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DOE OSTI2022

Community Resilience through Low-Temperature Geothermal Reservoir Thermal Energy Storage

Submitted data include simulations related to underground thermal battery (UTB) simulations described in Modeling and efficiency study of large scale underground thermal battery deployment, presented at GRC, October 2021. The UTB is comprised of a tank of water, a helical heat exchanger in the center of tank and connected to a water source heat pump, and a phase change material (PCM). Compared to a conventional VBGHE, the UTB is designed to be installed at a much shallower depth, therefore, with a cheaper cost. In addition, the GSHP efficiency is improved due to natural convection of water and additional load capacity provided by PCM. The goal of this study is to explore factors that may affect the efficiency of large-scale UTB deployment. The simulations found in this submission relate to the report on UTB deployment.

15 GEOTHERMAL ENERGY↗

DOE OSTI2023

Global impacts of vegetation clumping on regulating land surface heat fluxes

The clumping index (CI) quantifies the non-random distribution of vegetation across space, which regulates the canopy radiative transfer processes and land surface carbon, water, and energy cycles. However, its impact on global surface energy budget, particularly sensible heat fluxes and surface temperature, is not well understood. Additionally, while there have been studies showing significant seasonal variations in CI, the impacts of these variations on surface energy fluxes remain unclear. In this study, we incorporated satellite-derived spatially and temporally explicit CI data into the Community Land Model version 5 (CLM5) to evaluate the effects of CI on global land energy fluxes. Our results showed that including CI increased the global mean sensible heat flux dissipated from ground by 3.9 W m -2 (~18%), while decreasing the global mean vegetation sensible heat flux by 4.9 W m -2 (~65%), resulting in a total sensible heat decrease of 1.0 W m -2 (~3%). In contrast, CI increased the global mean latent heat flux by 0.8 W m -2 (~2%), primarily due to increased evapotranspiration (up to 11 W m -2 ) in tropical regions. We also found considerable impacts of seasonal variations in CI, particularly on sensible heat fluxes from ground and vegetation in evergreen needleleaf forests and deciduous needleleaf forests. Using constant CI rather than considering seasonal variations resulted in significant overestimation and underestimation of the sensible heat fluxes from vegetation and ground, respectively, in boreal summer. In conclusion, these changes in surface energy fluxes caused by CI and its seasonal variations led to up to 1.7 and 0.5 K differences in simulated mean ground temperature. These findings highlight the importance of including CI and considering its seasonal variations in modeling land surface energy fluxes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Hybridization Assessment of Trybrid Pumped Storage Hydropower System—Part 1: A Case Study of Corral Summit

This report is a part of the deliverables for technical assistance provided to Cat Creek Energy for the Coral Summit Trybrid (Triple Hybrid-Pumped Storage Hydropower, Battery Energy Storage System, and photovoltaic solar energy) energy project. This report explores the operational benefits and challenges of hybridizing an open loop PSH (200MW) located at Mackay, Custer County, Idaho with solar PV (Ground mount 300MW and floating 40MW) and battery (720MWhr). This document reports two activities performed as a part of the hybridization assessment task 1) optimal resource allocation and energy management strategy, and 2) power quality and reliability assessment. From optimal resource allocation and energy management strategy (activity 1), the following key findings can be observed: • Conventional PSH (CPSH) with two reversible pump turbines and separate penstocks can provide required flexibility equivalent to that from two ternary PSH with separate penstock. With single unit CPSH, upper reservoir head cannot be maintained accurately, the variation of water level is rapid and pump mode flexibility is not available. These disadvantages can be overcome by single unit TPSH. However, using two CPSH units with separate penstocks also overcome these disadvantages with the formation of the hydraulic short circuit between two conventional units. • Flooding of the lower reservoir is a severe concern when considering continuous operation for black start. This limits the duration of continuous operation from PSH alone to around 50 hours. Due to the complementary PV and battery action, the duration of continuous operation and smooth power output can be extended. • An optimization problem is framed that maximizes the power output on an hourly basis while minimizing constraint violations and respecting seasonal variations of solar PV and load profiles . Two value streams, arbitrage and baseload generation are served by this profile. It was uncovered that for smooth power output during regular operation, PV curtailment will be required, or the battery capacity needs to be increased above 90MW to accommodate additional PV. From power quality and reliability assessment (activity 2) the following takeaway points can be observed: • The Trybrid, when integrated at the Lost River bus, and limited to 250MW in generation mode and -150MW in the pump mode, causes no violation of voltage or flow.

