Engineering Papers⌕ Search

SEARCH · Engineering Papers

Results for “Mexico”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 289 records · Page 16
All sourcesNASA NTRSDOE OSTI
DOE OSTI2023

Coupled wave-current modeling for hydrodynamic load analysis of macroalgae cultivation farms

Large-scale cultivation of macroalgae is one of the most promising biofuel sources that could reduce our consumption of fossil fuels and would be particularly economically competitive when grown for the co-production of additional goods such as food and textiles. Current production of biofuel from algal biomass is limited by labor costs and lack of data on potential impacts of cultivation and harvesting on marine and coastal environments as well as a comprehensive characterization of the impact of environmental conditions on macroalgal feedstock and their bioproduct and biofuel yield and quality. Awarded by the United States (U.S.) Department of Energy Advanced Research Projects Agency-Energy (ARPA-E) Macroalgae Research Inspiring Novel Energy Resources (MARINER) program, which seeks to enable the U.S. as a global leader in the production of marine biomass, the Marine Biological Laboratory (MBL) has been developing a test system for tropical seaweed cultivation in the Gulf of Mexico and the Caribbean. An integral step in designing macroalgae cultivation farms is to adequately characterize the hydrodynamic climate at potential growth sites. In regions like the Gulf of Mexico and the Caribbean, which are highly exposed to tropical cyclones, it is critical to not only consider the day-to-day hydrodynamic conditions but to also assess the risk of extreme sea states to ensure the survivability of future macroalgae farms. Under these considerations, the Pacific Northwest National Laboratory (PNNL) is providing modeling support for MBL to inform the design and siting of the farm systems that have been proposed for their ARPA-E MARINER project. This report describes the development of a high-resolution coupled storm surge and wave model to simulate the hydrodynamics and wave climate at proposed macroalgae cultivation sites selected by MBL in Florida and Puerto Rico. Model results, including model validation, water level, current distributions, and sea states, are discussed for both selected sites in Florida and Puerto Rico coast. These simulations provide an accurate insight into the hydrodynamic conditions that a macroalgae farm is likely to experience during its operational lifetime, including current information to support fine-scale hydrodynamic load modeling, risk analysis and system design.

09 BIOMASS FUELS↗
DOE OSTI2024

Dr. Sahar Said Allam (1964-2022): A Memoriam

In this short talk, we memorialize the scientific life of AAS member Dr. Sahar Said Allam (1964-2022), an alumna of Cairo University and the National Research Institute of Astronomy \& Geophysics (NRIAG). Her scientific career took her to the Universitaet Potsdam (Germany), New Mexico State University (USA), the Space Telescope Science Institute (USA), and the Fermi National Accelerator Laboratory (Fermilab; USA), as well as to astronomical observatories in New Mexico, Arizona, Hawaii, Chile, and Australia. Among other projects, she worked on the Sloan Digital Sky Survey (SDSS) and the Dark Energy Survey (DES), achieving the coveted “Builders” status on both these projects. She was the discoverer of the (at the time) brightest known Lyman Break Galaxy, the strongly lensed “8 O’Clock Arc”, and played an important role in the discovery of the optical counterpart to the gravitational wave event GW170817. During her final illness, she began work as a Data Preview 0 (“DP0”) De legate for the Vera C. Rubin Legacy Survey of Space & Time (LSST) and was even the Principal Investigator on a successful observing proposal submitted posthumously. The asteroid “135979 Allam” is named after her.

Tucker, Douglas L.↗
DOE OSTI2025

Bioaccumulation Factor for Radium in Rio Grande Biota

The Los Alamos National Laboratory (LANL or Laboratory) Environmental Protection and Compliance Division’s Environmental Stewardship Group (EPC-ES) performs the radiological analysis portion of biota dose assessments using the computer program RESRAD-Biota (DOE 2004, DOE 2020). RESRAD-Biota uses a default bioaccumulation factor, B iv , for radium in aquatic animals. This bioaccumulation factor, also listed in Department of Energy (DOE) Standard, DOE-STD-1153-2019, is the ratio of a radionuclide concentration in fresh weight biota to the environment in which it resides, which for aquatic animals is water. DOE-STD-1153-2019 offers conservative values for these ratios that are specific to the radiological contaminant, the biota, and the environment. The B iv in RESRAD-Biota can be used for general screening (Level 1 screening). If the factor proves to be too conservative, then a site-specific B iv may be used. The biota dose assessment of fish from the northern New Mexico region of the Rio Grande fail the general screen, which indicates that further analysis is necessary. Level 2 analysis is site-specific but still has conservative limitations. Level 3 analysis is a more realistic and representative, sitespecific analysis. The purpose of this paper is to use data specific to the Rio Grande to calculate a new aquatic animal radium B iv . This B iv can then be used for Level 3 analysis of aquatic animals specifically in the northern New Mexico region of the Rio Grande. The calculated radium B iv is a useful value for performing detailed, accurate biota dose assessments and calculating dose to fish using RESRAD-Biota when only sediment data are available.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Large Vessel Activity and Low-Frequency Underwater Sound Benchmarks in United States Waters

