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At least 415 records · Page 23

Mu2e experiment: Simulation of the Production Target

The Mu2e experiment will search for coherent, neutrinoless conversion of muons to elections in an aluminum stopping target. A simulation program is used to experiment and design the production target of the Mu2e experiment. The module uses programing languages and libraries to work. The program called the Offline uses C++ as the programing language in the module. To construct the simulation, the Geant4 library constructs shapes and uses them in the simulation program, ROOT. The offline program simplifies the creation of the tube by organizing them into parameter objects and nesting them with other variables required to construct the tube-like center point, material, or if it is allowed to conflict with other solids. The parameter varies for every solid tube. The geometry file uploads the parameters by declaring and organizing the parameters in C++ using the configuration tools. The author describes the development and the future of this project.

43 PARTICLE ACCELERATORS↗

Mu2e experiment: Simulation of the Production Target

The Mu2e experiment will search for coherent, neutrinoless conversion of muons to elections in an aluminum stopping target. A simulation program is used to experiment and design the production target of the Mu2e experiment. The module uses programing languages and libraries to work. The program called the Offline uses C++ as the programing language in the module. To construct the simulation, the Geant4 library constructs shapes and uses them in the simulation program, ROOT. The offline program simplifies the creation of the tube by organizing them into parameter objects and nesting them with other variables required to construct the tube-like center point, material, or if it is allowed to conflict with other solids. The parameter varies for every solid tube. The geometry file uploads the parameters by declaring and organizing the parameters in C++ using the configuration tools. The author describes the development and the future of this project.

Szewczyk, Albert↗

Nutrient limitation shapes functional traits of mycorrhizal fungi and phosphorus-cycling bacteria across an elevation gradient

In nutrient-limited high-elevation ecosystems, plants rely on arbuscular mycorrhizal (AM) fungi to provide mineral phosphorus (P) in the form of phosphate (PO43-). AM fungi gather these nutrients from phosphorus-cycling bacteria (PCBs) that can mineralize PO43- from organic matter and solubilize mineral-bound P. How climate, soil factors, and nutrient limitation influence AM fungi and PCB assembly remains unclear. We collected soil from montane meadows across a 1,000-m elevation gradient on three replicate mountainsides and analyzed AM fungal marker genes, P-cycling genes from shotgun metagenomes, and edaphic measurements. High-elevation soils had nearly 50-fold less soil PO₄³⁻ and 60% more AM fungal hyphae than low-elevation soils. AM fungal turnover was linked to changes in pH, organic carbon, and PO₄³-. The composition of 198 P-cycling genes was influenced by the AM fungal community structure. Drivers of individual PCB functional genes, including pH and organic carbon, varied with gene phylogeny. We found a trade-off in P-cycling strategies across elevation: P-rich, low-elevation soils supported root-colonizing AM fungi and organic P-mineralizing bacteria. P-poor, high-elevation soils were dominated by stress-tolerant AM fungi and mineral P-solubilizing bacteria. Our results suggest that AM fungi and PCB community turnover across elevation are both shaped by pH, organic carbon, and P availability. With continued climate warming, the structure and function of mountaintop ecosystems might shift to resemble lower elevations, disrupting long-established and specialized microbial assemblages, with consequences for P-cycling dynamics and the total P available to plant communities.IMPORTANCEPhosphorus (P) limits plant productivity in high-elevation ecosystems, yet the microbial networks that mobilize P, including arbuscular mycorrhizal (AM) fungi and phosphorus-cycling bacteria (PCBs), remain under-characterized in these nutrient-poor soils. We show that across a 10,00-m elevation gradient, AM fungi and P-cycling gene assemblages shift predictably with pH, organic carbon, and phosphate availability. Higher elevations, with less available P, select for stress-tolerant AM fungal taxa and PCB strategies geared toward mineral solubilization, while low-elevation sites favor root colonization by AM fungi and organic P mineralization. These results suggest that nutrient limitation can constrain microbial community assembly in consistent ways across landscapes. High mountain soils are low in P and rely on a network of underground AM fungi and PCB to deliver nutrients to plants. This study shows how those underground relationships reorganize with elevation and how climate change could collapse long-standing microbial strategies by pushing high-elevation ecosystems toward lowland conditions. As soils warm and dry, the microbial scaffolding that supports alpine plant life may become increasingly unstable.

