An enterprise control assessment case study of the energy–water nexus for the ISO New England system
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Muhanji, Steffi Olesi↗
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Integrated Life Cycle and Techno-Economic Assessments of Central Appalachian Legacy Mine Sites for Biomass Development and Waste Coal Utilization
This project, funded by the U.S. Department of Energy – National Energy Technology Laboratory (DOE-NETL) under award DE-FE0032212, evaluated how legacy coal mine lands and coal refuse piles in Central Appalachia (West Virginia and Pennsylvania) can be reclaimed and repurposed to support biomass development and beneficial utilization of waste coal, with the long-term goal of supporting net-zero or net-negative greenhouse gas (GHG) pathways. The project had two primary objectives: 1. Characterize legacy mine sites (including site conditions, waste coal/refuse resources, and soil/ecosystem indicators) and develop reclamation and best management practices (BMPs) for biomass cultivation; and 2. Conduct integrated machine learning (ML)-assisted life cycle assessment (LCA) and techno-economic analysis (TEA) to quantify environmental and economic outcomes for multiple biomass and waste-coal utilization pathways. Across West Virginia, the team identified ~625 coal refuse sites covering ~19,705 acres, and developed methods to estimate refuse pile volume using digital elevation models (DEMs) and geospatial workflows. A large subset of sites received volume estimates totaling ~1.6 billion m³.
01 COAL, LIGNITE, AND PEAT↗
NEWTS Integrated Dataset (version 1.0)
The National Energy Water Treatment and Speciation (NEWTS) Integrated Dataset v1.0 provides water researchers, community leaders, and regulators with a unified and standardized energy-related wastewater stream database. This resource is derived from 27 state and federal entities, and scientific publications, and contains more than 400,000 sample records, many of which also provide geospatial information. The dataset includes data for several different energy-related wastewater types including produced water, other oil and gas wastewaters, mine drainage, coal ash leachate, and power plant wastewater. The NEWTS Integrated Dataset was built to support environmentally prudent decision-making, explore treatment opportunities, and identify potential critical mineral sources. A subset of this novel resource is also featured on NETL NEWTS State-Level Database Dashboard. Additional data can be found in the NEWTS EDX Group and the NEWTS Federal Database Dashboard.
abandoned mine drainage↗
Carbon ore, rare earth, and critical minerals (core-cm) assessment of san juan and raton coal basins: what is the future potential of coal in the san juan and raton basins, new mexico and colorado
This report summarizes results from the CORE-CM project in the San Juan and Raton basins of New Mexico and Colorado and ultimately begins to address what is the future of coal in the San Juan and Raton basins. The objective of this project was to determine the nonfuel carbon-based products (CBP), critical minerals, and rare earth elements (REE) potential in coal and related stratigraphic units in the San Juan and Raton basins and adjacent areas. This project delineated favorable geologic terrains and priority areas containing potential CBP, critical minerals, and REE deposits for the DOE mandate, which also is a priority of the NMBGMR and state of New Mexico. This project is important to the state because CBP, critical minerals, and REE resources must be identified before land use decisions are made by government officials. Future mining of CBP, critical minerals, and REE will directly benefit the economy of New Mexico. Furthermore, it is crucial to re-establish a domestic source of critical minerals and REE in the U.S. to help secure the nation’s clean energy future, to reduce the vulnerability of the U.S. to material shortages related to national defense, and to maintain our global technical and economic competitiveness. In addition to these benefits, students at New Mexico Institute of Mining and Technology (NMT) and San
01 COAL, LIGNITE, AND PEAT↗
An Overview of Policies Influencing Air Pollution from the Electricity Sector in Central Asia
