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At least 739 records · Page 41

A Probabilistic Methodology for Determining Collision Risk of Marine Animals with Tidal Energy Turbines

Commercial development of tidal stream energy is hampered by technical and financial challenges, and impeded by uncertainty about potential environmental effects that drive environmental risk assessments and permitting (consenting) processes. The effect of greatest concern for operational tidal stream energy devices is the potential for marine animals to collide with turbine blades, resulting in injury or death. Due to the turbulent and often turbid waters that frequently characterize tidal turbine sites, there is an absence of empirical evidence about collisions with marine animals. This paucity of observations often leads to risk-averse permitting decisions that further restrict the deployment of tidal energy devices that are needed to collect this evidence. This paper relies on the framework of stressors and receptors that is widely used in marine energy studies and outlines a stepwise probabilistic methodology that applies existing knowledge to further elucidate the risk to marine animals from operational tidal turbines. A case study using striped bass from the Bay of Fundy, Canada, accompanies the methodology, to partially demonstrate its application.

16 TIDAL AND WAVE POWER↗

Accelerating CO2 Storage Site Characterization through a New Understanding of Favorable Formation Properties and the Impact of Core-Scale Heterogeneities

CO2 sequestration in deep geologic formations can permanently reduce atmospheric CO2 emissions and help to abate climate change. Target formations must undergo a time- and resource-intensive site evaluation process, assessing storage capacity, environmental safety, and suitability for CO2 trapping via reactive transport models based on data from a limited number of core samples. As such, simulations are often simplified and omit heterogeneities in formation properties that may be significant but are not well understood. To facilitate more rapid site assessment, this work first defines the aquifer properties of favorable storage formations through the analysis of promising and active storage sites. Data show quartz is the most prevalent formation mineral with carbonate minerals, highly reactive with injected CO2, present in over 75% of formations. Porosity and permeability data are highly clustered at 10–30% and 10–1000 mD. Field-scale reactive transport simulations are then constructed and used to analyze CO2 trapping efficiency. The models consider porosity and carbonate mineral heterogeneity as well as the impacts of typical temperature gradients. Simulated sequestration efficiencies are compared to results from a comparable homogenous model to understand the implications of aquifer non-uniformities. The results show a lower sequestration efficiency in the homogeneous model during the injection phase. During the post-injection phase, the homogenization of porosity and carbonate mineralogy results in a higher sequestration efficiency. Incorporating the temperature gradient also increases the sequestration efficiency. Importantly, the maximum deviation between the homogeneous and heterogeneous simulations at the end of the 50-year study period is only ~10%. Larger impacts may be incurred for properties outside the defined, promising ranges suggested here.

Environmental Sciences & Ecology↗

Optimizing enzymes for plastic upcycling using machine learning design and high throughput experiments

Plastic use is ubiquitous in the modern world, and polyethylene terephthalate (PET) is one of the most abundantly produced plastics (and the most highly produced polyester), with ~65 million metric tons manufactured annually. To the consumer, PET is likely most recognizable as the plastic used to make beverage bottles. Like many plastics, traditional mechanical or chemical means of PET deconstruction and upcycling are costly and inefficient. Because of these challenges, recycled plastic is generally of lower quality and is more expensive to produce than virgin plastic derived from petroleum. Ultimately, this results in most plastic ending up as waste. We view plastic waste as an underutilized resource which, with the development of more efficient and high-quality recycling processes, could (1) generate significant economic value while (2) decreasing petroleum usage and greenhouse gas emissions, as well as (3) minimizing its negative environmental and health impacts. Biocatalytic recycling, or biomanufacturing the basic building blocks of new plastic from plastic waste, is a promising approach to plastic reuse that complements existing recycling technologies. Recently, biological enzymes capable of breaking down PET have garnered significant attention as an attractive means of dealing with the plastic problem. These enzymes are currently undergoing pilot studies for implementation in industrial-scale enzyme-based recycling. However, there are significant limitations to current enzymes, including the need to perform costly pre-processing of the plastic waste before the enzymes are able to work. Further optimization of these enzymes is necessary to make these technologies competitive, and ultimately incentivise industry-wide adoption of this biology-based green recycling technology. n this work we demonstrate a means to design and generate performant biological enzymes, capable of efficiently deconstructing plastic waste. Specifically, we applied recent advances in artificial intelligence, machine learning, and statistical analysis to design new versions and discover natural enzymes capable of breaking down PET. We focused on optimizing key properties that are important for industrial-scale enzymatic recycling such as pH and thermotolerance. Normal testing of enzymatic plastic-deconstruction is extremely labor intensive and so through this work we also developed a robotic-assisted experimental pipeline capable of characterizing thousands of candidate enzymes. The results of this iterative, AI-guided, multi-discipline approach have led to increases in enzymatic breakdown of over 150X over starting enzymes. This work supports the rapidly developing and transformative field of biocatalytic solutions to environmental problems beyond the discovery and predictive understanding of enzymes for polymer recycling, and has wide implications for tackling numerous energy problems such as carbon capture and fixation (e.g., engineering carbon monoxide dehydrogenase and the rubisco-pathway), biomining (e.g., design of lanthanide-binding proteins) and biomanufacturing (e.g., lignin-deconstruction enzymes).

