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DOE OSTI2025

Observed and Imputed Volumetric Soil Water Content Timeseries for the New Mexico Elevation Gradient

Reliable soil water content (SWC) data are essential for understanding dryland ecosystem dynamics, but high-frequency SWC sensors often fail, creating gaps in critical datasets. To address this, we developed a Bayesian mixture model that imputes missing SWC using both linear interpolation and an ecosystem water balance model (SOILWAT2), tested across six AmeriFlux eddy covariance tower sites in the New Mexico Elevation Gradient, demonstrating its effectiveness in reconstructing SWC patterns while providing insights into the factors driving SWC variability. Daily volumetric soil water content (SWC) data are provided as csv-formatted spreadsheets for the six AmeriFlux sites (US-Seg, US-Ses, US-Wjs, US-Mpi, US-Vcp, and US-Vcs). For each site there is an observed SWC file (site_SWC_gapfill.csv) and a file that contains imputed SWC (imputed_SWC_site.csv). The observed SWC files contain temperature corrected sensor values, tower precipitation data, as well as outputs from SOILWAT2 simulations that were used to impute SWC. The imputed files contain the original observed SWC values and the imputed missing SWC values. When SWC was missing from the original data, the missing value was imputed based on the Bayesian imputation mixture model. The posterior mean of all imputed values is reported as "mean_X". When the observed SWC was NOT missing, mean_X = observed SWC value (original data). The standard deviation, 2.5th percentile and the 97.5th percentile for the imputed values are also reported in the imputed files. There are readme text files for each file type explaining the contents of each column.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Observations of ozone, acyl peroxy nitrates, and their precursors during summer 2019 at Carlsbad Caverns National Park, New Mexico

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Observations of ozone, acyl peroxy nitrates, and their precursors during summer 2019 at Carlsbad Caverns National Park, New Mexico

Carlsbad Caverns National Park (CAVE) is located in southeastern New Mexico and is adjacent to the Permian Basin, one of the most productive oil and natural gas (O&G) production regions in the United States. Since 2018, ozone (O 3 ) at CAVE has frequently exceeded the 70 ppbv 8-hour National Ambient Air Quality Standard. We examine the influence of regional emissions on O 3 formation using observations of O 3 , nitrogen oxides (NO x = NO + NO 2 ), a suite of volatile organic compounds (VOCs), peroxyacetyl nitrate (PAN), and peroxypropionyl nitrate (PPN). Elevated O 3 and its precursors are observed when the wind is from the southeast, the direction of the Permian Basin. We identify 13 days during the July 25 to September 5, 2019 study period when the maximum daily 8-hour average (MDA8) O 3 exceeded 65 ppbv; MDA8 O 3 exceeded 70 ppbv on 5 of these days. The results of a positive matrix factorization (PMF) analysis are used to identify and attribute source contributions of VOCs and NO x . On days when the winds are from the southeast, there are larger contributions from factors associated with primary O&G emissions; and, on high O 3 days, there is more contribution from factors associated with secondary photochemical processing of O&G emissions. The observed ratio of VOCs to NO x is consistently high throughout the study period, consistent with NO x -limited O 3 production. Finally, all high O 3 days coincide with elevated acyl peroxy nitrate abundances with PPN to PAN ratios > 0.15 ppbv ppbv -1 indicating that anthropogenic VOC precursors, and often alkanes specifically, dominate the photochemistry. Implications: The results above strongly indicate NO x -sensitive photochemistry at Carlsbad Caverns National Park indicating that reductions in NO x emissions should drive reductions in O 3 . However, the NO x -sensitivity is largely driven by emissions of NO x into a VOC-rich environment, and a high PPN:PAN ratio and its relationship to O 3 indicate substantial influence from alkanes in the regional photochemistry. Thus, simultaneous reductions in emissions of NO x and non-methane VOCs from the oil and gas sector should be considered for reducing O 3 at Carlsbad Caverns National Park. Reductions in non-methane VOCs will have the added benefit of reducing formation of other secondary pollutants and air toxics.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

