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At least 703 records · Page 39

Interannual Variability in the Thermal Habitat of Alexandrium catenella in the Bay of Fundy and the Implications of Climate Change

Globally, harmful algal blooms (HABs) are an increasing problem. In the Gulf of Maine and Bay of Fundy, blooms of the toxic dinoflagellate Alexandrium catenella are annually recurrent phenomena. As this region is one of the most rapidly warming areas of the global ocean, an improved understanding of the mechanisms driving the initiation of local A. catenella blooms, their interannual variability and the implications of future climate change is critical to local monitoring strategies and marine resources management. A 27-year (1988–2014) time series of weekly A. catenella cell counts from the Bay of Fundy and concurrent satellite-measured sea surface temperature, freshwater discharge from the St. John River and wind-driven turbulence are compared to assess their relationship to variability in bloom phenology metrics. The mean thermal habitat associated with early detection of A. catenella is 6.5 ± 1.6°C, whereas that of bloom initiation averages 9.2 ± 1.5°C. Both thermal habitats for A. catenella are trending earlier over the study period. Bloom initiations that precede the arrival of the thermal habitat mean (occur in colder water) are associated with higher spring freshwater discharge and are generally weaker blooms. Increased spring freshwater discharge is also associated with earlier bloom initiation and earlier maximum concentration dates. No significant relationship was observed with the strength of wind-driven mixing. Removal of the mean thermal seasonal cycle shows that surface temperature anomalies have a strong negative relationship to the bloom phenology metrics and arrival of thermal habitat: warmer years are linked to earlier arrival of thermal habitats (∼12 days °C–1) and earlier detection and bloom initiation dates (∼33 days °C–1). Using these relationships and present trends in Bay of Fundy surface temperature warming over the period 1982–2019, we project the arrival dates of bloom thermal habitat and bloom phenology metrics out to the middle of this century. Based on current rates of sea surface temperature change, bloom phenology metrics (e.g., bloom initiation, early detection), can be expected to shift 1–2 months earlier in the season by mid-century. Such changes in the phenology of A. catenella blooms will need to be incorporated into both monitoring strategies and forecasting models for the region.

Andre F. Bucci↗

Understanding Economic and Deployment Benefits of Wind-PV Hybrid Power Plants

The least-cost approach to decarbonizing the U.S. electricity supply will likely involve a significantly expanded share of variable renewable energy (VRE) generation. Many strategies and approaches have been identified to address integration challenges in a VRE-dominated system, including standalone and coupled battery systems. In this study, we explored the current and future potential of utility-scale hybrid energy systems comprising PV, wind, and lithium-ion battery technologies (PV-wind-battery systems). Analysis results include temporal complementarity of wind and PV resources across the contiguous United States, with an emphasis on metrics that quantify reductions in variability that can be achieved through hybridization. We further use a price-taker model with simulated hourly energy and capacity prices to determine the revenue-maximizing dispatch of a range of PV-wind-battery configurations across Texas, from the present through 2050. We find that coupling PV, wind, and battery technologies allows for more effective utilization of interconnection capacity by increasing capacity factors to 60-80%+ and capacity credits to close to 100%, depending on battery capacity. We also compared the energy and capacity values of PV-wind and PV-wind-battery systems to the corresponding stability coefficient metric, which describes the location-and configuration-specific complementarity of PV and wind resources. Our results show that the stability coefficient effectively predicts the configuration-location combinations in which a smaller battery component can provide comparable economic performance in a PV-wind-battery system (compared to a PV-battery system). These PV-wind-battery hybrids can help integrate more VRE by providing smoother, more predictable generation and greater flexibility. Finally, capacity expansion modeling of PV-wind systems indicates that hybridization can reduce transmission expansion requirements associated with a heavily decarbonized U.S. electricity system.

complementarity↗

A Framework Using Applied Process Analysis Methods to Assess Water Security in the Vu Gia–Thu Bon River Basin, Vietnam