Chronic low-frequency noise from commercial shipping is a worldwide threat to marine animals that rely on sound for essential life functions. Although the U.S. National Oceanic and Atmospheric Administration recognizes the potential negative impacts of shipping noise in marine environments, there are currently no standard metrics to monitor and quantify shipping noise in U.S. marine waters. However, one-third octave band acoustic measurements centered at 63 and 125 Hz are used as international (European Union Marine Strategy Framework Directive) indicators for underwater ambient noise levels driven by shipping activity. We apply these metrics to passive acoustic monitoring data collected over 20 months in 2016–2017 at five dispersed sites throughout the U.S. Exclusive Economic Zone: Alaskan Arctic, Hawaii, Gulf of Mexico, Northeast Canyons and Seamounts Marine National Monument (Northwest Atlantic), and Cordell Bank National Marine Sanctuary (Northeast Pacific). To verify the relationship between shipping activity and underwater sound levels, vessel movement data from the Automatic Identification System (AIS) were paired to each passive acoustic monitoring site. Daily average sound levels were consistently near to or higher than 100 dB re 1 μPa in both the 63 and 125 Hz one-third octave bands at sites with high levels of shipping traffic (Gulf of Mexico, Northeast Canyons and Seamounts, and Cordell Bank). Where cargo vessels were less common (the Arctic and Hawaii), daily average sound levels were comparatively lower. Specifically, sound levels were ~20 dB lower year-round in Hawaii and ~10-20 dB lower in the Alaskan Arctic, depending on the season. Although these band-level measurements can only generally facilitate differentiation of sound sources, these results demonstrate that international acoustic indicators of commercial shipping can be applied to data collected in U.S. waters as a unified metric to approximate the influence of shipping as a driver of ambient noise levels, provide critical information to managers and policy makers about the status of marine environments, and to identify places and times for more detailed investigation regarding environmental impacts.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Calculating Methane Emissions from Offshore Facilities Using Bottom-Up Methods

With changing demands in regulation, understanding methane emissions from offshore oil and gas production infrastructure has become increasingly important. Reported emissions from facilities in the Gulf of Mexico range from zero to thousands of tons of methane per hour, but these is currently no clear understanding of how this range compares to expected emissions from normally operating facilities. To generate realistic emission estimates, we create two bottom-up models that simulate emissions from facilities operating in the Gulf of Mexico. We estimate type 1 prototypical facilities (typically unmanned, older, lower-producing platforms in shallow water with little processing equipment, compressors, or storage tanks) to emit an average of 13 kg CH 4 h −1 , which corresponds to a loss of 2.7% of the average facility production. Type 2 prototypical facilities (continuously manned, higher production and operate in deeper water with processing equipment, oil storage tanks, compressors and power generation) emit an average of 88 kg CH 4 h −1 , which corresponds to a loss of 2.5% of production. The average measured emission from type 1 facilities was 18 kg CH 4 h −1 with a median production loss estimated at 8%. The average measured emission from type 2 facilities was 36 kg CH 4 h −1 with a median production loss estimated at 2.4%. Using emission factors that consider the long-tail emission distribution partly reconciles the difference between modelled and measured emission estimates, but we suggest the current the fugitive emission estimate may be an underestimate and more data on the number and size of fugitive emissions could explain differences between the modelled and measured emission estimate. We suggest the bottom-up approach described here that uses production data coupled with facility equipment could be used to identify facilities that have abnormally large measured emissions, caused by methodological failure or larger than expected fugitive emissions, which should be targeted for further evaluation resulting in remeasurement or identification of source type so that a more accurate estimates can be made on the absolute emission.

bottom-up↗
DOE OSTI2023

Structuring Nutrient Yields throughout Mississippi/Atchafalaya River Basin Using Machine Learning Approaches

To minimize the eutrophication pressure along the Gulf of Mexico or reduce the size of the hypoxic zone in the Gulf of Mexico, it is important to understand the underlying temporal and spatial variations and correlations in excess nutrient loads, which are strongly associated with the formation of hypoxia. This study’s objective was to reveal and visualize structures in high-dimensional datasets of nutrient yield distributions throughout the Mississippi/Atchafalaya River Basin (MARB). For this purpose, the annual mean nutrient concentrations were collected from thirty-three US Geological Survey (USGS) water stations scattered in the upper and lower MARB from 1996 to 2020. Eight surface water quality indicators were selected to make comparisons among water stations along the MARB over the past two decades. Principal component analysis (PCA) was used to comprehensively evaluate the nutrient yields across thirty-three USGS monitoring stations and identify the major contributing nutrient loads. The results showed that all samples could be analyzed using two main components, which accounted for 81.6% of the total variance. The PCA results showed that yields of orthophosphate (OP), silica (SI), nitrate–nitrites (NO 3 -NO 2 ), and total suspended sediment (TSS) are major contributors to nutrient yields. It also showed that land-planted crops, density of population, domestic and industrial discharges, and precipitation are fundamental causes of excess nutrient loads in MARB. These factors are of great significance for the excess nutrient load management and pollution control of the Mississippi River. It was found that the average nutrient yields were stable within the sub-MARB area, but the large nitrogen yields in the upper MARB and the large phosphorus yields in the lower MARB were of great concern. t-distributed stochastic neighbor embedding (t-SNE) revealed interesting nonlinear and local structures in nutrient yield distributions. Clustering analysis (CA) showed the detailed development of similarities in the nutrient yield distribution. Moreover, PCA, t-SNE, and CA showed consistent clustering results. This study demonstrated that the integration of dimension reduction techniques, PCA, and t-SNE with CA techniques in machine learning are effective tools for the visualization of the structures of the correlations in high-dimensional datasets of nutrient yields and provide a comprehensive understanding of the correlations in the distributions of nutrient loads across the MARB.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Implications of Sea Breeze Circulations on boundary layer aerosols in the southern coastal Texas region