How New Mexico Leveraged a COVID-19 Case Forecasting Model to Preemptively Address the Healthcare Needs of the State: Quantitative Analysis

Prior to the COVID-19 pandemic, US hospitals relied on static projections of future trends for long-term planning and were only beginning to consider forecasting methods for short-term planning of staffing and other resources. With the overwhelming burden imposed by COVID-19 on the health care system, an emergent need exists to accurately forecast hospitalization needs within an actionable timeframe. Our goal was to leverage an existing COVID-19 case and death forecasting tool to generate the expected number of concurrent hospitalizations, occupied intensive care unit (ICU) beds, and in-use ventilators 1 day to 4 weeks in the future for New Mexico and each of its five health regions. We developed a probabilistic model that took as input the number of new COVID-19 cases for New Mexico from Los Alamos National Laboratory’s COVID-19 Forecasts Using Fast Evaluations and Estimation tool, and we used the model to estimate the number of new daily hospital admissions 4 weeks into the future based on current statewide hospitalization rates. The model estimated the number of new admissions that would require an ICU bed or use of a ventilator and then projected the individual lengths of hospital stays based on the resource need. By tracking the lengths of stay through time, we captured the projected simultaneous need for inpatient beds, ICU beds, and ventilators. We used a postprocessing method to adjust the forecasts based on the differences between prior forecasts and the subsequent observed data. Thus, we ensured that our forecasts could reflect a dynamically changing situation on the ground. Forecasts made between September 1 and December 9, 2020, showed variable accuracy across time, health care resource needs, and forecast horizon. Forecasts made in October, when new COVID-19 cases were steadily increasing, had an average accuracy error of 20.0%, while the error in forecasts made in September, a month with low COVID-19 activity, was 39.7%. Across health care use categories, state-level forecasts were more accurate than those at the regional level. Although the accuracy declined as the forecast was projected further into the future, the stated uncertainty of the prediction improved. Forecasts were within 5% of their stated uncertainty at the 50% and 90% prediction intervals at the 3- to 4-week forecast horizon for state-level inpatient and ICU needs. However, uncertainty intervals were too narrow for forecasts of state-level ventilator need and all regional health care resource needs. Real-time forecasting of the burden imposed by a spreading infectious disease is a crucial component of decision support during a public health emergency. Our proposed methodology demonstrated utility in providing near-term forecasts, particularly at the state level. This tool can aid other stakeholders as they face COVID-19 population impacts now and in the future.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

2022 Annual Site Environmental Report for Sandia National Laboratories, Albuquerque, New Mexico

Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration. The National Nuclear Security Administration’s Sandia Field Office administers the contract and oversees contractor operations at Sandia National Laboratories, New Mexico. Activities at the site support research and development programs with a wide variety of national security missions, resulting in technologies for nonproliferation, homeland security, energy and infrastructure, and defense systems and assessments. The U.S. Department of Energy and its management and operating contractor are committed to safeguarding the environment, assessing sustainability practices, and ensuring the validity and accuracy of the monitoring data presented in this annual site environmental report. This report summarizes the environmental protection and monitoring programs in place at Sandia National Laboratories, New Mexico, during calendar year 2022. Environmental topics include cultural resource management, chemical management, air quality, ecology, environmental restoration, oil storage, site sustainability, terrestrial surveillance, waste management, water quality, and implementation of the National Environmental Policy Act. This report is prepared in accordance with and as required by DOE O 231.1B, Admin Change 1, Environment, Safety and Health Reporting, and has been approved for public distribution.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2024