The Vu Gia–Thu Bon (VG–TB) river basin is facing numerous challenges to water security, particularly in light of the increasing impacts of climate change. These challenges, including salinity intrusion, shifts in rainfall patterns, and reduced water supply in downstream areas, are of great concern. This study comprehensively assessed the current state of water security in the basin using robust statistical analysis methods such as the Process Analysis Method (PAM), SMART principle, and Analytic Hierarchy Process (AHP). This resulted in the development of a comprehensive assessment framework for water security in the VG–TB river basin. This framework identified five key dimensions, with basin development activities (0.32), the ability to meet water needs (0.24), and natural disaster resilience (0.19) being the most crucial and water resource potential being the least crucial (0.11) according to the AHP methodology. The latter also highlighted 15 indicators, four of which are particularly influential, including waste resources (0.54), flood (0.53), water storage capacity (0.45), and basin governance (0.42). Furthermore, 28 variables with high weight factors were identified. This framework aligns with the UN-Water water security definition and addresses the global water sustainability criteria outlined in Sustainable Development Goal 6 (SDG6). It enables the computation of a comprehensive Water Security Index (WSI) for specific regions, providing a strong foundation for decision-making and policy formulation. It aims to enhance water security in the context of climate change and support sustainable basin development, thereby guiding future research and policy decisions in water resource management.

54 ENVIRONMENTAL SCIENCES↗

Sensitivity of Mountain Hydroclimate Simulations in Variable-Resolution CESM to Microphysics and Horizontal Resolution

Mountains are natural dams that impede atmospheric moisture transport and water towers that cool, condense, and store precipitation. They are essential in the western United States where precipitation is seasonal, and snowpack is needed to meet water demand. With anthropogenic climate change increasingly threatening mountain snowpack, there is a pressing need to better understand the driving climatological processes. However, the coarse resolution typical of modern global climate models renders them largely insufficient for this task, and signals a need for an advanced strategy. This paper continues the assessment of variable-resolution in the Community Earth System Model (VR-CESM) in modeling mountain hydroclimatology to understand the role of grid-spacing at 55, 28, 14, and 7 km and microphysics, specifically the Morrison and Gettelman (2008, MG1, https://doi.org/10.1175/2008JCLI2105.1) scheme versus the Gettelman and Morrison (2015, MG2, https://doi.org/10.1175/JCLI-D-14-00102.1) scheme. Eight VR-CESM simulations were performed from 1999 to 2015 with the F_AMIP_CAM5 component set, which couples the atmosphere-land models and prescribes ocean data. Refining horizontal grid-spacing from 28 to 7 km with the MG1 scheme did not improve the simulated mountain hydroclimatology. Substantial improvements occurred with the use of MG2 at grid-spacings ≤28 km compared to MG1 as shown with subsequent statistics. Average SWE bias diminished by 9.4X, 4.9X, and 3.5X from 55 to 7 km. The range in minimum (maximum) DJF spatial correlations increased by 0.1–0.2 in both precipitation and SWE. Mountain windward/leeward distributions and elevation profiles improved across hydroclimate variables, however not always with model resolution alone. Disconcertingly, all VR-CESM simulations exhibited a systemic mountain cold bias that worsened with elevation and will require further examination.

58 GEOSCIENCES↗

Representing Socio‐Economic Uncertainty in Human System Models

Abstract Socio‐economic development pathways and their implications for the environment are highly uncertain, and energy transitions will involve complex interactions among sectors. Here, traditional Monte Carlo analysis is paired with scenario discovery techniques to provide a richer portrait of these complexities. Modeled uncertain input variables include costs of advanced energy technologies, energy efficiency trends, fossil fuel resource availability, elasticities of substitution for labor, capital, and energy across economic sectors, population growth, and labor and capital productivity. The sampled values are simulated through a multi‐sector, multi‐region, recursively dynamic model of the world economy to explore a range of possible future outcomes. We find that many patterns of energy and technology development are possible for various long‐term environmental pathways and that sectoral output for most sectors is little affected through 2050 by the long‐term temperature target, but with tight constraints on emissions, emission intensities must fall much more rapidly. Scenario discovery techniques are applied to the large uncertainty ensembles to explore if there are prevailing storylines behind outcomes of interest. An illustrative investigation focused on different levels of economic growth shows many combinations of pathways and no single storyline emerging for a given economic outcome. This method can be extended to other outcomes of interest, exploring the nature of scenarios with both tail and median outcomes. Sampling from a Monte Carlo generated ensemble provides a rich set of scenarios to investigate, and potentially aids in avoiding heuristic biases in less structured scenario approaches.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Evaluation of Ocean Biogeochemistry and Carbon Cycling in CMIP Earth System Models With the International Ocean Model Benchmarking (IOMB) Software System