13 - HYDRO ENERGY↗

DOE OSTI2023

Accelerating the density-functional tight-binding method using graphical processing units

Acceleration of the density-functional tight-binding (DFTB) method on single and multiple graphical processing units (GPUs) was accomplished using the MAGMA linear algebra library. Herein two major computational bottlenecks of DFTB ground-state calculations were addressed in our implementation: the Hamiltonian matrix diagonalization and the density matrix construction. The code was implemented and benchmarked on two different computer systems: (1) the SUMMIT IBM Power9 supercomputer at the Oak Ridge National Laboratory Leadership Computing Facility with 1–6 NVIDIA Volta V100 GPUs per computer node and (2) an in-house Intel Xeon computer with 1–2 NVIDIA Tesla P100 GPUs. The performance and parallel scalability were measured for three molecular models of 1-, 2-, and 3-dimensional chemical systems, represented by carbon nanotubes, covalent organic frameworks, and water clusters.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

LA100 Equity Strategies. Chapter 1: Justice as Recognition

The LA100 Equity Strategies project synthesizes community guidance with robust research, modeling, and analysis to identify strategy options that can increase equitable outcomes in Los Angeles' clean energy transition. Grounded in the analysis of past and ongoing energy inequities and engagement with underserved communities, the project presents community-guided and community-tailored strategies that aim to operationalize recognition and procedural justice. This chapter focuses on recognition justice, identifying and analyzing past and present social, cultural, and institutional barriers to affordable and clean energy for LA communities, as well as disparities in the distribution of energy system burdens and benefits. Acknowledging historical and structural factors behind current energy inequities is a first step in developing energy equity strategies for the Los Angeles Department of Water and Power (LADWP) to achieve distributional justice - the just and equitable distribution of energy benefits and burdens in LA's energy transition. Recognition, procedural, and distributional justice are the three tenets of energy justice around which the LA100 Equity Strategies project is organized. In the United States, theory and practice around justice have historically focused on unequal distribution of environmental benefits and burdens. The historical siting of hazardous infrastructure such as power plants and transportation corridors in communities of color and low-income communities has disproportionately concentrated negative environmental impacts in their neighborhoods. Those inequities are reproduced via programs, policies, and other efforts (e.g., zoning and regulations, rebates and incentives, lending, investment, and financing) that directly affect people's lives and livelihoods. In recent decades, energy justice scholars and activists broadened their analysis to examine how environmental inequities intersect with other forms of social difference in the distribution of energy benefits and burdens. This approach investigates how differences in class, race, gender, age, and abilities, among others, intersect to understand the social, cultural, and institutional processes that create and perpetuate energy inequities. The LA100 Equity Strategies project embraces this approach to developing a more just clean energy future for LA. Because recognizing and understanding past and existing inequities is vital to addressing them in ways that ensure an equitable energy transition for all Angelenos, this chapter focuses on identifying and analyzing the challenges and inequities of LA's past and existing energy system, including LADWP programs.

community↗

DOE OSTI2021

Fine grinding of thermoplastics by high speed friction grinding assisted by guar gum

High speed friction grinding has been used to grind plant and food substances in water but never been explored for grinding of thermoplastics like polylactic acid (PLA), low and high density polyethylene and polypropylene. Such grinding was investigated in this work and was made possible by using 0.5% guar gum solution instead of just water because increasing the viscosity of water reduced their settling and the speed of passing through the grinder. Additionally, tensile, flexural, and impact strengths of the plastics were studied and higher grinding efficiency of PLA could be explained by its low elongation-at-break compared to low density polyethylene, high density polyethylene, and polypropylene. The microplastics (2000–45 μm) were studied for mass and particle size distributions and by scanning electron microscopy, 13 C CP/MAS NMR, Fourier transform infrared spectroscopy, differential scanning calorimetry, and thermogravimetric analysis. In addition, viscosity of guar gum and contact angles was measured. This new technology can produce finely ground microplastics (710–45 μm) for a variety of applications.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Insights of warm-cloud biases in Community Atmospheric Model 5 and 6 from the single-column modeling framework and Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) observations