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

Integrating Emerging Polymer Chemistries for the Advancement of Recyclable, Biodegradable, and Biocompatible Electronics

Abstract Through advances in molecular design, understanding of processing parameters, and development of non‐traditional device fabrication techniques, the field of wearable and implantable skin‐inspired devices is rapidly growing interest in the consumer market. Like previous technological advances, economic growth and efficiency is anticipated, as these devices will enable an augmented level of interaction between humans and the environment. However, the parallel growing electronic waste that is yet to be addressed has already left an adverse impact on the environment and human health. Looking forward, it is imperative to develop both human‐ and environmentally‐friendly electronics, which are contingent on emerging recyclable, biodegradable, and biocompatible polymer technologies. This review provides definitions for recyclable, biodegradable, and biocompatible polymers based on reported literature, an overview of the analytical techniques used to characterize mechanical and chemical property changes, and standard policies for real‐life applications. Then, various strategies in designing the next‐generation of polymers to be recyclable, biodegradable, or biocompatible with enhanced functionalities relative to traditional or commercial polymers are discussed. Finally, electronics that exhibit an element of recyclability, biodegradability, or biocompatibility with new molecular design are highlighted with the anticipation of integrating emerging polymer chemistries into future electronic devices.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Absolute light yield of the EJ-204 plastic scintillator

The absolute light yield of a scintillator, defined as the number of scintillation photons produced per unit energy deposited, is a useful quantity for scintillator development, research, and applications. Yet, literature data on the absolute light yield of organic scintillators are limited. The goal of this work is to assess the suitability of the EJ-204 plastic scintillator from Eljen Technology to serve as a reference standard for measurements of the absolute light yield of organic scintillators. Four EJ-204 samples were examined: two manufactured approximately four months prior and stored in high-purity nitrogen, and two aged approximately eleven years and stored in ambient air. The scintillator response was measured using a large-area avalanche photodiode calibrated using low energy $γ$-ray and X-ray sources. The product of the quantum efficiency of the photodetector and light collection efficiency of the housing was characterized using an experimentally-benchmarked optical photon simulation. The average absolute light yield of the fresh samples, 9100 ± 400 photons per MeV, is lower than the manufacturer-reported value of 10400 photons per MeV. Moreover, the aged samples demonstrated significantly lower light yields, deviating from the manufacturer specification by as much as 26%. These results are consistent with recent work showcasing environmental aging in plastic scintillators and suggest that experimenters should use caution when deploying plastic scintillators in photon counting applications.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗

Mesoporous Crystalline Niobium Oxide with a High Surface Area: A Solid Acid Catalyst for Alkyne Hydration

