite laboratory, the results of this study provide tools for calculating the amount of cost savings per day for excavation of contaminated soils for various scenarios including: - State, municipal or local property remediation where the remediation schedule becomes time-critical due to the extra cost and inconvenience to the town or municipality caused by the need for increased security and safety personnel, possible road closures and detours, and the inconvenience to the public due to modified or decreased services of State or municipal facilities; - Residential property where the remediation schedule becomes time-critical due to the inconvenience to the homeowner as well as the importance of maintaining good community relations; - Commercial property where the remediation schedule becomes time-critical due to the hardship and potential loss of revenue endured by the property owner; - Open area where treatment of excavation water is required, and - Open area where treatment of excavation water is not required. For every scenario, the number of matrices, radionuclide and metal contaminants of concern and the project duration are important factors. The costs for the onsite laboratory included the capital costs associated with setting up the lab such as trailer(s) or building(s), power and water hookup, analytical testing equipment, balances, computers, desks and bookcases; support equipment such as hot plates, filtration assemblies, safety equipment, ovens, etc.; and supplies such as glassware, pipettes, filters, etc. and ongoing costs such as labor, chemicals and reagents, standards, cost of the laboratory obtaining certification and maintenance. Offsite laboratory sample testing costs are generally very competitive and typically substantially lower than onsite laboratory costs if only the sample testing costs are considered. The great disadvantage of using an offsite laboratory is that they often cannot guarantee rapid turnaround times for results which creates project delays associated with the remediation process including delays determining the completeness of the characterization and remediation processes, delays in backfilling a property and additional costs for treating wastewater (excavation water, stormwater or both). These costs will vary greatly depending upon the area of the country in which the project is located due to the wide range of labor costs for the onsite laboratory and field workers, as well as the contaminants of interest, matrices and most importantly the size of the impacted area and the number of properties located in that area. This paper provides guidelines for calculating the cost savings that may be realized if an onsite laboratory can generate results more quickly than an offsite laboratory by estimating the costs associated with the remediation process for the various scenarios noted above such as work crew labor costs, excavator and dump truck equipment rentals, wastewater treatment costs (if applicable) and the additional costs incurred by homeowners, commercial property owners and towns/municipalities that are reimbursed by the potentially responsible parties. Key assumptions involve the typical quickest turnaround time provided by the onsite and offsite laboratories. Costs for the operation of a wastewater treatment system and the remediation of a site area or property were provided by personnel who have been involved in the operation of a large FUSRAP site in New Jersey for many years. This study provides valuable information for determining the most cost-effective approach for analysis of project samples and therefore may be used on upcoming FUSRAP projects. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗

DOE OSTI2025

Impact of nitrogen molecular breakup on divertor conditions in JET L-mode plasmas using SOLPS-ITER

SOLPS-ITER simulations of nitrogen-seeded, low-confinement mode plasmas in the Joint European Torus (JET) predict that the electron temperature in the low-field side (LFS) divertor leg is reduced locally by up to an order of magnitude when nitrogen is assumed to recycle as molecules (N 2 ) instead of atoms using a fixed nitrogen injection rate. The LFS divertor temperature reduction under the assumption of molecular recycling occurs due to a three-step mechanism: (1) the plasma penetration of nitrogen atoms is increased due to the strong triple bond of the N 2 molecule and the kinetic energy release in the dissociation event, both mechanisms contributing equally, (2) the abundance of (particularly multiply-charged) nitrogen ions in the divertor is increased and (3) the electron temperature is reduced due to the increase in radiation (by up to a factor of 4) from nitrogen ions. Setting the volume-integrated nitrogen radiated power to a constant value (0.6 MW) instead of the nitrogen injection rate, SOLPS-ITER predicts under the molecular nitrogen recycling assumption that the peak line-integrated N II, N III and N IV intensities in the LFS divertor are approximately within 15%, 35% and 5%, respectively, of the reference atomic nitrogen recycling case. The predicted peak N II, N III and N IV intensities under either assumption are within 30%, 65% and 5%, respectively, of measurements using the vertically viewing mirror-link divertor spectrometer (Meigs et al., 2010) in nitrogen-seeded JET L-mode plasmas (Lomanowski et al., 2019). ERO2.0 simulations using a constant nitrogen seeding rate on static background plasma solutions from EDGE2D-EIRENE (previously presented in Mäenpää et al., (2022), revised here to include fast reflections) predict that N II to N IV line emission is increased by 20% to 30% when nitrogen is assumed to recycle as molecules, demonstrating the importance of considering the effect of molecular dissociation reactions on the divertor plasma in a self-consistent manner.

