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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 73 records · Page 4

Energy Saving Estimation of ASHRAE Guideline 36 Supervisory Setpoint Reset Controls in a Commercial Large Office Building

Designing, commissioning, and retrofitting HVAC control systems for energy efficiency is crucial, but the use of ad-hoc control sequences by designers and contractors, based on scattered information, results in diverse and sub-optimal sequences. ASHRAE Guideline 36 (G36) addresses the challenge by providing standardized, rule-based HVAC control sequences that prioritize energy efficiency. However, there is limited evaluation of their energy performance at the building level, with only a few studies primarily focused on HVAC airside systems in small-to-medium-sized commercial buildings. In this study, the energy performance of ASHRAE Guideline 36 control sequences was assessed using a large office building emulator in Chicago. The emulator features a central plant system with multiple chillers and boilers as well as multiple variable air volume (VAV) systems with terminal reheat. To achieve a high-fidelity representation, we developed a Spawn-of-EnergyPlus-based model for the large office building, maintaining the DOE prototype large office building setup but substituting the HVAC system with its Modelica counterpart. This substitution ensures that the building thermal load, HVAC system's dynamics, and detailed control sequences are all accurately represented. The study involved evaluating and implementing control strategies outlined in ASHRAE Guideline 36-2021 to replace conventional controls. These strategies include the demand-based supply air temperature and duct static pressure setpoint reset and the request logic for demand-based reset of chilled/hot water supply temperature setpoints and pipe static pressure setpoints. Energy performance was evaluated under various load conditions, including cooling, heating, and transitional seasons, both for individual control strategies and in combination. The results indicate that the collective control strategies retrofit yield greater energy savings than the sum of individual strategies, highlighting the synergistic benefits of incorporating both airside and plant-side control retrofits. Additionally, energy savings of up to 41% in the heating season, 18% in the shoulder season, and 20 % in the cooling season were observed compared to baseline control while maintaining the thermal comfort level.

ASHRAE Guideline 36, Commercial buildings, Control↗

Combining stretching and gallic acid to decrease inflammation indices and promote extracellular matrix production in osteoarthritic human articular chondrocytes

Osteoarthritis (OA) patients undergo cartilage degradation and experience painful joint swelling. OA symptoms are caused by inflammatory molecules and the upregulation of catabolic genes leading to the breakdown of cartilage extracellular matrix (ECM). Here, we investigate the effects of gallic acid (GA) and mechanical stretching on the expression of anabolic and catabolic genes and restoring ECM production by osteoarthritic human articular chondrocytes (hAChs) cultured in monolayers. hAChs were seeded onto conventional plates or silicone chambers with or without 100 μM GA. A 5% cyclic tensile strain (CTS) was applied to the silicone chambers and the deposition of collagen and glycosaminoglycan, and gene expressions of collagen types II (COL2A1), XI (COL11A2), I (COL1A1), and X (COL10A1), and matrix metalloproteinases (MMP-1 and MMP-13) as inflammation markers, were quantified. CTS and GA acted synergistically to promote the deposition of collagen and glycosaminoglycan in the ECM by 14- and 7-fold, respectively. Furthermore, the synergistic stimuli selectively upregulated the expression of cartilage-specific proteins, COL11A2 by 7-fold, and COL2A1 by 47-fold, and, in contrast, downregulated the expression of MMP-1 by 2.5-fold and MMP-13 by 125-fold. GA supplementation with CTS is a promising approach for restoring osteoarthritic hAChs ECM production ability making them suitable for complex tissue engineering applications.

60 APPLIED LIFE SCIENCES↗

Nitridation of atomically smooth (111) diamond surfaces using a low temperature Penning plasma discharge

Diamond is a material with a wide band gap that can host a variety of isolated paramagnetic defects, called “color centers”1. These color centers have attractive optical and magnetic properties suitable for quantum applications including quantum computing, nanophotonics and quantum sensing. The most common one is the negatively charged nitrogen vacancy (NV) color center. For quantum sensing, it is desirable to reduce the distance between the NV center and the analyte by using shallow color centers in order to increase sensitivity. In this context, the diamond surface termination is especially critical. The appropriate surface termination is required to stabilize the color centers and mitigate surface magnetic noise. The nitrogen termination of diamond has been postulated as highly desirable for the NV color center. The goal of this project is to take advantage of an electron beam-generated ExB low temperature plasma developed by the Princeton Collaborative Low Temperature Plasma Research Facility (PCRF) at the Princeton Plasma Physics Laboratory (PPPL) to nitridate the surface of (100) diamond single crystals with minimal surface damage. In this reactor, the use of a magnetized plasma enables gentle processing of materials sensitive to ion damage. This is in strong contrast to radiofrequency plasma processing reactors which are known to etch and sputter the surface. XPS measurements indicate the incorporation of nitrogen and oxygen atoms at the surface in similar amounts. XAS measurements confirm the nitridation and indicate that the nitrogen termination is different from the nitrogen termination obtained using radiofrequency plasma treatment4. The combination of these results indicates the formation of amid species at the (100) diamond surface that are promising for the stabilization of NV centers for quantum sensing.

