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Lawrence Livermore National Laboratory (LLNL) collects effluent samples from its sewer outfall at the B196 Sewer Monitoring Station (SMS). Effluent flow-proportional composite samples are collected at the SMS on a daily (midnight-to-midnight), weekly (Thursday through Wednesday), and “monthly” (composited from daily) basis; effluent grab samples are also collected each month at that same location.
Model Evaluation Well ER-5-5 was drilled for the U.S. Department of Energy, National Nuclear Security Administration Nevada Site Office in support of Nevada Environmental Management Operations at the Nevada National Security Site (formerly known as the Nevada Test Site). The well was drilled in July and August 2012 as part of a model evaluation well program in the Frenchman Flat area of Nye County, Nevada. The primary purpose of the well was to provide detailed geologic, hydrogeologic, chemical, and radiological data that can be used to test and build confidence in the applicability of the Frenchman Flat Corrective Action Unit flow and transport models for their intended purpose. In particular, this well was designed to obtain data to evaluate the uncertainty in model forecasts of contaminant migration from the upgradient underground nuclear test MILK SHAKE, conducted in Emplacement Hole U-5k in 1968, which were considered to be uncertain due to the unknown extent of a basalt lava-flow aquifer present in this area. Well ER-5-5 is expected to provide information to refine the Phase II Frenchman Flat hydrostratigraphic framework model, if necessary, as well as to support future groundwater flow and transport modeling. The 31.1-centimeter (cm) diameter hole was drilled to a total depth of 331.3 meters (m). The completion string, set at the depth of 317.2 m, consists of 16.8-cm stainless-steel casing hanging from 19.4-cm carbon-steel casing. The 16.8-cm stainless-steel casing has one slotted interval open to the basalt lava-flow aquifer and limited intervals of the overlying and underlying alluvial aquifer. A piezometer string was also installed in the annulus between the completion string and the borehole wall. The piezometer is composed of 7.3-cm stainless-steel tubing suspended from 6.0-cm carbon-steel tubing. The piezometer string was landed at 319.2 m, to monitor the basalt lava-flow aquifer. Data collected during and shortly after hole construction include composite drill cuttings samples collected every 3.0 m, various geophysical logs, preliminary water quality measurements, and water-level measurements. The well penetrated 331.3 m of Quaternary–Tertiary alluvium, including an intercalated layer of saturated basalt lava rubble. No well development or hydrologic testing was conducted in this well immediately after completion; however, a preliminary water level was measured in the piezometer string at the depth of 283.4 m on September 25, 2012. No tritium above the minimum detection limit of the field instruments was detected in this hole. Future well development, sampling, and hydrologic testing planned for this well will provide more accurate hydrologic information for this site. The stratigraphy, general lithology, and water level were as expected, though the expected basalt lava-flow aquifer is basalt rubble and not the dense, fractured lava as modeled. The lack of tritium transport is likely due to the difference in hydraulic properties of the basalt lava-flow rubble encountered in the well, compared to those of the fractured aquifer used in the flow and transport models.