The Sea Breeze Circulation (SBC) influences atmospheric processes at multiple scales in coastal regions. Understanding how SBCs impact the aerosol number budget and aerosol–cloud interaction processes is essential. This study investigates sea breeze–aerosol interactions (SAIs) during 46 summertime SBC events using data from the TRacking Aerosol Convection Interactions Experiment (TRACER) field campaign across urban (main) and rural (supplemental) coastal sites in southern Texas. Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) simulations complement observations to explore spatio-temporal meteorological controls on boundary layer aerosols. During the summertime, Sea Breeze Fronts (SBF) penetrating inland transported cool, moist air over the land, introducing air masses with distinct properties compared to the preexisting continental air. These SAIs cause variability in number concentrations of up to a factor of two, with events typically lasting ∼ 5 h before returning to background conditions. SAI impact on aerosols varies with site proximity to water and the preceding sea breeze (SB) history, primarily affecting the marine-influenced accumulation mode. The main site, influenced by both Galveston Bay and the Gulf of Mexico, reflects a stronger marine influence. In contrast, a supplemental site, at a similar shoreline distance but exposed only to the Gulf of Mexico and typically upstream of the urban core, samples SB air that has traversed land and partially regained continental characteristics. Simulations show that the regional SAIs extend ∼ 50 km inland and reach up to the boundary layer height. SAIs further decrease cloud condensation nuclei relevant aerosol number concentrations in ∼ 20 % of events during SBF passage.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