36 MATERIALS SCIENCE↗

Effect of Using Regenerated Combined FAU and MOR Zeolites as Catalysts during the Pyrolysis of Kraft Lignin

The SiO 2 /Al 2 O 3 mole ratio, pore size, and acid sites are the key parameters of zeolite’s activity in lignin pyrolysis. In this study, the comparison of individual Y and M zeolites, the combined ‘Y + M’ sample after regeneration, and their effect on lignin pyrolysis were studied in five cycles (regeneration and reuse). The results were explained using Brunauer, Emmet, and Teller (BET), micropore surface area (MSA), and total acid sites (TAS) analyses. In comparison with the individual Y or M zeolite sample, the consistent higher catalytic activities of the combined ‘Y + M’ sample in repeated cycles were observed. Pyrolysis heavy oils were characterized by nuclear magnetic resonance (NMR) spectroscopy and gel permeation chromatography (GPC). The NMR analyses revealed that with increased zeolite regeneration cycles, p-hydroxy phenyl and methoxyl groups increased. Decreases in guaiacyl phenolic hydroxyl were less for the combined ‘Y + M’ sample than the individual Y and M zeolites. Lower weight average (M w ) of heavy oil for the combined ‘Y + M’ sample indicated the enhanced cleavage of lignin structures in pyrolysis. These results support the higher catalytic activity of regenerated zeolites for the combined ‘Y + M’ sample compared with individual Y and M zeolites due to the improved MSA and TAS.

59 BASIC BIOLOGICAL SCIENCES↗

Predictive biomarkers and mechanisms underlying resistance to PD1/PD-L1 blockade cancer immunotherapy

Immune checkpoint blockade targeting PD-1/PD-L1 has promising therapeutic efficacy in a variety of tumors, but resistance during treatment is a major issue. In this review, we describe the utility of PD-L1 expression levels, mutation burden, immune cell infiltration, and immune cell function for predicting the efficacy of PD-1/PD-L1 blockade therapy. Furthermore, we explore the mechanisms underlying immunotherapy resistance caused by PD-L1 expression on tumor cells, T cell dysfunction, and T cell exhaustion. Based on these mechanisms, we propose combination therapeutic strategies. We emphasize the importance of patient-specific treatment plans to reduce the economic burden and prolong the life of patients. The predictive indicators, resistance mechanisms, and combination therapies described in this review provide a basis for improved precision medicine.

60 APPLIED LIFE SCIENCES↗

Utilization of Ultrasonication as a Method of Reducing Organic and Inorganic Contamination in Post‐Consumer Plastic Film Waste

Post-consumer plastic film waste often carries organic and inorganic contaminants that challenge recycling processes and affect the quality of recycled products. An effective contaminant removal procedure through washing such single-used plastic films (SUPFs) can address environmental and waste management concerns. This study compares the efficiency of different washing techniques in reducing SUPF contamination. To evaluate the efficacy of each washing technique, film samples collected from material recovery facilities are individually exposed to friction, ultrasonic-assisted, and a combination of both washes. Thermal analysis indicates that the polymers' melting temperature, crystallization temperature, and crystallinity remain unaffected by the washing methods, demonstrating method aptness. Confocal laser scanning microscope images show that washing results in a cleaner sample surface. 91% ash reduction during the combined wash treatment indicates a high method efficiency compared to the individual friction and ultrasonic wash procedures. This is further validated by reducing characteristic contaminant IR bands (3600–3000, 1750–1600, and 1100–1000 cm −1 ). Elements of concern such as Cd, Cr, Hg, and Pb in SUPFs after each washing technique applied conform with regulations (<100 ppm) for packaging products. This research shows the novel ultrasonic washing reduces more contamination than friction with shorter wash times and no surfactants.