A mesoporous crystalline niobium oxide with tunable pore sizes was synthesized via the sol–gel-based inverse micelle method. The material shows a surface area of 127 m 2 /g, which is the highest surface area reported so far for crystalline niobium oxide synthesized by soft template methods. The material also has a monomodal pore size distribution with an average pore diameter of 5.6 nm. A comprehensive characterization of niobium oxide was performed using powder X-ray diffraction, Brunauer–Emmett–Teller, thermogravimetric analysis, scanning electron microscopy, transmission electron microscopy, UV–vis, and X-ray photoelectron spectroscopy. The material acts as an environmentally friendly, solid acid catalyst toward hydration of alkynes under with excellent catalytic activity (99% conversion, 99% selectivity, and 4.39 h –1 TOF). Brønsted acid sites present in the catalyst were found to be responsible for the high catalytic activity. Lastly, the catalyst was reusable up to five cycles without a significant loss of the activity.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Evaluating Sea Breezes and Associated Convective Cloud Evolution in the Model Gray Zone

We characterize convective clouds associated with sea‐breeze circulations (SBC) using multi‐agency observations and multi‐case ensemble model simulations. The focus is on assessing convective cloud lifecycle properties and their merging behavior, as well as the environmental conditions they are embedded in, particularly SBC features. In total, 46 SBC days over the Houston‐Galveston region are selected and simulated using the Weather Research and Forecasting (WRF) model at a gray zone scale with a forecast‐like parameterization setup. Advanced techniques, including change‐point detection, a Lagrangian cloud tracking method, and a newly developed cell merging and splitting detection algorithm, are applied and/or developed for this study. Our findings indicate that the WRF model at 1 km grid spacing well represents the thermodynamic conditions over the region, as well as SBC timing and intensity. However, for the associated convective cells, WRF overestimates the 30‐dBZ echo top height, cell area, and maximum radar reflectivity compared to radar observations. This overestimation is potentially due to under‐resolved entrainment processes, an overestimated merging frequency, and the overestimation of updraft intensity. Furthermore, the model exhibits a deficiency in simulating congestus clouds, showing a more rapid transition from shallow to deep convection compared to observed behavior. Moreover, observations indicate stronger, deeper, and wider clouds when merging happens. Conversely, in simulations, the merging process does not necessarily lead to higher or longer‐lived cells, as many cases experience rapid and frequent merging and splitting which may result in more variance in convective updraft velocity during the convection lifetime.

54 ENVIRONMENTAL SCIENCES↗

Nanocluster and single-atom catalysts for thermocatalytic conversion of CO and CO 2

In this Minireview, we discuss recent advances in understanding nanocluster and single-atom catalysts for CO and CO 2 emissions control applications. Through analyzing thermocatalytic CO oxidation and CO 2 reduction, two fundamentally and industrially important reactions, we compare representative nanocluster and single-atom catalytic systems from perspectives of intrinsic chemistry and reaction engineering. Generally, nanoclusters and single atoms display different catalytic performances (i.e., activity, selectivity, and stability) for these reactions depending on the synthesis methods, support materials, and reaction conditions. Key observations of activity and selectivity tradeoffs between nanoclusters and single-atom catalysts are highlighted. Here, the dynamic structural responses of these catalytic species under CO oxidation or CO 2 reduction reaction conditions are also discussed. Synthetic control and detailed experimental and computational characterization of single-atom and nanocluster catalysts for CO and CO 2 conversion have led to exciting progress over the past decade. Still, more efforts are needed to understand and develop catalysts that meet the environmental, energy, and technical requirements to power a sustainable global economy.

03 NATURAL GAS↗

Radiosonde Observations of Environments Supporting Deep Moist Convection Initiation during RELAMPAGO-CACTI