Abstract The International Ocean Model Benchmarking (IOMB) software package is a new community resource that we use here to evaluate surface and upper ocean biogeochemical variables and integrated anthropogenic carbon uptake from earth system models (ESMs) contributing to the 5th and 6th phases of the Coupled Model Intercomparison Project (CMIP5 and CMIP6). IOMB generates graphics and tables for systematically comparing model predictions against multiple datasets. Our analysis reveals some improvement in the multi‐model mean from CMIP5 to CMIP6 for most of the variables we examined. Compared to data‐constrained estimates of ocean anthropogenic carbon uptake for the 1994–2007 period, negative biases exist for many models between 30 and 50°S. Global model estimates of anthropogenic carbon uptake for the same period do not change significantly from CMIP5 to CMIP6, with the combined ensemble mean estimate of 27.8 ± 0.5 Pg C lower than a data‐constrained estimate of 33.0 ± 4.0 Pg C. At the same time, the change in the natural carbon inventory from CMIP is estimated to be a source of 0.7 ± 0.3 Pg C, which is considerably smaller in magnitude than a data‐constrained estimate of 5.0 ± 3.0 Pg C. With chlorofluorocarbon (CFC) predictions available for several models, we demonstrate that negative anthropogenic dissolved inorganic carbon biases coincide with negative biases in CFC concentration, highlighting the importance of weak exchange between the surface and interior ocean in regulating rates of anthropogenic carbon uptake. To examine the robustness of this attribution across the CMIP models, we calculate the global vertical temperature gradient between 200 and 1,000 m as a metric for global stratification and exchange between the surface and deeper waters. We find a linear relationship between the bias of the vertical temperature gradients and the bias in global anthropogenic carbon uptake, consistent with the hypothesis that model biases in anthropogenic carbon uptake are related to biases in surface‐to‐interior exchange by physical processes.

58 GEOSCIENCES↗

Extending the Frontier of Quantum Computers with Qutrits

Here, we advocate for a fundamentally different way to perform quantum computation by using three-level qutrits instead of qubits. In particular, we substantially reduce the resource requirements of quantum computations by exploiting a third state for temporary variables (ancilla) in quantum circuits. Past work with qutrits has demonstrated only constant factor improvements, owing to the log 2 (3) binary-to-ternary compression factor. We present a novel technique using qutrits to achieve a logarithmic runtime decomposition of the Generalized Toffoli gate using no ancilla - an exponential improvement over the best qubit-only equivalent. Our approach features a 70× improvement in total two-qudit gate count over the qubit-only decomposition. This results in improvements for important algorithms for arithmetic and QRAM. Simulation results under realistic noise models indicate over 90% mean reliability (fidelity) for our circuit, versus under 30% for the qubit-only baseline. These results suggest that qutrits offer a promising path toward extending the frontier of quantum computers.

97 MATHEMATICS AND COMPUTING↗

Assessing rare earth element concentrations in geothermal and oil and gas produced waters: A potential domestic source of strategic mineral commodities (Final Report)

The project team collected and analyzed 224 water samples and 101 matching rock samples. INL's improved method of measuring aqueous REEs allows study of samples previously thought too volume limited to measure. The study found that aqueous REEs occur at trace levels in all analyzed samples, and sometimes exceed ocean REE concentrations by a factor of 1,000. No significant predictive relationship to lithology, reservoir temperature, nor salinity was discovered, but aqueous REE concentration appears spatially controlled. Future work is needed to find the spatially-dependent variable that controls aqueous REE concentration.