42 ENGINEERING↗

Dark Energy Survey: Modeling strategy for multiprobe cluster cosmology and validation for the Full Six-year Dataset

We introduce an updated To&Krause2021 model for joint analyses of cluster abundances and large-scale two-point correlations of weak lensing and galaxy and cluster clustering (termed CL+3x2pt analysis) and validate that this model meets the systematic accuracy requirements of analyses with the statistical precision of the final Dark Energy Survey (DES) Year 6 (Y6) dataset. The validation program consists of two distinct approaches, (1) identification of modeling and parameterization choices and impact studies using simulated analyses with each possible model misspecification (2) end-to-end validation using mock catalogs from customized Cardinal simulations that incorporate realistic galaxy populations and DES-Y6-specific galaxy and cluster selection and photometric redshift modeling, which are the key observational systematics. In combination, these validation tests indicate that the model presented here meets the accuracy requirements of DES-Y6 for CL+3x2pt based on a large list of tests for known systematics. In addition, we also validate that the model is sufficient for several other data combinations: the CL+GC subset of this data vector (excluding galaxy--galaxy lensing and cosmic shear two-point statistics) and the CL+3x2pt+BAO+SN (combination of CL+3x2pt with the previously published Y6 DES baryonic acoustic oscillation and Y5 supernovae data).

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Dark energy survey: Modeling strategy for multiprobe cluster cosmology and validation for the full six-year dataset

Here, we introduce an updated To&Krause2021 model for joint analyses of cluster abundances and large-scale two-point correlations of weak lensing and galaxy and cluster clustering (termed CL+3×2 pt analysis) and validate that this model meets the systematic accuracy requirements of analyses with the statistical precision of the final Dark Energy Survey (DES) Year 6 (Y6) dataset. The validation program consists of two distinct approaches, (i) identification of modeling and parametrization choices and impact studies using simulated analyses with each possible model misspecification and (ii) end-to-end validation using mock catalogs from customized Cardinal simulations that incorporate realistic galaxy populations and DES-Y6-specific galaxy and cluster selection and photometric redshift modeling, which are the key observational systematics. In combination, these validation tests indicate that the model presented here meets the accuracy requirements of DES-Y6 for CL+3×2 pt based on a large list of tests for known systematics. In addition, we also validate that the model is sufficient for several other data combinations: the CL+GC subset of this data vector (excluding galaxy–galaxy lensing and cosmic shear two-point statistics) and the CL+3×2 pt+BAO+SN (combination of CL+3×2 pt with the previously published Y6 DES baryonic acoustic oscillation and Y5 supernovae data).

79 ASTRONOMY AND ASTROPHYSICS↗

Understanding relative metal prices and availability: Combining physical and economic perspectives

Abstract Scientists typically use physical indicators, such as average crustal abundance, and energy requirements in production, as measures of the availability of mineral resources. Economists, on the other hand, typically rely on measures such as prices, and extraction costs. This study investigates the role of crustal abundance, energy requirements, and other physical indicators in determining relative metal prices. The relationship between prices, and physical indicators is estimated statistically for a sample of 22 chemical elements over the period 1970–2013 using an economic market model. The results suggest that energy requirements in production explain 43% of observed variation in metal prices, crustal abundance 21%, and other physical indicators (toxicity, native metal status, and melting point) combine to explain 12% of the observed differences in metal prices.

Watson, Brett J.↗

GRUMDN: A Multi-Task Model for Predicting Human Patterns-of-Life from Stay Transition Data

Understanding human patterns-of-life (PoL) is essential towards ensuring safe and secure indoor facility environment as well as outdoor urban environment. Prediction of human movement in between places of interest is vital in understanding human PoL. Movement between spaces maybe represented and detected in one of the two forms: 1) trajectories: locations measured at regular time intervals by mobile sensors, bluetooth or GPS sensors; or 2) stay transitions: semantic PoI (points of interest) and stay duration data measurable by eventbased sensors that collect data when a check-in or check-out event is detected. Stay transition data provides a more compressed data format compared to trajectories data, especially in situations with longer stay durations, while preserving the information necessary for PoL analysis. Now as introduced briefly in the paper, our deployed end application (Digital Twin of a facility with non-player characters, besides the interactive user in virtual reality) needed a well-performing and validated AI/ML model for simulating high quality stay transitions behavior. In this study we thus primarily present our findings with developing and validating that model, which is a multi-task neural network for stay transition prediction. The neural network consists of two heads, for corresponding two tasks of stay category prediction and stay duration prediction. We evaluated gated recurrent units and multi-layer perceptrons of varying network sizes for stay category prediction; while mixture density networks, noisy generator-only networks, and generative adversarial networks of varying network sizes for stay duration prediction. We have then evaluated four multi-task models, constructed by combining these specialized models, on their ability to predict stay transition data. We tested our models on datasets from two different cases: 1) a simulation-generated dataset of indoor movement within the HFIR (high flux isotope reactor) nuclear reactor facility at Oak Ridge National Laboratory (ORNL); and 2) the GeoLife human mobility dataset of outdoor urban movement available in literature. Our results indicate that GRUMDN, which combines gated recurrent units (GRU) for stay category prediction task, and mixture density networks (MDN) for stay duration prediction task, did overall outperform other multitask models and the current state-of-the-art.