arbuscular mycorrhizal fungi↗

Temporal nitrogen dynamics in intensively managed loblolly pine early stand development

Forest production is strongly dependent on nutrient uptake; however, sustainable management of intensively managed plantations requires an improved understanding of this relationship when fertilization occurs frequently across short rotations. Here, we studied temporal nitrogen (N) concentration ([N]) and content (Nc) dynamics under different silvicultural practices (herbicide, fertilization, and planting density) throughout early loblolly pine (Pinus taeda) stand development (5 years). We describe relationships of [N] and Nc of different stand components (foliage, branches, stem, roots, and competing vegetation) with carbon and biomass. Our results demonstrate that [N] of perennial loblolly tissues do not respond to silvicultural practices and progressively decrease through development. While foliar [N] was most responsive to resource availability, it was not consistent across time. Controlling competing vegetation was crucial to promote the use of site resources by the crop tree and increased loblolly Nc by >500%. However, increased N uptake and expedited growth is dependent upon fertilization early in stand development. At age 5, herbicide plus reduced and full fertilization rates exhibited similar aboveground Nc, which was 32% higher than with herbicide only. Increasing planting density resulted in increased above- and belowground loblolly Nc; however, increases in Nc were not proportional with increases in planting density. Net primary productivity and N uptake were linearly related, but age/development strongly controlled N use efficiency. Our study helps to understand complex relationships between N, biomass, and silvicultural practices during early stand development and demonstrates that temporal evaluation of nutrient dynamics is crucial to better understand loblolly pine growth, carbon sequestration potential, and to inform sustainable silvicultural practices across short rotations.

54 ENVIRONMENTAL SCIENCES↗

Comparing Sensor Fusion and Multimodal Chemometric Models for Monitoring U(VI) in Complex Environments Representative of Irradiated Nuclear Fuel

Optical sensors and chemometric models were leveraged for the quantification of uranium(VI) (0–100 μg mL –1 ), europium (0–150 μg mL –1 ), samarium (0–250 μg mL –1 ), praseodymium (0–350 μg mL –1 ), neodymium (0–1000 μg mL –1 ), and HNO 3 (2–4 M) with varying corrosion product (iron, nickel, and chromium) levels using laser fluorescence, Raman scattering, and ultraviolet–visible–near-infrared absorption spectra. In this paper, an efficient approach to developing and evaluating tens of thousands of partial least-squares regression (PLSR) models, built from fused optical spectra or multimodal acquisitions, is discussed. Each PLSR model was optimized with unique preprocessing combinations, and features were selected using genetic algorithm filters. The 7-factor D-optimal design training set contained just 55 samples to minimize the number of samples. The performance of PLSR models was evaluated by using an automated latent variable selection script. PLS1 regression models tailored to each species outperformed a global PLS2 model. PLS1 models built using fused spectra data and a multimodal (i.e., analyzed separately) approach yielded similar information, resulting in percent root-mean-square error of prediction values of 0.9–5.7% for the seven factors. Further, the optical techniques and data processing strategies established in this study allow for the direct analysis of numerous species without measuring luminescence lifetimes or relying on a standard addition approach, making it optimal for near-real-time, in situ measurements. Nuclear reactor modeling helped bound training set conditions and identified elemental ratios of lanthanide fission products to characterize the burnup of irradiated nuclear fuel. Leveraging fluorescence, spectrophotometry, experimental design, and chemometrics can enable the remote quantification and characterization of complex systems with numerous species, monitor system performance, help identify the source of materials, and enable rapid high-throughput experiments in a variety of industrial processes and fundamental studies.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Temperature and Density on the Forsterite Liquid‐Vapor Phase Boundary

