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DOE OSTI2025

A hybrid numerical and machine learning framework for evaluating the performance of a 780 cm 2 aqueous organic redox flow battery

Aqueous organic redox flow battery (AORFB) is a promising cost-competitive technology for large-scale energy storage. Among existing work, the dihydroxyphenazine (DHP)-based AORFB has demonstrated high energy density and low capacity degradation in 10 cm2 cells during lab tests. However, its commercial-scale performance in more complex environments remains unknown, posing a barrier for commercialization. To address this gap, this work presents a comprehensive performance evaluation of a 780 cm 2 DHP-based AORFB by combining physics-based numerical model, machine learning (ML)-based surrogate models, and ML-derived sensitivity quantification. Specifically, we first select 12 key battery parameters that include 10 physicochemical quantities and 2 operation quantities, then select 6 performance metrics that include energy efficiency (EE), discharging capacity, charging energy, and power losses due to concentration, activation, and ohmic over-potentials. With such selection, 12800 combinations of the 12 parameters are subsequently generated using the Latin Hypercube Sampling method. These combinations, together with 38 pre-defined State of Charge, are then integrated to a validated AORFB model developed in COMSOL to compute the performance metrics. With both input parameters and performance metrics, 60 deep neural network (DNN) surrogate models are then trained to approximate the relationship between the 10 physicochemical quantities and 6 performance metrics at each flow rate and current density. Sensitivity scores are then calculated based on the DNN models. Two additional sensitivity analysis tools, i.e., MARS, and SHAP, are also used to cross-validate the sensitivity scores from the DNN. The results demonstrate that 1) the standard potential ranks the first in controlling EE and charging energy, 2) the membrane conductivity is most critical for power loss and EE, and 3) specific area and reaction rate control activation power loss.

25 ENERGY STORAGE↗

DOE OSTI2025

Probing Surface Plasmon Dynamics in Periodic Nanostructures through Ultrafast Electron Microscopy

Surface plasmon polaritons (SPPs) can be manipulated to localize and guide light in subwavelength distances, enabling them to find applications in a wide range of areas, from sensing to quantum computing. Among several methods of SPP excitation, periodic arrays of nano- and microstructures are of particular interest, as they enable engineering SPP properties through structural parameters. Here, in this study, using the photon-induced near-field electron microscopy (PINEM) technique, we investigated the mode formation, coupling, interference, and decay of SPPs in square and hexagonal arrays of circular nanoholes under both visible and near-infrared excitation. Polarization-resolved analysis revealed the key factors governing SPP localization and interference patterns, showing that the periodicity and symmetry of the array primarily determine the SPP interference patterns and their orientation, while pump polarization mainly modulates their intensity. Time-resolved PINEM measurements demonstrated the spatial dependence of the SPP temporal characteristics. In addition, cathodoluminescence (CL) spectroscopy was employed to examine the intrinsic plasmonic characteristics of the structure. Finite difference time domain (FDTD) simulations showed strong agreement with both PINEM and CL measurements on the spatial and spectral behavior of SPPs. Understanding the spatiotemporal dynamics of SPPs on nanostructures beyond the diffraction limit is crucial for optimizing plasmonic structures for advanced photonic and quantum technologies.

Plasmonics↗

DOE OSTI2025

Improved internal short circuit models for thermal runaway simulations in lithium-ion batteries

Thermal runaway (TR) modeling is one of the primary tools that can be used to overcome challenges associated with lithium-ion battery (LIB) safety. Among all LIB accidents that have occurred over the past decade, Internal Short Circuit (ISC) remains the most common trigger mechanism. Many available models in the literature either use a simplified approach to simulate ISC or completely ignore its contribution. The aim of this study is to understand the nature of the heat released for different types of ISC scenarios, including aluminum-anode, anode–cathode, and copper-cathode ISC. We study ISC behavior using a coupled electrochemical–thermal model with an integrated TR chemical kinetics solver built in the COMSOL Multiphysics framework. The time duration of heat release and the magnitude of the peak ISC current are studied as functions of parameters such as the size of the penetrating filament and the capacity of the cell. The numerical results are used to build an empirical model validated against the published experimental TR propagation data. Our model can be successfully used as a viable low-cost substitute in lower order (lumped) TR simulations to enable TR prevention and mitigation.