Gunaratne, Chathika [ORNL] (ORCID:0000000225088745↗

Revealing Intermetallic Active Sites of PtNi Nanocatalysts for Reverse Water Gas Shift Reaction

Bimetallic nanoparticles have gained great interest due to their potential applications in catalysis. By combining Lattice Boltzmann Modeling (LBM), Density Functional Theory (DFT) calculations, and kinetic Monte Carlo (KMC) simulation, here we rationalize the superior performance of supported Pt-Ni alloy nanostructures over Pt and Ni alone during the reverse Water Gas Shift (rWGS) reaction, which was observed previously. The LBM simulation including the diffusion and flow of the reacting gas molecules within the supporting nanoporous channels in SBA-15 indicates that the simple combination of contributions from Ni and Pt alone is not enough to result in the observed promotion in rWGS activity and selectivity of the Pt-Ni alloy. Instead, the synergy between Pt and Ni via a unique intermetallic motif is responsible according to the DFT and KMC simulation. In conclusion, compared to the monometallic counterparts, the intermetallic-introduced ensemble effect at the low-coordinated Pt-Ni hybrid site of Pt-Ni alloy nanocatalysts enables the enhanced activation of CO 2 and promoted removal of CO/H 2 O as gas phase product.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Electric Vehicle Charging Demand in the Chicago Metropolitan Area through 2030

This report outlines the collaborative efforts between Argonne National Laboratory and Exelon in advancing the Agent-Based Transportation Energy Analysis Model (ATEAM). Aligning with ComEd’s beneficial electrification plan, this study developed eight scenarios to access the temporal and spatial distribution of charging load and demand stemming from the widespread adoption of battery electric vehicles (BEV) adoption, augmented public charging infrastructure deployment, and increased multi-unit dwelling (MUD) charging availability. Enhancements to the ATEAM model encompassed the simulation of multiple days of travel behavior, estimation of total public charging infrastructure needs, user interface refinements, and output tracking at both vehicle and charging station levels. The total electricity consumption for residential and public charging to support over 800,000 BEVs in Chicago in 2029 is projected at approximately 10.2 GWh. Enhanced MUD home charging accessibility (70%) amplifies the home charging load in the study area by 1.5% compared to the baseline scenario (10%). The widespread adoption of BEVs reduces peak charging loads, owing to their inclusion across households with diverse income levels, thus fostering a more dispersed charging activity pattern. However, widespread BEV adoption increases the peak home charging load in areas with lower median household incomes, reflecting a higher BEV concentration in these locales and, subsequently, heightened peak charging demands. In the Widespread BEV adoption scenario, fewer census tracts exhibit elevated peak loads for combined home and public charging, indicating a more even distribution of charging demand across the study area. Predominantly, peak loads for combined charging—both home and public— occur between 2 p.m. and 10 p.m. across all scenarios, encompassing the majority of census tracts.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

A simulation study of carbon storage with active reservoir management

As part of the Integrated Midcontinent Stacked Carbon Storage Hub (IMSCS-Hub) project led by Battelle Memorial Institute, a study was conducted to determine the feasibility of storing carbon dioxide (CO 2 ) in the stacked saline rock formations of the Sleepy Hollow Field (SHF), located in Red Willow County, southern Nebraska. A series of CO 2 injection simulation scenarios, with and without active reservoir management (ARM; brine extraction), were evaluated to investigate the feasibility of storing 50+ million tonnes (Mt) of CO 2 . The results indicated CO 2 injection combined with ARM may enable permanent storage of 50+ Mt of CO 2 . The area of review (AOR), the area in which underground sources of drinking water (USDWs) might be endangered during CO 2 injection, was assessed for the simulation scenarios. In comparison to a case without ARM, brine extraction resulted in a much smaller AOR, covering an area of 42 square miles (108.8 km 2 ), roughly one-fourth the size of an AOR resulting from CO 2 injection without ARM. Our findings, presented in this paper, indicate that CO 2 injection with ARM can improve the CO 2 storage capacity of a geologic storage complex up to 100% while also reduce the rate of pressure buildup in the subsurface, resulting in a 75% reduction in AOR. This may help in lowering carbon capture and storage project costs, risks, and effort needed to meet monitoring requirements for a storage project.

