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At least 1,243 records · Page 69

Causes of and Solutions to Wind Speed Bias in NREL's 2020 Offshore Wind Resource Assessment for the California Pacific Outer Continental Shelf

This report provides the results of a detailed analysis into the causes of high wind speed bias in the 20-year wind resource data set for offshore California the National Renewable Energy Laboratory (NREL) released in 2020, herein called CA20. The data set was developed using the state-of-the-art Weather Research and Forecasting (WRF) model. Notably, no floating lidars were available at the time in offshore California to validate offshore hub-height wind speeds. In late 2020, the Pacific Northwest National Laboratory (PNNL) deployed two floating lidars in the California outer continental shelf (OCS), near the Bureau of Ocean Energy Management (BOEM) call areas of Humboldt and Morro Bay. Using these observations through 2021, NREL found considerable bias in modeled hub-height winds at both locations: up to +2 m/s at Humboldt over a 6-month period, and up to +1 m/s at Morro Bay over a one-year period. Upon the discovery of this bias, the Department of Energy (DOE) and BOEM funded NREL and PNNL to investigate the causes of, impacts of, and solutions to the bias in the CA20 data set. This report summarizes the findings of this research. We first investigated whether different WRF model setups could lead to reduced bias. We found that the choice of planetary boundary layer (PBL) scheme - which controls the vertical turbulent mixing of momentum, heat, and moisture in the lowermost part of the atmosphere - greatly affected hub-height wind speeds in the region. Specifically, switching from the Mellor-Yamada-Nakanishi-Niino (MYNN) scheme used in CA20 (and widely used across a range of operational and research weather models) to the less common Yonsei University (YSU) scheme nearly eliminated the bias at both the Humboldt and Morro Bay lidar locations. The large discrepancy between the MYNN- and YSU-modeled hub-height winds pointed towards the role of atmospheric stability. In general, PBL schemes agree well in conditions of high turbulence and mixing, normally referred to as "unstable" conditions. By contrast, PBL schemes start to diverge in "stable" conditions, where turbulence is low and thermal stratification (i.e., higher temperature air sitting on top of colder air) greatly suppresses vertical mixing. Under such conditions, winds aloft can decouple from surface effects and greatly accelerate, causing high wind speeds at hub-height and frequent low-level jets (LLJs). We determined that these stable conditions are in fact dominant in offshore California. The region is characterized by moderate-to-extreme stable stratification with a LLJ on average around 200 meters above sea-level. To our knowledge, no wind energy area globally has as strongly stable stratification as offshore California. Under these extreme conditions, we determined that the MYNN scheme models higher stability than YSU, resulting in less vertical turbulent mixing than YSU, allowing for the acceleration of hub-height winds, more intense LLJs, and higher-amplitude inertial oscillations. Using surface observations, we found that MYNN overestimates near-surface stability, whereas YSU tends to model stability better. We then considered several short-term case studies to assess additional meteorological drivers of the bias at Humboldt. We found that during synoptic scale northerly flows driven by the North Pacific High and inland thermal low, a coastal warm bias in the MYNN case studies contributes to the modeled wind speed bias by altering the boundary layer thermodynamics via a thermal wind mechanism. Given the strong performance of the YSU-based runs in offshore California, NREL has produced and published an updated version of the CA20 data set with YSU as the PBL scheme. This updated data set is now part of NREL's 2023 National Offshore Wind (NOW-23) data set, which covers all the U.S. offshore waters. The development and final validation of the NOW-23 data set in offshore California is documented in this report.

