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At least 289 records · Page 16

An Overview of Arizona's Electric Grid Resilience Using TASTI-GRID

This document provides a concise overview of the analytical capabilities of the TASTI-GRID team. Utilizing additional data and resources, it synthesizes platform insights to present a distinct perspective on investing in grid resilience throughout Mississippi. This document is not intended to influence or direct state- level decisions related to investments in grid resilience and reliability. TASTI-GRID should not be used for real-time monitoring, supporting the ESF #12 emergency response functions, or predicting the restoration times for outages.

24 POWER TRANSMISSION AND DISTRIBUTION↗

TASTI-GRID: An Overview of Minnesota's County and Tribal Electric Grid Resilience

This document provides a concise overview of the analytical capabilities of the TASTI-GRID team. Utilizing additional data and resources, it synthesizes platform insights to present a distinct perspective on investing in grid resilience throughout Mississippi. This document is not intended to influence or direct state- level decisions related to investments in grid resilience and reliability. TASTI-GRID should not be used for real-time monitoring, supporting the ESF #12 emergency response functions, or predicting the restoration times for outages.

24 POWER TRANSMISSION AND DISTRIBUTION↗

ARM Aerial Facility (AAF) Merged Value-Added Product Report for Historical G-1 Field Campaigns

For 30 years, the U.S. Department of Energy (DOE) Office of Science supported an instrumented Grumman Gulfstream-1 (G-1) aircraft for atmospheric field campaigns. Data from the final decade of G-1 operations were archived by the Atmospheric Radiation Measurement (ARM) user facility Data Center (ADC) and made publicly available at no cost to all registered users. To ensure a consistent data format and to improve the accessibility of the ARM airborne data, an integrated data set was recently developed covering the final six years of G-1 operations (2013 to 2018). The integrated data set includes data collected from 236 flights (766.4 hours). Four of the seven field campaigns were based in the U.S. One campaign collected data from the wildfires in the U.S. Pacific Northwest and agricultural burns in the lower Mississippi River valley as part of the Biomass Burning Observation Project (BBOP) in 2013. In 2015, the ARM Cloud Aerosol Precipitation Experiment provided data on atmospheric rivers and associated aerosol-cloud interactions that produce heavy precipitation on the U.S. west coast during the early spring. Research data from Airborne Carbon Measurements-V (ACME-V), collected during the summer of 2015, gave scientists insight into trends and variability of trace gases in the atmosphere over the North Slope of Alaska to improve arctic climate models. In the early summer and autumn of 2016, the Holistic Interactions of Shallow Clouds, Aerosols, and Land-Ecosystems (HI-SCALE) campaign provided an extensive data set geared toward coupled processes that affect the life cycle of shallow clouds through the interaction among aerosol, cloud, land surface, and ecosystems. In 2014 (March and October), the airborne sampling moved outside of the U.S. to the city of Manaus in central Amazonia, Brazil, where residential and industrial emissions were extensively characterized by flights of the G-1. The GoAmazon2014/15 aircraft campaign data are being integrated with aquatic and terrestrial ecosystem measurements to quantify anthropogenic perturbations to a usually pristine tropical environment. Another international airborne mission was carried out in the Eastern North Atlantic region. The Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) campaign saw the G-1 aircraft fly from Terceira Island in the Azores during the summer of 2017 and the winter of 2018. The campaign studied both seasons to measure key aerosol and cloud processes under various meteorological and cloud conditions with different aerosol sources. Then the G-1 deployed to the Sierras de Córdoba range in central Argentina from October to November 2018 for the Cloud, Aerosol, and Complex Terrain Interactions (CACTI) campaign to study orographic convective cloud interactions with their surrounding environment. These comprehensive datastreams provide much-needed insight into spatiotemporal variability of thermodynamic quantities, aerosol and cloud states, and properties for addressing essential science questions in Earth system process studies.

54 ENVIRONMENTAL SCIENCES↗

First Report and Molecular Variability of Belonolaimus longicaudatus Associated with Turfgrass in Maryland

Abstract Turfgrass is a crop used extensively in athletic fields and golf courses in Maryland. A soil sample collected in July 2023 from an athletic field in Baltimore County, Maryland, part of a turfgrass nematode survey, containedBelonolaimus longicaudatus. In the southeastern United States,B. longicaudatusis an economically important pathogen of warm season turfgrass. The density was four individuals/100 cm 3 of soil, and no visual symptoms were observed in the bermudagrass field. Morphological features and morphometrics of males and females were consistent withB. longicaudatusand placed the Maryland population in a subclade that was geographically represented by populations from north and west Florida, Texas, and South Carolina. Sequencing of the internal transcribed spacer region ITS1 and ITS2 and 28S large ribosomal subunit D2-23 expansion region confirmed the species' identity. Phylogenetic trees and parsimony network analysis placed the Maryland isolate in a large grouping ofB. longicaudatuspopulations including those from Alabama, Delaware, Florida, Indiana, Mississippi, South Carolina, and Texas. To our knowledge, this is the first report ofB. longicaudatusin Maryland.

