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At least 955 records · Page 53

Big Data Analytics for Long-Term Meteorological Observations at Hanford Site

A growing number of physical objects with embedded sensors with typically high volume and frequently updated data sets has accentuated the need to develop methodologies to extract useful information from big data for supporting decision making. This study applies a suite of data analytics and core principles of data science to characterize near real-time meteorological data with a focus on extreme weather events. To highlight the applicability of this work and make it more accessible from a risk management perspective, a foundation for a software platform with an intuitive Graphical User Interface (GUI) was developed to access and analyze data from a decommissioned nuclear production complex operated by the U.S. Department of Energy (DOE, Richland, USA). Exploratory data analysis (EDA), involving classical non-parametric statistics, and machine learning (ML) techniques, were used to develop statistical summaries and learn characteristic features of key weather patterns and signatures. The new approach and GUI provide key insights into using big data and ML to assist site operation related to safety management strategies for extreme weather events. Specifically, this work offers a practical guide to analyzing long-term meteorological data and highlights the integration of ML and classical statistics to applied risk and decision science.

54 ENVIRONMENTAL SCIENCES↗

East Tennessee Technology Park Biological Monitoring and Abatement Program 2024 Calendar Year Report

The East Tennessee Technology Park (ETTP) Biological Monitoring and Abatement Program (BMAP) consists of three tasks that reflect different but complementary approaches to evaluating the ecological integrity of waters near ETTP. These tasks include (1) bioaccumulation monitoring of fish and clams, (2) benthic macroinvertebrate species richness and density monitoring, and (3) fish community monitoring. The sampling and analysis requirements for the ETTP BMAP in calendar year 2024, covering in part both FY 2024 and FY 2025, are outlined in the respective FY sampling and analysis plans (UCOR 2023, 2024). Sampled water bodies and locations for the ETTP BMAP are shown in Figures 1 and 2. This ETTP BMAP report presents the CY 2024 results and provides context with results from previous years. The report also includes Oak Ridge National Laboratory (ORNL)–generated biological monitoring data collected for other US Department of Energy programs, including the UCOR Water Resources Restoration Program (WRRP) off-site fish bioaccumulation data (UCOR 2023) and select Y-12 National Security Complex (Y-12) BMAP fish bioaccumulation data. Historical data collected for the ETTP BMAP and other programs in the nearby Poplar Creek and Clinch River are provided where appropriate. This progress report provides an update on the biological monitoring activities supporting the ETTP UCOR Environmental Compliance organization, which sponsors the ETTP BMAP. In addition to this internal reporting, ETTP BMAP results are provided in the annual remediation effectiveness reports and the annual site environmental reports, both of which are publicly available. BMAP data are also available to the public via the Oak Ridge Environmental Information System (https://ucor.com/oak-ridge-environmental-information-system-oreis/).

54 ENVIRONMENTAL SCIENCES↗

Ten Years of VIIRS Land Surface Temperature Product Validation

The Visible Infrared Imaging Radiometer Suite (VIIRS) Land Surface Temperature (LST) has been operationally produced for a decade since the Suomi National Polar-orbiting Partnership (SNPP) launched in October 2011. A comprehensive evaluation of its accuracy and precision will be helpful for product users in climate studies and atmospheric models. In this study, the VIIRS LST is validated with ground observations from multiple high-quality radiation networks, including six stations from the Surface Radiation budget (SURFRAD) network, two stations from the Baseline Surface Radiation Network (BSRN), and 13 stations from the Atmospheric Radiation Measurement (ARM) network, to evaluate its performance over various land-cover types. The VNP21A1 LST was validated against the same ground observations as a reference. The results yield a close agreement between the SNPP VIIRS LST and ground LSTs with a bias of -0.4 K and a RMSE of 1.96 K over six SURFRAD sites; a bias of -0.2 K and a RMSE of 1.93 K over two BSRN sites; and a bias of -0.1 K and a RMSE of 1.7 K over the 13 ARM sites. The time series of the LST errors over individual sites indicate seasonal cycles. The data anomaly over the BSRN site in Cabauw and the SURFRAD site in Desert Rock is revealed and discussed in this study. In addition, a method using Landsat-8 data is applied to quantify the heterogeneity level of each ground station and the results provide promising insights. The validation results demonstrate the maturity of the JPSS VIIRS LST products and their readiness for various application studies.