HarDWR - Harmonized Water Rights Records

A dataset within the Harmonized Database of Western U.S. Water Rights (HarDWR). For a detailed description of the database, please see the meta-record v2.0. Changelog v2.0 - Recalculated based on data sourced from WestDAAT - Changed using a Site ID column to identify unique records to using aa combination of Site ID and Allocation ID - Removed the Water Management Area (WMA) column from the harmonized records. The replacement is a separate file which stores the relationship between allocations and WMAs. This allows for allocations to contribute to water right amounts to multiple WMAs during the subsequent cumulative process. - Added a column describing a water rights legal status - Added "Unspecified" was a water source category - Added an acre-foot (AF) column - Added a column for the classification of the right's owner v1.02 - Added a .RData file to the dataset as a convenience for anyone exploring our code. This is an internal file, and the one referenced in analysis scripts as the data objects are already in R data objects. v1.01 - Updated the names of each file with an ID number less than 3 digits to include leading 0s v1.0 - Initial public release Description Here we present an updated database of Western U.S. water right records. This database provides consistent unique identifiers for each water right record, and a consistent categorization scheme that puts each water right record into one of seven broad use categories. These data were instrumental in conducting a study of the multi-sector dynamics of inter-sectoral water allocation changes though water markets (Grogan et al., *in review*). Specifically, the data were formatted for use as input to a process-based hydrologic model, Water Balance Model (WBM), with a water rights module (Grogan et al., *in review*). While this specific study motivated the development of the database presented here, water management in the U.S. West is a rich area of study (e.g., Anderson and Woosly, 2005; Tidwell, 2014; Null and Prudencio, 2016; Carney et al., 2021) so releasing this database publicly with documentation and usage notes will enable other researchers to do further work on water management in the U.S. West. We produced the water rights database presented here in four main steps: (1) data collection, (2) data quality control, (3) data harmonization, and (4) generation of cumulative water rights curves. Each of steps (1)-(3) had to be completed in order to produce (4), the final product that was used in the modeling exercise in Grogan et al. (*in review*). All data in each step is associated with a spatial unit called a Water Management Area (WMA), which is the unit of water right administration utilized by the state in which the right came from. Steps (2) and (3) required use to make assumptions and interpretation, and to remove records from the raw data collection. We describe each of these assumptions and interpretations below so that other researchers can choose to implement alternative assumptions an interpretation as fits their research aims. Motivation for Changing Data Sources The most significant change has been a switch from collecting the raw water rights directly from each state to using the water rights records presented in WestDAAT, a product of the Water Data Exchange (WaDE) Program under the Western States Water Council (WSWC). One of the main reasons for this is that each state of interest is a member of the WSWC, meaning that WaDE is partially funded by these states, as well as many universities. As WestDAAT is also a database with consistent categorization, it has allowed us to spend less time on data collection and quality control and more time on answering research questions. This has included records from water right sources we had previously not known about when creating v1.0 of this database. The only major downside to utilizing the WestDAAT records as our raw data is that further updates are tied to when WestDAAT is updated, as some states update their public water right records daily. However, as our focus is on cumulative water amounts at the regional scale, it is unlikely most records updates would have a significant effect on our results. The structure of WestDAAT led to several important changes to how HarWR is formatted. The most significant change is that WaDE has calculated a field known as `SiteUUID`, which is a unique identifier for the Point of Diversion (POD), or where the water is drawn from. This separate from `AllocationNativeID`, which is the identifier for the allocation of water, or the amount of water associated with the water right. It should be noted that it is possible for a single site to have multiple allocations associated with it and for an allocation to be able to be extracted from multiple sites. The site-allocation structure has allowed us to adapt a more consistent, and hopefully more realistic, approach in organizing the water right records than we had with HarDWR v1.0. This was incredibly helpful as the raw data from many states had multiple water uses within a single field within a single row of their raw data, and it was not always clear if the first water use was the most important, or simply first alphabetically. WestDAAT has already addressed this data quality issue. Furthermore, with v1.0, when there were multiple records with the same water right ID, we selected the largest volume or flow amount and disregarded the rest. As WestDAAT was already a common structure for disparate data formats, we were better able to identify sites with multiple allocations and, perhaps more importantly, allocations with multiple sites. This is particularly helpful when an allocation has sites which cross WMA boundaries, instead of just assigning the full water amount to a single WMA we are now able to divide the amount of water between the number of relevant WMAs. As it is now possible to identify allocations with water used in multiple WMAs, it is no longer practical to store this information within a single column. Instead the stAllocationToWMATab.csv file was created, which is an allocation by WMA matrix containing the percent Place of Use area overlap with each WMA. We then use this percentage to divide the allocation's flow amount between the given WMAs during the cumulation process to hopefully provide more realistic totals of water use in each area. However, not every state provides areas of water use, so like HarDWR v1.0, a hierarchical decision tree was used to assign each allocation to a WMA. First, if a WMA could be identified based on the allocation ID, then that WMA was used; typically, when available, this applied to the entire state and no further steps were needed. Second was the spatial analysis of Place of Use to WMAs. Third was a spatial analysis of the POD locations to WMAs, with the assumption that allocation's POD is within the WMA it should belong to; if an allocation still had multiple WMAs based on its POD locations, then the allocation's flow amount would be divided equally between all WMAs. The fourth, and final, process was to include water allocations which spatially fell outside of the state WMA boundaries. This could be due to several reasons, such as coordinate errors / imprecision in the POD location, imprecision in the WMA boundaries, or rights attached with features, such as a reservoir, which crosses state boundaries. To include these records, we decided for any POD which was within one kilometer of the state's edge would be assigned to the nearest WMA. Other Changes WestDAAT has Allowed In addition to a more nuanced and consistent method of assigning water right's data to WMAs, there are other benefits gained from using the WestDAAT dataset. Among those is a consistent categorization of a water right's legal status. In HarDWR v1.0, legal status was effectively ignored, which led to many valid concerns about the quality of the database related to the amounts of water the rights allowed to be claimed. The main issue was that rights with legal status' such as "application withdrawn", "non-active", or "cancelled" were included within HarDWR v1.0. These, and other water rights status' which were deemed to not be in use have been removed from this version of the database. Another major change has been the addition of the "unspecified water source category. This is water that can come from either surface water or groundwater, or the source of which is unknown. The addition of this source category brings the total number of categories to three. Due to reviewer feedback, we decided to add the acre-foot (AF) column so that the data may be more applicable to a wider audience. We added the ownerClassification column so that the data may be more applicable to a wider audience. File Descriptions The dataset is a series of various files organized by state sub-directories. In addition, each file begins with the state's name, in case the file is separate from its sub-directory for some reason. After the state name is the text which describes the contents of the file. Here is each file described in detail. Note that st is a placeholder for the state's name. stFullRecords_HarmonizedRights.csv: A file of the complete water records for each state. The column headers for each of this type of file are: state - The name of the state to which the allocations belong to. FIPS - The two digit numeric state ID code. siteID - The site location ID for POD locations. A site may have multiple allocations, which are the actual amount of water which can be drawn. In a simplified hypothetical, a farm stead may have an allocation for "irrigation" and an allocation for "domestic" water use, but the water is drawn from the same pumping equipment. It should be noted that many of the site ID appear to have been added by WaDE, and therefore may not be recognized by a given state's water rights database. allocationID - The allocation ID for the water right. For most states this is the water right ID, and what is recommended to use should a right be looked up on a given state's water rights database. The water amounts associated with these IDs tend to be finer scaled than those associated with siteID. It should be noted that some allocations may be extracted from multiple sites, particularly for larger Places of Use. ownerClassification - A classification of the types of owners for water rights. The most common is `Private` which incorporates a wide range of entities. Several classifications would be grouped into a government category, most of which are for the U.S. Federal Government. These allocations could be listed as "Federal", "United States of America", or as the names of any number of federal agencies. The last major grouping of entities is for "Native American"s. priorityDate - The date we use as the water right priority date for our modeling analysis. This is the legal priority date when it is available. However, for some rights, specifically from California and New Mexico, we used a pseudo priority date (e.g. well completion date or start of well drilling date) when a legal priority date was not available. The most questionable dates come from New Mexico, where the only date associated with certain water right records was the date the allocation was recorded in the database. As the allocation record creation tended to be within a few months of the filing of the application of the water right, from manually double checking the water rights, and our analysis focuses on aggregating water rights on the timescale of years, we determined it was acceptable to use such dates to include as many records as possible. primaryBeneficialUse - From the numerous state water use categories, WaDE categorized them into 21 categories WestDAAT. This column is the original WaDE category for the primary water use at the PoD site. allocationBeneficialUse - From the numerous state water use categories, WaDE categorized them into 21 categories for WestDAAT. This column is the original WaDE category