2023 Annual Site Environmental Report for Sandia National Laboratories, Albuquerque, New Mexico

Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the U.S. Department of Energy’s National Nuclear Security Administration. The National Nuclear Security Administration’s Sandia Field Office administers the contract and oversees contractor operations at Sandia National Laboratories, New Mexico. Activities at the site support research and development programs with a wide variety of national security missions, resulting in technologies for nonproliferation, homeland security, energy and infrastructure, and defense systems and assessments. The U.S. Department of Energy and its management and operating contractor are committed to safeguarding the environment, assessing sustainability practices, and ensuring the validity and accuracy of the monitoring data presented in this annual site environmental report. This report summarizes the environmental protection and monitoring programs in place at Sandia National Laboratories, New Mexico, during calendar year 2023. Environmental topics include cultural resource management, chemical management, air quality, ecology, environmental restoration, oil storage, site sustainability, terrestrial surveillance, waste management, water quality, and implementation of the National Environmental Policy Act. This report is prepared in accordance with and as required by DOE O 231.1B, Admin Change 1, Environment, Safety and Health Reporting, and has been approved for public distribution.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Sandia National Laboratories Annual Site Environmental Report, 2019: New Mexico

Sandia National Laboratories is a multimission laboratory managed and operated by National Technology & Engineering Solutions of Sandia, LLC, a wholly owned subsidiary of Honeywell International Inc., for the United States Department of Energy (DOE) National Nuclear Security Administration. The National Nuclear Security Administration’s Sandia Field Office administers the contract and oversees contractor operations at Sandia National Laboratories, New Mexico. Activities at the site support research and development programs with a wide variety of national security missions, resulting in technologies for nonproliferation, homeland security, energy and infrastructure, and defense systems and assessments. DOE and its management and operating contractor are committed to safeguarding the environment, assessing sustainability practices, and ensuring the validity and accuracy of the monitoring data presented in this Annual Site Environmental Report. This report summarizes the environmental protection and monitoring programs in place at Sandia National Laboratories, New Mexico, during calendar year 2019. Environmental topics include air quality, ecology, environmental restoration, oil storage, site sustainability, terrestrial surveillance, waste management, water quality, and implementation of the National Environmental Policy Act. This report is prepared in accordance with and as required by DOE O 231.1B, Admin Change 1, Environment, Safety, and Health Reporting, and has been approved for public distribution.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2026

An ICP-OES method for the precise and accurate quantification of rare earth elements in natural water: A comparative study from mine waste sites in New Mexico, USA

Inductively coupled plasma techniques such as ICP-OES and ICP-MS are routinely used to determine the concentrations of rare earth elements (REE) in water samples. However, their performance for the determination of REE concentration in mine drainage waters from epithermal vein and porphyry copper mining districts has not been evaluated extensively. In this work, we develop an REE analysis method on an Agilent 5900 ICP-OES instrument and assess the accuracy and precision for the quantification of REE in the natural waters collected from mine adits and an acid seep of mine sites in the Steeple Rock and Hillsboro mining districts, New Mexico, USA. The total REE concentrations in the water samples were measured using the methods we developed for both ICP-OES and ICP-MS. The power of the new ICP-OES method lies in routine analysis of μg/L level concentrations normally analyzed using ICP-MS, including a U.S. Geological Survey standard reference sample, laboratory blank samples spiked with a National Institute of Standards and Technology traceable standard, and surface water samples from mine waste sites. This ICP-OES method achieves low quantification limits ranging from 0.2 to 5 μg/L and excellent analytical accuracy and precision for REE analysis. The precision of light (La-Gd) and heavy (Tb-Lu) REE analysis using this method are better than 5% at average concentrations above 5 ± 4 μg/L and 3 ± 2 μg/L, respectively, and 3% at average concentrations above 10 ± 9 μg/L and 5 ± 4 μg/L, respectively. This method also shows excellent sensitivity and reproducibility for our laboratory and field samples.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2025

The potential for New Mexico basalts to sequester CO 2 with a focus on critical element mobility

