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Annual report of activities conducted under the EMAC program including biological surveys, desert tortoise compliance, ecosystem monitoring, sensitive and protected/regulated plant and animal monitoring, and habitat restoration implementation and monitoring.
The Ecological Monitoring and Compliance Program (EMAC), funded through the U.S. Department of Energy, National Nuclear Security Administration Nevada Field Office (NNSA/NFO), monitors the ecosystem of the Nevada National Security Site (NNSS) and ensures compliance with laws and regulations pertaining to NNSS biota. This report summarizes the program’s activities conducted by Mission Support and Test Services, LLC (MSTS), during calendar year 2019. Program activities included (a) biological surveys at proposed activity sites, (b) desert tortoise compliance, (c) ecosystem monitoring, (d) sensitive and protected/regulated plant monitoring, (e) sensitive and protected/regulated animal monitoring, and (f) habitat restoration monitoring. During 2019, all applicable laws, regulations, and permit requirements were met, enabling EMAC to achieve its intended goals and objectives.
The Ecological Monitoring and Compliance Program (EMAC), funded through the U.S. Department of Energy, National Nuclear Security Administration Nevada Field Office (NNSA/NFO), monitors the ecosystem of the Nevada National Security Site (NNSS) and ensures compliance with laws and regulations pertaining to NNSS biota. This report summarizes the program’s activities conducted by Mission Support and Test Services, LLC (MSTS), during calendar year 2020. Program activities included (a) biological surveys at proposed activity sites, (b) desert tortoise compliance, (c) ecosystem monitoring, (d) sensitive and protected/regulated plant monitoring, (e) sensitive and protected/regulated animal monitoring, and (f) habitat restoration monitoring. During 2020, all applicable laws, regulations, and permit requirements were met, enabling EMAC to achieve its intended goals and objectives.
Summarizes work performed under the Ecological Monitoring and Compliance Program for 2022.
This report details accomplishments of the EMAC program during 2024.
This monitoring plan for Idaho National Laboratory’s Remote-Handled Low Level Waste Disposal Facility was developed to meet the requirements for monitoring low-level waste disposal facilities according to the U.S. Department of Energy (DOE) Order 435.1, “Radioactive Waste Management,” and the guidance provided in the associated technical standard “Disposal Authorization Statement and Tank Closure Documentation” (DOE-STD-5002-2017). The purpose of this monitoring plan is to document a monitoring strategy that includes (1) compliance monitoring activities to demonstrate compliance with regulatory standards/limits and (2) performance monitoring to build confidence the facility is performing as demonstrated in the facility performance assessment (PA) (DOE-ID 2018a), composite analysis (CA) (DOE ID 2012), and CA addendum (DOE-ID 2018b). The de minimus impact to the aquifer predicted by the PA suggests that aquifer compliance monitoring should be augmented with performance monitoring of the drainage course materials and sedimentary interbeds in the vadose zone beneath the facility to provide a more effective means of identifying performance deviations. The monitoring approach delineated in this document was informed by the systems evaluation of natural and engineered facility features presented in the PA, an assessment of aquifer baseline conditions (INL 2017d), the dose analysis conducted in support of the PA and CA, and monitoring data collected during the first four years of facility operations (baseline monitoring phase) (INL 2023b). This plan provides monitoring locations, sampling frequencies, and sampling methods; recommendations for data evaluation; and a description of the monitoring plan implementation. Collected data will be used to demonstrate facility compliance and to identify conditions that are not consistent with the key assumptions made by the PA and CA.
Model selection for water quality forecasting depends on many factors including analyst expertise and cost, stakeholder involvement and expected performance. Water quality forecasting in arid river basins is especially challenging given the importance of protecting beneficial uses in these environments and the livelihood of agricultural communities. In the agriculture-dominated San Joaquin River Basin of California, real-time salinity management (RTSM) is a state-sanctioned program that helps to maximize allowable salt export while protecting existing basin beneficial uses of water supply. The RTSM strategy supplants the federal total maximum daily load (TMDL) approach that could impose fines associated with exceedances of monthly and annual salt load allocations of up to $1 million per year based on average year hydrology and salt load export limits. The essential components of the current program include the establishment of telemetered sensor networks, a web-based information system for sharing data, a basin-scale salt load assimilative capacity forecasting model and institutional entities tasked with performing weekly forecasts of river salt assimilative capacity and scheduling west-side drainage export of salt loads. Web-based information portals have been developed to share model input data and salt assimilative capacity forecasts together with increasing stakeholder awareness and involvement in water quality resource management activities in the river basin. Two modeling approaches have been developed simultaneously. The first relies on a statistical analysis of the relationship between flow and salt concentration at three compliance monitoring sites and the use of these regression relationships for forecasting. The second salt load forecasting approach is a customized application of the Watershed Analysis Risk Management Framework (WARMF), a watershed water quality simulation model that has been configured to estimate daily river salt assimilative capacity and to provide decision support for real-time salinity management at the watershed level. Analysis of the results from both model-based forecasting approaches over a period of five years shows that the regression-based forecasting model, run daily Monday to Friday each week, provided marginally better performance. However, the regression-based forecasting model assumes the same general relationship between flow and salinity which breaks down during extreme weather events such as droughts when water allocation cutbacks among stakeholders are not evenly distributed across the basin. A recent test case shows the utility of both models in dealing with an exceedance event at one compliance monitoring site recently introduced in 2020.