Economics↗
DOE OSTI2020

HarDWR - Water Management Area (WMA) Shapefiles

A dataset within the Harmonized Database of Western U.S. Water Rights (HarDWR). For a detailed description of the database, please see the meta-record v2.0. Changelog v2.0 - No changes v1.0 - Initial public release Description Borders of all Water Management Areas (WMAs) across the 11 western-most states of the coterminous United States are available filtered through a single source. The legal name for this set of boundaries varies state-by-state. The data is provided as two compressed shapefiles. One, stateWMAs, contains data for all 11 states. For 10 of those states, Arizona being the exception, the polygons represent the legal management boundaries used by those states to manage their surface and groundwater resources respectively. WMAs refer to the set of boundaries a particular state uses to manage its water resources. Each set of boundaries was collected from the states individually, and then merged into one spatial layer. The merging process included renaming some columns to enable merging with all other source layers, as well as removing columns deemed not required for followup analysis. The retained columns for each boundary are: basinNum - the state provided unique numerical ID; basinName - the state provided English name of the area, where applicable; state - the state name; and uniID - a unique identifier we created by concatenating the state name, and underscore, and the state numerical ID. Arizona is unique within this collection of states in that surface and groundwater resources are managed using two separate sets of boundaries. During our followup analysis (Grogan et al., in review) we decided to focus on one set of boundaries, those for surface water. This is due to the recommendation of our hydrologists that the surface water boundary set is a more realist representation of how water moves across the landscape, as a few of the groundwater boundaries are based on political and/or economic considerations. Therefore, the Arizona surface WMAs are included within stateWMAs. The Arizona groundwater WMAs are provided as a separate file, azGroundWMAs, as a companion to the first file for completeness and general reference. WMA spatial boundary data sources by state: Arizona: Arizona Surface Water Watersheds; Collected February, 2020; https://gisdata2016-11-18t150447874z-azwater.opendata.arcgis.com/datasets/surface-watershed/explore?location=34.158174%2C-111.970823%2C7.50 Arizona: Arizona Ground Water Basins; Collected February, 2020; https://gisdata2016-11-18t150447874z-azwater.opendata.arcgis.com/datasets/groundwater-basin-2/explore?location=34.158174%2C-111.970823%2C7.50 California: California CalWater 2.2.1; Collected February, 2020; https://www.mlml.calstate.edu/mpsl-mlml/data-center/data-entry-tools/data-tools/gis-shapefile-layers/ Colorado: Colorado Water District Boundaries; Collected February, 2020; https://www.colorado.gov/pacific/cdss/gis-data-category Idaho: Idaho Department of Water Resources (IDWR) Administrative Basins; Collected November, 2015; https://data-idwr.opendata.arcgis.com/datasets/fb0df7d688a04074bad92ca8ef74cc26_4/explore?location=45.018686%2C-113.862284%2C6.93 Montana: Collected June, 2019; Directly contacted Montana Department of Natural Resources and Conservation (DNRC) Office of Information Technology (OIT) Nevada: Nevada State Engineer Admin Basin Boundaries; Collected April, 2020 https://ndwr.maps.arcgis.com/apps/mapviewer/index.html?layers=1364d0c3a0284fa1bcd90f952b2b9f1c New Mexico: New Mexico Office of the State Engineer (OSE) Declared Groundwater Basins; Collected April, 2020 https://geospatialdata-ose.opendata.arcgis.com/datasets/ose-declared-groundwater-basins/explore?location=34.179783%2C-105.996542%2C7.51 Oregon: Oregon Water Resources Department (OWRD) Administrative Basins; Collected February, 2020; https://www.oregon.gov/OWRD/access_Data/Pages/Data.aspx Utah: Utah Adjudication Books; Collected April, 2020; https://opendata.gis.utah.gov/datasets/utahDNR::utah-adjudication-books/explore?location=39.497165%2C-111.587782%2C-1.00 Washington: Washington Water Resource Inventory Areas (WRIA); Collected June, 2017; https://ecology.wa.gov/Research-Data/Data-resources/Geographic-Information-Systems-GIS/Data Wyoming: Wyoming State Engineer's Office Board of Control Water Districts; Collected June, 2019; Directly contacted Wyoming State Engineer's Office

Economics↗
DOE OSTI2020

Automated Data Review of Analytical Laboratory Results at Los Alamos National Laboratory - 20299