This study evaluates the potential of New Mexico basaltic rocks and mafic mine waste for CO₂ sequestration via mineral carbonation. Batch experiments up to 200 days at 40°C simulated CO₂-bearing fluid interactions with various crushed basaltic materials at different grain sizes. Results showed that 70–80% of injected CO₂ was mineralized, with the finest grain sizes showing the most rapid and effective drawdown. The experiments also assessed the mobility of critical metals (Cu, Ni, Zn, Co), revealing trends tied to mineral dissolution and secondary mineral formation. The findings support the dual potential of mine waste for CO₂ sequestration and critical element recovery, informing future carbon capture and resource upcycling strategies.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2024

Water Resource Assessment In The New Mexico Permian Basin: BLM 2023 Assessment Report

The Permian Basin is the highest producing oil field in the United States and is comprised of three component basins including; the Midland Basin, Delaware Basin and the Marfa Basin. This report describes the work conducted by Sandia National Laboratories (SNL) for the Bureau of Land Management (BLM) to investigate the occurrence of usable water (quality, and depth to water) in the Delaware Sub-basin of the Permian Basin. High Production Areas (HPAs) were identified for the region based on Reasonable Foreseeable Development Scenario (RFD) published by New Mexico Tech University. HPAs were established based on potential for future development of oil reserves. The study was initiated by the BLM-Carlsbad Field Office (CFO) based on concerns that special protections for groundwater in these HPAs may be warranted. A combination of analysis of existing data and field work to collect new data for analysis were used to complete the investigation objectives. This study summarizes the most recent analyses in an ongoing project and builds on previously completed work as listed in Table 1. Advancements in directional drilling and well completion technologies have resulted in an exponential growth in the use of hydraulic fracturing for oil and gas extraction in the Permian Basin. Within the New Mexico portion of the Delaware Sub-basin, water demand to complete each hydraulically fractured well is estimated to average 7.3 acre-feet (2.4 million gallons), resulting in 30 billion barrels of water over the life of the plan or 1.5 billion barrels per year. This rising demand is creating concern for the regions ability to provide the necessary water in a manner that fulfills BLM’s role of protecting human health and the environment while sustainably meeting the needs of various water users in the region. This report documents water-level and water chemistry baselines to aid the BLM in understanding the regional water supply dynamics under various management, policy, and growth scenarios and to pre-emptively identify risks to water sustainability.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Tracking natural CO 2 migration through a sandstone aquifer using Sr, U and C isotopes: Chimayó, New Mexico, USA

The geochemical and isotopic characteristics of groundwaters in Chimayó, New Mexico, reflect processes that affect water quality in the Tesuque Aquifer, which overlies a leaking natural CO 2 source in a structurally complex region. In this study, select isotopes (δ 13 C, 87 Sr/ 86 Sr, 234 U/ 238 U) are applied to groundwaters to better understand CO 2 transport mechanisms and related water-rock interactions that impact Chimayó groundwater. Carbon stable isotope ratios of dissolved inorganic carbon (DIC; δ 13 CDIC = -15.10‰ to 4.50‰) identify a distinct source of upward-migrating CO 2 that interacts with the groundwater. Additionally, groundwater 87 Sr/ 86 Sr compositions (0.7098 to 0.7154) reflect intrusion of varying amounts of saline water associated with the high CO 2 source, while 234 U/ 238 U ratios corroborate presence of deep groundwater and suggest impacts from distinctive natural uranium sources are affecting groundwater. Previous work proposed two CO 2 transport mechanisms at the site: (1) dissolved in deep brine that underlies the aquifer and (2) in the gas phase; this study uses isotope mixing models to identify wells that are affected by these CO 2 transport mechanisms and demonstrates that both transport mechanisms are associated with impaired groundwaters. Overall, this study demonstrates that applying multiple isotope systems (δ 13 CDIC, 87 Sr/ 86 Sr, 234 U/ 238 U) is a dynamic tool for identifying and measuring the impact of CO 2 leakage from a sequestration site.