The Remote Sensing of Electrification, Lightning, and Mesoscale/Microscale Processes with Adaptive Ground Observations (RELAMPAGO) and Cloud, Aerosol, and Complex Terrain Interactions (CACTI) projects deployed a high-spatiotemporal-resolution radiosonde network to examine environments supporting deep convection in the complex terrain of central Argentina. This study aims to characterize atmospheric profiles most representative of the near-cloud environment (in time and space) to identify the mesoscale ingredients affecting storm initiation and growth. Spatiotemporal autocorrelation analysis of the soundings reveals that there is considerable environmental heterogeneity, with boundary layer thermodynamic and kinematic fields becoming statistically uncorrelated on scales of 1–2 h and 30 km. Using this as guidance, we examine a variety of environmental parameters derived from soundings collected within close proximity (30 km in space and 30 min in time) of 44 events over 9 days where the atmosphere either: 1) supported the initiation of sustained precipitating convection, 2) yielded weak and short-lived precipitating convection, or 3) produced no precipitating convection in disagreement with numerical forecasts from convection-allowing models (i.e., Null events). There are large statistical differences between the Null event environments and those supporting any convective precipitation. Null event profiles contained larger convective available potential energy, but had low free-tropospheric relative humidity, higher freezing levels, and evidence of limited horizontal convergence near the terrain at low levels that likely suppressed deep convective growth. Here, we also present evidence from the radiosonde and satellite measurements that flow–terrain interactions may yield gravity wave activity that affects CI outcome.

54 ENVIRONMENTAL SCIENCES↗

Measuring and Simulating T1 and T2 for Qubits

Quantum computers perform computations exploiting quantum mechanics to a possible advantage, allowing us to prepare and manipulate states that do not have a classical equivalent. In particular, phenomena like superposition and entanglement may enable quantum computers to outperform their classical counterparts in certain applications. Implementing these useful quantum algorithms is contingent upon building accurate quantum hardware that is not affected by noise. Environmental noise decreases coherence time of qubits, meaning that qubits do not stay in a desired state long enough to carry out a complex computation. To that end, harnessing the full power of quantum computers necessitate characterization of noise sources and how they impact a given quantum system. Often times, T1and T2 are used to quantify noise. In this project, we provide an approach as to how T1 and T2 values are calculated and simulated for quantum systems. In addition, we compare simulated values of T1 and T2 with those of real quantum computer’s measurements. IBMQ Experience, an open source software allowing users to simulate and use real quantum hardware, is used. QuTip, a Python-based toolbox offering quantum simulation tools for open quantum systems, is also used.

Youssef, Rahaf↗

Wabash CarbonSAFE. Final Report

This document summarizes work detailed in separate Wabash CarbonSAFE reports; the report describes the data collection efforts of the project and consolidates the geologic characterization, well testing, and storage complex modeling results for the Mt. Simon Sandstone and Potosi Dolomite, two distinct reservoirs characterized at the Wabash CarbonSAFE project site. Also presented are summaries of work to characterize the CO 2 source and infrastructure network, as well as summaries of reports analyzing stakeholder engagement options, policy, regulatory and legal considerations, and risk assessment associated with the Wabash CarbonSAFE project site. The report then presents recommendations for the next steps for site characterization, identifies data gaps for future activities, and provides an overall assessment of site potential.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

Intrabasin Comparison of Produced Fluid From Hydraulically Fractured Wells in the Permian Region

The Permian Basin is the highest producing oil and gas reservoir in the United States. Hydrocarbon extraction methods in this region are often associated with frac hits, or interwell communication events where an established well is affected by the pumping of fracture fluid into a new well. Our previous work revealed a unique geochemical signal indicating the presence of frac hits in the Permian Basin. We returned to this area with the overall goal of expanding our understanding of the microbial and geochemical dynamics common in this region. To do so, we collected produced water from 25 unique sites across the Permian Basin, 10 of which had previously been characterized during an active frac hit with the rest being novel. For each sample, we measured the pH, alkalinity, geochemical composition, microbial load (qPCR), and microbial community composition (16S rRNA sequencing). Permian Basin produced water is characterized by higher sulfate and lower total dissolved solids (TDS) concentrations compared to other regions. Interestingly, wells impacted by frac hits have a geochemical profile that resembles that of fracture fluid, with both lowered sulfate and lowered TDS concentrations compared to unaffected wells in this region. Due to the year-long recovery window between sample collection periods, we anticipate that all of our data will be characterized by the typical high sulfate, low TDS concentrations.

environmental microbiology↗

Global land use for 2015-2100 at 0.05° resolution under diverse socioeconomic and climate scenarios