Singh, Bakhshish Preet (ORCID:0000000264751992)↗

DOE OSTI2024

Investigation of two-dimensional radio-frequency sheath properties using a microscale fluid model

Abstract In previous work (Kohno and Myra 2023 Comput. Phys. Commun. 291 108841), we developed a numerical scheme based on a two-dimensional microscale radio-frequency (RF) sheath model with periodically curved wall boundaries. Here, we expand the capability of this scheme through modification of the boundary conditions (BCs) on the conducting walls, which allows the ion flow to turn back to the plasma at locations on the walls where the electromagnetic force on the ions is reversed from its usual direction. Numerical simulations are carried out to investigate the dependences of the surface-integrated admittances on the wall bump height, ion magnetization, ion mobility, and the magnetic field angle, and to visualize the sheath structures in several cases. One of the main results is the ion cyclotron admittance resonance observed under the condition of low ion mobility (high normalized frequency). It is shown that the amplitude of the resonance peak depends on the wall bump height and the ion velocity is reversed on the sides of the bump in an RF cycle for the resonance cases. Furthermore, the differences in the admittances between the one- and two-dimensional microscale models are assessed for the purpose of understanding non-locality of the sheath near the wall surface for the parameters considered in this study. This information will be essential for improving the sheath BC for macroscale calculations in the future.

Kohno, H. (ORCID:0000000332690010)↗

DOE OSTI2024

Sustainable production of 2,3,5,6-Tetramethylpyrazine at high titer in engineered Corynebacterium glutamicum

The industrial amino acid production workhorse, Corynebacterium glutamicum naturally produces low levels of 2,3,5,6-tetramethylpyrazine (TMP), a valuable flavor, fragrance, and commodity chemical. Here, we demonstrate TMP production (~0.8 g L –1 ) in C. glutamicum type strain ATCC13032 via overexpression of acetolactate synthase and/or α-acetolactate decarboxylase from Lactococcus lactis in CGXII minimal medium supplemented with 40 g L –1 glucose. This engineered strain also demonstrated growth and TMP production when the minimal medium was supplemented with up to 40% (v v –1 ) hydrolysates derived from ionic liquid-pretreated sorghum biomass. Further, a key objective was to take the fully engineered strain developed in this study and interrogate medium parameters that influence the production of TMP, a critical post-strain engineering optimization. Design of experiments in a high-throughput plate format identified glucose, urea, and their ratio as significant components affecting TMP production. These two components were further optimized using response surface methodology. In the optimized CGXII medium, the engineered strain could produce up to 3.56 g L –1 TMP (4-fold enhancement in titers and 2-fold enhancement in yield, mol mol –1 ) from 80 g L –1 glucose and 11.9 g L –1 urea in shake flask batch cultivation.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Is the trace anomaly at its minimum value at neutron star centers?

While the equation of state (EOS) 𝑃⁡(𝜖) of neutron star (NS) matter has been extensively studied, the EOS-parameter 𝜙 =𝑃/𝜖 or equivalently the dimensionless trace anomaly Δ =1/3 −𝜙, which quantifies the balance between pressure 𝑃 and energy density 𝜖, remains far less explored, especially in NS cores. Its bounds and density profile carry crucial information about the nature of superdense matter. Physically, the EOS-parameter 𝜙 represents the mean stiffness of matter accumulated from the stellar surface up to a given density. Based on the intrinsic structure of the Tolman-Oppenheimer-Volkoff equations, we show that 𝜙 decreases monotonically outward from the NS center, independent of any specific input NS EOS model. Furthermore, observational evidence of a peak in the SSS density profile near the center effectively rules out a valley and a subsequent peak in the radial profile of 𝜙 at similar densities, reinforcing its monotonic decrease. Finally, these model-independent relations impose strong constraints on the near-center behavior of the EOS-parameter 𝜙, particularly demonstrating that the mean stiffness (or equivalently Δ) reaches a local maximum (minimum) at the center.

nuclear astrophysics↗

DOE OSTI2024

Emulating ab initio computations of infinite nucleonic matter

We construct efficient emulators for the computation of the infinite nuclear matter equation of state. These emulators are based on the subspace-projected coupled-cluster method for which we here develop a new algorithm called small-batch voting to eliminate spurious states that might appear when emulating quantum many-body methods based on a non-Hermitian Hamiltonian. The efficiency and accuracy of these emulators facilitate a rigorous statistical analysis within which we explore nuclear matter predictions for > 10 6 different parametrizations of a chiral interaction model with explicit Δ -isobars at next-to-next-to leading order. Constrained by nucleon-nucleon scattering phase shifts and bound-state observables of light nuclei up to He 4 , we use history matching to identify nonimplausible domains for the low-energy coupling constants of the chiral interaction. Within these domains we perform a Bayesian analysis using sampling and importance resampling with different likelihood calibrations and study correlations between interaction parameters, calibration observables in light nuclei, and nuclear matter saturation properties. Published by the American Physical Society 2024

