Characterizing Wet Season Precipitation in the Central Amazon Using a Mesoscale Convective System Tracking Algorithm
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54 ENVIRONMENTAL SCIENCES↗
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Results for “environmental characterization”
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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The BRIAR Dataset: A Comprehensive Whole-Body Biometric Recognition Benchmark at Extreme Distances and Altitudes (Collections 1-6)
The Biometric Recognition and Identification at Altitude and Range (BRIAR) program aims to extend biometric capabilities into severe operational environments characterized by long ranges, atmospheric turbulence, and elevated viewpoints. This paper introduces the program’s two final government collections expanding activities, environments, viewpoints, distances, and modalities, and adding appearance and environmental stressors. We refine curation/evaluation and include sequestered subsets to support controlled assessments. These updates strengthen BRIAR as a comprehensive resource for whole-body, face, and gait recognition at altitude and range, while maintaining privacy-first practices.
Yoon, Rocky [ORNL] (ORCID:0009000491499165)↗
Environmental controls on observed spatial variability of soil pore water geochemistry in small headwater catchments underlain with permafrost
Abstract. Soil pore water (SPW) chemistry can vary substantially across multiple scales in Arctic permafrost landscapes. The magnitude of these variations and their relationship to scale are critical considerations for understanding current controls on geochemical cycling and for predicting future changes. These aspects are especially important for Arctic change modeling where accurate representation of sub-grid variability may be necessary to predict watershed-scale behaviors. Our research goal is to characterize intra- and inter-watershed soil water geochemical variations at two contrasting locations in the Seward Peninsula of Alaska, USA. We then attempt to identify the key factors controlling concentrations of important pore water solutes in these systems. The SPW geochemistry of 18 locations spanning two small Arctic catchments was examined for spatial variability and its dominant environmental controls. The primary environmental controls considered were vegetation, soil moisture and/or redox condition, water–soil interactions and hydrologic transport, and mineral solubility. The sampling locations varied in terms of vegetation type and canopy height, presence or absence of near-surface permafrost, soil moisture, and hillslope position. Vegetation was found to have a significant impact on SPW NO3- concentrations, associated with the localized presence of nitrogen-fixing alders and mineralization and nitrification of leaf litter from tall willow shrubs. The elevated NO3- concentrations were, however, frequently equipoised by increased microbial denitrification in regions with sufficient moisture to support it. Vegetation also had an observable impact on soil-moisture-sensitive constituents, but the effect was less significant. The redox conditions in both catchments were generally limited by Fe reduction, seemingly well-buffered by a cache of amorphous Fe hydroxides, with the most reducing conditions found at sampling locations with the highest soil moisture content. Non-redox-sensitive cations were affected by a wide variety of water–soil interactions that affect mineral solubility and transport. Identification of the dominant controls on current SPW hydrogeochemistry allows for qualitative prediction of future geochemical trends in small Arctic catchments that are likely to experience warming and permafrost thaw. As source areas for geochemical fluxes to the broader Arctic hydrologic system, geochemical processes occurring in these environments are particularly important to understand and predict with regards to such environmental changes.
Conroy, Nathan Alec (ORCID:0000000305973373)↗
Characteristics and Variability of the Nearshore Wave Resource on the U.S. West Coast
Characterizing the nearshore wave resource at a regional scale poses a great challenge because high-quality wave data are required. This paper presents a detailed analysis of nearshore wave climate and resource characterization on the U.S. West Coast based on a 32-year, regional wave hindcast. Resource characterization closely followed the International Electrotechnical Commission standards. The wave hindcast data were generated from an unstructured-grid SWAN model with approximately 300 m grid resolution in the nearshore region. Statistics of six IEC wave resource parameters at the 50 m water depth were calculated for four sub-regions along the coast, including Washington, Oregon, and Northern and Southern California. Results indicate that the Washington and Oregon coast has a similar nearshore wave resource. The wave resource in Southern California is significantly less than that of the Washington and Oregon coast. Alongshore and cross-shore variabilities of wave power were assessed. Temporal variability, at seasonal, inter-annual, and decadal scales were analyzed. Overall, strong seasonal variation is observed; high wave energy occurs in the winter months and calm seas in the summer. Finally, extreme environmental conditions, i.e., the 100-year extreme environmental contours, for different locations along the West Coast were investigated.