The electricity sector is a substantial source of air pollution and associated health problems in Central Asia and elsewhere. Fossil-fueled power plants emit a wide variety of harmful pollutants and their chemical precursors. The pollutants with the greatest health impacts are particulate matter and ozone. Once released into the atmosphere, there is no practical way to remove air pollutants, which means that policies designed to improve air quality have to limit the pollutants before release. However, tackling such pollution is challenging, particularly in developing economies, due to the need to provide electricity as a basic necessity for citizens and as an engine of economic growth. This report provides examples of policies impacting air pollution from the electricity sector in the Central Asian countries of Kazakhstan, Kyrgyzstan, Tajikistan, Turkmenistan, and Uzbekistan. It is a partner publication to an earlier report that addressed policies in South Asia. As with the South Asia report, information on policies in some countries was difficult to locate; therefore, this is not a comprehensive study, but rather an overview or "scan" of the sector that includes examples of: (1) policies that directly regulate air quality by limiting emissions from specific point sources (by restricting operating hours, for instance); and (2) indirect policies that incentivize or disincentivize polluting activities, such as policies to encourage fuel switching to or from cleaner renewable resources. Note that this report was prepared before the Russia-Ukraine conflict and therefore doesn't address consequences of that war for Central Asia. The report finds: (1) That Central Asian countries typically have relatively few policy instruments available for regulating national air emissions; (2) That many countries, especially those that have a mismatch between seasonal demand and resource availability, could improve energy security and reduce air pollution through increased cross-border electricity trade; (3) That some countries have seemingly contradictory policies (promoting both coal and renewables, for instance). This report is also available in Russian: https://www.nrel.gov/docs/fy23osti/85192.pdf.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Middle Kittanning Coal Waste and Underclay as an Alternative Rare Earth Elements Feedstock
In order to secure domestic sources of rare earth elements (REE) from coal related materials, there must be validation of representative feedstocks. Actively producing coal mines that target the Middle Kittanning coal seam in the Appalachian Basin were compiled. These mines were cross-referenced with publicly available geochemical data such as the U.S. Geological Survey (USGS) Earth Mapping Resources Initiative geochemical data along with samples evaluated and characterized by the National Energy Technology Laboratory (NETL). This work evaluated the extent of elevated Middle Kittanning underclay concentrations of REE in comparison to other underclay formations. Therefore, further up-scaling of research associated with the separation and extraction of REE and other critical minerals can be beneficial to utilizing domestic REE supplies for various technology sectors, to include energy, biomedical, and defense. Numerous current active mines targeting the Middle Kittanning coal seam represent a geographically significant opportunity for shared feedstocks and collaborations to further understand the role of Middle Kittanning underclay as a critical mineral feedstock.
01 COAL, LIGNITE, AND PEAT↗
Forecast of Future Aviation Fuels. Part 1: Scenarios
A preliminary set of scenarios is described for depicting the air transport industry as it grows and changes, up to the year 2025. This provides the background for predicting the needs for future aviation fuels to meet the requirements of the industry as new basic sources, such as oil shale and coal, which are utilized to supplement petroleum. Five scenarios are written to encompass a range of futures from a serious resource-constrained economy to a continuous and optimistic economic growth. A unique feature is the choice of one immediate range scenario which is based on a serious interruption of economic growth occasioned by an energy shortfall. This is presumed to occur due to lags in starting a synfuels program.
English, J. M.↗
NEWTS Integrated Dataset (version 2.0)
The National Energy Water Treatment and Speciation (NEWTS) Integrated Dataset v2.0 provides water researchers, community leaders, regulators, and industry stakeholders with a unified and standardized energy-process wastewater chemistry database. This resource is derived from 39 state and federal entities, and scientific publications, and contains more than 700,000 sample records, many of which also provide geospatial information. The dataset includes chemistry data for several different energy-process wastewater types including produced water, other oil and gas wastewaters, mine drainage, coal ash leachate, power plant wastewater, and geothermal fluids. The NEWTS Integrated Dataset was built to support prudent decision-making, characterization of potential critical mineral sources, and modeling of treatment and valorization options. A subset of this novel resource is also featured on the NEWTS State-Level Database Dashboard. Additional data can be found in the NEWTS EDX Group and the NEWTS Federal Database Dashboard.