Abstract The physical processes during planet formation span a large range of pressures and temperatures. Giant impacts, such as the one that formed the Moon, achieve peak pressures of 100s of GPa. The peak shock states generate sufficient entropy such that subsequent decompression to low pressures intersects the liquid‐vapor phase boundary. The entire shock‐and‐release thermodynamic path must be calculated accurately in order to predict the post‐impact structures of planetary bodies. Forsterite (Mg 2 SiO 4 ) is a commonly used mineral to represent the mantles of differentiated bodies in hydrocode models of planetary collisions. Here, we performed shock experiments on the Sandia Z Machine to obtain the density and temperature of the liquid branch of the liquid‐vapor phase boundary of forsterite. This work is combined with previous work constraining pressure, density, temperature, and entropy of the forsterite principal Hugoniot. We find that the vapor curves in previous forsterite equation of state models used in giant impacts vary substantially from our experimental results, and we compare our results to a recently updated equation of state. We have also found that due to under‐predicted entropy production on the principal Hugoniot and elevated temperatures of the liquid vapor phase boundary of these past models, past impact studies may have underestimated vapor production. Furthermore, our results provide experimental support to the idea that giant impacts can transform much of the mantles of rocky planets into supercritical fluids.

58 GEOSCIENCES↗

Protoplast-Based Transient Expression and Gene Editing in Shrub Willow ( Salix purpurea L .)

Shrub willows (Salix section Vetrix) are grown as a bioenergy crop in multiple countries and as ornamentals across the northern hemisphere. To facilitate the breeding and genetic advancement of shrub willow, there is a strong interest in the characterization and functional validation of genes involved in plant growth and biomass production. While protocols for shoot regeneration in tissue culture and production of stably transformed lines have greatly advanced this research in the closely related genus Populus, a lack of efficient methods for regeneration and transformation has stymied similar advancements in willow functional genomics. Moreover, transient expression assays in willow have been limited to callus tissue and hairy root systems. Here we report an efficient method for protoplast isolation from S. purpurea leaf tissue, along with transient overexpression and CRISPR-Cas9 mediated mutations. This is the first such report of transient gene expression in Salix protoplasts as well as the first application of CRISPR technology in this genus. These new capabilities pave the way for future functional genomics studies in this important bioenergy and ornamental crop.

59 BASIC BIOLOGICAL SCIENCES↗

Spatio-temporal control of phenylpropanoid biosynthesis by inducible complementation of a cinnamate 4-hydroxylase mutant

Abstract Cinnamate 4-hydroxylase (C4H) is a cytochrome P450-dependent monooxygenase that catalyzes the second step of the general phenylpropanoid pathway. Arabidopsis reduced epidermal fluorescence 3 (ref3) mutants, which carry hypomorphic mutations in C4H, exhibit global alterations in phenylpropanoid biosynthesis and have developmental abnormalities including dwarfing. Here we report the characterization of a conditional Arabidopsis C4H line (ref3-2pOpC4H), in which wild-type C4H is expressed in the ref3-2 background. Expression of C4H in plants with well-developed primary inflorescence stems resulted in restoration of fertility and the production of substantial amounts of lignin, revealing that the developmental window for lignification is remarkably plastic. Following induction of C4H expression in ref3-2pOpC4H, we observed rapid and significant reductions in the levels of numerous metabolites, including several benzoyl and cinnamoyl esters and amino acid conjugates. These atypical conjugates were quickly replaced with their sinapoylated equivalents, suggesting that phenolic esters are subjected to substantial amounts of turnover in wild-type plants. Furthermore, using localized application of dexamethasone to ref3-2pOpC4H, we show that phenylpropanoids are not transported appreciably from their site of synthesis. Finally, we identified a defective Casparian strip diffusion barrier in the ref3-2 mutant root endodermis, which is restored by induction of C4H expression.

Plant Sciences↗

Toward efficient polynomial preconditioning for GMRES

Here, we present a polynomial preconditioner for solving large systems of linear equations. The polynomial is derived from the minimum residual polynomial (the GMRES polynomial) and is more straightforward to compute and implement than many previous polynomial preconditioners. Our current implementation of this polynomial using its roots is naturally more stable than previous methods of computing the same polynomial. We implement further stability control using added roots, and this allows for high degree polynomials. We discuss the effectiveness and challenges of root-adding and give an additional check for stability. In this article, we study the polynomial preconditioner applied to GMRES; however it could be used with any Krylov solver. This polynomial preconditioning algorithm can dramatically improve convergence for some problems, especially for difficult problems, and can reduce dot products by an even greater margin.