15 GEOTHERMAL ENERGY↗

Microbial Community Structure–Function Relationships in Yaquina Bay Estuary Reveal Spatially Distinct Carbon and Nitrogen Cycling Capacities

Linking microbial community structure to ecological processes requires understanding of the functional roles among individual populations and the factors that influence their distributions. These structure–function relationships are particularly difficult to disentangle in estuaries, due to highly variable physico-chemical conditions. Yet, examining microbe-mediated turnover of resources in these “bioreactor” ecosystems is critical for understanding estuarine ecology. In this study, a combined metagenomics and metaproteomics approach was used to show that the unequal distribution of microbial populations across the Yaquina Bay estuary led to a habitat-specific taxonomic and functional structure and a clear spatial distribution in microbe-mediated capacities for cycling of carbon and nitrogen. For example, size-fractionation revealed that communities inhabiting suspended particulate material encoded more diverse types of metabolisms (e.g., fermentation and denitrification) than those with a planktonic lifestyle, suggesting that the metabolic reactions can differ between size fractions of the same parcel of an estuarine water column. Similarly, communities inhabiting oligotrophic conditions in the lower estuary were enriched in genes involved in central carbon metabolism (e.g., TCA cycle), while communities in the upper estuary were enriched in genes typical of copiotrophic populations (e.g., cell growth, cell division). Integrating gene and protein data revealed that abundant populations of Flavobacteriales and Rhodobacterales encoded similar genomic functions, yet differed significantly in protein expression, dedicating a large proportion of their respective proteomes to rapid growth and division versus metabolic versatility and resource acquisition. This suggested potentially distinct life-strategies between these two co-occurring lineages and was concomitant with differing patterns of positive evolutionary selection on their encoded genes. Microbial communities and their functions across Yaquina Bay appear to be structured by population-level habitat preferences, resulting in spatially distinct elemental cycling, while within each community, forces such as competitive exclusion and evolutionary selection influence species life-strategies and may help maintain microbial diversity.

59 BASIC BIOLOGICAL SCIENCES↗

Examining Uncertainty in Demand Response Baseline Models and Variability in Automated Response to Dynamic Pricing

Controlling electric loads to deliver power system services presents a number of interesting challenges. For example, changes in electricity consumption of Commercial and Industrial (C&I) facilities are usually estimated using counterfactual baseline models, and model uncertainty makes it difficult to precisely quantify control responsiveness. Moreover, C&I facilities exhibit variability in their response. This paper seeks to understand baseline model error and demand-side variability in responses to open-loop control signals (i.e. dynamic prices). Using a regression-based baseline model, we define several Demand Response (DR) parameters, which characterize changes in electricity use on DR days, and then present a method for computing the error associated with DR parameter estimates. In addition to analyzing the magnitude of DR parameter error, we develop a metric to determine how much observed DR parameter variability is attributable to real event-to-event variability versus simply baseline model error. Using data from 38 C&I facilities that participated in an automated DR program in California, we find that DR parameter errors are large. For most facilities, observed DR parameter variability is likely explained by baseline model error, not real DR parameter variability; however, a number of facilities exhibit real DR parameter variability. In some cases, the aggregate population of C&I facilities exhibits real DR parameter variability, resulting in implications for the system operator with respect to both resource planning and system stability.

24 POWER TRANSMISSION AND DISTRIBUTION↗

Computational Risk Analysis of Propane Releases in Maintenance Facilities

Liquefied petroleum gas (LPG) is a viable, cleaner alternative to traditional diesel fuel used in busses and other heavy-duty vehicles and could play a role in helping the US meet its lower emission goals. While the LPG industry has focused efforts on developing vehicles and fueling infrastructure, we must also establish safe parameters for maintenance facilities which are servicing LPG fueled vehicles. Current safety standards aid in the design of maintenance facilities, but additional quantitative analysis is needed to prove safeguards are adequate and suggest improvements where needed. In this report we aim to quantify the amount of flammable mass associated with propane releases from vehicle mounted fuel vessels within enclosed garages. Furthermore, we seek to qualify harm mitigation with variable ventilations and facility layout. To accomplish this we leverage validated computational resources at Sandia National Laboratories to simulate various release scenarios representative of real world vehicles and maintenance facilities. Flow solvers are used to predict the dynamics of fuel systems as well as the evolution of propane during release events. From our simulated results we observe that both inflow and outflow ventilation locations play a critical role in reducing flammable cloud size and potential overpressure values during a possible combustion event.