Newport News Nuclear BWXT-Los Alamos, LLC (N3B) collects samples in support of the U.S. Department of Energy's (DOE) Office of Environmental Management (EM) Los Alamos Legacy Cleanup Contract (LLCC). N3B receives and reviews over 1.6 million sample data points annually in support of various ongoing environmental monitoring and remediation projects of the LLCC. N3B must demonstrate and document that reported external analytical laboratory data produced for the LLCC are of sufficient quality to fulfill their intended purpose and to support defensible decision making as described in EPA QA/G4 Guidance for the Data Quality Objectives Process 1994. In 2018, N3B assumed management of the LLCC along with the Environmental Information Management (EIM) database that contains all historical and current environmental data associated with the LLCC. The entire EIM database is shared between N3B, Triad National Security, LLC (Triad), and New Mexico Environment Department (NMED). These three parties jointly manage the database, its configuration, and changes / updates. All environmental data that are entered into EIM are updated and available, on a daily basis, in the linked public database Intellus New Mexico (Intellus). The quality and defensibility of the environmental data generated from sampling activities is a key component of an effective remediation process. Providing quality data is accomplished through a data assessment process that includes examination, verification, and validation. Examination is the assessment of completeness of the deliverables, identification of any reporting errors, and determining the usability of the data based on the laboratory's evaluation of its data as described in the case narrative received with the data. Verification consists of an evaluation of the Electronic Data Deliverables (EDD) data report to determine the extent to which the external analytical laboratories met method and contract-specific quality control and reporting requirements. Validation consists of determining the data quality and the extent to which the external analytical laboratories accurately and completely reported all sample and quality control results and satisfied all contract requirements. EIM contains an automatic Data Validation Module which performs automated data review (DVM ADR). DVM ADR is a tool to assist in the validation process. When DVM ADR is used in conjunction with manual examination of sample data packages, the combination of the two will meet and exceed the requirements of verification. N3B recognized an opportunity for process improvement, focusing on DVM ADR configuration and enhancements in EIM. Testing EIM's configuration provided proof of the DVM ADR's capabilities and flexibility to accurately perform routine data checks based on analytical methods and regulatory requirements. In addition, the DVM ADR module was improved through enhancements for all analytes, particularly upgrades for radiochemistry data. Extensive testing of the DVM ADR module occurred using EDDs from actual laboratory analyses on the EIM testing site. During this process, N3B manipulated EDD information to verify that the actual outcomes matched the expected outcomes. The results of this testing were shared with the database architects, and configuration improvements were identified to address these results. During this process, N3B identified that the radiochemical DVM ADR capabilities were underutilized, and so enhanced the DVM ADR functionality with respect to radioanalytical assessment. N3B environmental data uploads to Intellus on a daily basis from EIM, once the analytical data undergoes examination and verification. As such, it is important to have a high level of confidence in the quality and defensibility of the data. The process of manual examination, along with the DVM ADR, in conjunction with full validation of a percentage the data specified through the Data Quality Objectives greatly increases efficiency of data review and confidence level of the quality of the data, and gives the project managers, governmental offices, and the public expedited access to high-quality data. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Spent Nuclear Fuel Storage and Radioactive Waste Disposal in the United States: A Law and Policy Analysis - 20302

While Congress plays political football, spent nuclear fuel continues to sit in de facto interim nuclear waste storage sites throughout the country. This ad hoc approach - if it can even be called an approach - to nuclear waste management is in no one's best interests, because of financial, safety, environmental, and national security concerns with the status quo. Senate leadership had asserted that an up-or-down vote on the Yucca Mountain Project would take place in September or October 2019, but that did not occur. Rather, a conference bill was agreed to, and it provided that, although the nuclear program should receive some funding, funding was not made available for centralized interim storage ('CIS') or the Yucca Mountain Project. The President's FY2021 Budget Request does not contain any proposed funding for the Yucca Mountain Project ('the Project'). This paper will discuss the implications of that process, both for the Project itself and for the U.S. nuclear waste program more generally. In order to provide context for the current situation, this paper will begin by chronicling the history of U.S. nuclear waste management, from the passage of the Nuclear Waste Policy Act of 1982 and to the present day. It will discuss the roles of the U.S. Department of Energy, the Nuclear Regulatory Commission, federal and state political delegations, and the nuclear energy industry. The paper will then identify key themes that can be expected to affect the future of nuclear waste management in the United States. For example, it will consider whether development of additional CIS facilities is a viable short- to medium-term solution. CIS facilities may relieve immediate pressure at decommissioned or soon-to-be-decommissioned nuclear power plants; but with that pressure partially alleviated, support for building a long-term repository may be reduced. It will also discuss opposition by the State of New Mexico and others to the proposed New Mexico CIS project, based not only on siting concerns but also whether it might become a de facto repository, and whether the State of Texas and others may also be opposed, for similar reasons, to the proposed CIS facility in Texas. Additionally, the paper will examine consent-based siting and its implications for Nevada and other states that are potential hosts for spent nuclear fuel storage and disposal facilities. Further, if the Project is not a politically viable solution, the paper will examine whether it is now time for serious consideration of an alternate location for a permanent repository, as well as consideration of other options entirely, such as deep geologic disposal. The paper will conclude by looking ahead to the 2020 elections. It will describe the positions of candidates (particularly Presidential candidates) on spent nuclear fuel storage and disposal options, without advocating for any particular candidate or political party. Perhaps in 2020, we will at least see a start to a solution to the seemingly intractable problem of nuclear waste management in the United States. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

Uranium Mill Tailings Radiation Control Act Title II DOE Due Diligence and Lessons Learned from a Previous Site Transfer - 20352