Model Evaluation Well ER-11-2 was drilled for the U.S. Department of Energy, National Nuclear Security Administration Nevada Site Office in support of Nevada Environmental Management Operations at the Nevada National Security Site (formerly known as the Nevada Test Site). The well was drilled in August 2012 as part of a model evaluation program in the Frenchman Flat area of Nye County, Nevada. The primary purpose of the well was to provide detailed geologic, hydrogeologic, chemical, and radionuclide data that can be used to test and build confidence in the applicability of the Frenchman Flat Corrective Action Unit flow and transport models for their intended purpose. In particular, this well was designed to provide data to evaluate the uncertainty in model forecasts of contaminant migration from the upgradient underground nuclear test PIN STRIPE, conducted in borehole U-11b in 1966. Well ER-11-2 will provide information that can be used to refine the Phase II Frenchman Flat hydrostratigraphic framework model if necessary, as well as to support future groundwater flow and transport modeling. The main 31.1-centimeter (cm) hole was drilled to a total depth of 399.6 meters (m). A completion casing string was not set in Well ER-11-2. However, a piezometer string was installed in the 31.1-cm open hole. The piezometer is composed of 7.3-cm stainless-steel tubing hung on 6.0-cm carbon-steel tubing via a crossover sub. The piezometer string was landed at 394.5 m, for monitoring the lower tuff confining unit. Data collected during and shortly after hole construction include composite drill cuttings samples collected every 3.0 m, various geophysical logs, water quality (including tritium and other test-related radionuclides) measurements, and water level measurements. The well penetrated 42.7 m of Quaternary and Tertiary alluvium and 356.9 m of Tertiary volcanic rock. The water-level measured in the piezometer string on September 25, 2012, was 353.8 m below ground surface. No tritium above levels detectable by field methods were encountered in this hole. No well development or hydrologic testing was conducted in this well immediately after completion, and future well development, sampling, and hydrologic testing planned for this well will be limited due to the diameter of the piezometer string. The stratigraphy, general lithology, and the water level are as expected, but the section of geology encountered is higher than expected due to faulting. No tritium above the minimum detection limit of the field equipment was detected because the target aquifer (the Topopah Spring aquifer) at Well ER-11-2 is structurally higher than expected and thus unsaturated.
Remote sensing, or Earth Observation (EO), is increasingly used to understand Earth system dynamics and create continuous and categorical maps of biophysical properties and land cover, especially based on recent advances in machine learning (ML). ML models typically require large, spatially explicit training datasets to make accurate predictions. Training data (TD) are typically generated by digitizing polygons on high spatial-resolution imagery, by collecting in situ data, or by using pre-existing datasets. TD are often assumed to accurately represent the truth, but in practice almost always have error, stemming from (1) sample design, and (2) sample collection errors. The latter is particularly relevant for image-interpreted TD, an increasingly commonly used method due to its practicality and the increasing training sample size requirements of modern ML algorithms. TD errors can cause substantial errors in the maps created using ML algorithms, which may impact map use and interpretation. Despite these potential errors and their real-world consequences for map-based decisions, TD error is often not accounted for or reported in EO research. Here we review the current practices for collecting and handling TD. We identify the sources of TD error, and illustrate their impacts using several case studies representing different EO applications (infrastructure mapping, global surface flux estimates, and agricultural monitoring), and provide guidelines for minimizing and accounting for TD errors. To harmonize terminology, we distinguish TD from three other classes of data that should be used to create and assess ML models: training reference data, used to assess the quality of TD during data generation; validation data, used to iteratively improve models; and map reference data, used only for final accuracy assessment. We focus primarily on TD, but our advice is generally applicable to all four classes, and we ground our review in established best practices for map accuracy assessment literature. EO researchers should start by determining the tolerable levels of map error and appropriate error metrics. Next, TD error should be minimized during sample design by choosing a representative spatio-temporal collection strategy, by using spatially and temporally relevant imagery and ancillary data sources during TD creation, and by selecting a set of legend definitions supported by the data. Furthermore, TD error can be minimized during the collection of individual samples by using consensus-based collection strategies, by directly comparing interpreted training observations against expert-generated training reference data to derive TD error metrics, and by providing image interpreters with thorough application-specific training. We strongly advise that TD error is incorporated in model outputs, either directly in bias and variance estimates or, at a minimum, by documenting the sources and implications of error. TD should be fully documented and made available via an open TD repository, allowing others to replicate and assess its use. To guide researchers in this process, we propose three tiers of TD error accounting standards. Finally, we advise researchers to clearly communicate the magnitude and impacts of TD error on map outputs, with specific consideration given to the likely map audience.