There has been a growing concern that most climate models predict precipitation that is too frequent, likely due to lack of reliable subgrid variability and vertical variations in microphysical processes in low-level warm clouds. In this study, the warm-cloud physics parameterizations in the singe-column configurations of NCAR Community Atmospheric Model version 6 and 5 (SCAM6 and SCAM5, respectively) are evaluated using ground-based and airborne observations from the Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) Aerosol and Cloud Experiments in the Eastern North Atlantic (ACE-ENA) field campaign near the Azores islands during 2017–2018. The 8-month single-column model (SCM) simulations show that both SCAM6 and SCAM5 can generally reproduce marine boundary layer cloud structure, major macrophysical properties, and their transition. The improvement in warm-cloud properties from the Community Atmospheric Model 5 and 6 (CAM5 to CAM6) physics can be found through comparison with the observations. Meanwhile, both physical schemes underestimate cloud liquid water content, cloud droplet size, and rain liquid water content but overestimate surface rainfall. Modeled cloud condensation nuclei (CCN) concentrations are comparable with aircraft-observed ones in the summer but are overestimated by a factor of 2 in winter, largely due to the biases in the long-range transport of anthropogenic aerosols like sulfate. We also test the newly recalibrated autoconversion and accretion parameterizations that account for vertical variations in droplet size. Compared to the observations, more significant improvement is found in SCAM5 than in SCAM6. This result is likely explained by the introduction of subgrid variations in cloud properties in CAM6 cloud microphysics, which further suppresses the scheme's sensitivity to individual warm-rain microphysical parameters. The predicted cloud susceptibilities to CCN perturbations in CAM6 are within a reasonable range, indicating significant progress since CAM5 which produces an aerosol indirect effect that is too strong. The present study emphasizes the importance of understanding biases in cloud physics parameterizations by combining SCM with in situ observations.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Examination of Humidity and Ice Supersaturation Profiles Over West Antarctica Using Ground-Based G-Band Radiometer Retrievals

Humidity profiles retrieved from a ground-based millimeter-wave radiometer located at McMurdo Station, Antarctica and the West Antarctica Ice Sheet Divide are presented and their suitability to study the humidity of the polar climate is assessed. The dry conditions of the Antarctic winter and spring are ideal for ground-based millimeter-wave measurements and the retrievals appear to realistically reproduce the spatial and temporal variability of humidity at both sites. Furthermore, the radiometer has the ability to capture daily variability of very low humidity (0.5 to 4 g/kg) in the low-to-mid troposphere with an uncertainty of 10-20% during the Antarctic winter, spring, and summer. Despite the coarse vertical resolution (200-600 m in the first 4 km), the retrievals provide additional information with respect to the European Centre for Medium Range Weather Forecasts (ECMWF) profiles used as background information. The radiometer is also able to realistically identify the location and frequency of supersaturated layers with respect to ice in the mid troposphere. The occurrence of supersaturated layers is correlated with the occurrence of ice clouds identified by a cloud mask. Overall, results show that ground-based microwave and millimeter-wave radiometry is a viable complement to satellite observations to provide continuous information on the thermodynamic state of the low-to-mid troposphere at high latitudes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Comparison of CERES SYN1deg Radiative Fluxes with Those Derived from Observations at the ARM ENA Site

Profiles of radiative fluxes simulated from thermodynamic and cloud observations made at the Atmospheric Radiation Measurement (ARM) eastern North Atlantic (ENA) site for a 6-yr period are termed as ENARad. ENARad radiative fluxes are compared to those from the Clouds and the Earth’s Radiant Energy System (CERES) 1°-resolution synoptic product (SYN1deg)-simulated radiative flux profiles as well as the CERES instrument observed top-of-the-atmosphere (TOA) fluxes and ground site broadband radiometer measurements. Monthly average differences between ENARad and surface radiometer reported fluxes and differences between ENARad, SYN1deg, and observed fluxes at TOA were statistically insignificant. SYN1deg significantly overestimated surface downwelling shortwave flux by 12 ± 52 W m −2 and surface downwelling longwave flux by 5 ± 20 W m −2 on monthly time scales. Such overestimations were traced to a moister and warmer subcloud layer, a drier cloud layer, and a moister and colder above-cloud-free troposphere in the ancillary thermodynamic and cloud properties used by SYN1deg than observed. Similarly, low-cloud coverage, boundaries, and liquid water paths utilized by SYN1deg were also significantly higher than observed. Intramodel differences in the hourly values of shortwave fluxes exceeded 100 W m−2 at the TOA and the surface. These differences were also due to inaccuracies in the representation of low-cloud properties within the SYN1deg product relative to those determined by ENA ARM instrumentation and used as ENARad ancillary data. Results presented are relevant to investigations employing the CERES SYN1deg data product, studies that estimate radiative fluxes from surface-based or satellite-borne observations, and comparative analyses of radiative fluxes derived using different methodological approaches.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Using Machine Learning to Improve Thermostability of MHETase