03 NATURAL GAS↗

Spatial variability of surface temperature as related to cropping practice with implications for irrigation management

Crop stress measured using thermal infrared emission is evaluated with the stress-degree-day (SDD) concept. Throughout the season, the accumulation of SDD during the reproductive stage of growth is inversely related to yield. This relationship is shown for durum wheat, hard red winter wheat, barley, grain sorghum and soybeans. It is noted that SDD can be used to schedule irrigations for maximizing yields and for applying remotely sensed data to management of water resources. An airborne flight with a thermal-IR scanner was used to examine the variability in temperature that may exist from one field to another and to determine realistic within-field temperature variations. It was found that the airborne and the ground-based data agreed very well and that there was less variability in the fields that were completely covered with crops than those of bare soil.

Hatfield, J. L.↗

Specification of parameters for development of a spatial database for drought monitoring and famine early warning in the African Sahel

Parameters were described for spatial database to facilitate drought monitoring and famine early warning in the African Sahel. The proposed system, referred to as the African Drought and Famine Information System (ADFIS) is ultimately recommended for implementation with the NASA/FEMA Spatial Analysis and Modeling System (SAMS), a GIS/Dymanic Modeling software package, currently under development. SAMS is derived from FEMA'S Integration Emergency Management Information System (IEMIS) and the Pacific Northwest Laborotory's/Engineering Topographic Laboratory's Airland Battlefield Environment (ALBE) GIS. SAMS is primarily intended for disaster planning and resource management applications with the developing countries. Sources of data for the system would include the Developing Economics Branch of the U.S. Dept. of Agriculture, the World Bank, Tulane University School of Public Health and Tropical Medicine's Famine Early Warning Systems (FEWS) Project, the USAID's Foreign Disaster Assistance Section, the World Resources Institute, the World Meterological Institute, the USGS, the UNFAO, UNICEF, and the United Nations Disaster Relief Organization (UNDRO). Satellite imagery would include decadal AVHRR imagery and Normalized Difference Vegetation Index (NDVI) values from 1981 to the present for the African continent and selected Landsat scenes for the Sudan pilot study. The system is initially conceived for the MicroVAX 2/GPX, running VMS. To facilitate comparative analysis, a global time-series database (1950 to 1987) is included for a basic set of 125 socio-economic variables per country per year. A more detailed database for the Sahelian countries includes soil type, water resources, agricultural production, agricultural import and export, food aid, and consumption. A pilot dataset for the Sudan with over 2,500 variables from the World Bank's ANDREX system, also includes epidemiological data on incidence of kwashiorkor, marasmus, other nutritional deficiencies, and synergistically-related infectious diseases.

Rochon, Gilbert L.↗

A Data-Driven Approach to Dynamic Var Compensator Placement for Local Voltage Stabilization on Feeders with High PV Penetration

Distribution feeders with a high penetration of distributed photovoltaic (PV) systems can experience voltage variability caused by the changing load flow injections corresponding to the availability of the solar resource. The rapid, uncontrolled voltage range fluctuations can affect the system. Tap-changing voltage regulators, switched capacitors, and smart inverter functions have been used to stabilize voltage. However, in some cases, when these options are insufficient or unavailable, dedicated reactive power control devices such as dynamic var compensators (DVCs) can be used for local voltage stabilization. This paper introduces a statistical framework to characterize voltage variability and stabilization, proposes a data-driven approach to DVC placement, and presents the results of a planning study on a real feeder using real data.

Reiman, Andrew P.↗

Queue wait time prediction in high performance computing (HPC) systems

High Performance Computing (HPC) systems are critical enablers for groundbreaking scientific research across various domains. Efficient resource allocation, facilitated by job scheduling, is paramount for maximizing the utilization of HPC systems. However, the variability in wait times for queued jobs poses challenges for users, necessitating accurate job wait time estimation. This paper explores the influence of job characteristics, including job size (the number of nodes requested and walltime), the queue to which the job is submitted and other resource requirements, on job wait times in leadership-class HPC systems. Focusing on the Theta Cray XC40 and Polaris machines at Argonne National Laboratory, the study evaluates the performance of different supervised learning algorithms in predicting job wait times. It also evaluates the impact of data preprocessing, including outlier detection, Principal Component Analysis (PCA), and feature selection, on the performance of wait time prediction models. The findings reveal insights into the relationship between job characteristics and wait times, offering a foundation for optimizing resource allocation and enhancing user experience. The methodologies and tools developed in this study are adaptable to other leadership-class HPC systems, providing a valuable contribution to the broader HPC community aiming to improve job scheduling efficiency and user satisfaction.