Zoology↗

ARPA-E Grid Optimization (GO) Competition Challenge 3

Synthetic Input Data and Team Results for the GO Competition Challenge 3 for Events 1 - 4 and the Sandbox, along with problem and format descriptions and code to validate data and solutions, are available here. Data for industry scenarios will not be made public. The Grid Optimization (GO) Competition Challenge 3 focused on the security-constrained optimal power flow (SCOPF) problem. It is part of a continuing effort begun with Challenges 1 and 2, to successfully discover, develop, and test innovative and disruptive software solutions for critical energy challenges and to overcome existing barriers. The broader goal of the of the GO Competition is to accelerate the development of transformational and disruptive methods for solving problems related to the electric power grid and to provide a transparent, fair, and comprehensive evaluation of new solution methods. Challenge 3 used multiperiod dynamic markets, including advisory models for extreme weather events, day-ahead markets, and the real-time markets with an extended look-ahead. In Event 4, whose submission window was August 31-September 4, 2023, 14 teams solved for the objective values of 669 scenarios (39 scenarios required solutions both with and without line switching being allowed). The 591 synthetic scenarios from 9 network models (3.6 GB) are available here. Ten teams were funded to participate and 7 won prizes totaling $2,400,000. The largest prize ($550,000) went to Mississippi State University. An additional $600,000 was awarded in Event 3 (6/15-16/2023). No prizes were awarded in Events 1 (1/25-27/2023) or 2 (4/13-14/2023). For more information on the competition and challenge see the "GO Competition Challenge 3 Information" resource below.

ACOPF↗

The Influence of Shallow Subsurface Properties on Particle Motion in Acoustic-Seismic Coupling

Atmospheric acoustic waves transmit energy into the solid Earth through air-to-ground coupling. These waves are recorded by seismic sensors and provide insight into both atmospheric phenomena and subsurface properties. Interpreting these signals is often challenging because they are modulated by subsurface structure and the incidence angle of the acoustic wave. This study examines acoustic--seismic coupling generated by the 2012 Camp Minden Explosion, which was recorded by hundreds of seismoacoustic stations. We apply a novel technique to quantify the seismic particle motion, model coupled waves with a propagator matrix approach, and apply a Bayesian inversion to infer properties of the shallow subsurface. Our analysis reveals that prograde motion is widespread and focused in low shear-wave velocity regions, such as the Mississippi Embayment, and retrograde motion is more common in higher shear-velocity areas. Inversion results at some stations produce plausible subsurface models with strong waveform fits, while inversions at other sites are less successful. These results indicate prograde particle motion in air-to-ground coupled waves is more prevalent than previously recognized and may serve as a diagnostic for shallow velocity structure. Our comprehensive modeling and inversion framework provides a potential method to extract layered near-surface properties from acoustic-seismic coupling observations.

58 GEOSCIENCES↗

Comprehensive Economic Impacts ofWild Pigs on Producers of Six Crops in the South-Eastern US and California

Wild pigs (Sus scrofa) cause damage to agricultural crops in their native range as well as in the portions of the globe where they have been introduced. In the US, states with the highest introduced wild pig populations are Alabama, Arkansas, California, Florida, Georgia, Louisiana, Mississippi, Missouri, North Carolina, South Carolina, and Texas. The present study summarizes the first survey-based effort to value the full extent of wild pig damage to producers of six crops in these eleven US states. The survey was distributed by the USDA National Agricultural Statistical Service in the summer of 2022 to a sample of 11,495 producers of corn (Zea mays), soybeans (Glycine max), wheat (Triticum spp.), rice (Oryza sativa), peanuts (Arachis hypogaea), and sorghum (Sorghum bicolor) in these 11 states. Our findings suggest that the economic burden of wild pigs on producers of these crops is substantial and not limited to the direct and most identifiable categories of crop damage (i.e., production value lost due to depredation, trampling and rooting). We estimate that the annual cost to producers of these six crops in the surveyed states in 2021 was almost USD 700 million.