97 MATHEMATICS AND COMPUTING↗

Small-x structure of oxygen and neon isotopes as seen by the Large Hadron Collider

Results on collisions of O-16 nuclei performed at the Relativistic Heavy Ion Collider (RHIC) have been presented for the first time at Quark Matter 2023 by the STAR collaboration. O-16+O-16 collisions are also expected to take place in the near future at the Large Hadron Collider (LHC) at much higher beam energies. We explore the potential of beam-energy-dependent studies for this system to probe small-x dynamics and QCD evolution. We perform 3+1D IP-Glasma simulations to predict the rapidity dependence of the initial geometry of light-ion collisions, focusing on O-16+O-16 and Ne-20+Ne-20 collisions at root s(NN) = 70 GeV and 7 TeV. The choice of Ne-20 is motivated by its strongly elongated geometry, which may respond differently to the effect of the high-energy evolution compared to the more spherical O-16. We find that smearing induced by soft gluon production at high energy causes mild variations in the initial-state eccentricities as a function of the collision energy. These effects could be resolved in future experiments and deserve further investigation.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Impacts of Legacy and Contemporary Nitrogen Inputs on N 2 O and CO 2 Emissions in Miscanthus and Maize Cultivated Soils

ABSTRACT Nutrient inputs influence the sustainability of bioenergy crop production through contemporary (shortly after addition) and legacy effects (persisting over years) on microbial nitrogen (N) and carbon cycling, which contribute to greenhouse gas emissions. However, the relative importance of contemporary and legacy effects and how that could vary by crop functional types is poorly understood. Considering its rhizomatous roots and perennial growth, we hypothesized that Miscanthus × giganteus (M×g) would be more sensitive to legacy N fertilization and the historical context of its environment than an annual crop like maize. To test this hypothesis, we examined the effects of legacy and contemporary N inputs on nitrous oxide (N 2 O) and carbon dioxide (CO 2 ) emissions, as well as key N cycling genes in soils where M×g and maize were grown. A 150‐day soil incubation experiment was conducted using soils from a long‐term M×g and maize fertility experiment with three historic N fertilization rates (0, 112, and 336 kg N ha −1 year −1 ) and a contemporary amendment (60 mg N kg −1 ) with negative control (0 mg N kg −1 ). We observed significant increases in cumulative N 2 O emissions in Mxg soils relative to maize soils, particularly at higher legacy fertilization rates, while contemporary N had no significant effect. Bacterial amo A gene abundance, which plays a significant role in nitrification in nutrient‐rich soils, also increased with higher legacy fertilization rates in M×g soils but was unaffected by the contemporary N. In maize soils, legacy and contemporary N did not significantly affect N 2 O emissions, but cumulative CO 2 emissions and amo A gene abundance significantly increased. The abundances of nor B genes were not significantly influenced by either legacy fertilization or contemporary N amendments in either soil. Our findings demonstrate the greater importance of fertilization history over contemporary N in mediating soil N 2 O emissions, particularly for perennial bioenergy crops.

09 BIOMASS FUELS↗

germs-lab/PAPER_miscanthus_soil_response

Nutrient inputs influence the sustainability of bioenergy crop production through contemporary (shortly after addition) and legacy effects (persisting over years) on microbial nitrogen (N) and carbon cycling, which contribute to greenhouse gas emissions. However, the relative importance of contemporary and legacy effects and how that could vary by crop functional types is poorly understood. Considering its rhizomatous roots and perennial growth, we hypothesized that Miscanthus × giganteus (M×g) would be more sensitive to legacy N fertilization and the historical context of its environment than an annual crop like maize. To test this hypothesis, we examined the effects of legacy and contemporary N inputs on nitrous oxide (N2O) and carbon dioxide (CO2) emissions, as well as key N cycling genes in soils where M×g and maize were grown. A 150-day soil incubation experiment was conducted using soils from a long-term M×g and maize fertility experiment with three historic N fertilization rates (0, 112, and 336 kg N ha−1 year−1) and a contemporary amendment (60 mg N kg−1) with negative control (0 mg N kg−1). We observed significant increases in cumulative N2O emissions in Mxg soils relative to maize soils, particularly at higher legacy fertilization rates, while contemporary N had no significant effect. Bacterial amoA gene abundance, which plays a significant role in nitrification in nutrient-rich soils, also increased with higher legacy fertilization rates in M×g soils but was unaffected by the contemporary N. In maize soils, legacy and contemporary N did not significantly affect N2O emissions, but cumulative CO2 emissions and amoA gene abundance significantly increased. The abundances of norB genes were not significantly influenced by either legacy fertilization or contemporary N amendments in either soil. Our findings demonstrate the greater importance of fertilization history over contemporary N in mediating soil N2O emissions, particularly for perennial bioenergy crops.