54 ENVIRONMENTAL SCIENCES↗

AmeriFlux US-GL1 Stannard Rock

This is the AmeriFlux version of the carbon flux data for the site US-GL1 Stannard Rock. Site Description - Stannard Rock is located 39 km from the nearest shore (Keweenaw Peninsula) in Lake Superior, 44 miles NNE of Marquette, Michigan, and 24 miles ESE of Manitou Island. The site is located on the historic Stannard Rock Lighthouse, which was completed in 1882. Eddy covariance instrumentation was installed in 2008 by a network of scientists from both US and Canada, eventually to be called the Great Lakes Evaporation Network (GLEN). The intent of GLEN has been to provide observations of over-lake meteorology and evaporation, improve forecasting of Great Lakes water levels, and support a wide variety of stakeholders, including the National Weather Service (NWS), Environment and Climate Change Canada, National Oceanic and Atmospheric Administration, U.S. Coast Guard, recreational boaters and commercial shipping, emergency management officials, and the Great Lakes research community. The eddy covariance station along with other ancillary meteorological instrumentation is located at an approximate elevation of 39.2 meters above mean lake water level. Meteorological data from the lighthouse are sent to the National Data Buoy Center, where they can be viewed in real-time at http://www.ndbc.noaa.gov/station_page.php?station=stdm4 Uncorrected half-hour fluxes were computed directly on the logger using a 30-minute block averaging period as high-frequency data were not available. The half hour flux measurements downloaded from the datalogger were post-processed with the following filters and corrections. Latent and sensible heat and carbon dioxide fluxes were corrected with 2-D coordinate rotation. Although the primary objective of data collection at Stannard Rock was to quantify the evaporative flux, additional preliminary measurements of the carbon dioxide concentration and flux from the LI-7500 are also included in this dataset but it is advised to use the carbon data with caution. Carbon data reported in this dataset includes turbulent fluxes of CO2 with no storage correction (FC, µmol m-2 s-1) and CO2 density in mole fraction of wet air (CO2), which was originally output on the datalogger as average CO2 density (mg m-2 s-1) and converted into µmol mol-1 using air temperature and pressure in post-processing. Webb, Pearman, and Leuning terms were applied to account for density fluctuations for water vapor and CO2. Sonic path length, high-frequency attenuation and sensor separation were accounted for according to Horst and Massman, and the oxygen absorption correction for the KH2O hygrometer was also applied. Latent and sensible heat fluxes were assumed to be unrealistic above an absolute value of 1000 W m-2 and were removed. Both carbon flux (FC) and carbon dioxide mole fraction in wet air (CO2) and were assumed to be unrealistic above 1000 µmol m-2 s-1 and 1000 µmol mol-1 respectively. Spikes in latent and sensible heat and carbon fluxes and densities (often due to periods of precipitation) were identified by computing the mean and standard deviation over a moving, overlapping window of 336 half-hours (7 days), similar to Shao et al., and were removed when the flux was more than 1.5 standard deviations from the moving window’s mean. While Vickers and Mahrt use a threshold of 3.5 standard deviations from the mean, a conservative value of 1.5 was chosen due to the noisy nature of over-lake data at this particular site. This process was repeated twice for latent and sensible heat, and carbon dioxide fluxes and densities and therefore it is possible that some real, realistic data was filtered out in this process. No detrending was performed. As per AmeriFlux standards, no friction velocity (USTAR, m s-1) filtering was performed.