99 GENERAL AND MISCELLANEOUS↗

CO2 Storage Site Analysis, Screening, and Resource Estimation for Cenozoic Offshore Reservoirs in the Central Gulf of Mexico

The storage potential of hydrocarbon reservoirs in the central Gulf of Mexico (GOM) makes future development of CO2 storage projects in those areas promising for secure, large-scale, and long-term storage purposes. Focusing on the producing and depleted hydrocarbon fields in the continental slope of the central GOM, this paper analyzed, assessed, and screened the producing sands and evaluated their CO2 storage potential. A live interactive CO2 storage site screening system was built in the SAS® Viya system with a broad range of screening criteria combined from published studies. This offers the users a real-time assessment of the storage sites and enables them to adjust the filters and visualize the results to determine the most suitable filter range. The CO2 storage resources of the sands were estimated using a volumetric equation and the correlation developed by the National Energy Technology Laboratory (NETL). The results of this study indicate that 1.05 gigatons of CO2 storage resources are available in the developed reservoirs at the upper slope area of the central GOM. The Mississippi Canyon and Green Canyon protraction areas contain the fields with the largest storage resources.

Hu, Xitong↗

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

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

54 ENVIRONMENTAL SCIENCES↗

Ground-Active Arthropod Diversity Under Energycane and Biomass Sorghum Production

Energycane and biomass sorghum are two of the most promising cellulosic energy crops in the southeastern US. Research on these two energy crops has focused mainly on biomass production, and there is a lack of knowledge on their ability to promote biodiversity and ecosystem services. This paper presents results from a comprehensive study on ground-active arthropod diversity in seven sites across five states in the southeastern US (Florida, Georgia, Louisiana, Mississippi, and Texas). Pitfall traps were deployed four times during each crop season for energycane, biomass sorghum, and a local reference conventional crop from 2020 to 2022. Arthropod abundance (individuals/(trap × day)) values were 4.9 ± 0.46, 3.7 ± 0.18, and 2.6 ± 0.16 (mean ± stderr) for conventional crops, biomass sorghum, and energycane, respectively, with a significant difference found only between conventional crops and energycane. Individuals were identified to arthropod orders, and Hill’s diversity indices were calculated based on the number of individuals in each arthropod order instead of the number of individuals in each arthropod species. Order-based arthropod richness values were 5.3, 5.2, and 4.8 for biomass sorghum, conventional crops, and energycane, with significant difference found only between biomass sorghum and energycane. There was no significant difference in the order-based Shannon diversity and Simpson diversity between the three crop types. The effective number of arthropod orders for the two energy crops decreased from 5.0 to 3.4 to 2.9 with increasing order of diversity from arthropod richness to Shannon diversity to Simpson diversity. The explained variability by environmental factors also decreased with increasing Hill’s order of diversity. The results from this study indicate no significant advantage in order-based arthropod diversity in growing biomass sorghum and energycane. This research fills a critical knowledge gap in understanding the impacts of cellulosic energy crop production on biodiversity and ecosystem services.

Yang, Yubin↗

Vulnerability of Wetlands Due to Projected Sea-Level Rise in the Coastal Plains of the South and Southeast United States

Coastal wetlands are vulnerable to accelerated sea-level rise, yet knowledge about their extent and distribution is often limited. We developed a land cover classification of wetlands in the coastal plains of the southern United States along the Gulf of Mexico (Texas, Louisiana, Mississippi, Alabama, and Florida) using 6161 very-high (2 m per pixel) resolution WorldView-2 and WorldView-3 satellite images from 2012 to 2015. Area extent estimations were obtained for the following vegetated classes: marsh, scrub, grass, forested upland, and forested wetland, located in elevation brackets between 0 and 10 m above sea level at 0.1 m intervals. Sea-level trends were estimated for each coastal state using tide gauge data collected over the period 1983–2021 and projected for 2100 using the trend estimated over that period. These trends were considered conservative, as sea level rise in the region accelerated between 2010 and 2021. Estimated losses in vegetation area due to sea level rise by 2100 are projected to be at least 12,587 km 2 , of which 3224 km 2 would be coastal wetlands. Louisiana is expected to suffer the largest losses in vegetation (80%) and coastal wetlands (75%) by 2100. Such high-resolution coastal mapping products help to guide adaptation plans in the region, including planning for wetland conservation and coastal development.

54 ENVIRONMENTAL SCIENCES↗

CCS Opportunity Along the Gulf Coast Corridor

The Gulf Coast corridor, onshore and offshore, from Corpus Christ to the Mississippi River presents a high concentration of CO2 from industrial sources and excellent storage reservoirs in the underlying Cretaceous and Tertiary sands. Analysis of the technical, geologic, economic and social aspects of this CCS opportunity is necessary for successful deployment of CCS technology and eventual attainment of NetZero goals. This is the conference paper accompanying an oral presentation made at the Offshore Technology Conference (OTC) held in Houston, Texas, May 6-9, 2024.