Protein engineering is a field which utilizes proteins as tools, which has many useful applications in medicine, industry, biofuels and more.1 One such protein is MHETase, which is a protein that plays an important function in the degradation of polyethylene terephthalate (PET) plastics, which are commonly used in water and soda bottles.2 However, these proteins are adapted to work in specific conditions, and may not satisfy the desired properties that a new application would desire, or could be improved. For instance, a more thermostable MHETase would be more effective in the plastic degradation conditions.3 To make these desired changes, the primary structure of the protein is mutated, but there are many possible mutations and positions to mutate to make with the 20 canonical amino acids. Therefore, to narrow down the possibilities and to make the process of finding a thermostable MHETase variant, we used sequence design tools that are grounded in machine learning to find mutations that would improve thermostability of MHETase.4 In particular, we used the tools Protein MPNN and Fireprot to design a more thermostable MHETase enzyme. We then compiled these mutations into a library and grew these proteins using bacteria colonies, and measured their effectiveness using a fluorescent protein marker. Thermostable proteins and their marker would fold correctly and fluorescence would be seen, but if neither folded correctly then there would be no marker detected. We grew these proteins in bacteria and then intend to use these methods to evaluate their thermostability.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2025

Using Machine Learning to Improve Thermostability of MHETase

Protein engineering is a field which utilizes proteins as tools, which has many useful applications in medicine, industry, biofuels and more. One such protein is MHETase, which is a protein that plays an important function in the degradation of polyethylene terephthalate (PET) plastics, which are commonly used in water and soda bottles.2 However, these proteins are adapted to work in specific conditions, and may not satisfy the desired properties that a new application would desire, or could be improved. For instance, a more thermostable MHETase would be more effective in the plastic degradation conditions.3 To make these desired changes, the primary structure of the protein is mutated, but there are many possible mutations and positions to mutate to make with the 20 canonical amino acids. Therefore, to narrow down the possibilities and to make the process of finding a thermostable MHETase variant, we used sequence design tools that are grounded in machine learning to find mutations that would improve thermostability of MHETase.4 In particular, we used the tools Protein MPNN and FireProt to design a more thermostable MHETase enzyme. We then compiled these mutations into a library and grew these proteins using bacteria colonies, and measured their effectiveness using a fluorescent protein marker. Thermostable proteins and their marker would fold correctly and fluorescence would be seen, but if neither folded correctly then there would be no marker detected. We grew these proteins in bacteria and then intend to use these methods to evaluate their thermostability.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2023

Application of unsupervised deep learning to image segmentation and in-situ contact angle measurements in a CO 2 -water-rock system

Rock surface wettability is a critical property that regulates multiphase flows in porous media, which can be quantified using the surface contact angle (CA). X-ray micro-computed tomography (μCT) provides an effective approach to in-situ measurements of surface CAs. However, the CA measurement accuracy depends significantly on the quality of CT image segmentation, which is the clustering of CT pixels into separate phases. Inspired by this, we developed a deep learning (DL)-based CA measurement workflow. Motivated by the recent tremendous progress in unsupervised learning techniques and aiming to avoid expensive manual data annotations, an unsupervised DL pipeline for CT image segmentation was proposed and implemented, which includes unsupervised model training and post-processing. The unsupervised model training was driven by a novel loss function constrained with feature similarity and spatial continuity and implemented by iterative forward and backward paths; the former clustered the pixel-wise feature vectors extracted by convolution neural networks, whereas the latter updated the parameters using gradient descent. An over-segmentation strategy was adopted for model training. The post-processing steps based on agglomerative hierarchical clustering (AHC) were implemented to further merge the over-segmented model output to the desired cluster number, which is intended to improve the efficiency of image segmentation. The developed unsupervised DL pipeline was compared with other commonly-used image segmentation methods using pixel-wise and physics-based evaluation metrics on a synthetic raw-image dataset, which had a known ground truth. The unsupervised DL pipeline showed the best performance. Next, the segmented images were input to an automatic CA measurement tool, and the results were validated by comparisons with manual measurements. The CA values from the manual and automatic measurements showed similar distributions and statistical properties. The automatic measurement demonstrated a wider spectrum because of the much larger number of measurement data points. The primary novelty of the unsupervised DL pipeline developed in this study lies in the novel loss function and the over-segmentation strategy associated with AHC post-processing. Finally, the workflow has been proven an efficient tool for pore-scale wettability characterization, which has a wide range of applications in fundamental studies of multiphase flows in natural porous media, which have critical implications to geological carbon sequestration, hydrocarbon energy recovery, and contaminant transport in groundwater.