Summarizes work done for EMAC program during 2021.
The purpose of this document is to summarize environmental monitoring data collected at the Remote-Handled Low-Level Waste (RHLLW) Disposal Facility during the first four years of facility operations (FY 2019 through FY 2022). This summary provides a “baseline” condition for the facility, which can be used to distinguish contaminant releases from the RHLLW Disposal Facility from pre existing contamination as well as potential future releases from other sources (i.e., upgradient aquifer sources), as specified in the facility monitoring plan. Sufficient data has been collected over the first four years of operation of the RHLLW Disposal Facility to establish baseline conditions for future compliance monitoring of aquifer wells and performance monitoring of vadose zone lysimeters. Except for seven elevated tritium measurements from lysimeter HFEF-South believed to have been impacted by waste disposals, all data was deemed appropriate for establishing baseline concentrations. Monitoring of the aquifer detected indicator analytes gross alpha and gross beta and target analytes tritium and C-14. There were a few C-14 detections prior to an increase in the required detection level (RDL) after the first round of sampling. I-129 and Tc-99 were not detected above RDLs in aquifer samples. Lysimeter samples detected indicator analytes gross alpha and gross beta and target analyte tritium. Target analytes C-14, I-129, and Tc-99 were not detected above RDLs in lysimeter samples. Except for tritium, baseline concentrations of indicator and target analytes measured during the first four years of RHLLW facility operations are expected to represent conditions through the expected 20 year operating period of the facility. Elevated tritium in the aquifer, a result of past discharges of tritium at upgradient facilities, showed a decline over the first four years of operations, and levels are expected to continue to decline with time as a result of dilution and decay. Current tritium levels in lysimeter samples may be elevated due to tritium in the water applied during construction and infiltration testing of the facility. As a result, tritium concentrations in lysimeters may decline with time as a result of dilution and decay. Statistical measures (i.e., mean, standard deviation, and 99% upper confidence level [UCL]) were calculated for all detected analytes using the four years of concentration data. These measures will be used to evaluate future monitoring results and to demonstrate the facility is performing, or not performing, as established in the facility performance assessment (PA). Future monitoring results will also be combined with the baseline data in this report to further establish temporal trends and natural variability in the measurements. Based on the data collected during the baseline period, it is recommended the gross alpha action level for performance monitoring increase from 10 to 20 pCi/L due to several baseline measurements exceeding the preliminary action level of 10. An action level of 20 pCi/L is slightly greater than the 99% UCL, is protective of the aquifer, and would reduce unnecessary sampling. It is also recommended that tritium be added to the lysimeter analyte list for post-baseline period monitoring. Tritium, while not a dose concern, is a good tracer that can provide valuable information on water flow in and around the RHLLW Disposal Facility. Recommendations for a tritium action level are provided if considered necessary.
This report, prepared by the SLAC National Accelerator Laboratory (SLAC) for the U.S. Department of Energy (DOE), SLAC Site Office (SSO), provides a comprehensive summary of the environmental program activities at SLAC for calendar year 2022. Annual Site Environmental Reports (ASERs) are prepared for all DOE sites with significant environmental activities, and distributed to relevant external regulatory agencies and other interested organizations or individuals. To the best of my knowledge, this report accurately summarizes the results of the 2022 environmental monitoring, compliance, and restoration programs at SLAC. This assurance can be made based on SSO and SLAC review of the ASER, and quality assurance protocols applied to monitoring and data analyses at SLAC.
This report, prepared by the SLAC National Accelerator Laboratory (SLAC) for the U.S. Department of Energy (DOE), SLAC Site Office (SSO), provides a comprehensive summary of the environmental program activities at SLAC for calendar year 2023. Annual Site Environmental Reports (ASERs) are prepared for all DOE sites with significant environmental activities and distributed to relevant external regulatory agencies and other interested organizations or individuals. To the best of my knowledge, this report accurately summarizes the results of the 2023 environmental monitoring, compliance, and restoration programs at SLAC. This assurance can be made based on SSO and SLAC review of the ASER, and quality assurance protocols applied to monitoring and data analyses at SLAC.