We found that the production of Z bosons is studied in the dimuon and dielectron decay channels in PbPb and pp collisions at √s NN =2.76 TeV, using data collected by the CMS experiment at the LHC. The PbPb data sample corresponds to an integrated luminosity of about 166 μb -1 , while the pp data sample collected in 2013 at the same nucleon-nucleon centre-of-mass energy has an integrated luminosity of 5.4 pb -1 . The Z boson yield is measured as a function of rapidity, transverse momentum, and collision centrality. The ratio of PbPb to pp yields, scaled by the number of inelastic nucleon-nucleon collisions, is found to be 1.06 ± 0.05 (stat) ± 0.08 (syst) in the dimuon channel and 1.02 ± 0.08 (stat) ± 0.15 (syst) in the dielectron channel, for centrality-integrated Z boson production. Finally, this binary collision scaling is seen to hold in the entire kinematic region studied, as expected for a colourless probe that is unaffected by the hot and dense QCD medium produced in heavy ion collisions.
The Building Restoration Operations Optimization Model (BROOM) software system, developed by Sandia National Laboratories, is a comprehensive system designed to improve the efficiency and quality of sample collection, data management, and interpretation. Currently, BROOM is capable of supporting sampling efforts at facilities contaminated with chemical and/or biological agents. BROOM provides advanced visualization, analysis, and sampling optimization functions, which speed up the sampling process and lower the associated sampling costs. BROOM enables the user to develop a defensible sampling plan based on statistical analysis of sample results. BROOM consists of two applications: one that runs on a hand-held PDA and one that runs on a Windows desktop/laptop. This document covers the installation and basic operation of both components and provides examples of the application of these tools during and following an actual field exercise.
The U.S. Department of Energy (DOE) and the Sun Grant Initiative began the Regional Feedstock Partnership (RFP) in 2007 primarily to address information gaps associated with sustainably and reliably producing a billion-tons of biomass annually by the year 2030 for the U.S. bioenergy industry. The culmination of these efforts were reported in the Sun Grant/DOE Regional Feedstock Partnership Final Technical Report. The same biomass resources used to support these yield and sustainability efforts included analytical characterization data representing biomass quality. Considerable effort has been put into collection, harmonization, and archival of the analytical data, metadata, and physical samples associated with the thousands of samples collected from the RFP field trials. This data provides a unique opportunity to understand the impacts of agronomic and forest production practices, as well as environmental factors, on biomass material attributes relevant to bioenergy production. To more efficiently develop these relationships, this workshop was held to bring together the experts who conducted the RFP field trials and the biomass attribute data analysts. The objectives of the workshop included the following: • Enable face-to-face interactions with field trial experts, allowing for insights into the species and field trials themselves that are not obvious looking at data alone • Fill in metadata and analytical gaps from the RFP for future analyses • Share results from analysis of RFP biomass properties for each species along with associated field experiment observations/results • Discuss the potential to develop biomass quality maps • Discuss preparation of peer-reviewed publications for each species • Discuss outlines for a comprehensive summary report on the evaluation of RFP biomass material attributes for quality determination, focusing on the results of peer-reviewed publications and analysis of compiled RFP biomass attribute datasets
Natural organic matter (NOM) is composed of a highly complex mixture of thousands of organic compounds which, historically, proved difficult to characterize. However, to understand the thermodynamic and kinetic controls on greenhouse gas (carbon dioxide [CO 2 ] and methane [CH 4 ]) production resulting from the decomposition of NOM, a molecular-level characterization coupled with microbial proteome analyses is necessary. Further, climate and environmental changes are expected to perturb natural ecosystems, potentially upsetting complex interactions that influence both the supply of organic matter substrates and the microorganisms performing the transformations. A detailed molecular characterization of the organic matter, microbial proteomics, and the pathways and transformations by which organic matter is decomposed will be necessary to predict the direction and magnitude of the effects of environmental changes. This article describes a methodological throughput for comprehensive metabolite characterization in a single sample by direct injection Fourier transform ion cyclotron resonance mass spectrometry (FTICR-MS), gas chromatography mass spectrometry (GC-MS), nuclear magnetic resonance (NMR) spectroscopy, liquid chromatography mass spectrometry (LC-MS), and proteomics analysis. Furthermore, this approach results in a fully-paired dataset which improves statistical confidence for inferring pathways of organic matter decomposition, the resulting CO 2 and CH 4 production rates, and their responses to environmental perturbation. Herein we present results of applying this method to NOM samples collected from peatlands; however, the protocol is applicable to any NOM sample (e.g., peat, forested soils, marine sediments, etc.).