wave resource characterization, nearshore, west co↗
Circular economy framework for automobiles: Closing energy and material loops
Abstract Corporations, including automotive manufacturers, are increasingly exploring extended circular economy strategies as a means to enhance the sustainability of their products. The circular economy paradigm focuses on reducing nonrenewable materials and energy, promoting renewable feedstocks and energy, and keeping products/materials in use across the life cycle of a system. As such, life cycle environmental burdens associated with vehicle manufacturing, use, and disposal could potentially be reduced through circular economy strategies; however, no such comprehensive circular economy framework currently exists for the automotive industry. We develop the first circular economy schematic of automobiles, derived from the Ellen MacArthur Foundation's framework. Further, we characterize the current automotive circular economy using metrics of renewable energy and recycled materials. Specifically, for current U.S. average sedans, we find that internal combustion engine vehicles (ICEVs) use ∼6% renewable life cycle primary energy and 27% recycled materials; for battery electric vehicles (BEVs), these measures are ∼8% and 21%, respectively. On a vehicle‐miles‐traveled basis, BEVs use ∼47% less nonrenewable life cycle primary energy than ICEVs, highlighting the importance of electrification as a strategy for automotive manufacturers to reduce environmental burdens. Our proposed circular economy framework is then applied to Ford Motor Company's sustainability programs and initiatives as an example. This schematic aims to provide a starting point for the automotive industry to operationalize circular economy strategies, the application of which could advance its overall sustainability performance.
Aguilar Esteva, Laura C.↗
Microbial and Environmental Processes Shape the Link between Organic Matter Functional Traits and Composition
Dissolved organic matter (DOM) is a large and complex mixture of molecules that fuels biogeochemical reaction in virtually all ecosystems on Earth. However, the relative importance of deterministic and stochastic processes in structuring DOM composition remains poorly characterized. Here we develop a framework for partitioning molecular composition based on key molecular traits, including lability vs. recalcitrance and activity vs. inactivity. Within this framework, we examine the ecological processes governing the assembly of DOM fractions by deploying aquatic microcosms on mountainsides that span gradients of temperature and nutrient loading in subtropical and subarctic ecosystems. Across study regions, deterministic and stochastic processes primarily structure active and inactive fractions, respectively. However, recalcitrant molecules are more deterministically assembled than labile molecules in the inactive fraction. Deterministic processes leading to variable selection generally exhibit more variation across the energy supply gradient for inactive fractions, and their importance increases with energy supply for recalcitrant molecules in both active and inactive fractions. Together, our results indicate that active and inactive fractions of DOM assemblages are structured by contrasting ecological processes, and their recalcitrant components are sensitive to global change. In conclusion, our framework opens new avenues to understand the assembly and turnover of DOM in a changing world, which can be used to predict carbon cycling at local to global scales.
54 ENVIRONMENTAL SCIENCES↗
Environmental degradation of electroplated nickel and copper coated SS316H in molten FLiNaK salt
Corrosion of nickel and copper electroplated coatings on SS316H in molten FLiNaK salt was studied. 500- and 1000-hour static corrosion tests were performed in molten FLiNaK at 700 degrees Celsius. Characterization of the coatings following corrosion indicated that they did not degrade in the molten salt during the corrosion experiment and fully protected the underlying SS316H from chromium dissolution. Interdiffusion between the copper coating and SS316H was extremely limited, interdiffusion between the nickel coating and SS316H. Diffusion modelling revealed that the nickel coatings still significantly reduced chromium dissolution over 60 years despite the interdiffusion.