AMD↗
Valuing the Future Electric Grid: A Bid-Based Approach
Energy storage resources (ESRs) and other zero marginal cost (ZMC) resources have unique characteristics that are not fully captured in today’s electricity planning and operations modeling tools. Because the modeling assumptions used in these tools are simplified approximations of how operations and investment decisions occur in the real-world, accurately representing cost and operational characteristics are key for determining how these resources impact price formation. Questions such as—Where should we build new transmission? Will a small modular reactor earn enough revenue to participate in the future electric grid? Is retrofitting a coal plant with carbon capture technology economically feasible?—all require accurate electricity prices, which aren’t available from today’s electricity planning and operations modeling tools. As an example, production cost models (PCMs) are heavily utilized tools that determine the cost and reliability of the electric system. However, as PCMs were developed to help thermal generators manage their fuel inventories, production cost modeling is largely based on fuel prices. Because ESRs do not incur fuel costs, they are often modeled as ZMC resources. In reality, ESRs incur opportunity costs as well as technology-specific (degradation) costs that are non-trivial to calculate but are important for price formation. In this research, we identify options to incorporate more realistic opportunity and degradation costs in ESR bidding algorithms. Expanding available bidding assumptions allows energy system modelers to develop more accurate economic valuations for ESRs, leading to more accurate price formation from leading energy system modeling tools.
24 POWER TRANSMISSION AND DISTRIBUTION↗
Influence of the Anionic Zinc-Adeninate Metal–Organic Framework Structure on the Luminescent Detection of Rare Earth Ions in Aqueous Streams
Rare earth elements (REEs) are critical to numerous technologies; however, a combination of increasing demand, environmental concerns, and monopolistic marketplace conditions has spurred interest in boosting the domestic REE production from sources such as coal utilization byproducts. The economic viability of this approach requires rapid, inexpensive, and sensitive analytical techniques capable of characterizing the REE content during resource exploration and downstream REE processing (e.g., analyzing REE separation, concentration, and purification production steps). Luminescence-based sensors are attractive because many REEs may be sensitized to produce element-specific emission. Hence, a single material may simultaneously detect and distinguish multiple REEs. Metal–organic frameworks (MOFs) can sensitize multiple REEs, but their viability has been hindered by sensitivity and selectivity challenges. Understanding how the MOF structure impacts the REE sensing efficacy is critical to the rational design of new sensors. Here, we evaluate the sensing performance of seven different anionic zinc-adeninate MOFs with different organic linkers and/or structures for the visible-emitting REEs Tb, Dy, Sm, and Eu. The choice of a linker determines which REEs are sensitized and significantly influences their sensitivity and selectivity against competing species (here, Fe(II) and HCl). For a given linker, structural changes to the MOF can further fine-tune the performance. The MOFs produce some of the lowest detection limits (sub-10 ppb for Tb) reported for the aqueous sensitization-based REE detection. Importantly, the most selective MOFs demonstrated the ability to sensitize the REE signal at sub-ppm levels in a REE-spiked acid mine drainage matrix, highlighting their potential for use in real-world sensing applications.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Demand Response in Bangalore: Implications for Electricity System Operations
Recent Greening the Grid studies for India highlight the benefits of flexible resources for integrating variable renewable energy onto India’s electricity system. India’s ambitious renewable energy targets, which are particularly focused on renewable resource states such as Karnataka, will face fewer challenges when combined with new planning and operational strategies and technologies. This report explores one such strategy - demand response - by which the system operator shifts load throughout a day to minimize system wide production costs. To explore this strategy, we added demand response resources to Karnataka’s electricity system in a production cost model of India, using load shifting potential analyzed by Lawrence Berkeley National Labs. We then investigated the impacts of increasing demand response capacity under several renewable resource scenarios. Our results show the addition of demand response enables fuel shifting from high-marginal-cost and emissions-intensive subcritical coal and diesel generation to zero-marginal-cost and emissions-free renewable generation. Accordingly, the value that demand response provides to the system increases as the renewable penetration increases. In addition to reducing production costs and emissions, demand response reduces the time that thermal generators spend at their minimum output levels, which typically represents a less efficient and costlier operational state. Agricultural load shifting provides greater value to the system than residential, commercial, or industrial loads. Agricultural demand response is more flexible than other sectors because it is not exposed to subdaily operational constraints and it can operate for more hours per day without impacting customer satisfaction. Further, the first increment of demand response that is added to a system provides the greatest value; further additions provide additional benefits but have a decreasing impact. The insights we discuss could be leveraged by system planners and operators in other jurisdictions, particularly those facing significant renewable energy penetrations, to develop their own demand response programs.