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

DOE OSTI2024

Detection of bosenovae with quantum sensors on Earth and in space

In a broad class of theories, the accumulation of ultralight dark matter (ULDM) with particles of mass 10 − 22 eV < m ϕ < 1 eV leads to the formation of long-lived bound states known as boson stars. When the ULDM exhibits self-interactions, prodigious bursts of energy carried by relativistic bosons are released from collapsing boson stars in bosenova explosions. We extensively explore the potential reach of terrestrial and space-based experiments for detecting transient signatures of emitted relativistic bursts of scalar particles, including ULDM coupled to photons, electrons, and gluons, capturing a wide range of motivated theories. For the scenario of relaxion ULDM, we demonstrate that upcoming experiments and technology such as nuclear clocks as well as space-based interferometers will be able to sensitively probe orders of magnitude in the ULDM coupling-mass parameter space, challenging to study otherwise, by detecting signatures of transient bosenova events. Detection of a bosenova event may also give information about microphysics properties of ϕ that would otherwise be difficult with typical direct detection methods. Our analysis can be readily extended to different scenarios of relativistic scalar particle emission. Published by the American Physical Society 2024

Arakawa, Jason (ORCID:0000000237889486)↗

DOE OSTI2025

Thermal expansion of LaB 6 from 298 to 998 K

We propose LaB 6 as a temperature calibration standard for high-temperature (HT) X-ray diffractometry owing to its high temperature stability. Such HT applications require a reliable HT lattice parameter or, equivalently, peak position data, which have not been readily accessible to the diffraction community to date. As such, the thermal expansion behavior of NIST SRM 660a LaB6 was assessed in the temperature range 298–998 K using HT Bragg–Brentano parafocusing θ:θ X-ray diffractometry in conjunction with Rietveld analysis. Data were collected in the 2θ range 20–150° at a data collection rate of 0.5° θ min −1 in air and at 1 atm. The temperature was stepped in 50 K increments. The cubic unit-cell lattice parameter [a(T)] of LaB 6 in Å was found to vary as a(T) = 4.15678 (±0.00001) + Ξ(T − 298 K) + Ψ(T − 298 K) 2 , where Ξ = 2.4645 × 10 −5 (±4.8904 × 10 −8 ) Å K −1 and Ψ = 1.0325 × 10 −8 (±6.7376 × 10 −11 ) Å K −1 . The isobaric volume thermal expansion coefficient (TEC) was obtained as α V P = (5.9291 × 10 −6 ) + (4.9680 × 10 −9 )(T − 298 K) K −1 , from which the corresponding linear TEC was obtained as α L P = (1.9764 × 10 −6 ) + (1.6560 × 10 −9 )(T − 298 K) K −1 . The 3 × 3 matrix representations of the single-crystal isobaric linear TEC and the volume expansivity were obtained for the cubic crystal class to which LaB 6 belongs. Also, the temperature dependence of the lattice parameter data of this study was compared with past landmark studies on LaB 6 by Dutchak et al. [Inorg. Mater. (1972), 8, 1877–1880] and Aivazov et al. [Inorg. Mater. (1979), 15, 1015–1016].

LaB6 standard material↗

DOE OSTI2026

Soil and groundwater environmental sensor data, Wax Lake Delta, Louisiana, March 2023 - March 2024

This study evaluates how environmental parameters that integrate biogeochemical processes vary with water table fluctuations in the freshwater Wax Lake Delta (WLD) in Louisiana, U.S.A. This data package contains seven *.csv files and one Excel file that compiles all the data from the individual .csv files. This dataset reports high frequency (15-min) observations of water level, soil redox potential, specific conductance, and pH made for one year along elevation transects located on the older, proximal (OT) and younger, distal (YT) ends of a deltaic island. Water depth relative to the ground surface (cm; HOBO U20L-04; error ± 0.4 cm), water pH and temperature (HOBO MX2501), and specific conductance and temperature (HOBO U24-001) sensors were installed in March 2023. Water depth was corrected for barometric pressure recorded by a separate logger secured to a platform above the highest water level. Soil redox probes (SWAP ORP-40-4-B) were also installed in March 2023. Each probe had four Pt sensors (2 mm width) placed at 10 cm, 20 cm, 30 cm, and 40 cm below the ground surface. Redox data were referenced to an external Ag0/AgCl (3M KCl) reference probe placed in saturated ground and recorded on CR1000X dataloggers (Campbell Scientific) powered by solar panels. A second reference probe was positioned near the primary reference probe for backup and data correction. The tops of the soil redox probes and soil moisture probes were flush with the soil surface so that sensors are reported at their indicated depths below ground surface. Here, we report data collected between 15 March 2023 to 15 March 2024 for all sensors, with some differences due to exact dates of sensor placement or data gaps associated with sensor malfunction. For example, water depth at OT4 was not recorded between March to November 2023. Data flags indicate whether a value is valid (1) or was excluded from data analysis in the associated manuscript (-1).