This report, prepared by the SLAC National Accelerator Laboratory (SLAC) for the U.S. Department of Energy (DOE), SLAC Site Office (SSO), provides a comprehensive summary of the environmental program activities at SLAC for calendar year 2021. Annual Site Environmental Reports (ASERs) are prepared for all DOE sites with significant environmental activities and distributed to relevant external regulatory agencies and other interested organizations or individuals. To the best of my knowledge, this report accurately summarizes the results of the 2021 environmental monitoring, compliance, and restoration programs at SLAC. This assurance can be made based on SSO and SLAC review of the ASER, and quality assurance protocols applied to monitoring and data analyses at SLAC.
Background: Humans are primary drivers of environmental–contaminant exposures worldwide, including in drinking-water (DW). In the United States, point-of-use DW (POU–DW) is supplied via private tapwater (TW), public-supply TW, and bottled water (BW). Differences in management, monitoring, and messaging and lack of directly–intercomparable exposure data influence the actual and perceived quality and safety of different DW supplies and directly impact consumer decision–making. Objectives: The purpose of this paper is to provide a meta-analysis (quantitative synthesis) of POU–DW contaminant–mixture exposures and corresponding potential human–health effects of private-TW, public-TW, and BW by aggregating exposure results and harmonizing apical–health–benchmark–weighted and bioactivity–weighted effects predictions across previous studies by this research group. Discussion: Simultaneous exposures to multiple inorganic and organic contaminants of known or suspected human-health concern are common across all three DW supplies, with substantial variability observed in each and no systematic difference in predicted cumulative risk between supplies. Differences in contaminant or contaminant–class exposures, with important implications for DW–quality improvements, were observed and attributed to corresponding differences in regulation and compliance monitoring. Conclusion: The results indicate that human-health risks from contaminant exposures are common to and comparable in all three DW–supplies, including BW. Importantly, this study’s target analytical coverage, which exceeds that currently feasible for water purveyors or homeowners, nevertheless is a substantial underestimation of the breadth of contaminant mixtures in the environment and potentially present in DW. Thus, the results emphasize the need for improved understanding of the adverse human-health implications of long-term exposures to low–level inorganic–/organic–contaminant mixtures across all three distribution pipelines and do not support commercial messaging of BW as a systematically safer alternative to public-TW. Regardless of the supply, increased public engagement in source-water protection and drinking–water treatment is necessary to reduce risks associated with long-term DW–contaminant exposures, especially in vulnerable populations, and to reduce environmental waste and plastics contamination.
Gamma-gamma coincidence spectrometers have the potential to significantly enhance detection sensitivity for ultra-trace radionuclide measurements. The implementation of these spectrometers, however, is limited by the complexity of acquisition hardware, data processing and quantification. This work reports development of a novel radionuclide quantification software for γ-γ coincidence measurements. For any radionuclide, the software parses the Evaluated Nuclear Structure Data File (ENSDF) database, recursively simulating all possible γ-γ coincidence signatures and their respective emission and detection probabilities. Implemented using Python programming language, the software employs several strategies to boost overall computational performance. Since coincidence-based spectrometers are of notable interest in monitoring compliance for the Comprehensive Nuclear-Test-Ban Treaty (CTBT), the software’s execution was tested for 84 CTBT-relevant radionuclides. To date, the software has been experimentally validated for 15 radionuclides using the Advanced Radionuclide Gamma spectrOmeter (ARGO) at Pacific Northwest National Laboratory, USA (PNNL). Notably, the software can be operated in convergence mode, whereby coincidence detection efficiency’s convergence behavior can help avoid unreliable radionuclide activity estimates. With growing number of coincidence spectrometers worldwide, this paper aims to assist the radiation metrology community in developing similar software for their system.