Divertor↗

DOE OSTI2024

A Mid-Century Net-Zero Scenario for the State of Wyoming and its Economic Impacts

Clean hydrogen has the potential to help achieve 10% economy-wide emissions reductions by 2050 relative to 2005, promote energy security and resilience, and develop a new economy in the United States. In 2030, the hydrogen economy could create about 100,000 new jobs to build new capital projects and clean hydrogen infrastructure. The Wyoming Energy Authority recently announced the state’s energy strategy, which establishes a goal of net-zero emissions by 2050. Under all likely scenarios, achieving a mid-century net-zero target will pose challenges and create opportunities for Wyoming’s energy sector. If executed properly, the transition could favorably affect the state’s economy overall in the long term. This research program examines the economic impact of fossil energy production in Wyoming and provides various predictions for future energy mixes to achieve net-zero emissions. Preliminary work suggests that Wyoming-based hydrogen production could have significant economic benefits and job creation implications for Wyoming. This study further assesses Wyoming’s opportunities to create hydrogen-based industries, assess economic impacts, identify knowledge gaps and research needs, and create a Hydrogen Center of Excellence to accelerate commercialization and deployment. This project helped to understand Wyoming's areas of focus for research and development and identified its areas of strength and potential challenges in creating a hydrogen ecosystem. As a result of this study, we estimate that for blue hydrogen produced from coal and gas resources, the overall cost reduction will be driven mainly by the carbon-sequestration tax credit and the improvement in carbon capture. Mature technologies, like SMR and PSA, will make limited contributions. They have no or limited reductions from an additional capacity deployment in future costs. We also understand the importance of continued support from public and private sectors for Carbon Capture and Storage (CCS)-related research, development, and demonstration programs at federal and state levels. The successful and efficient production of blue hydrogen requires a unique blend of energy resources, geology, regulation, law, and infrastructure. Wyoming has the distinction of meeting all these demands. The team also estimates that the availability and command of water resources accessible for hydrogen production are crucial for developing new projects. Water treatment, use, and disposal after treatment will also make projects possible. Primarily, this is relevant for hydrogen made using renewable energy. Wyoming has one of the best wind resource capacity in the nation. Harnessing this resource is challenging due to limited transmission line availability. Hydrogen could become one of the solutions to the stranded resource problem, primarily if the water availability challenge is addressed. Using produced oil & gas water could help to solve the problem. A commonly cited barrier to the expansion of hydrogen markets is the cost associated with constructing new pipelines, which typically require large amounts of capital to develop. Wyoming already possesses much of the export infrastructure needed to connect Wyoming’s hydrogen production with major markets across the West Coast, Pacific Northwest, Midwest, and Front Range regions of the United States, where a large portion of Wyoming’s natural gas is already transported. In addition to transportation by pipeline, rail transportation of hydrogen has also proven feasible. Wyoming uses its extensive railway system to transport large amounts of coal to its export partners across the United States. By using cryogenic or compressed-gas cars, Wyoming has the potential to add hydrogen to its existing network of railroad energy exports. The same technology may also be applied to hydrogen transport via trucks traveling interstate highways. Wyoming’s workforce is ready to meet the demands of clean hydrogen development. Many of the skills and training needed for hydrogen production are the same skills already possessed by Wyoming’s oil & gas and coal workforce. Many government and industry leaders expect clean hydrogen and other low-carbon energy projects to generate significant job growth and to recruit many already-trained oil & gas and coal workers whose jobs may be displaced. As energy companies seek to penetrate the markets for Wyoming hydrogen production, there is a natural mutual benefit to Wyoming’s workers and companies seeking to launch projects with the assistance of a trained workforce. Wyoming’s university and community college system have adopted several programs to ensure that highly qualified engineers and other technically skilled employees continue to graduate with skills to support the development of hydrogen and other innovative energy projects moving forward. Throughout the project, stakeholder outreach and education took many forms, including meetings with several major companies in the industry, collaborating with local government organizations, educational organizations, and national laboratories, tribal outreach and engagement, the sponsoring of several hydrogen-focused projects in many departments throughout the University of Wyoming, and developing a collaboration with international universities. The products of these collaborations consist of working relationships with several companies in the industry, educational institutions, national labs, and local government, as well as strong connections with individuals who will play an essential role in the success of the Hydrogen Energy Research Center.