Spence, Chris↗

QProR: An Efficient Framework for Quantity-of-Interest Based Progressive Retrieval with Guaranteed Error Control

Scientific applications generate an unprecedented volume of data, overwhelming the network and file systems’ bandwidth and posing challenges for efficient and scalable data retrieval and analysis. Progressive data compression offers a promising solution by enabling on-demand retrieval at reduced size. However, existing progressive methods either fail to bound the errors in essential quantities of interest (QoIs) derived from raw data or suffer from suboptimal retrieval efficiency. In this work, we propose QProR, an efficient QoI-based progressive framework that optimizes progressive retrieval for target QoIs. Our key contributions include: (1) a systematic framework that integrates error-controlled lossy compressors with bitplane encoding while decoupling the two processes for high flexibility and adaptability; (2) a novel weighted bitplane encoding method which incorperates QoI knowledge into data refactoring to enhance retrieval efficiency; (3) an optimized retrieval strategy that accounts for the varying impacts of different variables on multivariate QoIs; (4) comprehensive evaluations using six real-world datasets from multiple scientific applications and thorough comparisons against state of the arts. Experimental results demonstrate that QProR achieves up to 80.38% reduction in the retrieval size under the same requested QoI error tolerance, when compared with the best-performing existing methods. When transferring 384 GB of scientific data to remote sites, QProR delivers up to 1.68 × speedup in the end-to-end data transfer performance.

Li, Wenbo [University of Kentucky]↗

LDES-Sizing-and-siting-model (Power grid test cases for long-duration energy storage (LDES) siting) [SWR-25-75]

This repository contains code and data for performing a siting analysis of long-duration energy storage (LDES) in the 5-bus and RTS systems using the Sienna suite developed by the National Renewable Energy Laboratory for production cost modeling (PCM). This analysis involves moving the LDES component to different buses in the system, running a simulation, and considering the production cost of the simulation. Different system configurations are also analyzed with these scripts (such as moving load or renewable dispatch generators to different buses) to observe the impacts the system configuration has on optimal siting. This repository contains three sub directories discussed below. Both the 5-bus and RTS systems have two different initial configurations for the renewable energy components in them, one that is predominantly PV-driven and one that is predominantly wind-driven. Sienna suite can be found here: https://github.com/NREL-Sienna

Cole, David [University of Wisconsin]↗

Oak Ridge National Laboratory 2025 Site Sustainability Plan With FY 2024 Performance Data

At the close of each fiscal year, the US Department of Energy (DOE) Sustainability Performance Office (SPO) issues instruction documents and technical resource aids/tools necessary for DOE sites and national laboratories to complete sustainability reporting requirements. SPO is part of the DOE Office of Asset Management. As required by DOE Order 436.1A, Departmental Sustainability, each site develops and commits to an annual site sustainability plan (SSP) that identifies its respective contribution toward meeting DOE’s sustainability goals. SPO collects and compiles information reported by each site to develop an agency-wide sustainability report and implementation plan, which are used to report DOE sustainability progress to the federal government as required by all major federal agencies.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Stacked Greenfield and Brownfield ROZ Fairways in the Illinois Basin Geo-Laboratory: Co-Optimization of EOR and Associated CO 2 Storage

Residual oil zones (ROZs) are economically viable targets for carbon dioxide enhanced oil recovery (CO 2 -EOR); thick, carbonate ROZs in the San Andres Formation in the Wasson Field of the Permian Basin are an example. Incremental oil produced from CO 2 -EOR can be carbon negative via associated storage of injected CO 2 . Given the regional extent of ROZ fairways and generally higher net utilization of CO 2 (compared to conventional CO 2 -EOR), ROZs provide the opportunity for significant carbon neutral to carbon negative oil production with associated CO 2 storage, and therefore should be a priority target for exploration. However, ROZs have not been widely recognized or identified due to poor or no conventional oil production. Hence, in places like the Illinois Basin (ILB), exploratory analyses are required to recognize the existence of an ROZ. As part of this study, four formations were selected for detailed regional characterization and analysis: Carper Sandstone (part of the Borden Siltstone), Tar Springs Sandstone, Cypress Sandstone, and Middle Devonian (Geneva Dolomite and associated Dutch Creek Sandstone). The four formations underwent regional geological characterization to develop a regional geologic framework for the ROZs and their overlying seals. Findings of this study are supported by data from two field laboratory sites, one with stacked greenfield ROZs and the other with a stacked complex that includes a brownfield ROZ and depleted conventional reservoirs. The field laboratory sites were used to collect data and conduct tests to validate ROZ detection methodologies and identify economic field-deployable strategies to co-optimize CO 2 -EOR and associated storage in stacked ROZs. Findings from these field sites were extrapolated to characterize the basin-wide stacked ROZ fairway resource.