54 ENVIRONMENTAL SCIENCES↗

Benchtop assessment of sealing efficacy and breathability of additively manufactured (AM) face masks

The onset of the 2019 novel coronavirus disease (COVID-19) led to a shortage of personal protective equipment (PPE), medical devices, and other medical supplies causing many stakeholders and the general public alike to turn to additive manufacturing (AM) as a stopgap when normally accessible devices were not available. However, without a method to test these AM constructs, there continued to be a disconnect between AM suppliers and the community’s needs. The objective of this study was to characterize the pressure drop and leakage of four different publicly available AM face mask models with two filter material combinations, as well as to investigate the impact of frame modification techniques including the use of foam strips and hot-water face forming to improve fit when the masks are donned on manikin head forms. AM face mask frame designs were downloaded from public repositories during the early stages of the COVID-19 pandemic. AM face masks were fabricated and tested on manikin head forms within a custom chamber containing dry aerosolized NaCl. Pressure drops, particle penetration, and leakage were evaluated for various flow rates and NaCl concentrations. Results indicated that filter material combination and frame modification played a major role in the overall performance of the AM face masks studied. Filter material combinations showed improved performance when high filtration fabric was used, and the cross-sectional area of the fabric was increased. AM frame modifications appeared to improve AM face mask leakage performance by as much as 69.6%.

36 MATERIALS SCIENCE↗

Simulating image coaddition with the Nancy Grace Roman Space Telescope – II. Analysis of the simulated images and implications for weak lensing

One challenge for applying current weak lensing analysis tools to the Nancy Grace Roman Space Telescope is that individual images will be undersampled. Our companion paper presented an initial application of Imcom – an algorithm that builds an optimal mapping from input to output pixels to reconstruct a fully sampled combined image – on the Roman image simulations. In this paper, we measure the output noise power spectra, identify the sources of the major features in the power spectra, and show that simple analytic models that ignore sampling effects underestimate the power spectra of the coadded noise images. We compute the moments of both idealized injected stars and fully simulated stars in the coadded images, and their one- and two-point statistics. We show that the idealized injected stars have root-mean-square ellipticity errors (1–6) × 10 -4 per component depending on the band; the correlation functions are ≥2 orders of magnitude below requirements, indicating that the image combination step itself is using a small fraction of the overall Roman second moment error budget, although the fourth moments are larger and warrant further investigation. The stars in the simulated sky images, which include blending and chromaticity effects, have correlation functions near the requirement level (and below the requirement level in a wide-band image constructed by stacking all four filters). We evaluate the noise-induced biases in the ellipticities of injected stars, and explain the resulting trends with an analytical model. We conclude by enumerating the next steps in developing an image coaddition pipeline for Roman.

79 ASTRONOMY AND ASTROPHYSICS↗

Joint analysis of 6dFGS and SDSS peculiar velocities for the growth rate of cosmic structure and tests of gravity

ABSTRACT Measurement of peculiar velocities by combining redshifts and distance indicators is a powerful way to measure the growth rate of a cosmic structure and test theories of gravity at low redshift. Here we constrain the growth rate of the structure by comparing observed Fundamental Plane peculiar velocities for 15 894 galaxies from the 6dF Galaxy Survey (6dFGS) and Sloan Digital Sky Survey (SDSS) with predicted velocities and densities from the 2M++ redshift survey. We measure the velocity scale parameter $\beta \equiv {\Omega _{\rm m}^\gamma }/b = 0.372^{+0.034}_{-0.050}$ and $0.314^{+0.031}_{-0.047}$ for 6dFGS and SDSS, respectively, where Ωm is the mass density parameter, γ is the growth index, and b is the bias parameter normalized to the characteristic luminosity of galaxies, L*. Combining 6dFGS and SDSS, we obtain β = 0.341 ± 0.024, implying that the amplitude of the product of the growth rate and the mass fluctuation amplitude is fσ8 = 0.338 ± 0.027 at an effective redshift z = 0.035. Adopting Ωm = 0.315 ± 0.007, as favoured by Planck and using γ = 6/11 for General Relativity and γ = 11/16 for DGP gravity, we get $S_8(z=0) = \sigma _8 \sqrt{\Omega _{\rm m}/0.3} =0.637 \pm 0.054$ and 0.741 ± 0.062 for GR and DGP, respectively. This measurement agrees with other low-redshift probes of large-scale structure but deviates by more than 3σ from the latest Planck CMB measurement. Our results favour values of the growth index γ > 6/11 or a Hubble constant H0 > 70 km s−1 Mpc−1 or a fluctuation amplitude σ8 < 0.8 or some combination of these. Imminent redshift surveys such as Taipan, DESI, WALLABY, and SKA1-MID will help to resolve this tension by measuring the growth rate of cosmic structure to 1 per cent in the redshift range 0 < z < 1.