17 WIND ENERGY↗

Computationally Efficient Control Co-Design Optimization Framework with Mixed-Fidelity Fluid and Structure Analysis: OpenTurbineCoDe (OTCD) - ARPA-E ATLANTIS Phase I Project (Final Technical Report)

The goal of the Department of Energy (DOE) Advanced Research Projects Agency-Energy (ARPA-E) Aerodynamic Turbines Lighter and Afloat with Nautical Technologies and Integrated Servo-control (ATLANTIS) Program is to develop new technologies for floating offshore wind turbines, or wind farms, using the discipline of control co-design (CCD.) In this context, our goal is to develop a computationally efficient optimization framework for design of floating offshore wind turbines. Our specific aim is to utilize high-fidelity structural, aerodynamic, aero-structural tools, and to derive control-oriented reduced- or low-order models directly from the high-fidelity tools. We proposed a mixed-fidelity modeling approach which means that we are also using low- and mid-fidelity tools when necessary. This research is conducted by a multidisciplinary team consisting of Rutgers University, University of Michigan, Brigham Young University, and the National Renewable Energy Laboratory (NREL). The computational framework, called OpenTurbineCoDe, is designed to integrate, where possible, traditional structural, aerodynamic, aeroelastic models (e.g., OpenFAST) and advanced control algorithms with higher fidelity simulation tools including Reynolds-averaged Navier–Stokes (RANS) solvers, and three-dimensional structural finite element solvers. All the high-fidelity tools used in this research provide numerically exact gradients to facilitate both efficient optimization and local linearization for control implementation.

17 WIND ENERGY↗

OC7 Phase I Definition Document

The Offshore Code Comparison Collaboration 7 (OC7) project is organized under the International Energy Agency Wind Technology Collaboration Programme Task 56 with an objective to evaluate and enhance the predictive accuracy of engineering-level modeling tools used in the design of offshore wind energy systems. Phase I of OC7 is focused on improving the models and modeling practices of hydrodynamic viscous loads on floating offshore wind turbine platforms. In alignment with this goal, Work Package 1.1 of OC7 Phase I is formulated to investigate the modeling of hydrodynamic viscous loads on several different geometric components commonly encountered with floating offshore wind platform designs, including cylindrical columns, heave plates, and rectangular pontoons. Work Package 1.1 also explores the dependence of hydrodynamic coefficients on the sea state to drive toward practical guidance on how these coefficients can be selected or adjusted for different conditions. This report outlines the motivation and objectives behind each subphase of OC7 Phase I, along with the necessary technical specifications and load case definitions to guide the project participants. It also serves as an important part of the project documentation for future modelers who would like to reproduce this work or make use of the data and information generated from the OC7 project.

17 WIND ENERGY↗

TEAMER – Enhanced Flow Measurement for Aquantis Tidal Turbine Test

The AQ10 is a floating, two-bladed, passive yawing tidal turbine developed by Aquantis that has a 10-meterrotor diameter, 160 kW rating, and employs reliable off-the-shelf powertrain and power conversion hardware. Aquantis is planning on-water turbine power performance and loads (blade loading and thrust)testing, where the turbine will be pushed through still water up to 4 knots and placed in a ‘station keeping’ tow in a tidal race up to its rated speed. On-water testing will be conducted using vessels and floating platforms on the sea surface to improve ease of testing and reduce disturbance to the environment. In this TEAMER project, Pacific Northwest National Laboratory (PNNL) will conduct water velocity and turbulence measurements in front of the turbine during on-water testing using acoustic Doppler instrumentation. By measuring both the tidal current flowing past the turbine and the resulting electrical power output, test results will provide a power curve (power vs flow speed) for the turbine up to rated power. Measurements of turbulence and velocity shear in front of the rotor will also provide information to assess the structural response of the rotor blades. With this analysis, Aquantis can use the performance and loads data to validate Tidal Bladed and OpenFAST simulations of the measured operating conditions. Measuring the power performance of a prototype turbine is a valuable step to improving device development and conducting a complete power performance assessment to IEC/TS 62600-200 standards in the future.