Title II of the Uranium Mill Tailings Radiation Control Act (UMTRCA) established that a government agency will provide perpetual care for closed uranium and thorium ore-processing sites that were operating under an NRC source material license in 1978 or were licensed thereafter. Commercial owners (licensees) operating under an NRC or agreement state specific license when UMTRCA was passed are responsible for conducting reclamation of any byproduct material remaining from uranium-ore processing operations in accordance with an NRC or agreement state approved reclamation plan. Reclamation includes both surface and groundwater remedies. Upon completion of reclamation and approval by NRC, the site is required to be transferred to either the host state or the DOE for long-term surveillance and maintenance. Since UMTRCA's enactment, six Title II sites have been transferred to DOE; an additional 24 Title II sites are anticipated to be transferred before 2050. DoE's role mandated under UMTRCA Title II as the long-term care custodian is to perform 'monitoring, maintenance, and emergency measures necessary to protect the public health and safety.' UMTRCA requires that the licensee pay a long-term surveillance charge 'sufficient to cover the annual costs of site surveillance.' However, at some sites such as the Bluewater, New Mexico, Disposal Site, this mandate has required additional effort and expense by DOE, beyond the originally anticipated and intended scope within UMTRCA, but within the authority of DOE under UMTRCA. In 1997, the Bluewater site became the second UMTRCA Title II site to be transferred to DOE. The site was the location of a uranium mill operated from 1953 until 1982. The specific licensee began site reclamation in 1991, and by 1995 all tailings and contaminated materials were encapsulated in two tailings disposal cells and other disposal areas. In addition to surface contamination, milling activities impacted groundwater in the two upper aquifers. In 1989, the specific licensee attempted active groundwater remediation; however, no significant reduction in contaminant concentrations was observed. As a result, the specific licensee applied to NRC for alternate concentration limits (ACLs) in 1990, which were approved in 1996 as being protective, after additional corrective actions were performed. Since transfer of the Bluewater site to DOE, unforeseen challenges have occurred, requiring additional actions. The first challenge is the occurrence of surface depressions located on the northern section of the main tailings disposal cell. The depressions were first observed during DoE's initial inspection in 1998; however, evidence of these can be observed on satellite images taken prior to transfer. Since being first observed, the depressions have continued to grow both in depth and areal extent. Due to the design of the main tailings disposal cell, the depressions impede storm water from being effectively shed off the 101- hectare (250-acre) top slope of the main tailings disposal cell. Instead, storm water accumulates in the depressions, forming a large ephemeral pond that has stored up to 16.3 x 10{sup 6} liters (4.3 million gallons) of stormwater. The ponding poses a potential risk to the integrity of the main tailings disposal cell in the case of a large storm event, with the potential to cause the pond to overtop and erode the cover material and underlying waste. DOE has taken a number of short-term actions to monitor, measure, and reduce the ponding and is currently working with the US Army Corps of Engineers to design and construct a repair. Additional challenges are associated with groundwater at the Bluewater site. Nine wells were present on the 1335-hectare (3300-acre) site upon transfer. Groundwater compliance was called into question after the State of New Mexico reduced its uranium groundwater standard from 5.0 to 0.03 milligrams per liter in 2004, and when an ACL for uranium was exceeded in a site monitoring well in 2010. Acquiring historical groundwater data and subsequent evaluations as well as additional DOE groundwater monitoring led to installing 10 new monitoring wells and performing additional site hydrogeology recharacterization. DOE continues to evaluate groundwater conditions at the site and works with the NRC to determine regulatory requirements and a path forward. As a result of lessons learned at the Bluewater site and other Title II sites, improved processes have been implemented at a programmatic level to increase due diligence before site transfer and prevent similar issues from occurring at other UMTRCA Title II sites under long-term management. DoE's due diligence process is documented in the Process for Transition of UMTRCA Title II Disposal Sites to DOE for Long-Term Surveillance and Maintenance and is designed to ensure that DOE has no technical or compliance concerns with regulatory decisions that might compromise protectiveness following site transfer to DOE. Implementation of the due diligence process has increased DoE's role prior to site transfer and has been effective in identifying potential issues. Actions by NRC and specific licensees, in response to enhanced due diligence efforts by DOE, are expected to minimize, if not totally prevent, the need for unanticipated actions by DOE pertaining to the surface and groundwater remedies after site transfer. (authors)

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2025

Rapid and Temporary Deployment of Fiber-Optic Arrays to Measure Surface Chemical Explosion Series with Distributed Acoustic Sensing

Rapid and temporary distributed acoustic sensing (DAS) deployments are crucial for accurately capturing the seismic wavefield following major events, such as earthquakes, or in anticipation of known events of interest, such as chemical explosions. We provide an overview of two DAS campaigns conducted in May and October 2024 to record the seismoacoustic waves generated by two series of surface chemical explosions in New Mexico, United States, involving 1- and 10-ton trinitrotoluene-equivalent charges. In both campaigns, we deployed approximately 2 km of fiber-optic cables in a dry riverbed, about 12 km east of the explosion sites. For the October campaign, seven geophones and two anemometers were collocated with the fiber. We describe the field deployments and present preliminary results from the recorded signals. Specifically, we cross analyze the data recorded in May and October, validate the DAS data with geophone measurements, and highlight the benefits of burying fibers to reduce wind noise and improve signal-to-noise ratios. This study demonstrates the potential of DAS to record the seismoacoustic waves generated by surface chemical explosions of varying sizes at distances of approximately 10 km from the source.

58 GEOSCIENCES↗
DOE OSTI2025

CO2 Storage Economic Analysis: CarbonSAFE Use Case

Poster on “CO2 Storage Economic Analysis: CarbonSAFE Use Case” for the CCUS 2025 conference held in Houston, Texas March 3-5, 2025. The cost of designing, permitting, constructing, operating, and closing a CO2 storage project is of vital importance to project developers. The National Energy Technology Laboratory has developed the NRAP/SMART Technoeconomic and Liability Evaluation for Storage (TALES) Model to provide quantitative cost-based insights to support developers planning CO2 injection and storage projects. This study presents a collaborative economic analysis applying TALES with data from the San Juan Basin CarbonSAFE Phase III project led by the New Mexico Institute of Mining and Technology to estimate potential costs incurred during the implementation of a real-world commercial-scale carbon storage project. Scenario analysis was implemented in which different operational and cost attributes were varied and the associated cost implications observed. Key results data and project cost summary metrics, first-year breakeven price of CO2 ($/tonne) and net present value (NPV), are presented for base and alternative cases. Output provides a unique perspective for project stakeholders towards evaluating the influence of different operational strategies and financing approaches on overall project cost and financial viability.