01 COAL, LIGNITE, AND PEAT↗

Assessment of Contaminant Bioaccumulation in Aquatic Biota on and Adjacent to the Oak Ridge Reservation—2020

This report provides information on contaminant concentrations in multiple wildlife prey species inhabiting or associated with water bodies on and downstream from the Oak Ridge Reservation (ORR), including regional reference sites. This information can be used to understand the nature and extent of contaminant exposure and transfer through the food web and to provide a baseline for evaluating temporal trends in contaminant exposure and accumulation. This information was gathered as part of the Comprehensive Environmental Response, Compensation, and Liability Act (CERCLA) Five-Year Review (FYR) process, and it also addresses regulator comments on the annual Remediation Effectiveness Report (RER). This report summarizes the results of biological sampling completed in the spring and summer of 2020, prior to the 2021 FYR. Sampled locations included key sites upstream from the point sources of contaminants, along with watershed integration points on and off the ORR. Integration points are spatially the most important sampling sites because they capture biological responses to upstream contaminant inputs from both aqueous and groundwater sources, as well as responses to various remedial actions. These sites are most often located at a watershed administration unit boundary and may have regulatory significance for performance measures. In many cases, there are long-term biological and other monitoring data associated with these sites; these data generally fall within the areas of exposure and effects.

54 ENVIRONMENTAL SCIENCES↗

Leveraging Environmental Monitoring Results from Department of Energy Sites for Research on the Food-Energy-Water Nexus

The Annual Site Environmental Report (ASER) from a U.S. Department of Energy (DOE) Site summarizes environmental data; environmental management performance; compliance with applicable DOE, federal, state, and local regulations; and restoration and surveillance monitoring programs. The Savannah River Site (SRS) produces ASERs that include results of monitoring mercury levels in fish samples obtained in the vicinity of SRS. Mercury is a toxic trace metal and the methylated organic form is a neurotoxin that bioaccumulates in the food web, endangering humans and other organisms. In United States, power plants are the largest source of mercury emissions. Research Objective: To determine the patterns of mercury levels in fish samples reported in the SRS environmental monitoring reports. We developed box plot visualizations to make sense of the data as well as identify fish species, dates and location with outlier mercury content. The integration and visual representation of multi-year datasets can support decision making processes on environmental compliance and environmental sustainability conducted at U.S. DOE Sites. We are constructing datasets from textual, image and multivariable data sources in the multi-year ASERs of the U.S. DOE Savannah River Site (SRS https://www.srs.gov/general/pubs/ERsum/index.html). The Fish Surveillance for mercury presents a case study for the intersection of food, energy and water systems. The dataset of 864 records (2008 and 2009) of mercury levels includes water location of fish, fish species, collection date and mercury content of fish sample. The patterns of mercury levels in the fish species as well as locations provide knowledge for further investigations. A research area for future studies is the composition of microbial communities in fish guts of varying levels of mercury.

54 ENVIRONMENTAL SCIENCES↗

Wind River Experimental Forest Subcanopy Tower Information Sheet

Wind River was one of three sites that collected 3d sonic anemometer data for an ICOS subcanopy observation study. The three sites were defined by the following features and terrain: a deciduous broadleaf forest in flat terrain (Lanžhot, Czech Republic), a coniferous forest in mountainous terrain (Renon, Italy), and a tall conifer forest in mountain-valley terrain (Wind River, USA). The Wind River subcanopy towers were deployed in a high LAI, old-growth evergreen conifer forest and collected approximately 11 months of data. The site is an ecologically rich temperate rainforest in the western Cascade Mountains, and the biological carbon sink and source strength has been measured since 1998 using eddy covariance on the top of a 74 m tall flux tower (currently called the Wind River NEON tower). Additionally, forest inventory records date back to the 1920s. In 2024, four subcanopy towers were installed near the Wind River NEON tower to measure wind flow in the understory canopy layer for better understanding canopy flow coupling and decoupling in the subcanopy and how this affects the interpretation of overstory fluxes. The subcanopy tower installation was done by Lawrence Livermore National Laboratory and Washington State University (WSU) with collaborations from the University of Utah and the National Ecological Observatory Network (NEON).

54 ENVIRONMENTAL SCIENCES↗