29 ENERGY PLANNING, POLICY, AND ECONOMY↗
Exploring Sustainable Critical Mineral Production in Central Appalachia: A Pathway to Economic Revitalization & Environmental Justice
The Evolve Central Appalachia (Evolve CAPP) project team was formed to explore the sustainability of critical mineral production within the Central Appalachian coal basin, spanning Virginia, West Virginia, Kentucky, and Tennessee in the United States. The initiative is evaluating the rare earth and critical mineral resource potential essential for powering clean energy technologies, while fostering a circular economy throughout the energy transition. Opportunities are being sought to address environmental justice, workforce development and responsible sourcing. By promoting greater resource utilization, the project is identifying downstream value-added industries, further fostering economic revitalization in the region.
Bishop, Richard↗
Multi-functional Sorbent Development for Separation of Critical Minerals and Pollutants
Critical Metals (CMs), including Rare Earth Elements (REEs), aluminum, manganese, cobalt, and others outlined by the U.S. Department of the Interior’s Geological Survey are essential to the national and economic security of the US, and whose supply chain is susceptible to disruption. Because of the negative environmental impacts inherent with the conventional mining and processing of solid ores for CMs, adsorption-based recovery of naturally dissolved species from coal wastewaters is appealing. Acid mine drainage (AMD) remains a relatively untapped source that can be rich in REEs, and especially in Al, Mn, and other CMs. NETL’s Multi-functional Sorbent Technology (MUST) has been developed originally from the functionalized silica sorbents for carbon capture. Ongoing work aims to find AMD sites enriched with either REEs or other CM, and to perform additional field tests at these sites. Overall, our work shows the viability of recovering CMs from AMD and other coal waste streams, using a fixed-bed adsorption system that can also employ a selective elution technique to achieve highly purified metal resources.
Shi, Fan↗
Characterization of Rare-Earth Elements in Lignite Coal of the Williston Basin: Past Efforts and Ongoing Work
Rare-earth elements (REEs) have been a subject area of high interest for their unique properties. REEs are crucial materials used in an incredible array of consumer goods, energy system components, and military defense applications. While the United States has one operating REE mine, the product is sent overseas for refining into usable metals making the United States 100% import-reliant on these critical materials. This has led the Federal Government to declare the REE market an issue of national security. The Energy and Environmental Research Center (EERC) under funding provided by the Department of Energy (DOE) has undertaken efforts to determine if the lignite coal found in the Williston Basin has the potential to be an ore body containing sufficient quantities of REEs and Critical Minerals (CM) for extraction and processing. In one such effort, the EERC collected over 400 samples from the Williston Basin lignite coal seams including outcrops as well as active mines. Those efforts have been followed up with ongoing work under the U.S. DOE’s Carbon Ore, Rare Earth and Critical Minerals Initiative (CORE-CM) currently ongoing in the Williston Basin as well as other basins in the United States. This ongoing work in the Williston Basin characterizing REEs in coal has focused on the collection of new sampling and analysis of REEs in coal and building upon previous characterization work. This information is being used to understand the spatial distribution of REEs through mapping and 3D modeling. The goals of these efforts are to better understand the mechanisms for distribution of the REEs in lignite coal as well as their concentration and determine knowledge gaps in characterization and to start to build the database required to understand the potential resource in the Williston Basin.
Feole, Ian K.↗
Rare Earth Element Detection and Quantification in Coal and Rock Mineral Matrices
As global demand for rare earth elements (REEs) increases, maintaining the production and supply chain is critical. Technologies capable of being used in the field and in situ in the subsurface for rapid REE detection and quantification facilitates the efficient mining of known resources and exploration of new and unconventional resources. Laser-induced breakdown spectroscopy (LIBS) is a promising technique for rapid elemental analysis both in the laboratory and in the field. Multiple articles have been published evaluating LIBS for detection and quantification of REEs; however, REEs in their natural deposits have not been adequately studied. In this work, detection and quantification of two REEs, La and Nd, have been studied in both synthetic and natural mineral matrices at concentrations relevant to REE extraction. Measurements were performed on REE-containing rock and coal samples (natural and synthetic) utilizing different LIBS instruments and techniques, specifically a commercial benchtop instrument, a custom benchtop instrument (single- and double-pulse modes), and a custom LIBS probe currently being developed for in situ, subsurface, borehole wall detection and quantification of REEs. Plasma expansion, emission intensity, detection limits, and double-pulse signal enhancement were studied. The limits of detection (LOD) were found to be 10/14 ppm for La and 15/25 ppm for Nd in simulated coal/rock matrices in single-pulse mode. Signal enhancement of 3.5 to 6-fold was obtained with double-pulse mode as compared to single-pulse operation.