Grant, Timothy↗

Subsurface hydrological controls on the short-term effects of hurricanes on nitrate–nitrogen runoff loading: a case study of Hurricane Ida using the Energy Exascale Earth System Model (E3SM) Land Model (v2.1)

When the nutrient level in the soil surpasses vegetation demand, nutrient losses due to surface runoff and subsurface leaching are the major reasons for the deterioration of water quality. The lower Mississippi River basin (LMRB) is one of the sub-basins that deliver the highest nitrogen loads to the Gulf of Mexico. Potential changes in episodic events induced by hurricanes may exacerbate water quality issue in the future. However, uncertainties in modeling the hydrologic response to hurricanes may limit the modeling of nutrient losses during such events. Using a machine learning approach, we calibrated the land component of the Energy Exascale Earth System Model (E3SM), or ELM, version 2.1, based on the water table depth (WTD) of a calibrated 3D subsurface hydrology model. While the overall performance of the calibrated ELM is satisfactory, some discrepancies in WTD remain in slope areas with low precipitation due to the missing lateral flow process in ELM. Simulations including biogeochemistry performed using ELM with and without model calibration showed important influences of soil hydrology, precipitation intensity, and runoff parameterization on the magnitude of nitrogen runoff loss and the leaching pathway. Despite such sensitivities, both ELM simulations produced reduced WTD and increased runoff and accelerated nitrate–nitrogen runoff loading during Hurricane Ida in August 2021, consistent with the observations. With observations suggesting more pronounced effects of Hurricane Ida on nitrogen runoff than the simulations, we identified factors for model improvement to provide a useful tool for studying hurricane-induced nutrient losses in the LMRB region.

54 ENVIRONMENTAL SCIENCES↗

Understanding the compound flood risk along the coast of the contiguous United States

Abstract. Compound flooding is a type of flood event caused by multiple flood drivers. The associated risk has usually been assessed using statistics-based analyses or hydrodynamics-based numerical models. This study proposes a compound flood (CF) risk assessment (CFRA) framework for coastal regions in the contiguous United States (CONUS). In this framework, a large-scale river model is coupled with a global ocean reanalysis dataset to (a) evaluate the CF exposure related to the coastal backwater effects on river basins, and (b) generate spatially distributed data for analyzing the CF hazard using a bivariate statistical model of river discharge and storm surge. The two kinds of risk are also combined to achieve a holistic understanding of the continental-scale CF risk. The estimated CF risk shows remarkable inter- and intra-basin variabilities along the CONUS coast with more variabilities in the CF hazard over the US west and Gulf coastal basins. Different risk assessment methods present significantly different patterns in a few key regions such as the San Francisco Bay area, the lower Mississippi River, and Puget Sound. Our results highlight the need to weigh different CF risk measures and avoid using single statistics-based or hydrodynamics-based CFRAs. Uncertainty sources in these CFRAs include the use of gauge observations, which cannot account for the flow physics or resolve the spatial variability of risks, and underestimations of the flood extremes and the dependence of CF drivers in large-scale models, highlighting the importance of understanding the CF risks for developing a more robust CFRA.

54 ENVIRONMENTAL SCIENCES↗

Assignment of Freight Traffic in a Large-scale Intermodal Network under Uncertainty

This paper presents a methodology for freight traffic assignment in a large-scale road-rail intermodal network under uncertainty. Network uncertainties caused by natural disasters have dramatically increased in recent years. Several of these disasters (e.g., Hurricane Sandy, Mississippi River Flooding, and Hurricane Harvey) severely disrupted the U.S. freight transportation network, and consequently, the supply chain. To account for these network uncertainties, a stochastic freight traffic assignment model is formulated. An algorithmic framework, involving the sample average approximation and gradient projection algorithm, is proposed to solve this challenging problem. The developed methodology is tested on the U.S. intermodal network with freight flow data from the Freight Analysis Framework. The experiments consider three types of natural disasters that have different risks and impacts on transportation networks: earthquakes, hurricanes, and floods. It is found that for all disaster scenarios, freight ton-miles are higher compared to the base case without uncertainty. The increase in freight ton-miles is the highest under the flooding scenario; this is because there are more states in the flood-risk areas, and they are scattered throughout the U.S.