08 HYDROGEN↗

DOE OSTI2021

Combined Mesonet and Tracker

Title: Combined Mesonet and Trackers (UNL Mobile Mesonets) Authors University of Nebraska PI: Adam Houston, UNL Professor (ahouston2@unl.edu) Mailing Address: 126 Bessey Hall P.O. Box 880340 Lincoln, NE 68588-0340 CoMeT Overview The University of Nebraska-Lincoln operates three Combined Mesonet and Tracker (CoMeTs). CoMeTs are Ford Explorers (model years 2015, 2017, and 2019) with forward-mounted suites of meteorological sensors and dual moonroofs, combining the capability of a mobile mesonet to collect near-surface observations with the capability of an unmanned aircraft systems (UAS) tracker vehicle, which enables an observer in the second row of seats to see the aircraft and maintain compliance with Federal Aviation Administration policies on UAS operation. The CoMeTs collect observations of slow temperature and humidity at ~2 m above ground level (AGL) using a Vaisala HMP155A, fast temperature at ~2 m AGL using a Campbell Scientific 109SS-L thermistor, pressure at ~2.5 m AGL using a Vaisala PTB210, wind speed and direction at ~3.25 m AGL using an R.M. Young 05103 propeller anemometer, and vehicle heading using a KVH Industries C-100 fluxgate compass (Barbieri et al. 2019). The HMP155A and 109SS-L thermistor are shielded and aspirated within a U-tube (Waugh and Frederickson 2010; Houston et al. 2016). This list of sensors is also included in the CoMeT data file metadata. Manufacturer specifications for these instruments are given in Table 1 of Hanft and Houston (2018). The reported measured quantities are summarized below.CoMeT-3 was funded through an equipment allocation included in the NSF TORUS award (AGS-1824649). Instrument Description The specific sensors included on each CoMeT are summarized in the table at the end of this section. In general each CoMeT collects observations of slow temperature and humidity at ~2 m above ground level (AGL) using a Vaisala HMP155, fast temperature at ~2 m AGL using a Campbell Scientific 109SS-L thermistor, pressure at ~2.5 m AGL using a Vaisala PTB210 barometer with a Gill pressure port, wind speed and direction at ~3.25 m AGL using an R.M. Young 05103 propeller anemometer, position using a Garmin 19x HVS receiver, and vehicle heading using a KVH Industries C-100 fluxgate compass. The HMP155 and 109SS are shielded and aspirated within a U-tube (Waugh and Frederickson 2010; Houston et al. 2016). Fast temperature and corrected RH measurements (using sensors housed within the U-tube) have a time constant of 10-12 s based on data collected across a temperature and RH shock during the CLOUD-MAP 2017 calibration/validation tests on June 26, 2017. Vehicle speed was < 10 kts for this test. CoMeT-1 CoMeT-2 CoMeT-3 Slow Temperature Slow RH Vaisala HMP155A-L20-PT Part #: 22280-7 Vaisala HMP155E Part #: E1AA11A0B1A1A0A Vaisala HMP155E Part #: E1AA11A0B1A1A0A Fast temperature Campbell Scientific 109SS-L20-PT Part #: 21448-3 Campbell Scientific 109SS-L12-PW Part #: 21448-109 Campbell Scientific 109SS-L12-PW Part #: 21448-150 Pressure Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Vaisala PTB-210 Part #: A1A1B Gill Pressure Port Part #: 61002 Wind RM Young 05103-L20-PT Part #: 18435-310 RM Young 05103-L20-PW Part #: 18435-244 RM Young 05103-L20-PW Part #: 18435-244 GPS Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Garmin GPS 19x HVS (NMEA 0183) Part #: 010-01010-00 Compass KVH C-100 Part #: 01-0177-15 KVH C-100 Part #: 01-0177-15 KVH C-100 Part #: 01-0177-15 Logger Campbell Scientific CR6-NA-XT-SW Part #: 28385-9 Campbell Scientific CR6-WIFI-XT-SW Part #: 28385-6 Campbell Scientific CR6-WIFI-XT-SW Part #: 28385-6 Data Collection and Real-Time Processing The reported measured quantities are summarized in the table below. Quantity Units Source Epoch time Seconds GPS Latitude and longitude Degrees GPS Altitude m GPS Pressure hPa PTB210 Temperature (fast) deg C 109SS-L Temperature (slow) deg C HMP155 RH (slow) % HMP155 Vehicle speed m/s GPS Vehicle heading deg C-100 and GPS In addition to the measured variables, several derived variables are calculated. Corrected/fast relative humidity (%) Relative humidity is adjusted to the fast temperature following Richardson et al. (1998) and Houston et al. (2016). Water vapor mixing ratio (g/kg) Dew point temperature (°C) Potential temperature (Kelvin) Virtual potential temperature (Kelvin) Equivalent potential temperature (Kelvin) Regular intercomparisons between all three CoMeTs were performed during TORUS 2019. Comparisons were also conducted between CoMeT-1 and CoMeT-2 during LAPSE-RATE (2018) on 14 July. In these intercomparisons, the vehicles were parked adjacent to each other aligned perpendicular to (and facing into) the wind. To minimize engine heating effects, intercomparisons were only conducted when the wind speed was >10 kts. Data Format Original data files for each deployment are saved as text files and then converted to NetCDF. NetCDF versions have units that are CF compliant and may not match the original units in the txt files. The naming convention for the NetCDF files is as follows: UNL.CoMeT3.