16 TIDAL AND WAVE POWER↗

Causes of and Solutions to Wind Speed Bias in NREL’s 2020 Offshore Wind Resource Assessment for the California Pacific Outer Continental Shelf

This report provides the results of a detailed analysis of the causes of high wind speed bias in the 20-year wind resource data set for offshore California that the National Renewable Energy Laboratory (NREL) released in 2020, herein called CA20. The data set was developed using the state-of-the-art Weather Research and Forecasting model. Notably, no floating lidars were available at the time in offshore California to validate offshore hub-height wind speeds. In late 2020, the Pacific Northwest National Laboratory (PNNL) deployed two floating lidars in the California Outer Continental Shelf, near the Bureau of Ocean Energy Management (BOEM) call areas of Humboldt and Morro Bay. Using these observations through 2021, NREL found considerable bias in modeled hub-height winds at both locations: up to +2 m/s at Humboldt over a 6-month period, and up to +1 m/s at Morro Bay over a 1-year period.

17 WIND ENERGY↗

U.S. Pacific Coast Workshop Report on Preconstruction Research Recommendations (U.S. Offshore Wind Synthesis of Environmental Effects Research (SEER) Project)

In May 2022, the U.S. Offshore Wind Synthesis of Environmental Effects Research (SEER) project team hosted a stakeholder workshop focused on preconstruction (baseline) research needs for potential floating offshore wind (OSW) energy development on the U.S. Pacific Coast, including California, Oregon, and Washington. Prior to the workshop, the SEER team developed a set of initial synthesized research recommendations that were identified based on a review of relevant, publicly available resources and with advisory group input. The workshop covered three marine life breakout groups on subsequent days to discuss research recommendations related to 1) marine mammals and sea turtles, 2) fish and invertebrates, and 3) birds and bats. As part of the workshop, over a hundred participants from the public and private sectors provided feedback on various aspects of the initial research recommendations, including associated data and knowledge gaps, benefits/limitations of available methods and technologies, and technological advancements or infrastructure needed to address the recommendation. Approximately 1,000 total comments were received on the workshop MURAL boards and were synthesized in this report. Based on workshop feedback, SEER developed a final database of over 500 specific research recommendations based on more than 40 resources. In Fall 2022, the full database and a tool with updated synthesized research recommendations were disseminated on Tethys (https://tethys.pnnl.gov) to assist with informing future funding opportunities and research programming. There is a continued need to improve awareness of the potential environmental effects, monitoring technologies, and management strategies for floating OSW energy development on the U.S. Pacific Coast. Coordination of these activities will require the sustained involvement of multiple stakeholders from across sectors. Beyond the baseline considerations discussed in this workshop, future state-of-the-science activities should be planned to consider research needs across wind energy life cycle phases for all relevant wildlife taxa and associated habitat and ecosystem processes.

17 WIND ENERGY↗

Additional Data Focused on Phase 1 Geared Toward Computational Fluid Dynamics (CFD) validation

A new validation campaign was developed within the Offshore Code Comparison Collaboration, Continued, with Correlation and unCertainty (OC6) to better understand the complex interactions between components of a floating wind system (e.g., columns, pontoons, etc.) in a more generic sense, and to validate modeling approaches for a variety of floating designs. A set of cylinders based on the Offshore Code Comparison Collaboration Continuation (OC4)-DeepCwind semidesign were tested under wave loading, both individually and in different combinations (including the attachment of heave plates of different sizes). The cylinders were held rigid, and pressure sensors were used to measure the distributed loading on the structures, while load cells measured the total integrated hydrodynamic loads.