36 MATERIALS SCIENCE↗
Seasonal drivers of dissolved oxygen across a tidal creek–marsh interface revealed by machine learning
Abstract Dissolved oxygen (DO) is a key biogeochemical control in coastal systems, and its concentration and drivers vary markedly through time and space. This makes it difficult to accurately represent coastal DO and associated biogeochemical processes in models, limiting our ability to predict how these systems will respond to global change. We obtained high‐frequency (5‐min) in situ measurements of DO collected at three locations across the interface of a tidal creek and coastal marsh in the Pacific Northwest, USA. Random Forest machine learning models quantified the importance of three categories of environmental drivers (Aquatic, Climatic, and Terrestrial) of DO variability across the creek–marsh interface. We selected two 4‐month datasets representing Summer and Winter seasonal periods to test two hypotheses on the dominant drivers of DO at the coastal interface. We found that the Terrestrial driver—characterized by long periods of anaerobic conditions and episodic pulses in DO after floods—was most important during the Winter, whereas the Aquatic driver—characterized by variability over tidal, diel, and lunar cycles—was most important during the Summer. We explored how future climate change scenarios could alter the drivers of DO variability using a cumulative sums driver–response framework. Our results suggest that under climate change, Aquatic and Climatic drivers may increase in importance during the Summer, potentially linked to changing metabolic regimes and sea level, with Terrestrial driver importance potentially increasing during the Winter. Our approach highlights useful methods for understanding the spatiotemporal complexity of oxygen across coastal interfaces and quantifying the relative importance of distinct environmental drivers.
54 ENVIRONMENTAL SCIENCES↗
Temporal dynamics of protein and post-translational modification abundances in Populus leaf across a diurnal period
Populus spp. are dedicated woody biomass feedstocks for advanced biofuels and bioproducts. Proper growth and fitness of poplar as a sustainable feedstock depends on timely perception and response to environmental signals (e.g., light, temperature, water). Poplar leaves, like other C3 photosynthesis plants, have evolved oscillating or circadian rhythms that play important roles in synchronizing biological processes with external cues. To characterize this phenomenon at a molecular level, we employed bottom-up proteomics using high-resolution mass spectrometry and de novo-assisted database searching to identify abundance changes in proteins and post-translational modifications in poplar leaf tissue sampled across a 12/12-hour light/dark diurnal period.
09 BIOMASS FUELS↗
Hourglass–Shaped Nanocages with Concaved Structures Based on Selective Self–Complementary Coordination Ligands and Tunable Hierarchical Self–Assembly
Three-dimensional (3D) structures constructed via coordination-driven self-assemblies have recently garnered increasing attention due to the challenges in structural design and potential applications. In particular, developing new strategy for the convenient and precise self-assemblies of 3D supramolecular structures is of utmost interest. Introducing the concept of self-coordination ligands, herein the design and synthesis of two meta-modified terpyridyl ligands with selective self-complementary coordination moiety are reported and their capability to assemble into two hourglass-shaped nanocages SA and SB is demonstrated. Within these 3D structures, the meta-modified terpyridyl unit preferably coordinates with itself to serve as concave part. By changing the arm length of the ligands, hexamer (SA) and tetramer (SB) are obtained respectively. In-depth studies on the assembly mechanism of SA and SB indicate that the dimers could be formed first via self-complementary coordination and play crucial roles in controlling the final structures. Moreover, both SA and SB can go through hierarchical self-assemblies in solution as well as on solid–liquid interface, which are characterized by transmission electron microscope (TEM) and scanning tunneling microscopy (STM). As a result, it is further demonstrated that various higher-order assembly structures can be achieved by tuning the environmental conditions.
3D metallo-supramolecules↗
Optimization-based approaches to control of connected and automated vehicles: Principles, complexities, applications, challenges, and outlook
Safe and optimal motion control for connected and automated vehicles (CAVs) poses a fundamental optimization challenge at the intersection of system complexity, environmental uncertainty, and stringent real-time constraints. Existing surveys address this challenge in isolation – focusing either on specific control techniques or individual uncertainty sources – without providing a unified framework that characterizes the trade-offs among computational tractability, performance verifiability, and adaptive generalization across paradigms. This review addresses that gap by presenting a cohesive analytical framework concentrated on the decision-making and trajectory optimization layers of the CAV autonomy stack. We systematically analyze three major optimization paradigms – first-principles model-based optimization, data-driven methods, and hybrid synergistic architectures – evaluating each against four core complexity axes: problem formulation, constraint handling, optimality guarantees, and robustness. Key applications including platooning, trajectory planning, collision avoidance, and cooperative control are examined to reveal recurring methodological patterns and critical operational constraints that limit real-world performance. Our synthesis identifies verifiable hybrid architectures, incentive-aligned multi-agent cooperation, and hardware-algorithm co-design as the defining research frontiers, and distills a targeted agenda for developing CAV control systems that are simultaneously safe, computationally efficient, and deployable in the full complexity of real-world traffic environments.