Lee, Jaejin↗

Production of muonic kaon atoms at high-energy colliders

We develop a framework for the formation of exotic muonic kaon atoms ($K\mu$) in semileptonic $D^{0}$ decays, using the effective weak Hamiltonian, a helicity-based treatment of the leptonic current, and a nonrelativistic bound-state projection. The resulting branching ratio, $\mathrm{BR}(D^{0}\!\to(K\mu )\nu_{\mu})=2.29\times10^{-10}$, is implemented in a ROOT-based code to estimate yields at RHIC, LHC, and STCF. We show quantitatively that $K\mu$ atoms—also produced through coalescence in the quark--gluon plasma (QGP)—provide a sensitive probe of low-momentum primordial muons and early-time electromagnetic radiation, offering complementary constraints in an otherwise unexplored phase space for thermal dilepton and photon emission. Newly estimated dissociation cross sections in detector material indicate that secondary‑vertex reconstruction should be experimentally feasible, allowing clean experimental identification of the atoms. Projected yields from QGP coalescence in LHC and RHIC heavy-ion collisions, and from $D^{0}$ decays in LHC high-luminosity $p+p$ collisions indicate that the first observation of $K\mu$ atoms is within reach. Content from this work may be used under the terms of the Creative Commons Attribution 3.0 licence. Any further distribution of this work must maintain attribution to the author(s) and the title of the work, journal citation and DOI. Article funded by SCOAP3 and published under licence by Chinese Physical Society and the Institute of High Energy Physics of the Chinese Academy of Science and the Institute of Modern Physics of the Chinese Academy of Sciences and IOP Publishing Ltd.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Refining water and carbon fluxes modeling in terrestrial ecosystems via plant hydraulics integration

Plant hydraulics substantially affects terrestrial water and carbon cycles by modulating water transport and carbon assimilation. Despite improved drought simulations in certain ecosystems through their integration into land surface models (LSMs), the broader application of plant hydraulics in diverse ecosystems and hydroclimates is still underexplored. Here, in this study, we implemented the recently developed Noah-Multiparameterization Land Surface Model (Noah-MP LSM) equipped with a plant hydraulics scheme (Noah-MP-PHS) across 40 FLUXNET sites globally. Employing the Shuffled Complex Evolution-University of Arizona (SCE-UA) auto-calibration algorithm, we optimized key plant hydraulics parameters for these sites spanning eight vegetation types in both arid and humid climates. Noah-MP-PHS significantly improves the simulation of evapotranspiration (ET) and gross primary production (GPP) by better representing atmospheric and soil water stress compared to traditional soil hydraulic schemes (SHSs, such as Noah and CLM). The augmented Noah-MP-PHS models reduce surface flux overestimation and underestimation, exhibiting an average increase of 0.14 and 0.15 in Kling-Gupta Efficiency (KGE) compared to Noah and CLM, respectively. The explicit consideration of plant capacitance in PHS reveals substantial deep-layer and nocturnal root water uptake especially under dry conditions. We employed eXplainable Machine learning (XML) to quantify the model’s relative sensitivity to newly introduced leaf-, stem and root-related parameters in PHS. The sensitivity analysis reveals a rise in root parameter importance and a decline in leaf and stem parameters as conditions shift from humid to arid. These findings indicate that as aridity states vary, the most influential parameters affecting surface fluxes variation may change in parameter calibration for PHS applications. Our findings underscore the importance of incorporating plant hydraulics into LSMs to enhance simulations of terrestrial water and carbon dynamics. These findings are crucial for understanding ecosystem responses to global climate changes and guide the broader application of PHS at larger scales.