17 WIND ENERGY↗

OC6 Phase III: Validation of Wind Turbine Aerodynamic Loading During Surge/Pitch Motion

The objective of Phase III of the Offshore Code Comparison Collaboration, Continued, with Correlation and unCertainty (OC6) project was to validate the accuracy of aerodynamic load predictions by offshore wind modeling tools for a floating offshore wind turbine as it experiences large surge-translational and pitch-rotational motion, as would occur during normal operation. The test data considered were generated at Politecnico di Milano – a wind tunnel with a robotic excitation system to emulate wave loading on the wind turbine. Testing was performed using a scaled version of the DTU 10-MW reference model, and motion was prescribed as harmonic oscillations in the surge and pitch directions, independently. A variety of models were examined in the project, performing a three-way validation between engineering-level tools, higher-fidelity tools, and measurement data from two wind tunnel experimental campaigns. The Load Cases (LC) considered in this testing are as follows: LC 1.X - Steady Wind LC 2.X - Unsteady Wind - Surge Motion LC 3.X - Unsteady Wind - Pitch Motion Details on the results of the OC6 Phase III campaign can be found in the following reference: Bergua R., et al. OC6 project Phase III: validation of the aerodynamic loading on a wind turbine rotor undergoing large motion caused by a floating support structure, Wind Energ. Sci., 8, 465–485, https://doi.org/10.5194/wes-8-465-2023, 2023.

17 WIND ENERGY↗

OC6 Phase Ia - Nonlinear hydrodynamic loading validation dataset

Two validation campaigns were examined within the Offshore Code Comparison Collaboration, Continued, with Correlation and unCertainty (OC6) Phase 1 project to examine the modeling tools' underprediction of loads and motion of a floating wind semisubmersible (semi) at their surge and pitch natural frequencies. These campaigns were performed at the Maritime Research Institute Netherlands (MARIN) in 2017 and 2018. The load cases (LC) considered include: LC1 – Load measurements across semi under current loading; LC2 - Load measurements across semi under forced surge oscillation; LC3 – Load measurements across semi under wave loading, while held fixed; LC4 – Free-decay motion measurements in surge, pitch, and heave; and LC5 – Motion measurements under wave loading. Details on the results from the OC6 Phase Ia project can be found in the reference, “OC6 Phase 1: Investigating the underprediction of low-frequency hydrodynamic loads and responses of floating wind turbines”, J Phys: Conf Series 1618 032033.

17 WIND ENERGY↗

FOCAL Campaign I: Advanced Wind Turbine Control Strategies

Campaign I of the Floating Offshore-wind Controls Advanced Laboratory Experimental Program (FOCAL) aims to generate a dataset enabling the validation of aerodynamic performance of a scaled turbine mounted on a rigid tower in a fixed condition. The turbine considered in the FOCAL testing campaigns is the IEA-Wind 15MW Reference Wind Turbine. This scaled model is capable of simulating advanced blade-pitch control strategies in a high-quality wind field. The turbine is fully instrumented to record a variety of parameters in real time such as structural loads and dynamics. The test data considered was generated at the University of Maine's Harold Alfond Wind and Wave (W2) testing facility. The Load Cases (LC) considered in this testing campaign are as follows: LC 1.X - Constant wind and blade-pitch with varying rotor speeds LC 2.X - Constant wind and rotor speed with varying blade-pitch LC 3.X - Varying wind with active closed-loop control Detailed properties on the modeled system are found in the following reference: Lenfest E., Floating Offshore-wind Controls Advanced Laboratory (FOCAL) Experimental Program - Campaign I: 1:70 Model-scale Testing of the IEA-Wind 15MW Reference Turbine. UMaine ASCC Report Number 23-40-1183. Details on the results of the verification and validation are found in the following reference: Mendoza, Nicole et al., "Verification and Validation of Model-Scale Turbine Performance and Control for the IEA Wind 15 MW Reference Wind Turbine," Energies, vol. 15, no. 20, 2022, https://doi.org/10.3390/en15207649.