EARTH SCIENCE > LAND SURFACE > SOILS↗

DOE OSTI2024

Embedding of Optical Fibers with Electric Field Assisted Sintering

The Electric Field Assisted Sintering (EFAS) technique was used for embedding the fibers, involving rapid heating via an electric current and pressure, reducing fiber exposure to high temperatures. Stainless steel guide tubes were inserted at the fiber-matrix junctions to prevent fiber breakage during the sintering process. The study varied key EFAS parameters—temperature (800°C to 980°C), pressure (40-50 MPa), and hold time (5-10 minutes)—to assess how they influenced fiber embedding. After embedding, the fibers were inspected using optical frequency domain reflectometry (OFDR) to evaluate optical losses and strain along the fiber length. The OFDR scans confirmed that the fibers remained intact, and subsequent transmission tests demonstrated no macroscopic fractures. The embedded samples were also analyzed using scanning electron microscopy (SEM) and X-ray computed tomography (CT) scans. These tests confirmed good bonding between the fiber and matrix with no cracking, though some porosity was present in samples fabricated at lower temperatures. At higher temperatures (980°C), the fiber-matrix bonding was continuous and defect-free, with metal coatings aiding in the bonding process. Elemental analysis showed interdiffusion between the fiber coatings and matrix materials, particularly between the gold coating and stainless steel. Helium leak tests revealed that lower sintering temperatures resulted in matrix porosity, causing leaks, but samples fabricated at 980°C were leak-tight.

46 - INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AN↗

DOE OSTI2025

Fabricating Silver Nanowire–IZO Composite Transparent Conducting Electrodes at Roll-to-Roll Speed for Perovskite Solar Cells

This study addresses the challenges of efficient, large-scale production of flexible transparent conducting electrodes (TCEs). We fabricate TCEs on polyethylene terephthalate (PET) substrates using a high-speed roll-to-roll (R2R) compatible method that combines gravure printing and photonic curing. The hybrid TCEs consist of Ag metal bus lines (Ag MBLs) coated with silver nanowires (AgNWs) and indium zinc oxide (IZO) layers. All materials are solutions deposited at speeds exceeding 10 m/min using gravure printing. We conduct a systematic study to optimize coating parameters and tune solvent composition to achieve a uniform AgNW network. The entire stack undergoes photonic curing, a low-energy annealing method that can be completed at high speeds and will not damage the plastic substrates. The resulting hybrid TCEs exhibit a transmittance of 92% averaged from 400 nm to 1100 nm and a sheet resistance of 11 Ω/sq. Mechanical durability is tested by bending the hybrid TCEs to a strain of 1% for 2000 cycles. The results show a minimal increase (<5%) in resistance. The high-throughput potential is established by showing that each hybrid TCE fabrication step can be completed at 30 m/min. We further fabricate methylammonium lead iodide solar cells to demonstrate the practical use of these TCEs, achieving an average power conversion efficiency (PCE) of 13%. The high-performance hybrid TCEs produced using R2R-compatible processes show potential as a viable choice for replacing vacuum-deposited indium tin oxide films on PET.