Determination of Mytilus galloprovincialis larvae median effect concentration (EC50), of Cu in coastal marine waters by diffusive gradient in thin-films (DGT), has been shown to effectively reduce the need to consider dissolved organic carbon (DOC) concentration and quality. West coast marine and estuarine organisms’ chronic toxicity test protocol was used to validate previously modelled protective effects, afforded to highly sensitive marine larvae by ligand competition, in five diverse site waters. The results demonstrate significant narrowing of toxicological endpoints, where EC50s ranged from 3.74 – 6.67 µg/L as CDGT Cu versus 8.76 – 26.8 µg/L as CuDISS over a DOC range of 0.74 – 3.11 mg/L. Additionally, DOC quality (characterized by fluorescence excitation and emission matrices) indicates that the heterogeneity of competing Cu binding ligands, in common marine waters, minimizes the need for class determinations toward explaining the degree of protection, when assumptions in criterion maximum concentration (CMC) setting are conservative. A CDGT Cu EC50 of 3.7 µg/L, and corresponding CMC CDGT Cu of 1.8 µg/L, for universal application by regulatory compliance-monitoring programs, are proposed as a superior approach toward both integration of dynamic water quality over effective exposure periods and quantification of biologically-relevant trace Cu speciation and are demonstrated by in situ data.
Artificial intelligence is emerging as a transformative force in addressing the multifaceted challenges of food safety, food quality, and food security. This review synthesizes advancements in AI-driven technologies, such as machine learning, deep learning, natural language processing, and computer vision, and their applications across the food supply chain, based on a comprehensive analysis of literature published from 1990 to 2024. AI enhances food safety through real-time contamination detection, predictive risk modeling, and compliance monitoring, reducing public health risks. It improves food quality by automating defect detection, optimizing shelf-life predictions, and ensuring consistency in taste, texture, and appearance. Furthermore, AI addresses food security by enabling resource-efficient agriculture, yield forecasting, and supply chain optimization to ensure the availability and accessibility of nutritious food resources. This review also highlights the integration of AI with advanced food processing techniques such as high-pressure processing, ultraviolet treatment, pulsed electric fields, cold plasma, and irradiation, which ensure microbial safety, extend shelf life, and enhance product quality. Additionally, the integration of AI with emerging technologies such as the Internet of Things, blockchain, and AI-powered sensors enables proactive risk management, predictive analytics, and automated quality control. By examining these innovations' potential to enhance transparency, efficiency, and decision-making within food systems, this review identifies current research gaps and proposes strategies to address barriers such as data limitations, model generalizability, and ethical concerns. These insights underscore the critical role of AI in advancing safer, higher-quality, and more secure food systems, guiding future research and fostering sustainable food systems that benefit public health and consumer trust.
Accurate prediction of the subsurface transport of iodine species is important for the assessment of long-term nuclear waste repository performance, as well as monitoring compliance with the Comprehensive Nuclear-Test-Ban Treaty, given that radioiodine decays into radioxenon. However, the transport of iodine through intact geologic media is not well understood, compromising our ability to assess risk associated with radioiodine migration. The current study's goal is to quantify the matrix diffusion of iodine species through saturated volcanic rock, with particular attention paid to the redox environment and potential speciation changes. Here, diffusion experiments were run for iodide through lithophysae-rich lava, lithophysae-poor lava, and welded tuff, whereas iodate diffusion was studied through welded tuff. Iodine transport was compared with a conservative tracer, HDO, and effective diffusion coefficients were calculated. Likely due to a combination of size and anion exclusion effects, iodine species diffused more slowly than the conservative tracer through all rock types tested. Furthermore, oxidation of iodide to iodate was observed in the lithophysae-poor lava, affecting transport. Results provide much needed data for subsurface transport models that predict radioiodine migration from underground sources, and indicate the pressing need for geochemical and redox interactions to be incorporated into these models.
The Comprehensive Nuclear-Test-Ban Treaty mandates the four verification technologies to be used by the International Monitoring System (IMS) to monitor compliance to the Treaty. These technologies are seismic, hydroacoustic, infrasound, and radionuclide. Operational manuals for each of these technologies specify the requirements that equipment installed at IMS stations must meet for data from said stations to be accepted by the International Data Center. Following a model in which a revised set of infrasound sensor specifications and accompanying test procedures were developed in an international collaboration overseen by the Comprehensive Nuclear-Test-Ban Treaty Organization, the same process was recently followed for seismometers potentially of use by the IMS. This document, a product of that collaboration, defines key concepts and recommends test procedures to be followed to characterize broadband seismometers in a consistent and standardized way. Results from these test procedures can be used to verify that a seismometer meets the manufacturers stated specifications and IMS requirements. ACKNOWLEDGEMENTS The writers of this document would like to acknowledge Charles R. Hutt, John R. Evans, Fred Followill, Robert L. Nigbor, and Erhard Wielandt, the authors of the 2009 Guidelines for Standardized Testing of Broadband Seismometers and Accelerometers funded by the U.S. Department of Interior, on which this document is based. Although this document is limited in scope to seismometers and much of the document has been updated, the structure remains essentially the same.