54 ENVIRONMENTAL SCIENCES↗

Triacylglycerol, total fatty acid, and biomass accumulation of metabolically engineered energycane grown under field conditions confirms its potential as feedstock for drop‐in fuel production

Abstract Metabolic engineering for hyperaccumulation of lipids in vegetative tissues of high biomass crops promises a step change in oil yields for the production of advanced biofuels. Energycane is the ideal feedstock for this approach due to its exceptional biomass production and persistence under marginal conditions. Here, we evaluated metabolically engineered energycane with constitutive expression of the lipogenic factors WRINKLED 1 ( WRI 1), DIACYLGLYCEROL ACYLTRANSFERASE 1 ( DGAT 1), and OLEOSIN 1 ( OLE 1) for the accumulation of triacylglycerol (TAG), total fatty acid (TFA), and biomass under field conditions at the University of Florida‐IFAS experiment station near Citra, Florida. TAG and TFA accumulation were highest in leaves (up to 9.9% and 12.9% of DW, respectively), followed by juice from crushed stems, stems, and roots. TAG and TFA accumulation increased up to harvest time and correlated highest with OLE 1 and DGAT 1 expression. Biomass dry weight, TAG, and TFA content differed greatly depending on DGAT 1 and OLE 1 expression in transgenic lines with similar WRI 1 expression. Biomass did not significantly differ between WT and line L2 with DAGT 1 and OLE 1 expressed at low levels and TAG and TFA accumulating to 12‐ and 1.6‐fold that of WT leaves, respectively. In contrast, line L13, with intron‐mediated enhancement of DGAT 1 expression, displayed a 245‐ to 330‐fold increase in TAG and a 4.75‐ to 6.45‐fold increase in TFA content compared with WT leaves and a biomass reduction of 52%. These results provide the basis for developing novel feedstocks for expanding plant lipid production and point to new prospects for advanced biofuels.

59 BASIC BIOLOGICAL SCIENCES↗

A methodology for decay heat characterization in molten salt reactors

Accurate decay heat prediction in molten salt reactors (MSRs) faces dual challenges: complex operational uncertainties and the need for interpretable models compatible with engineering workflows. This work presents a hybrid machine learning and segmented polynomial methodology that addresses both requirements through three key innovations. First, a modular data architecture encodes MSR-specific operational parameters (power density: 1-100 W cm -3 , humidity: 0-0.1 wt %, air ingress: 0-0.1 mol %) with uncertainty-aware temporal discretization spanning 15 orders of magnitude. Second, region-optimized machine learning models achieve 92.3 % root mean square error (RMSE) reduction over conventional polynomials while maintaining physical interpretability through automated piecewise equation generation. Third, dual front-end interfaces accelerate safety analyses — a Jupyter environment enables researchers to explore 10,000+ parameter combinations via interactive widgets, while a Streamlit web application reduces design iteration cycles through production-grade visualization tools. Operational deployment demonstrates prediction times of only a couple hundred milliseconds for 10 4 years decay profiles, enabling real-time optimization of spent fuel container designs.

42 - ENGINEERING↗

On the Relationship Between Methane Production in Anaerobic Incubations of Peat Material and In Situ Methane Emissions

Anaerobic incubations of peat have been widely used to explore soil processes, but this in vitro technique raises many questions as to how well it reproduces in situ conditions. To investigate this, we conducted 60–100 days (+25 days pre‐incubation) anaerobic, temperature‐controlled incubation experiments across a temperature range of 1–26°C on samples from bog and fen habitats, at two different depths (9–19 and 25–35 cm). Here, we observed exponential increases in CO 2 and methane production with temperature in all conditions. We then compared field‐based measurements of methane emission with modeled expectations by extrapolating incubation‐determined methane production rates based on (a) soil temperature profiles, (b) the observed incubation temperature‐methane production relationship, and (c) seasonal thaw depth from each site. The resulting incubation‐extrapolated methane production agreed with measured emission rates within a factor of two at both sites and corresponded to 182 ± 54% and 59 ± 14% of the measured average yearly fluxes from the field for the bog and fen, respectively. The underestimation of fen methane fluxes may be due to the lack of living plant root‐derived dissolved organic carbon inputs in incubations, a key process in fens. Conversely, the overestimation in bogs could be attributed to methane oxidation in the field, which is absent in anaerobic incubation conditions. Nonetheless incubations predicted greenhouse gas emissions from a northern peatland within a factor of two.