14 SOLAR ENERGY↗

DOE OSTI2026

Strong-Drive Limits in Josephson Circuits: From Chaos to an Unbound-Resonance Threshold

Strong microwave drives enable fast measurement and parametric control in superconducting circuits but can induce transitions out of the intended low-energy manifold. We develop a unified description of strong-drive limits in flux- and charge-driven Josephson circuits across drive frequency and dc flux bias. Using classical phase-space analysis and Floquet--Markov simulations, we identify distinct low- and high-frequency mechanisms. At low frequency, we characterize bound-state resonances and separatrix chaos and find that the flux-drive chaos threshold depends strongly on dc flux bias. At high frequency, these mechanisms are suppressed, and the dissipative steady state transfers from the central bound-state sector to outer resonances formed by above-barrier running trajectories. The resulting unbound-resonance threshold is nearly independent of drive frequency and circuit parameters over the regime studied and is controlled primarily by dc flux bias. Coherent simulations show that parametric operation persists beyond this threshold, but at a reduced rate, setting an effective upper bound on the achievable operation speed. We derive analytical criteria for both thresholds, validate them numerically, and experimentally confirm the predicted dc-bias dependence of the low-frequency threshold in a flux-driven SQUID. We also determine the timescales for transfer into the unbound-resonance regime and relaxation back to the bound-state manifold after the drive is removed. Finally, we relate the stability limits to a complementary picture based on the junction critical current and extend the framework to multitone drives and inductively shunted circuits. Together, these results identify the mechanisms limiting strong driving and suggest routes to extend the stable operating range of Josephson circuits.

You, Xinyuan [Fermilab] (ORCID:0000000291789419)↗

DOE OSTI2024

Analysis of biokinetic parameters reveals patterns in mercury accumulation across aquatic species

Mercury (Hg) is a potent neurotoxicant and poses a risk to human health through the ingestion of Hg-contaminated fish. Mercury, especially in its organic form methylmercury (MeHg), biomagnifies up food chains such that even small aqueous concentrations of Hg can result in significant concentrations of total Hg in fish. Understanding the ecological and human health risks associated with Hg and MeHg exposure requires an understanding of the factors that affect its bioaccumulation in aquatic species. We compiled estimates of three biokinetic parameters: uptake rate (k u ), assimilation efficiency (AE), and efflux rate (k e ). These parameters describe contaminant uptake from aqueous (k u ) and dietary (AE) exposure and the rate of excretion (k e ). We found parameter values for 38 and 34 different species of fish and aquatic invertebrates, respectively, and collected 502 parameter values in total. Here, we used a machine learning technique to establish the relationships between experimental and physiological variables and these parameter values. We found differences in which variables were associated with biokinetic parameter values for fish and aquatic invertebrates. The form of Hg was the most impactful variable, influencing values of all parameters except k u for invertebrates, for which aqueous exposure time was the only significant predicator variable. The parameter k e were the only values significantly influenced by more than one variable, with water type (freshwater, brackish, or marine), organism weight, and form of Hg significantly impacting parameter values for fish and/or invertebrates. To our knowledge, this study represents the most extensive review of biokinetic parameters of Hg and MeHg accumulation in aquatic organisms. Environmental parameters found to significantly impact Hg and MeHg bioaccumulation in past studies were not identified as important in our analyses across aquatic ecosystems and species. Our dataset and analysis reveal novel patterns that may help us better understand and manage Hg bioaccumulation.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

The relative importance of building design parameters in reducing energy use and sensible heat release from buildings in light of forecasted future weather data and building coverage ratio

Buildings typically have a 60-to-75-year lifespan before they require significant maintenance or modifications. However, most builders evaluate the performance of their new buildings using whole-building energy simulation tools based on the current typical meteorological year (TMY) file or actual meteorological year. The energy use consumption and sensible heat release pattern observed from buildings could potentially change based on shifting global climates. Therefore, the recommended energy-efficiency design parameters might also change during these periods. In this study, we evaluate the role of different building design parameters, such as material reflectivity, HVAC COP, and insulation values, on building energy usage and sensible heat release from buildings with different building coverage ratios (BCR), based on the current and future weather file TMY (fTMY) for the middle of the century (2040–2060). The role of sensible heat release from buildings is not accounted for accurately while estimating building energy usage in most whole-building energy simulations. The study conducts a series of whole-building energy simulation analyses using EnergyPlus to evaluate the role of different design parameters based on TMY and fTMY weather conditions. The analysis is conducted for two hot desert climatic cities: Phoenix (USA) and Abu Dhabi (UAE). The results show that, for the base case in a future climate, the sensible heat release is reduced by an average of 30% due to the reduced delta T between the surface and ambient air. Further, the results show an increase in total energy consumption by 5% annually. The results also show that, for buildings with traditional coatings, shorter buildings release more heat than taller buildings. On the other hand, for buildings with reflective paints, shorter buildings release less heat than taller buildings. The findings from this study can be used by policymakers, utility companies, and builders to better understand the relative role of different building design parameters while constructing new and retrofitting existing buildings.