17 WIND ENERGY↗

Dataset for the Danczak et al., 2025 manuscript about bacterial-fungal interactions

We generated genome-resolved multiomics data from a series of metagenomic and metatranscriptomic sequencing. Specifically, we acquired, functionally annotated, and taxonomically classified both bacterial and eukaryotic metagenome assembled genomes (MAGs). For bacterial MAGs, we assembled eukaryotic float metagenomic sequencing data from JGI using MEGAHIT, binned and refined MAGs using MetaWRAP and dRep, functionally annotated MAGs using eggNOG mapper, and assigned taxonomy using GTDB-tk. For eukaryotic MAGs, we first identified potentially eukaryotic contigs from a coassembly of eukaryotic float metagenomic sequencing data from JGI using EukRep and Whokaryote, binned MAGs using MetaBAT2, functionally annotated MAGs using eggNOG mapper, and assigned taxonomy using Eukulele. Bulk metatranscriptomic reads were mapped to bacterial MAGs and polyA-metatranscriptomic read were mapped to eukaryotic MAGs using bbmap.

Danczak, Robert E. [Pacific Northwest National Lab↗

An Automated Method for Mapping Giant Kelp Canopy Dynamics from UAV

Satellite and aerial imagery have been used extensively for mapping the abundance and distribution of giant kelp ( Macrocystis pyrifera ) in southern California. There is now great potential for using unoccupied aerial vehicles (UAVs) to map kelp canopy at very high resolutions. However, tides and currents have been shown to affect the amount of floating kelp canopy on the water surface, and the impacts of these processes on remotely sensed kelp estimates in this region have not been fully quantified. UAVs were used to map fine-scale changes in canopy area due to tidal height and current speed at kelp forests off the coast of Palos Verdes, CA and Santa Barbara, CA. An automated method for detecting kelp canopy was developed that was 67% accurate using red-green-blue (RGB) UAV imagery and 93% accurate using multispectral UAV imagery across a range of weather, ocean, and illumination conditions. Increases in tidal height of 1 m reduced the amount of floating kelp canopy by 15% in Santa Barbara and by over 30% in Palos Verdes. The effect of current speed on visible kelp canopy was inconclusive, but there was a trend towards lower canopy area with increased current speed. Therefore, while tidal height and current speed can introduce significant variability to estimates of kelp abundance, the magnitude of this variability is site specific. Still, UAVs are a valuable tool for mapping of kelp canopy and can provide greater spatial resolution and temporal coverage than is possible from many satellite sensors. This data can provide insight into the patterns and drivers of high frequency fluctuations in kelp abundance.

54 ENVIRONMENTAL SCIENCES↗

Fungi contribute critical but spatially varying roles in nitrogen and carbon cycling in acid mine drainage

The ecosystem roles of fungi have been extensively studied by targeting one organism and/or biological process at a time, but the full metabolic potential of fungi has rarely been captured in an environmental context. We hypothesized that fungal genome sequences could be assembled directly from the environment using metagenomics and that transcriptomics and proteomics could simultaneously reveal metabolic differentiation across habitats. We reconstructed the near-complete 27 Mbp genome of a filamentous fungus, Acidomyces richmondensis , and evaluated transcript and protein expression in floating and streamer biofilms from an acid mine drainage (AMD) system. A. richmondensis transcripts involved in denitrification and in the degradation of complex carbon sources (including cellulose) were up-regulated in floating biofilms, whereas central carbon metabolism and stress-related transcripts were significantly up-regulated in streamer biofilms. Finally, these findings suggest that the biofilm niches are distinguished by distinct carbon and nitrogen resource utilization, oxygen availability, and environmental challenges. An isolated A. richmondensis strain from this environment was used to validate the metagenomics-derived genome and confirm nitrous oxide production at pH 1. Overall, our analyses defined mechanisms of fungal adaptation and identified a functional shift related to different roles in carbon and nitrogen turnover for the same species of fungi growing in closely located but distinct biofilm niches.