58 GEOSCIENCES↗

DOE OSTI2021

New Mexico Small Business Assistance Program Pairs Inventors with National Labs

NMSBA provides New Mexico small businesses facing technical challenges access to the unique expertise and capabilities of Los Alamos and Sandia national laboratories. At no cost to the business, small businesses can seek assistance from lab scientists and engineers to solve challenges and overcome barriers to company success.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2021

GeoThermalCloud framework for fusion of big data and multi-physics models in Nevada and Southwest New Mexico

Our GeoThermalCloud framework is designed to process geothermal datasets using a novel toolbox for unsupervised and physics-informed machine learning called SmartTensors. More information about GeoThermalCloud can be found at the GeoThermalCloud GitHub Repository. More information about SmartTensors can be found at the SmartTensors Github Repository and the SmartTensors page at LANL.gov. Links to these pages are included in this submission. GeoThermalCloud.jl is a repository containing all the data and codes required to demonstrate applications of machine learning methods for geothermal exploration. GeoThermalCloud.jl includes: - site data - simulation scripts - jupyter notebooks - intermediate results - code outputs - summary figures - readme markdown files GeoThermalCloud.jl showcases the machine learning analyses performed for the following geothermal sites: - Brady: geothermal exploration of the Brady geothermal site, Nevada - SWNM: geothermal exploration of the Southwest New Mexico (SWNM) region - GreatBasin: geothermal exploration of the Great Basin region, Nevada Reports, research papers, and presentations summarizing these machine learning analyses are also available and will be posted soon.

15 GEOTHERMAL ENERGY↗

DOE OSTI2022

An Analysis of PNM's Renewable Reserve Requirements to Meet New Mexico's Decarbonization Goals

Over the next three years, the Public Service Company of New Mexico (PNM) plans to increase utility-scale solar photovoltaic (PV) capacity from today’s roughly 330MW to about 1600MW. This massive increase in variable generation—from about 15% to 75% of peak load—will require changes in how PNM operates their system. We characterize the 5 and 30-minute solar and wind forecast errors that the system is likely to experience in order to determine the level of reserves needed to counteract such events. Our focus in this study is on negative forecast error (in other words, shortfalls relative to forecast) – whereas excess variable generation can be curtailed if needed, a shortfall must be compensated for to avoid loss of load. Calculating forecast error requires the use of the same forecasting methods that PNM uses or a reasonable approximation thereof. For wind, we use a persistence forecast on actual 5-minute 2019 wind output data (scaled up to reflect the amount of wind capacity planned for 2025). For solar, we use a formula incorporating the clear sky index (CSI) for the forecast. As the solar on the grid now is a small fraction of what is planned for 2025, we generated 5-minute solar data using 2019 weather inputs. We find that to handle 99.9% of the 5-minute negative forecast errors, a maximum of 275MW of variable generation reserve during daylight hours, and a maximum of 75MW during non-daylight hours, should be sufficient. Note that this variable generation reserve is an additional reserve category that specifies reserves over and above what are currently carried for contingency reserve. This would require a significant increase in reserve relative to what PNM currently carries or can call upon from other utilities per reserve sharing agreements. This variable generation reserve specification may overestimate the actual level needed to deal with PNM’s planned variable generation in 2025. The forecasting methodologies used in this study likely underperform PNM’s forecasting – and better forecasting allows for less reserve. To obtain more precise estimates, it is necessary to consider load and use the same forecasting inputs and methods used by PNM.