Abstract. Reports on the composition of ultrafine particles (<100 nm in diameter) in the Amazon are scarce, due in part to the fact that new-particle formation has rarely been observed near ground level. Ultrafine particles near the surface have nevertheless been observed, leaving open questions regarding the sources and chemistry of their formation and growth, particularly as these vary across seasons. Here, we present measurements of the composition of ultrafine particles collected in the Tapajós National Forest (2.857° S, 54.959° W) during three different seasonal periods: 10–30 September 2016 (SEP), 18 November–23 December 2016 (DEC), and 22 May–21 June 2017 (JUN). Size-selected (5–70 nm) particles were collected daily (for 22 h each day) using an offline sampler. Samples collected during the three time periods were compiled and analyzed using liquid chromatography coupled with Orbitrap high-resolution mass spectrometry. Our findings suggest a sustained influence of isoprene organosulfate chemistry on ultrafine particles from the different periods. We present chemical evidence that indicates that biological-spore fragmentation impacted ultrafine-particle composition during the late wet season (JUN), while chemical markers for biomass burning and secondary chemistry peaked during the dry season (SEP and DEC). Higher oxidation states and degrees of unsaturation were observed for organics in the dry season (SEP and DEC), suggesting greater extents of aerosol aging. Finally, applying a volatility parameterization to the observed compounds suggests that organic sulfur species are likely key drivers of new-particle growth in the region due to their low volatility compared to other species.
If a terrorist nuclear explosion were to occur in the United States, high-quality (accurate and precise) legally defensible nuclear forensics measurements will be required to assure the certainty and confidence needed, for conclusions drawn from these data will be coupled with law enforcement and intelligence information for the purposes of attribution and retribution. Standard Reference Materials (SRMs)/Certified Reference Materials (CRMs) establish the traceability, accuracy, and precision of nuclear forensic measurements and provide the ability to benchmark measurement methods essential to meeting the requirements of legal scrutiny. Currently there is a critical shortage of key SRMs/CRMs required for accurate and precise measurements that are fundamental to nuclear measurements supporting pre- and post-detonation nuclear forensics. Supplies either do not exist, are not good enough, are in short supply, and/or are very expensive. The radionuclide measurement techniques and data quality objectives for pre- and post-detonation nuclear forensics are quite different than the applications for which the current suite of available SRMs/CRMs was developed. Specifically, 1) modern mass spectrometry methods have largely replaced traditional activity-based measurement methods for quantifying small quantities of long-lived radionuclides and most trace radionuclide SRMs/CRMs are certified for activity and are thus not adequate for current applications, 2) modern instrumental methods are capable of higher precision than historic measurement techniques, and in some cases exceed the precision of the available SRMs/CRMs, and 3) the quality assurance requirements for pre- and post-detonation nuclear forensics are such that the existing cadre of SRMs/CRMs does not adequately support the needs for method validation. There are numerous governmental stakeholders both within the US (DOE, DoD) and internationally (IAEA, JRC-ITU) whose missions are either directly involved with nuclear forensics measurements or rely on the forensic data obtained to make the exacting policy decisions (DOJ (FBI), DHS, CIA, DIA, DoD) associated with disrupting the production of illicit nuclear materials, interdicted nuclear materials or a nuclear/radiological detonation event. Starting in 2008 the DHS NTNFC, in collaboration with NBL and NIST, took on the production of suitable SRMs/CRMs for the pre-detonation nuclear forensics community. Two CRMs have been released since the start of this effort and two more are slated for completion in 2016. More recently, NIST, as a part of its mission as the US National Metrology Institute (NMI) to deliver standards (providing traceability) and foster homeland security, has launched the first certification campaign of a measurement traceable post nuclear detonation SRM. NIST, in cooperation with partner labs (AFIT (DoD), FBI (DOJ), and NPL) and with support from the FBI, has developed two Surrogate Post-Detonation Urban Debris (SPUD) Standard Reference Materials (SRMs) - SRM 4600 and 4601. These SRMs have been developed to simulate the expected debris mixture from the detonation of an Improvised Nuclear Device (IND) in an urban environment, which is capable of producing fresh fission as well as activation products. The elemental composition of the vitrified debris materials is a composite of minerals and metals characteristic of the concrete and steel, the building materials that would be exposed to a nuclear detonation and whose resulting activation products would be found in rubble samples collected for forensics evidence and attribution. Additionally, because post-detonation samples would also contain short-lived fission products, the debris materials have been doped with Uranium (U). To create the nuclear fission products, samples of the SPUD materials can be placed in a well-characterized nuclear reactor and exposed to a set neutron flux and energy, causing the encased U atoms to split and yield short-lived fission products. Because a known amount of U is added to the SPUD materials it is feasible to determine the concentration of the resulting fission products. The subsequent irradiated SPUD glass would be chemically similar to samples that would be generated in an actual detonation, and thus can serve as a standardized reference material for nuclear forensic post detonation measurements. (authors)
ABSTRACT Worldwide, there is growing interest in the use of pharmaceutical baits to control populations of wild pigs ( Sus scrofa ). In this study we evaluated the utility of Rhodamine B (RB), a chemical marker commonly used in wildlife research and management, as a potential biomarker for quantifying bait uptake in wild pigs. Thirty wild pigs were live‐trapped, transported to a captive facility on the Department of Energy's Savannah River Site located in South Carolina, USA, during autumn 2013, and administered RB orally at a dosage of 30 mg/kg. Eight vibrissae and guard hairs were collected pre‐ and post‐RB exposure (7 or 14 days) and evaluated for the presence of RB using fluorescence microscopy. No evidence of RB marking was observed in any samples collected pre‐RB administration. In contrast, we observed fluorescent marking post‐RB exposure that was indicative of the presence of RB for all individuals, with 98% of vibrissae and 100% of guard hairs exhibiting RB marks. The uniform detection of RB among individuals and consistent manifestation of marks in both guard hair and vibrissae, samples that easily can be collected and stored by untrained field personnel from live or deceased pigs, suggests that RB is an effective biomarker for use in large‐scale management programs to control wild pigs. In particular, our results, combined with previous studies evaluating uptake of RB in other species, suggest that RB can be used to develop baiting programs to deliver pharmaceuticals to free‐ranging wild pigs, as well as evaluate the potential impacts of pig baits on non‐target species. © 2014 The Wildlife Society.
Abstract We conducted laboratory experiments to investigate a suspected effect of tetrahydrofuran (THF) on quantifying crystalline silica in samples collected from working with engineered stone when THF is used to process samples prior to the X-ray diffraction (XRD) analysis. Two groups of samples from grinding either engineered stone or granite were simultaneously taken from a laboratory testing system, with one group of samples using THF for processing and another group using muffle furnace for ashing. For each stone type, we also tested four levels of respirable dust loading on the samples by varying the grinding time from 1 to 8 min. Statistical analysis of the experimental results on crystalline silica contents of the two groups of samples showed that the difference between the two methods was not significant (P ≥ 0.05) for the granite at all four levels of respirable dust loading and for the engineered stone at the two levels of respirable dust loading greater than 0.5 mg. However, the crystalline silica content from using THF processing was significantly lower (P = 0.001) than that from using muffle furnace ashing for engineered stone when the respirable dust loading levels were less than 0.5 mg. For the engineered stone dust samples with grinding times of 1 and 2 min, the average respirable dust loading was about 0.19 and 0.34 mg, respectively; while the crystalline silica content from using THF processing was 30.9 and 21.5% lower than that from using muffle furnace ashing, respectively. Since most full-shift samples from field assessments in this industry are expected to have respirable dust loading less than 0.5 mg, muffle furnace or radio frequency plasma ashing should be specified as the preferred sample processing method instead of the THF processing method for quantification of crystalline silica when engineered stone is expected to present to avoid artificially reduced silica content values, which are likely caused by the reactions between THF and the resins in engineered stone.