La detection↗
Advanced Characterization of Wastewaters with a Focus on the Environment & Economics (Final Technical Progress Report)
This project, funded by the U.S. Department of Energy under award DE-FE0032457 and conducted at the University of Illinois at Urbana-Champaign, focused on advancing the characterization of coal combustion residual (CCR) effluents. The primary objectives were to develop analytical methods for detecting major cations, anions, trace metals, and rare earth elements (REEs) in CCR wastewater, assess environmental impacts, and explore opportunities for resource recovery. The project advanced the development of a "One-Shot" analysis system designed to simultaneously analyze multiple analytes in CCR effluents.
01 COAL, LIGNITE, AND PEAT↗
Characterization Inform Sustainable Recovery of Critical Minerals from Fossil Energy Waste Feedstocks
Rare earth elements (REE) and other critical minerals (CM, e.g., Co, Ni, Li) have important uses in green energy and modern technologies, yet are vulnerable to potential supply chain disruptions. One potential domestic CM source is fossil energy wastes, such as acid mine drainage (AMD) and treatment solids (AMD solids), coal combustion ash, and Oil and Gas (O&G) drilling wastes (drill cuttings and produced waters). While they can contain lower CM concentrations then traditional ore, the quantity and fast availability as waste feedstock makes them a promising CM resource. To explore their promise, researchers at DOE’s National Energy Technology Laboratory (NETL) have collected and analyzed CM data for aforementioned fossil energy wastes, and utilized advanced geochemical characterization (e.g., synchrotron microprobe and sequential extraction) to identify the CM speciation and binding environments, and developed sustainable and targeted CM recovery. Successful examples include: (1) the discovery of easily mobile REE phases in Ca-rich coal combustion ash and developing a patented REE recovery process from Ca-rich Powder River Basin coal ash; (2) the successful identification of REE/Co/Ni/Zn hosting phases in acid mine drainage treatment solids (AMD solids) with diverse chemical composition (Al, Mn, or Fe-rich) informing the sequential recovery of different REE/CMs from AMD solids; (3) the recovery potential of Li and other CMs in O&G produced waters and drill cuttings. The innovations driven by characterization have the potential to offset the cost of waste management and wastewater treatments while reducing the cost and environmental footprint of CM extraction.
Stuckman, Mengling↗
Real-time optimization of multi-cell industrial evaporative cooling towers using machine learning and particle swarm optimization
Existing electrical generating stations must operate with greater flexibility due to increasing renewable energy penetration on the electrical grid, and many coal-fired power stations have transitioned away from baseload operation to load-following operation to aid in grid stability. In cases where multiple independently controlled cooling tower cells are used in parallel for the cooling purposes of such stations, there is an opportunity to increase plant efficiency through data-driven optimization across their full load ranges. This work presents a novel application of real-time optimization using machine learning and particle swarm optimization on a multi-cell induced-draft cooling tower servicing a coal-fired power station under variable load. This is the first work to demonstrate simultaneous optimization of a multi-cell cooling tower, in addition to using machine learning for closed-loop control on a cooling tower. A novel control configuration is presented that ensures original control logic is not adversely affected and that the overall plant process is not disrupted using only existing hardware and operational data. To verify this methodology, the 12 independent cooling tower cells are simulated in parallel using historic operating data to demonstrate the effectiveness of real-time optimization compared to current practice. An artificial neural network is trained to predict overall cooling tower power consumption using only operational data and ambient conditions with an R2 value of greater than 0.96. The real-time optimization using particle swarm yields 6.7% annual energy usage savings compared to current practices, although the extent of the real-time savings varies greatly with both plant load and environmental conditions. This is particularly significant for a variable load situation because frequent ramping typically results in reduced overall efficiency. Furthermore, this proposed AI-based solution presents an opportunity to improve the overall heat rate of a load-following coal-fired power plant without the need to perform extensive first-principles modeling or add additional hardware to the cooling tower, resulting in more resources conserved and less overall emissions per unit of electricity generated.
42 ENGINEERING↗