{deployment date YYYYMMDD}.{start time of observation collection in UTC HHMM}.L2.{post-processing codes}.cdf example: UNL.CoMeT3.20190627.1931.L2.g1.f1.cdf Post-processing codes are included to track modifications to the raw data. These codes are closely connected to error flags associated with each record. Each letter corresponds to a particular instrument: g: GPS p: Barometer tf: Fast temperature ts: Slow temperature rh: Relative humidity f: Compass w: Wind monitor a: All instruments Each number corresponds to a particular post-processing action described more below. Measured and derived variables are included in the following table. Variable Heading Standard Name Units time Time seconds since 00:00:00, 01-01-1970 Alt Altitude meters lat Latitude degrees north lon Longitude degrees east fast_temp Air Temperature kelvin slow_temp Air Temperature kelvin pressure Air Pressure pascals logger_RH Relative Humidity percent calc_corr_RH Relative Humidity percent wind_speed Wind Speed meters per second wind_dir Wind From Direction degrees vehicle_dir Vehicle Direction degrees dewpoint Dew Point Temperature kelvin mixing_ratio Humidity Mixing Ratio g/g theta Air Potential Temperature kelvin theta_v Virtual Potential Temperature kelvin theta_e Equivalent Potential Temperature Kelvin error_flag The error_flag variable is a string that matches the post-processing codes listed above. All instruments will have an associated code, but will have a “0” if the datum is unchanged from the initial processed value. Error Codes The following table summarizes the error codes for data collected before 2020: Error Code Relevant CoMeT Description g1 1,2,3 Exact correction. GPS position and time reprocessed from raw data g2 1 As far as we can tell this is an exact correction to an error in the GPS time. During the correct time periods the time suddenly went backwards ~250s and stayed at this offset for 750s when it corrected itself. The offset was applied to the “time warp” period. p1 2 Approximate correction. Hole in the pressure tube connecting the pressure port to the barometer. Resulted in erroneously low air pressure measurements when the vehicle was in motion. Derived variables recalculated (dew point temperature [e depends on qv and p], water vapor mixing ratio, potential temperature, virtual potential temperature, equivalent potential temperature) a1 3 Exact correction. Missing data reprocessed from raw data a2 1 Bug fix to bias correction for ts1, ts2, and rh1: water vapor mixing ratio was off by a factor of 10 and virtual potential temperature was wrong because of this. f1 3 No correction, missing data. Fluxgate compass inoperable. Wind speed and direction calculated using GPS-derived vehicle heading instead. rh1 1 Approximate correction. Constant bias of +1.7% removed from relative humidity. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) ts1 1 Approximate correction. Constant bias of +0.6 K removed from slow temperature. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) ts2 1 Approximate correction. Constant bias of +1.0 K removed. Derived variables recalculated (corrected/fast relative humidity, dew point temperature, water vapor mixing ratio, virtual potential temperature, equivalent potential temperature) References Bolton, D., 1980: The Computation of Equivalent Potential Temperature. Mon. Wea. Rev., 108, 1046–1053, https://doi.org/10.1175/1520-0493(1980)108<1046:TCOEPT>2.0.CO;2. Hanft, W., and A. L. Houston, 2018: An Observational and Modeling Study of Mesoscale Air Masses with High Theta-E. Mon. Wea. Rev., 146, 2503–2524, https://doi.org/10.1175/MWR-D-17-0389.1.Wexler Houston, A. L., R. J. Laurence III, T. W. Nichols, S. Waugh, B. Argrow, and C. L. Ziegler, 2016: Intercomparison of unmanned aircraft-borne and mobile mesonet atmospheric sensors. Journal of Atmospheric and Oceanic Technology. 33, 1569-1582, doi: 10.1175/JTECH-D-15-0178.1. Lowe, P. R., 1977: An Approximating Polynomial for the Computation of Saturation Vapor Pressure. J. Applied Meteorology, 16, 100–103. Richardson, S. J., S. E. Frederickson, F. V. Brock, and J. A. Brotzge, 1998: Combination temperature and relative humidity probes: Avoiding large air temperature errors and associated relative humidity errors. Preprints, 10th Symp. On Meteorological Observations and Instrumentation, Phoenix, AZ, Amer. Meteor. Soc., 278–283. Waugh, S., and S. E. Frederickson, 2010: An improved aspirated temperature system for mobile meteorological observations, especially in severe weather. 25th Conf. on Severe Local Storms, Denver, CO, Amer. Meteor. Soc., P5.2. [Available online at https://ams.confex.com/ams/25SLS/techprogram/paper_176205.htm.]

54 ENVIRONMENTAL SCIENCES↗