Background: Humans emit approximately 30 million microbial cells per hour into their immediate vicinity. However, sampling of aerosolized microbial taxa (aerobiome) remains largely uncharacterized due to the complexity and limitations of sampling techniques, which are highly susceptible to low biomass and rapid sample degradation. Recently, there has been an interest in developing technology that collects naturally occurring water from the atmosphere, even within the built environment. Here, we analyze the feasibility of indoor aerosol condensation collection as a method to capture and analyze the aerobiome. Methods: Aerosols were collected via condensation or active impingement in a laboratory setting over the course of 8 h. Microbial DNA was extracted from collected samples and sequenced (16S rRNA) to analyze microbial diversity and community composition. Dimensional reduction and multivariate statistics were employed to identify significant (p < 0.05) differences in relative abundances of specific microbial taxa observed between the two sampling platforms. Results: Aerosol condensation capture is highly efficient with a yield greater than 95% when compared to expected values. Compared to air impingement, aerosol condensation showed no significant difference (ANOVA, p > 0.05) in microbial diversity. Among identified taxa, Streptophyta and Pseudomonadales comprised approximately 70% of the microbial community composition. Conclusion: The results suggest that condensation of atmospheric humidity is a suitable method for the capture of airborne microbial taxa reflected by microbial community similarity between devices. Future investigation of aerosol condensation may provide insight into the efficacy and viability of this new tool to investigate airborne microorganisms.
Flow-through reactor (FTR) experiments were conducted at three different downward vertical flow rates to study the transport and retention of particulate organic matter (Chlorella powder) in riverbed sediments. This data package includes data files (.csv) regarding effluent collected from the FTRs during the experiments (time, duration, volume of each sample collection; concentration of nonreactive bromide tracer; concentration of suspended Chlorella determined by absorbance measurements) and sediment (sand) slices collected from the FTRs after the experiments (mass of Chlorella retained in 1 cm depth intervals determined by loss-on-ignition method). More detailed descriptions of data are provided in the data dictionary, and detailed methods are available in the associated MSc thesis listed in ‘Related References.’ The data dictionary and file level meta data (FLMD) are included in the data package as both .csv and .xlsx files. This data package also includes timelapse videos (.mp4) of the experiments, and modelling scripts associated with the experiments. The modelling scripts are included as MATLAB ‘live scripts’ (.mlx, which can be run using MATLAB), and are also included as .pdf and .html files with output plots included (which can be viewed without a MATLAB license and installation). The data files and modelling scripts are organized into a .zip folder for each of the three FTR experiments (three flow rates).
This report summarizes the analytical data reported by the F/H and Savannah River National Laboratories for the 2012 cross-check analysis for high level waste supernatant liquid samples from SRS Tanks 30 and 37. The intent of this Tank 30 and 37 sample analyses was to perform cross-checks against routine F/H Laboratory analyses (corrosion and evaporator feed qualification programs) using samples collected at the same time from both tanks as well as split samples from the tanks.