Biological and medical sciences,Geosciences,Enviro↗

Co-Firing Switchgrass and Waste Coal in A Power Plant: A Techno-Economic and Life Cycle Evaluation for The Ohio River Valley (SWITCH) (Final Technical Report for Ohio State/FE0032204)

Abandoned coal mine lands (AMLs) represent one of the most persistent environmental challenges in the United States. Prior to the enactment of the Surface Mining Control and Reclamation Act (SMCRA) in 1977, coal mining operations were not legally required to reclaim disturbed lands, leaving behind approximately 500,000 AML sites nationwide. These sites pose severe environmental and health risks, including acid mine drainage, soil and water contamination, and spontaneous combustion of waste coal piles. Millions of Americans live within one mile of these AMLs, underscoring the urgency of remediation. Traditional reclamation practices, such as planting cool-season grasses, often fail to fully restore ecological function or leverage the economic potential of these lands. This project addressed these challenges by developing integrated strategies for resource recovery, land reclamation, and sustainable energy production. This project evaluated an integrated strategy to convert this liability into an opportunity by recovering waste coal and co-firing it with switchgrass (Panicum virgatum L.) cultivated on reclaimed or marginal AML areas in existing coal-fired power plants. Switchgrass not only provides a renewable feedstock but also aids in land reclamation and carbon sequestration. 1) Remote Sensing and Machine Learning for Waste Coal Identification Using Sentinel-2 satellite imagery and supervised classification, we applied four machine learning models to detect historical waste coal piles. Random Forest achieved the highest accuracy (precision: 86%, recall: 77%). Time-series analysis revealed gradual vegetation recovery since 1986, indicating natural reclamation processes in historical sites, while active mining areas showed ongoing disturbance. This workflow enables scalable monitoring and prioritization of reclamation efforts. 2) UAS-Based Stockpile Volume Estimation To quantify recoverable waste coal, we evaluated Unmanned Aerial Systems (UAS) equipped with Light Detection and Ranging (LiDAR) and multispectral sensors. Structure-from-Motion (SfM) photogrammetry combined with interpolated Digital Terrain Models (DTMs) achieved strong agreement with LiDAR reference volumes (Root Mean Square Error (RMSE) ≈147 m 3 , Mean Absolute Percentage Error (MAPE) ≈2%). Sensitivity analysis confirmed that spatial resolution significantly influences accuracy, emphasizing the need for high-resolution data for precise volume estimation. This approach offers a scalable, cost-effective, and accurate alternative to conventional ground-based surveys. 3) Switchgrass Cultivation for Bioenergy and Water Quality Improvement We assessed the hydrological and water quality impacts of converting AMLs to switchgrass production areas using the Soil and Water Assessment Tool (SWAT). Results showed that converting 10% of the watershed area into the switchgrass production zone reduced streamflow by 3.1%, total suspended solids by 18.1%, total nitrogen by 7.6%, and total phosphorus by 6.2%, while achieving biomass yields of 8.6–9.2 metric tons per hectare. These findings highlight switchgrass as a dual-benefit strategy for land reclamation and bioenergy feedstock production. 4) Integrated Co-Firing and CCS for Carbon-Negative Power Generation We modeled co-firing scenarios using the Power Plant Flexible Model (PPFM) to evaluate plant efficiency, greenhouse gas (GHG) emissions, and levelized cost of electricity (LCOE). Without carbon capture and storage (CCS), increasing switchgrass co-firing ratios reduced LCOE from $\$$150/MWh at 0% biomass to $\$$110/MWh at full substitution. Under CCS, costs remained higher (~$\$$250/MWh at 0% biomass) but decreased to $\$$200/MWh at 100% biomass, while enabling net-zero or carbon-negative electricity due to switchgrass sequestration benefits. Although CCS introduced efficiency penalties, pairing it with biomass co-firing offset these impacts and maximized climate benefits. Overall, optimizing co-firing ratios between 60-100%, supported by reliable logistics and storage strategies, emerged as a practical pathway to balance affordability, sustainability, and net-zero or negative GHG emissions while promoting productive reuse of AMLs.

01 COAL, LIGNITE, AND PEAT↗