Alhazmi, Mansour [King Fahd University of Petroleu↗

DOE OSTI2024

Uncertainties in greenhouse gas emission factors: A comprehensive analysis of switchgrass‐based biofuel production

Abstract This study investigates uncertainties in greenhouse gas (GHG) emission factors related to switchgrass‐based biofuel production in Michigan. Using three life cycle assessment (LCA) databases—US lifecycle inventory (USLCI) database, GREET, and Ecoinvent—each with multiple versions, we recalculated the global warming intensity (GWI) and GHG mitigation potential in a static calculation. Employing Monte Carlo simulations along with local and global sensitivity analyses, we assess uncertainties and pinpoint key parameters influencing GWI. The convergence of results across our previous study, static calculations, and Monte Carlo simulations enhances the credibility of estimated GWI values. Static calculations, validated by Monte Carlo simulations, offer reasonable central tendencies, providing a robust foundation for policy considerations. However, the wider range observed in Monte Carlo simulations underscores the importance of potential variations and uncertainties in real‐world applications. Sensitivity analyses identify biofuel yield, GHG emissions of electricity, and soil organic carbon (SOC) change as pivotal parameters influencing GWI. Decreasing uncertainties in GWI may be achieved by making greater efforts to acquire more precise data on these parameters. Our study emphasizes the significance of considering diverse GHG factors and databases in GWI assessments and stresses the need for accurate electricity fuel mixes, crucial information for refining GWI assessments and informing strategies for sustainable biofuel production.

Kim, Seungdo↗

DOE OSTI2024

The Onset of Nucleate Boiling Prediction in a Mini Channel with the Eulerian Multiphase Flow

The prediction of boiling incipience is a critical issue for a reactor. Vapor lock causes operating instability and undesirable temperature rise, especially for small channels. This study uses the Eulerian multiphase flow boiling model to predict the onset of nucleate boiling in a millimeter scale rectangular channel. Two wall boiling models, namely the RPI (Rensselaer Polytechnic Institute) and the non-equilibrium sub cooled model are applied. Computational fluid dynamics is employed for this study to investigate the impact of operating conditions like liquid flow rate, operating pressure, heat flux, velocity profile, turbulence model, and inlet liquid temperature. Here, the effect of fundamental boiling parameters on the surface wall temperature and vapor volume fraction is also studied. The parameters under consideration are the bubble departure diameter, bubble departure frequency, nucleate site density, quenching time period, and interface heat transfer coefficients. A series of CFD calculations is conducted by varying the considered variables systematically in a wide range of flow conditions covering laminar, transition, and turbulent flows. The sub-component heat fluxes like the liquid convective, the vapor convective, the evaporative, and the quenching terms are monitored to infer the boiling dynamics in the transition region from the single-phase flow to the nucleate boiling zone. It is found that the CFD approach to detecting the boiling incipience point agrees reasonably with available experimental data. However, its limitations, like inaccuracy for lower flow rates and early transition to boiling flow, are also noticed due to the nature of the considered RPI model.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

DOE OSTI2024

Machine Learning Driven Sensitivity Analysis of E3SM Land Model Parameters for Wetland Methane Emissions

Methane (CH 4 ) is globally the second most critical greenhouse gas after carbon dioxide, contributing to 16%–25% of the observed atmospheric warming. Wetlands are the primary natural source of methane emissions globally. However, wetland methane emission estimates from biogeochemistry models contain considerable uncertainty. One of the main sources of this uncertainty arises from the numerous uncertain model parameters within various physical, biological, and chemical processes that influence methane production, oxidation, and transport. Sensitivity Analysis (SA) can help identify critical parameters for methane emission and achieve reduced biases and uncertainties in future projections. This study performs SA for 19 selected parameters responsible for critical biogeochemical processes in the methane module of the Energy Exascale Earth System Model (E3SM) land model (ELM). The impact of these parameters on various CH 4 fluxes is examined at 14 FLUXNET- CH 4 sites with diverse vegetation types. Given the extensive number of model simulations needed for global variance-based SA, we employ a machine learning (ML) algorithm to emulate the complex behavior of ELM methane biogeochemistry. We found that parameters linked to CH 4 production and diffusion generally present the highest sensitivities despite apparent seasonal variation. Comparing simulated emissions from perturbed parameter sets against FLUXNET-CH 4 observations revealed that better performances can be achieved at each site compared to the default parameter values. This presents a scope for further improving simulated emissions using parameter calibration with advanced optimization techniques.

54 ENVIRONMENTAL SCIENCES↗