The Phase I report prepared for the Department of Energy addresses U.S. Executive Order 13817 titled A Federal Strategy to Ensure Secure and Reliable Supplies of Critical Minerals, issued on December 20, 2017, that lists 35 critical minerals that are vulnerable to supply disruption. A comprehensive review of each of the minerals was conducted to determine the criticality based primarily on extractability from coal-based resources. Several other factors were also considered such as gaps in supply and demand, use in current technology, and the existence of viable substitutes. It was determined that the critical minerals that show highest potential for extraction from coal-based resources are lithium, rare earth elements (REEs), cobalt, and manganese. All four of the critical minerals listed serve an important role in the technology industry, have few substitutes, and have a heavy import reliance. Most notably are lithium, which is widely used in the electric vehicle industry, and the REEs which can be found in virtually all electronic devices. The research of critical mineral extraction from coal-based resources was completed using a combination of literature review from public sources as well as cooperation from coal mines and power plants across the United States. Samples collected from six different geographical locations across the U.S. were subjected to sample preparation (i.e., pH measurement, moisture content, particle size analysis) and characterization studies using Inductively Coupled Plasma-Mass Spectroscopy (ICP-MS) and Scanning Electron Microscopy, Energy Dispersive X-Ray Spectroscopy (SEM-EDX) instruments. 27 samples of coal waste materials such as refuse, sludge, and fly ash were tested to characterize the rare earth element concentration by total rare earth elements (TREEs), heavy rare earth elements (HREEs), and light rare earth elements (LREEs). Of the 27 samples tested, 22 contained a TREE concentration higher than the threshold of 300 ppm, which is considered a viable feedstock material. 3 samples contained less than 300 ppm of TREEs; however, they were within 20 ppm of the threshold, and could potentially be considered viable sources in the future pending the advancement of more efficient extraction technologies. 2 of the 27 samples had significantly low TREE concentrations, which does not imply any potential for being a source for REEs. For the minerals identified as most critical in the literature review, a conceptual process flow diagram (PFD) was developed for their extraction from different coal-based feedstocks. The process targets selective recovery of one commodity (i.e., rare earths, lithium, cobalt, and manganese) via several hydrometallurgical separation methods. By identifying potentially extractable coal-based critical mineral resources, a study of the current and future market environments for each critical mineral, and a review of current processing methodologies for critical mineral extraction from coal-based resources, the foundation has been laid to further characterize and explore new resources and extraction techniques. As reliance on technologies in industries such as the production of electronic devices, batteries, and alloys containing critical minerals utilizing critical minerals continues to increase, a sound understanding of our nation’s dependence on and even the global criticality of certain critical minerals, will serve as a catalyst for innovation in virtually all fields of science.
The calendar year 2023 annual sampling letter report presents Plan implementation and a summary of field activities, sampling methods, well completion diagrams, and analytical laboratory results from sampling of wells associated with the Pahute Mesa CAUs. The CY 2023 letter report also presents data from samples collected from Well ER-EC-11_p3 as part of a sampling investigation. This well was resampled because of anomalously low standard tritium (3H) results from bailer sampling that occurred in July 2021.
One objective of TRACER-Tethersonde campaign was to deploy a volatile organic compound (VOC) sampler on the Tethered Balloon System (TBS) to create vertical profiles and characterize VOC composition. Volatile organic compounds (VOCs) are highly reactive precursor species that undergo atmospheric processing to form secondary products, including aerosol. VOC emissions are influenced by many factors that include but are not limited to temperature, time of day, local anthropogenic activities, and local vegetation, which result in large spatiotemporal variability. The vertical distribution of volatile species is crucial for understanding gas-phase processing for particle production but challenging to accomplish using currently available sampling devices. The standalone sampler built during the campaign enabled the execution of robust experimental designs, including sample collection using resin tubes at multiple altitudes on subsequent flights. Following field sampling, resin tubes were transported back to Baylor University for chemical analysis using a Markes International thermal desorption unit coupled with a gas chromatograph-tandem mass spectrometer (Thermo Scientific). The target analyte list includes biogenic and anthropogenic VOCs.