42 ENGINEERING↗

DOE OSTI2023

TRACER UAS CopterSonde Profiles

This dataset comes from a rotary-wing, weather-sensing uncrewed aerial system called the CopterSonde. Temperature, pressure, humidity, wind speed, and direction are gathered during vertical profiles. The vertical resolution is 5 m up to 609 m above ground level and the temporal resolution is on average 30 minutes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Plasma breakdown in bubbles passing between two pin electrodes

The ignition of plasmas in liquids has applications from medical instrumentation to manipulation of liquid chemistry. Formation of plasmas directly in a liquid often requires prohibitively large voltages to initiate breakdown. Producing plasma streamers in bubbles submerged in a liquid with higher permittivity can significantly lower the voltage needed to initiate a discharge by reducing the electric field required to produce breakdown. The proximity of the bubble to the electrodes and the shape of the bubbles play critical roles in the manner in which the plasma is produced in, and propagates through, the bubble. In this paper, we discuss results from a three-dimensional direct numerical simulation (DNS) used to investigate the shapes of bubbles formed by injection of air into water. Comparisons are made to results from a companion experiment. A two-dimensional plasma hydrodynamics model was then used to capture the plasma streamer propagation in the bubble using a static bubble geometry generated by the DNS The simulations showed two different modes for streamer formation depending on the bubble shape. In an elliptical bubble, a short electron avalanche triggered a surface ionization wave (SIWs) resulting in plasma propagating along the surface of the bubble. In a circular bubble, an electron avalanche first traveled through the middle of the bubble before two SIWs began to propagate from the point closest to the grounded electrode where a volumetric streamer intersected the surface. In an elliptical bubble approaching a powered electrode in a pin-to-pin configuration, we experimentally observed streamer behavior that qualitatively corresponds with computational results. Optical emission captured over the lifetime of the streamer curve along the path of deformed bubbles, suggesting propagation of the streamer along the liquid/gas boundary interface. Plasma generation supported by the local field enhancement of the deformed bubble surface boundaries is a mechanism that is likely responsible for initiating streamer formation.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2025

Topography, surface water distribution and subsurface structure in 2023 across an Arctic coastal tundra site near Utqiagvik, Alaska

Subsurface electrical resistivity tomography (ERT), active layer thickness measurements, photogrammetry, and topographic data were collected in September 2023 along a 475 m long, 20 m wide corridor that traverses various polygon types within the Barrow Environmental Observatory (BEO) on the Alaskan Arctic Coastal Plain, approximately 4 miles from the Beaufort Sea near Utqiaġvik, Alaska. These measurements were designed to assess decadal changes in surface water distribution, topography, and subsurface structure across this dynamic landscape. This archive contains the datasets acquired in 2023 and references to the datasets acquired previously at the same location. The ERT survey was conducted along the 475 m transect using 0.5 m electrode spacing and a roll-along acquisition strategy. Thaw layer thicknesses were measured with a tile probe along the same transect. Photogrammetry data were acquired using an unoccupied aerial vehicle (UAV) and were used to generate a digital elevation model and an RGB mosaic. A real-time kinematic (RTK) GPS was used to survey the ERT electrodes and the ground control points for the aerial imagery. The dataset contains 5 *.csv data files, 6 *.csv metadata files, and 6 *.tif files.The Next-Generation Ecosystem Experiments: Arctic (NGEE Arctic), was a research effort to reduce uncertainty in Earth System Models by developing a predictive understanding of carbon-rich Arctic ecosystems and feedbacks to climate. NGEE Arctic was supported by the Department of Energy's Office of Biological and Environmental Research. The NGEE Arctic project had two field research sites: 1) located within the Arctic polygonal tundra coastal region on the Barrow Environmental Observatory (BEO) and the North Slope near Utqiagvik (Barrow), Alaska and 2) multiple areas on the discontinuous permafrost region of the Seward Peninsula north of Nome, Alaska. Through observations, experiments, and synthesis with existing datasets, NGEE Arctic provided an enhanced knowledge base for multi-scale modeling and contributed to improved process representation at global pan-Arctic scales within the Department of Energy's Earth system Model (the Energy Exascale Earth System Model, or E3SM), and specifically within the E3SM Land Model component (ELM).