42 ENGINEERING↗

State and Regional Variation in Prescription- and Payment-Related Promoters of Adherence to Blood Pressure Medication

Introduction: Medication adherence can improve hypertension management. How blood pressure medications are prescribed and purchased can promote or impede adherence. Methods: We used comprehensive dispensing data on prescription blood pressure medication from Symphony Health’s 2017 Integrated Dataverse to assess how prescription- and payment-related factors that promote medication adherence (ie, fixed-dose combinations, generic formulations, mail order, low-cost or no-copay medications) vary across US states and census regions and across the market segments (grouped by patient age, prescriber type, and payer type) responsible for the greatest number of blood pressure medication fills. Results: In 2017, 706.5 million prescriptions for blood pressure medication were filled, accounting for $29.0 billion in total spending (17.0% incurred by patients). As a proportion of all fills, factors that promoted adherence varied by state: fixed-dose combinations (from 5.8% in Maine to 17.9% in Mississippi); generic formulations (from 95.2% in New Jersey to 98.4% in Minnesota); mail order (from 4.7% in Rhode Island to 14.5% in Delaware); and lower or no copayment (from 56.6% in Utah to 72.8% in California). Furthermore, mean days’ supply per fill (from 43.1 in Arkansas to 63.8 in Maine) and patient spending per therapy year (from $38 in Hawaii to $76 in Georgia) varied. Concentration of adherence factors differed by market segment. Patients aged 18 to 64 with a primary care physician prescriber and Medicaid coverage had the lowest concentration of fixed-dose combination fills, mean days’ supply per fill, and patient spending per therapy year. Patients aged 65 years or older with a primary care physician prescriber and commercial insurance had the highest concentration of fixeddose combinations fills and mail order fills. Conclusion: Addressing regional and market segment variation in factors promoting blood pressure medication adherence may increase adherence and improve hypertension management.

60 APPLIED LIFE SCIENCES↗

Ground testing at MSFC

The large-scale field collection of acoustic data and their analysis are described in this review. The entire sound-field program has the purpose of solving complex problems of excessive noise propagation associated with the static test firing of large space-booster powerplants. The site of data collection has been Mississippi Test Facility (MTF), where far-field sound-propagation and correlated meteorological measurements were initiated in 1962. The statistical evaluation of sound-measurement data shows that the polar distribution of sound in the springtime (at MTF) is determined mainly by the temperature field of the atmosphere. Greater deformation of sound-intensity polar distribution occurs in the autumn as a result of the influence of the wind field. The data on sound attenuation as a function of distance from its source revealed attenuation in excess of the expected magnitude. The excess was mainly between 1 and 10 kilometers from the source, with maximum attenuation (17 to 18 decibels) near 6 kilometers. Excess sound attenuation was compared with calculated sound dispersion. For all sound frequencies in all seasons the deviation between reference and empirical attenuation values formed a bell-shaped distribution on a semilogarithmic plot. The physical causes for the sound- attenuation behavior are considered to be atmospheric diffraction and scattering effects. Statistical analysis of sod-intensity extremes indicated amplification of the sound signals by focusing which could be expected along selected azimuths. Empirical amplification values showed the maximum occurring in winter (50 decibels at 22 kilometers). For the analysis of correlation between empirical sound data and local atmospheric sound- propagation conditions, #e concept of analytical classification of sound-velocity profiles has been developed. Examination of over a quarter-million individual sound-velocity profiles indicates that 33 profile types for heights up to 3 kilometers constitute the empirical possibilities of sound-propagation conditions in southeastern United States. Since the focusing qualities of each sound- velocity profile can be determined as a class characteristic, the overall probabilities of focusing occurrence can he obtained. The severity of focusing, as based upon lateral spread of focusing areas, has been determined. The data for MTF indicate focusing is most severe in winter, with the direction toward east being most affected. Sound propagation is a fluctuating phenomenon because atmospheric conditions vary continuously. A measuring system for analyzing the nonstationary sound-propagation phenomena has been established. The analysis of the acoustic fluctuation data is sup- posed to provide "dynamic” perturbation functions of sound, which are to be superimposed on the related characteristic sound-velocity-profile type. The ultimate result of the program will be the establishment of reliable contingency tables showing the relationship between atmospheric parameters and far-field sound intensities. These data will be the basis for more accurate sound-propagation forecasting for static firing tests.

STATIC TESTING↗

Special projects of the geographic applications program

Alternative uses were investigated for the Mississippi Test Facility since the phaseout of Saturn 5 engine testing. Using the facility for collecting remotely sensed data is suggested for regional studies. The capabilities of various remote sensing devices to detect, identify, monitor, or determine effects of environmental pollution are summarized. Which pollutants could be monitored from spacecraft, high and low altitude aircraft, and ground based platforms are determined. Examples of special processing and enhancement and analysis techniques used in connection with remote sensing data are provided.

North, G. W.↗