Global future land use (LU) is an important input for Earth system models for projecting Earth system dynamics and is critical for many modeling studies on future global change. Here we generated a new global gridded LU dataset using the Global Change Analysis Model (GCAM) and a land use spatial downscaling model, named Demeter, under the five Shared Socioeconomic Pathways (SSPs) and four Representative Concentration Pathways (RCPs) scenarios. Compared to existing similar datasets, the presented dataset has a higher spatial resolution (0.05°×0.05°) and spreads under a more comprehensive set of SSP-RCP scenarios (in total 15 scenarios), and considers uncertainties from the forcing climates. We compared our dataset with the Land Use Harmonization version 2 (LUH2) dataset and found our results are in general spatially consistent with LUH2. The presented dataset will be useful for global Earth system modeling studies, especially for the analysis of the impacts of land use and land cover change and socioeconomics, as well as the characterizing the uncertainties associated with these impacts.

54 ENVIRONMENTAL SCIENCES↗

Impact of intense sanitization procedures on bacterial communities recovered from floor drains in pork processing plants

Pork processing plants in the United States (US) cease operations for 24–48 h every six or twelve months to perform intense sanitization (IS) using fogging, foaming, and further antimicrobial treatments to disrupt natural biofilms that may harbor pathogens and spoilage organisms. The impact such treatments have on short-term changes in environmental microorganisms is not well understood, nor is the rate at which bacterial communities return. Swab samples were collected from floor drains to provide representative environmental microorganisms at two US pork processing plants before, during, and after an IS procedure. Samples were collected from four coolers where finished carcasses were chilled and from four locations near cutting tables. Each sample was characterized by total mesophile count (TMC), total psychrophile count (TPC), and other indicator bacteria; their biofilm-forming ability, tolerance of the formed biofilm to a quaternary ammonium compound (300 ppm, QAC), and ability to protect co-inoculated Salmonella enterica. In addition, bacterial community composition was determined using shotgun metagenomic sequencing. IS procedures disrupted bacteria present but to different extents depending on the plant and the area of the plant. IS reduced TPC and TMC, by up to 1.5 Log 10 CFU only to return to pre-IS levels within 2–3 days. The impact of IS on microorganisms in coolers was varied, with reductions of 2–4 Log 10 , and required 2 to 4 weeks to return to pre-IS levels. The results near fabrication lines were mixed, with little to no significant changes at one plant, while at the other, two processing lines showed 4 to 6 Log 10 reductions. Resistance to QAC and the protection of Salmonella by the biofilms varied between plants and between areas of the plants as well. Community profiling of bacteria at the genus level showed that IS reduced species diversity and the disruption led to new community compositions that in some cases did not return to the pre-IS state even after 15 to 16 weeks. The results found here reveal the impact of using IS to disrupt the presence of pathogen or spoilage microorganisms in US pork processing facilities may not have the intended effect.

59 BASIC BIOLOGICAL SCIENCES↗

Next-Generation Ecosystem Experiments–Arctic Flyer

An important challenge for Earth system models (ESMs) is to accurately represent land surface and subsurface processes and their complex interactions. This is true for all regions of the world, but is especially important for high-latitude Arctic ecosystems that are characterized by ice-rich landscapes where topography, hydrology, vegetation, and biogeochemistry are inexplicitly linked. To address this challenge, the Terrestrial Ecosystem Science (TES) program within the Department of Energy’s (DOE) Office of Biological and Environmental Research (BER) is supporting a next-generation ecosystem experiments project in the Arctic (NGEE–Arctic).