carbon storage↗
DOE OSTI2025

Adaptation and Plasticity of Nannochloropsis sp. in Response to Seasonal and Geographic Climate Variation

Phytoplankton respond to their environment through genetic adaptation and plasticity to maintain fitness. This poses challenges when growing microalgae for industrial applications because, inherently, outdoor mass cultivation may lead to adaptations that alter desirable phenotypic traits and environmental niches. Here, we used common garden experiments to quantify the plasticity and adaptive responses to seasonal and geographic climate variation of Nannochloropsis, a microalga commonly used in biotechnology. An initially monoclonal strain was grown outdoors across four locations in Hawaii, Texas, California, and New Mexico. Following 17 and 22 months of cultivation outdoors, we collected samples during winter and summer, respectively, and we compared strains' growth from the four sites across temperature and light gradients in the laboratory. Despite hundreds of generations of exposure to divergent climates, with ~20°C and three-fold differences in daily light intensity, strains showed only minor differences in performance. Thermal performance varied more among seasons than sites, whereas light performance varied with both season and site. Our study indicates that Nannochloropsis exhibits broad plasticity in response to light and temperature, which may inhibit genetic adaptation in space or time. Highly variable field conditions, with daily and seasonal climate fluctuations, may favor plasticity and prevent the rapid adaptation often seen in laboratory studies of microorganisms in constant environments.

common garden experiment↗
DOE OSTI2025

Thermal Characterization and Exhumation of Northwest San Juan Basin Area, NM

The San Juan Basin (SJB), located in southwestern Colorado northwestern New Mexico, containing Paleozoic through middle Cenozoic strata, formed as a partitioned basin approximately 80 Ma in response to the Laramide orogeny. The SJB is a commercially mature, petroleum-producing basin, and currently being explored for CCUS and geothermal resources. Modern heat flow within the SJB is spatially variable with higher geothermal gradients in its northern and eastern portions. The temporal history of the basin thermal history is essential for understanding capacity for carbon storage and geothermal exploration. We present thermochronometric analyses of two surface and two subsurface samples to constrain spatial-temporal thermal evolution of the northwestern San Juan Basin. Apatite (U-Th)/He thermochronometric analyses were conducted on Cliff House and Kirtland Formation outcrops and subsurface samples of the Ojo Alamo and Pictured Cliffs Formations from a DOE funded, CCUS project pilot-well. In addition, vitrinite reflectance data and 1D basin modelling constrain possible time-temperature pathways of the samples in an area where no previous studies have constrained the uplift/exhumation of the Hogback Monocline using thermochronometry. Modeling suggests that elevated subsurface temperatures developed simultaneously with regional late Oligiocene volcanism in the San Juan Volcanic field and timing of maximum burial in the SJB. Late Miocene to Pliocene cooling/exhumation through the apatite (U-Th)/He partial retention zone support stratigraphic evidence of the Colorado Plateau uplift, possibly regional epeirogenic uplift driven by mantle processes.

02 PETROLEUM↗
DOE OSTI2025

Whole metagenome sequencing and 16S rRNA gene amplicon analyses reveal the complex microbiome responsible for the success of enhanced in-situ reductive dechlorination (ERD) of a tetrachloroethene-contaminated Superfund site

The North Railroad Avenue Plume (NRAP) Superfund site in New Mexico, USA exemplifies successful chlorinated solvent bioremediation. NRAP was the result of leakage from a dry-cleaning that operated for 37 years. The presence of tetrachloroethene biodegradation byproducts, organohalide respiring genera (OHRG), and reductive dehalogenase (rdh) genes detected in groundwater samples indicated that enhanced reductive dechlorination (ERD) was the remedy of choice. This was achieved through biostimulation by mixing emulsified vegetable oil into the contaminated aquifer. This report combines metagenomic techniques with site monitoring metadata to reveal new details of ERD. DNA extracts from groundwater samples collected prior to and at four, 23 and 39 months after remedy implementation were subjected to whole metagenome sequencing (WMS) and 16S rRNA gene amplicon (16S) analyses. The response of the indigenous NRAP microbiome to ERD protocols is consistent with results obtained from microcosms, dechlorinating consortia, and observations at other contaminated sites. WMS detects three times as many phyla and six times as many genera as 16S. Both techniques reveal abundance changes in Dehalococcoides and Dehalobacter that reflect organohalide form and availability. Methane was not detected before biostimulation but appeared afterwards, corresponding to an increase in methanogenic Archaea. Assembly of WMS reads produced scaffolds containing rdh genes from Dehalococcoides, Dehalobacter, Dehalogenimonas, Desulfocarbo, and Desulfobacula. Anaerobic and aerobic cometabolic organohalide degrading microbes that increase in abundance include methanogenic Archaea, methanotrophs, Dechloromonas, and Xanthobacter, some of which contain hydrolytic dehalogenase genes. Aerobic cometabolism may be supported by oxygen gradients existing in aquifer microenvironments or by microbes that produce O 2 via microbial dismutation. The NRAP model for successful ERD is consistent with the established pathway and identifies new taxa and processes that support this syntrophic process. This project explores the potential of metagenomic tools (MGT) as the next advancement in bioremediation.

59 BASIC BIOLOGICAL SCIENCES↗