59 BASIC BIOLOGICAL SCIENCES↗

Editorial: Neuroscience, computing, performance, and benchmarks: Why it matters to neuroscience how fast we can compute

At the turn of the millennium the computational neuroscience community realized that neuroscience was in a software crisis: software development was no longer progressing as expected and reproducibility declined. The International Neuroinformatics Coordinating Facility (INCF) was inaugurated in 2007 as an initiative to improve this situation. The INCF has since pursued its mission to help the development of standards and best practices. In a community paper published this very same year, Brette et al. tried to assess the state of the field and to establish a scientific approach to simulation technology, addressing foundational topics, such as which simulation schemes are best suited for the types of models we see in neuroscience. In 2015, a Frontiers Research Topic “Python in neuroscience” by Muller et al. triggered and documented a revolution in the neuroscience community, namely in the usage of the scripting language Python as a common language for interfacing with simulation codes and connecting between applications. The review by Einevoll et al. documented that simulation tools have since further matured and become reliable research instruments used by many scientific groups for their respective questions. Open source and community standard simulators today allow research groups to focus on their scientific questions and leave the details of the computational work to the community of simulator developers. A parallel development has occurred, which has been barely visible in neuroscientific circles beyond the community of simulator developers: Supercomputers used for large and complex scientific calculations have increased their performance from ~10 TeraFLOPS (10 13 floating point operations per second) in the early 2000s to above 1 ExaFLOPS (10 18 floating point operations per second) in the year 2022. This represents a 100,000-fold increase in our computational capabilities, or almost 17 doublings of computational capability in 22 years. Moore's law (the observation that it is economically viable to double the number of transistors in an integrated circuit every other 18–24 months) explains a part of this; our ability and willingness to build and operate physically larger computers, explains another part. It should be clear, however, that such a technological advancement requires software adaptations and under the hood, simulators had to reinvent themselves and change substantially to embrace this technological opportunity. It actually is quite remarkable that—apart from the change in semantics for the parallelization—this has mostly happened without the users knowing. The current Research Topic was motivated by the wish to assemble an update on the state of neuroscientific software (mostly simulators) in 2022, to assess whether we can see more clearly which scientific questions can (or cannot) be asked due to our increased capability of simulation, and also to anticipate whether and for how long we can expect this increase of computational capabilities to continue.

biophysically detailed models↗

Load Estimation of Offshore Wind Turbines

The influence of 3 MW Hywind-II wind turbine wakes from an upstream offshore floating wind turbine on a downstream turbine with a separation distance of seven rotor diameters was studied for a site in the Gulf of Maine. The turbines and the platforms were subjected to atmospheric boundary layer flows. Various sensitivity studies on fatigue loads with respect to the positions of the downstream turbine were performed and validated with a large-eddy simulation tool. In particular, the effect of various lateral positions of the downstream turbine relative to the upstream turbine were considered using time-series turbine wake data generated from the large-eddy simulation tool which served as an input to an aero-elastic wind turbine model to assess the loads. The load response from the rotor, tower, and the floating platform for the downstream turbine were sensitive to the lateral offset positions where turbines that were partially exposed to upstream turbine wakes yielded significant increases in the cyclic load range. For the given set of lateral positions for the downstream turbine, the largest damage equivalent load occurred when the turbine was one rotor diameter to the left of the centerline, when looking upstream, which is the position of the turbine fully exposed to upstream turbine wake. On the other hand, the fatigue load on the downstream turbine placed on the right side of the position fully exposed to the upstream turbine wake, yielded lower stress due to the non-symmetric shape of the turbine wake. The configuration associated with the largest damage equivalent loads was further investigated in a large-eddy simulation, modeling both the upstream and downstream turbines. It was found that the energy spectra at the blade rotational frequency were a magnitude order higher for the downstream turbine, especially for surge, heave, pitch, and yaw motion of the platform. In conclusion, the increase of the damage equivalent load for the flapwise blade root moment was 45% compared to the upstream turbine, which can potentially reduce the turbine service life time.