Okafor, Nwamaka↗

Seasonal variability of wake impacts on US mid-Atlantic offshore wind plant power production

Abstract. The mid-Atlantic will experience rapid wind plant development due to its promising wind resource located near large population centers. Wind turbines and wind plants create wakes, or regions of reduced wind speed, that may negatively affect downwind turbines and plants. We evaluate wake variability and annual energy production with the first yearlong modeling assessment using the Weather Research and Forecasting model, deploying 12 MW turbines across the domain at a density of 3.14 MW km−2, matching the planned density of 3 MW km−2. Using a series of simulations with no wind plants, one wind plant, and complete build-out of lease areas, we calculate wake effects and distinguish the effect of wakes generated internally within one plant from those generated externally between plants. We also provide a first step towards uncertainty quantification by testing the amount of added turbulence kinetic energy (TKE) by 0 % and 100 %. We provide a sensitivity analysis by additionally comparing 25 % and 50 % for a short case study period. The strongest wakes, propagating 55 km, occur in summertime stable stratification, just when New England's grid demand peaks in summer. The seasonal variability of wakes in this offshore region is much stronger than the diurnal variability of wakes. Overall, yearlong simulated wake impacts reduce power output by a range between 38.2 % and 34.1 % (for 0 %–100 % added TKE). Internal wakes cause greater yearlong power losses, from 29.2 % to 25.7 %, compared to external wakes, from 14.7 % to 13.4 %. The overall impact is different from the linear sum of internal wakes and external wakes due to non-linear processes. Additional simulations quantify wake uncertainty by modifying the added amount of turbulent kinetic energy from wind turbines, introducing power output variability of 3.8 %. Finally, we compare annual energy production to New England grid demand and find that the lease areas can supply 58.8 % to 61.2 % of annual load. We note that the results of this assessment are not intended to make nor are they suitable to make commercial judgments about specific wind projects.

17 WIND ENERGY↗

Enhancing Power System Operational Flexibility With Flexible Ramping Products: A Review

With the increased variability and uncertainty of net load induced from high penetrations of renewable energy resources and more flexible interchange schedules, power systems are facing great operational challenges in maintaining balance. Among these, the scarcity of ramp capability is an important culprit of power balance violations and high scarcity prices. To address this issue, market-based flexible ramping products (FRPs) have been proposed in the industry to improve the availability of ramp capacity. This paper presents an in-depth review of the modeling and implementation of FRPs. The major motivation is that although FRPs are widely discussed in the literature, it is still unclear to many how they can be incorporated into a co-optimization framework that includes energy and ancillary services. The concept and a definition of power system operational flexibility as well as the needs for FRPs are introduced. The industrial practices of implementing FRPs under different market structures are presented. Market operation issues and future research topics are also discussed. In conclusion, this paper can provide researchers and power engineers with further insights into the state of the art, technical barriers, and potential directions for FRPs.

24 POWER TRANSMISSION AND DISTRIBUTION↗

An Examination of the Hydropower Licensing and Federal Authorization Process

Site-permitting and regulation are necessary to ensure hydropower projects (both original and relicensed) comply with statutory requirements and address multiple stakeholder priorities that consider a range of factors, including water quality, species protection, cultural resource impacts, and recreation. However, the time involved in acquiring a license for an individual hydropower project can be highly variable by project, leading to increased project costs, financial risks, and uncertainties. In part, this variability is the result of a regulatory structure that has evolved over time to include multiple approvals and compliance requirements administered by the Federal Energy Regulatory Commission (FERC), U.S. Army Corp of Engineers (USACE), federal land management agencies, federal and state resource agencies, and Indian Tribes. Ultimately, the time, benefits, costs, and risks to developers associated with hydropower regulatory processes and/or the preparation (e.g., studies) required for regulatory agency review are not well documented or synthesized in the public domain, which may increase uncertainty and variability within the process. This report addresses these needs by presenting results of a comprehensive examination of hydropower licensing including quantitative and qualitative analyses of timelines, causal factors, and their combined effect on risk and costs to developers.

13 HYDRO ENERGY↗