Said, Khaled↗

Factors controlling pore network development of thermally mature Early Palaeozoic mudstones from the Baltic Basin (N Poland)

Understanding the formation of pore space, especially in low porosity shales (as source rocks and as unconventional resources), is critical to the oil and gas industry, since pores control the space available for hydrocarbon and participate in hydrocarbon transport. We examined 87 Ordovician and Silurian mudstone samples collected from four wells located in the Pomeranian part of the Baltic Basin (northern Poland), one of the primary Polish targets for hydrocarbon exploration. These samples represent the Pelplin, the Paslek, the Jantar, the Prabuty, and the Sasino Formations, which still requires more detailed porosity studies. Our study aimed to identify factors controlling porosity development, by applying bulk techniques (organic petrology and TOC analyses, quantitative mineralogy, and porosimetry) as well as nano- to microscale techniques (thin section petrography, electron microscopy). The studied samples are mainly argillaceous mudstones. The results of porosimetry measurements, combined with image analysis, indicate that the pores of all studied rocks are dominated by micropores (pores < 2 nm in diameter), mesopores (2-50 nm in diameter) and small macropores. The SEM images showed three main pore types: a) voids related to clay mineral aggregates, b) pores inside organic matter particles, and c) pores between other mineral grains. In the Jantar and Sasino mudstones, the organic matter content and its thermal maturity control porosity. The occurrence of solid bitumen in the rocks from these formations reduces samples’ mesoporosity because of the pore-clogging effect. In contrast, in the Paslek and Prabuty Formations, there is low organic matter content and specific surface area and the volume of mesopores increase with clay minerals content. In the Pelplin mudstones, there are no prevailing factors controlling porosity. As a result, we suggest that a combination of SEM image analysis and dual liquid porosity (DLP) measurements is a powerful method to assess porosity available for petroleum flow in mudstones.

03 NATURAL GAS↗

Simulated plant-mediated oxygen input has strong impacts on fine-scale porewater biogeochemistry and weak impacts on integrated methane fluxes in coastal wetlands

Methane (CH 4 ) emissions from wetland ecosystems are controlled by redox conditions in the soil, which are currently underrepresented in Earth system models. Plant-mediated radial oxygen loss (ROL) can increase soil O 2 availability, affect local redox conditions, and cause heterogeneous distribution of redox-sensitive chemical species at the root scale, which would affect CH 4 emissions integrated over larger scales. In this study, we used a subsurface geochemical simulator (PFLOTRAN) to quantify the effects of incorporating either spatially homogeneous ROL or more complex heterogeneous ROL on model predictions of porewater solute concentration depth profiles (dissolved organic carbon, methane, sulfate, sulfide) and column integrated CH 4 fluxes for a tidal coastal wetland. From the heterogeneous ROL simulation, we obtained 18% higher column averaged CH 4 concentration at the rooting zone but 5% lower total CH 4 flux compared to simulations of the homogeneous ROL or without ROL. This difference is because lower CH 4 concentrations occurred in the same rhizosphere volume that was directly connected with plant-mediated transport of CH 4 from the rooting zone to the atmosphere. Sensitivity analysis indicated that the impacts of heterogeneous ROL on model predictions of porewater oxygen and sulfide concentrations will be more important under conditions of higher ROL fluxes or more heterogeneous root distribution (lower root densities). Despite the small impact on predicted CH 4 emissions, the simulated ROL drastically reduced porewater concentrations of sulfide, an effective phytotoxin, indicating that incorporating ROL combined with sulfur cycling into ecosystem models could potentially improve predictions of plant productivity in coastal wetland ecosystems.

54 ENVIRONMENTAL SCIENCES↗