14 SOLAR ENERGY↗

DOE OSTI2022

New Mexico's Clean Energy Jobs Potential Through 2030

According to the U.S. Census Bureau, New Mexico had 1,325,163 people in its working population (15 to 64 years of age) in 2019. The graphs below show solar photovoltaic (PV), land-based wind, battery energy storage (BES), and energy efficiency job estimates in 2020, 2025, and 2030. These job estimates do not represent net job creation. Rather, they represent the size of the workforce required to achieve projected national deployment levels of each technology for 2025 and 2030 if the state captures the same proportion of jobs in the sector as it did in 2020.

clean energy↗

DOE OSTI2025

Per- and polyfluoroalkyl substances (PFAS) in fish collected from the Rio Grande and reservoirs in northern New Mexico

Per- and polyfluoroalkyl substances (PFAS) are a group of industrial and commercial chemicals widely used throughout the world due to their beneficial chemical properties. Because of their widespread use, their chemical stability, and their ability to be transported over long distances through atmospheric deposition and movement through waterways, PFAS are found throughout most aquatic ecosystems; yet large sampling gaps exist among reservoir and river ecosystems in the desert southwest of the United States. In this study, we examine PFAS concentrations in the tissue of fish (catfish [channel and blue], common carp, smallmouth bass, northern pike, walleye, white crappie and white sucker) collected in northern New Mexico, including examining PFAS composition and concentration relative to trophic level distribution. We collected fish from two man-made reservoirs and from the Rio Grande. We then collected muscle and liver tissues from fish specimens, which were screened for 39 PFAS compounds. We detected PFAS compounds in most fish tissue sampled, including the biomagnification of PFAS compounds within liver samples, with PFOS concentrations ranged from 1.13 to 350.1 (64.4 average) times higher in the liver samples compared to muscle samples. Most PFAS concentrations within muscle samples were within the range of atmospheric transportation previously reported and average tissue concentrations of PFAS were calculated to be 2.02 ± 1.81 ng g -1 . Using stable isotopes as a predictor of trophic-foraging exposure and PFAS concentrations, we noted a correlation between enriched δ 15 N values, which had higher perfluorodecanoic acid concentrations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Hazmat Incident in New Mexico: Sulfur Dioxide Alarm

Sandia National Laboratories (SNL) is a multimission laboratory located in Albuquerque, New Mexico, and is one of three National Nuclear Security Administration research and development laboratories located in the United States. Recently, SNL’s Emergency Response Team (ERT) responded to an incident involving a sulfur dioxide (SO2)-fixed monitor, setting off the alarm inside a laboratory and in the adjacent hallway. The potential sources for the alarm were various experiments involving batteries and an uninterrupted power supply (UPS) in the immediate area.

99 GENERAL AND MISCELLANEOUS↗

DOE OSTI2024

iButton snow-ground interface temperature measurements in Los Alamos, New Mexico from 2023-2024

Snow/ground interface temperature measurements were collected at two sites in Los Alamos, New Mexico. Data were collected from November 29, 2023 to April 8, 2024 using iButton Link DS1921G-F5# Thermochron miniature temperature sensors (https://www.ibuttonlink.com/products/ds1921g). These sensors are a cost-efficient way to collect snowpack temperatures at a higher spatial resolution than what is normally achieved. iButton data were collected every 3 hours from a total of 19 iButtons. iButtons were placed in pairs, with one iButton placed at the ground surface and another buried 1 - 5 cm below the ground surface. One buried iButton did not successfully collect data, and therefore was excluded from this dataset. Data were collected throughout the snow cover season so that snowpack characteristics could be derived using the temperature data. Specifically, this dataset was used as a validation source for a novel machine learning approach to estimating snow depth (see related publication). Sensors were placed in areas with bare ground or minimal grass coverage, located away from any large vegetation. At Site A (TA51), manual snow depths were collected as validation data. These measurements were taken next to iButtons periodically throughout the winter, and notes on other precipitation types were also recorded. At Site B (TA6 Meteorological Station), a nearby sensor collected snow depths throughout the winter. This dataset contains one *.csv file of snow/ground interface temperatures at two sites, one *.csv file of manually collected snow depths, and one *.kml file of sensor locations. The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic) was a 15-year research effort (2012-2027) 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↗