17 WIND ENERGY↗

Generalized Quasi-Static Mooring System Modeling with Analytic Jacobians

This paper presents a generalized and efficient method for quasi-static analysis of mooring systems, including complex scenarios such as when shared mooring lines interconnect multiple floating wind or wave energy devices. While quasi-static mooring models are well established, most published formulations are focused on specific applications, and no publicly available implementations provide efficient handling of large mooring system networks. The present formulation addresses these gaps by: (1) formulating solutions for edge cases not typically supported by quasi-static models; (2) creating a fully generalized model structure such that any combination of mooring lines, point masses, and floating bodies can be assembled; and (3) deriving analytic expressions for the system Jacobians (stiffness matrices) so that systems with many degrees of freedom can be solved efficiently. These techniques form the theory basis of MoorPy, an open-source mooring analysis library. The model is demonstrated on nine scenarios of increasing complexity with features of interest for offshore renewable energy applications. When compared with steady-state results from a lumped-mass dynamic model, the results show that the quasi-static formulation accurately calculates profiles and tensions and that its analytic approach provides more efficient and reliable computation of system stiffness matrices than finite-differencing methods. These results verify the accuracy of the MoorPy model.

16 TIDAL AND WAVE POWER↗

High-precision arithmetic in mathematical physics

For many scientific calculations, particularly those involving empirical data, IEEE 32-bit floating-point arithmetic produces results of sufficient accuracy, while for other applications IEEE 64-bit floating-point is more appropriate. But for some very demanding applications, even higher levels of precision are often required. Furthermore, this article discusses the challenge of high-precision computation, in the context of mathematical physics, and highlights what facilities are required to support future computation, in light of emerging developments in computer architecture.

97 MATHEMATICS AND COMPUTING↗

Pretreatment of Bituminous Coal By-Products for the Hydrometallurgical Extraction of Rare Earth Elements

Low-temperature plasma (LTP) oxidation has been widely used to study the mineralogy of the mineral matter existing in coal sources. The current study investigated the potential of LTP oxidation as a pre-treatment method to improve rare earth element (REE) leachability from coal and its by-products. Representative density-fractionated samples of Baker and Fire Clay coarse refuse seam materials were ground to a top size of 180 µm and subjected to low-temperature plasma oxidation. Subsequently, the treated samples were leached at 1% w/v solids concentration and 75 °C for 5 h using (i) de-ionized (DI) water, (ii) 0.1 mol/L of ammonium sulfate, and (iii) 1.2 mol/L of sulfuric acid. It was determined that LTP treatment improved REE leaching characteristics, especially the leaching of heavy REEs (HREE), existing in the lighter density fractions of the Baker seam coarse refuse material. For instance, the HREE recovery for the 1.6 specific gravity (SG) float fraction increased from 8% to 33% using 0.1 mol/L of ammonium sulfate solution after 32 h of LTP treatment. This finding indicated that HREEs associated with the organic matter were released by the LTP treatment and adsorbed onto the surfaces of highly negative charged mineral matter and was exchanged with ammonium to allow their recovery. Similarly, when using 1.2 mol/L of sulfuric acid, the HREE recovery increased from 23% to 53% for the 1.6 SG float fraction. Interestingly, LTP oxidation did not provide significant improvement in REE recovery from the 2.2 sink density fractions, which was likely due to its lower organic content. No significant benefits were observed when treating the Fire Clay coarse refuse material, which was likely due to the lack of organic affinity and the difficult-to-leach REE minerals associated with the coal source such as monazite, xenotime, and zircon. Conversely, high-temperature oxidation within a temperature range of 600–750 °C significantly improved REE leaching characteristics for both coal sources. Improvement in REE recovery was due to decarbonization of the material, clay dehydroxylation and subsequent conversion of liberated REE-bearing minerals into a more leachable form. However, increasing the temperature above 800 °C decreased REE recovery due to the conversion of meta-kaolinite into mullite, which is chemically stable.

58 GEOSCIENCES↗