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Seismo-Acoustic Wave Simulation for Earthquake-Generated Infrasound

It is well known that underground explosions or earthquakes can generate infrasound in the atmosphere. Seismoacoustic coupling between the ground motions and atmosphere is a key mechanism for infrasound generation. Epicentral infrasound which is direct response to epicentral ground motions are extensively studied for event detection and discrimination. Diffracted infrasound generated from Rayleigh waves are often observed and reported. Recent studies suggested the surface topography is also important for infrasound generation, and mountains or topographic peaks can act as effective secondary infrasound sources. In this study, we perform full 3-D seismoacoustic simulations to understand a coupled seismic and acoustic wave generation by an earthquake and energy partitioning across the solid Earthocean-atmosphere system. By including the effects of realistic topography, bathymetry, and earthquake focal mechanism, we provide quantitative information about seismoacoustic wavefields and secondary infrasound sources across the solid-water, solid-air, and water-air interfaces. Acoustic wave transmission across water-air interface is also investigated by using synthetic waveforms. Our study suggests that shallow seas near the coastline or over elevated seafloors can transmit significant amount of energy from acoustic waves in water and can be effective secondary infrasound sources.

58 GEOSCIENCES↗

DOE OSTI2021

Seismo-Acoustic Wave Simulation for the 2016 Kumamoto Earthquake

It is well known that underground explosions or earthquakes can generate infrasound in the atmosphere. Seismoacoustic coupling between the ground motions and atmosphere is a key mechanism for infrasound generation. Epicentral infrasound which is direct response to epicentral ground motions are extensively studied for event detection and discrimination. Diffracted infrasound generated from Rayleigh waves are often observed and reported. Recent studies suggested the surface topography is also important for infrasound generation, and mountains or topographic peaks can act as effective secondary infrasound sources. In this study, we perform full 3-D seismoacoustic simulations to understand a coupled seismic and acoustic wave generation by an earthquake and energy partitioning across the solid Earth-ocean-atmosphere system. By including the effects of realistic topography, bathymetry, and earthquake focal mechanism, we provide quantitative information about seismoacoustic wavefields and secondary infrasound sources across the solid-water, solid-air, and water-air interfaces. Acoustic wave transmission across water-air interface is also investigated by using synthetic waveforms. Our study suggests that shallow seas near the coastline or over elevated seafloors can transmit significant amount of energy from acoustic waves in water and can be effective secondary infrasound sources.

58 GEOSCIENCES↗

DOE OSTI2020

Changes in Physical Properties of Everglades Peat Soils Induced by Increased Salinity at the Laboratory Scale: Implications for Changes in Biogenic Gas Dynamics

Abstract Saltwater intrusion due to sea level rise is a major concern for the Florida Everglades because it may induce shifts in ecosystem productivity and physical soil properties. However, the effects of saline water intrusion into the current carbon gas dynamics of the Everglades (particularly in terms of biogenic gas production and emissions, i.e., CH 4 and CO 2 ) are still uncertain. In this work, we present a laboratory‐based study to simulate how sea level rise may alter the physical properties (i.e., hydraulic conductivity) of peat soils from the Everglades and consequently affect the accumulation and release of biogenic gases within the peat matrix. Peat monoliths collected from the Everglades were subjected to progressive increases in salinity from a NaCl solution, and changes to the biogenic gas dynamics regime were simultaneously monitored using a combination of time‐lapse ground‐penetrating radar measurements, manometers, time‐lapse photography, and gas traps. Physical changes to the peat matrix at each salinity interval were assessed using constant head permeameter tests. Consistent with previous research, results show that a progressive increase in salinity (from fresh to saltwater) results in (1) a progressive increase in hydraulic conductivity and (2) a progressive decrease in gas content within the peat matrix (i.e., production) and gas releases. This work has implications for better understanding the potential effects of saltwater intrusion into freshwater peatland systems in the Everglades, particularly in terms of carbon gas dynamics.

Sirianni, Matthew J.↗