54 ENVIRONMENTAL SCIENCES↗

Innovative Biomonitoring and Remediation of Heavy Metals Using Phytotechnologies at the Savannah River Site (SRS) Coal Combustion Product (CCP) Impoundment Sites

The Savannah River Site (SRS) contains legacy coal combustion product (CCP) impoundments that are impacted by elevated concentrations of heavy metals and radionuclides, posing long-term risks to soil health, ecosystem functioning, and environmental sustainability. Traditional environmental monitoring approaches rely primarily on chemical analyses to quantify contaminant concentrations but often provide limited information regarding biological responses or ecosystem recovery. This project addressed these limitations by integrating environmental chemistry, microbial ecology, artificial intelligence (AI), and bioremediation into a comprehensive framework for environmental diagnostics and restoration of contaminated soils. The overarching goal of this collaborative project between Florida A&M University (FAMU) and the University of Georgia's Savannah River Ecology Laboratory (SREL) was to develop innovative biomonitoring and remediation strategies for heavy metal-contaminated CCP impoundment sites at the Savannah River Site. Specifically, the project sought to (i) characterize heavy metal contamination, (ii) determine microbial responses to contamination, (iii) isolate indigenous heavy metal-resistant microorganisms for remediation applications, (iv) develop a microbial ecological health index using machine learning, and (v) optimize fungal-mediated bioremediation using artificial intelligence.

01 COAL, LIGNITE, AND PEAT↗

Using the red chromatic coordinate to characterize the phenology of forest canopy photosynthesis

Vegetation phenology has received increasing attention in climate change research. Near-surface sensing using digital repeat photography has proven to be useful for ecosystem-scale monitoring of vegetation phenology. However, our understanding of the link between phenological metrics derived from digital repeat photography and the phenology of forest canopy photosynthesis is still incomplete, especially for evergreen plant species. Using 49 site-years of digital images from the PhenoCam Network from eight evergreen needleleaf forest (ENF) and six deciduous broadleaf forest (DBF) sites in North America, we explored the potential of the green chromatic (GCC) and red chromatic coordinates (RCC) in tracking forest canopy photosynthesis by comparing camera-derived start- and end-of-growing season (SOS and EOS, respectively) with corresponding estimates derived from eddy covariance-derived daily gross primary productivity (GPP). We found that for DBF sites, both GCC and RCC performed comparable in capturing SOS and EOS. However, similar to earlier studies, GCC had limited potential in capturing GPP-based SOS or EOS for ENF sites. In contrast, we found RCC was a better predictor of both GPP-based SOS and EOS for ENF sites. Environmental and ecological explanations were both provided that phenological transitions derived from RCC were highly correlated with spring and autumn meteorological conditions, as well as having overall higher correlations with phenology based on LAI, a critical variable for describing canopy development. Our results demonstrate that RCC is an underappreciated metric for tracking vegetation phenology, especially for ENF sites where GCC failed to provide reliable estimates for GPP-based SOS or EOS. Our results improve confidence in using digital repeat photography to characterize the phenology of canopy photosynthesis across forest types.

54 ENVIRONMENTAL SCIENCES↗

Literature Review of Documented Persistent Secondary Uranium Sources at DOE LM Sites

The U.S. Department of Energy Office of Legacy Management (LM) has the responsibility to protect human health and the environment at 101 legacy uranium sites across the nation by implementing long-term surveillance and maintenance requirements. Included in these responsibilities is to provide for the safe and environmentally sound disposal, long-term stabilization, and control of uranium mill tailings in a manner that minimizes or eliminates radiation health hazards to the public at 21 Uranium Mill Tailings Radiation Control Act (UMTRCA) Title I sites; 6 UMTRCA Title II sites; and 9 Comprehensive Environmental Response, Compensation, and Liability Act/Resource Conservation and Recovery Act sites. These sites are former uranium mills (processing sites), or sites with wastes from processing sites encapsulated in engineered disposal cells (disposal sites), or sites where components of atomic weapons were manufactured. During site characterization, groundwater contamination was often discovered and evaluated or modeled for future movement with the inclusion of uranium sorption in the groundwater plume. Much of this original work did identify uranium processing wastes as the original contaminant source. However, more recent work has identified the existence and influence of persistent secondary uranium sources that may prevent uranium in groundwater from attenuating as quickly as initial evaluations or modeling indicated. By understanding these processes, better decisions can be made to choose the appropriate remediation and closure strategies, identify long-term surveillance and maintenance activities, and more accurately estimate life-cycle costs. The purpose of this report is to summarize the literature available on documented persistence secondary uranium sources at LM sites as part of the Applied Studies and Technology Persistent Secondary Contaminant Sources Project.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