Muzahid, Abu Jafar Md [University of Tennessee, Kn↗
Characterizing soil water content variability across spatial scales from optimized high-resolution distributed temperature sensing technique
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54 ENVIRONMENTAL SCIENCES↗
Using the Black Carbon Particle Mixing State to Characterize the Lifecycle of Biomass Burning Aerosols
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54 ENVIRONMENTAL SCIENCES↗
Earthworms Exposed to Polyethylene and Biodegradable Microplastics in Soil: Microplastic Characterization and Microbial Community Analysis
While much is known about microplastics in aquatic environments, only few studies have focused on how microplastics interact with terrestrial organisms. The objective of our study was to investigate the interactions of earthworms with microplastics in a natural environment with environmentally realistic plastic concentrations. Here we investigated whether earthworms would ingest microplastics and incorporate them into their bodies and cast, and whether microplastics would alter the intestinal and soil microbiome. Lumbricus terrestris was exposed to two types of mi croplastics, biodegradable polybutylene adipate terephthalate (PBAT) and low-density polyethylene (LDPE) in mesocosoms filled with natural soil. Microplastics were mixed with poplar leaves and earthworms were allowed to forage for food for 20 days. Surface and bulk soil, earthworm cast, and earthworms themselves were sampled and analyzed for plastic content and microbial communities. Earthworms did not show macroscopic health deterioration (weight loss, vitality). We observed microplastics particles in earthworm casts and guts. Raman spectroscopy indicated that PBAT in guts and cast had degraded to some extent; however, LDPE remained unchanged among the different samples. Microbial analysis showed that soil and casts has similar microbial communities; however, they were signicantly different from the guts samples. Microplastic treatments did not result in a statistically signicant change in bacterial richness, diversity or community composition compared to controls. Taken together, our results suggest that, at environmentally realistic concentrations and short exposure times, PBAT and LDPE microplastics do not have adverse effects on Lumbricus terrestris earthworms.
37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗
Neglecting Model Parametric Uncertainty Can Drastically Underestimate Flood Risks
Abstract Floods drive dynamic and deeply uncertain risks for people and infrastructures. Uncertainty characterization is a crucial step in improving the predictive understanding of multi‐sector dynamics and the design of risk‐management strategies. Current approaches to estimate flood hazards often sample only a relatively small subset of the known unknowns, for example, the uncertainties surrounding the model parameters. This approach neglects the impacts of key uncertainties on hazards and system dynamics. Here we mainstream a recently developed method for Bayesian inference to calibrate a computationally expensive distributed hydrologic model. We compare three different calibration approaches: (a) stepwise line search, (b) precalibration or screening, and (c) the Fast Model Calibrations (FaMoS) approach. FaMoS deploys a particle‐based approach that takes advantage of the massive parallelization afforded by modern high‐performance computing systems. We quantify how neglecting parametric uncertainty and data discrepancy can drastically underestimate extreme flood events and risks. Precalibration improves prediction skill score over a stepwise line search. The Bayesian calibration improves the uncertainty characterization of model parameters and flood risk projections.
54 ENVIRONMENTAL SCIENCES↗
Quantitative temporally and spatially resolved X-ray fluorescence microprobe characterization of the manganese dissolution-deposition mechanism in aqueous Zn/α-MnO 2 batteries
Rechargeable aqueous Zn/α-MnO 2 batteries are a possible alternative to lithium ion batteries for scalable stationary energy storage applications due to their low cost, safety and environmentally benign components. A critical need for advancement of this battery system is a full understanding of the electrochemical reaction mechanisms, which remain unclear. In this report, operando , spatiotemporal resolved synchrotron X-ray fluorescence mapping measurements on a custom aqueous Zn/α-MnO 2 cell provided direct evidence of a Mn dissolution-deposition faradaic mechanism that governs the electrochemistry. Simultaneous visualization and quantification of the Mn distribution in the electrolyte revealed the formation of aqueous Mn species during discharge and depletion on charge. The findings are supported by ex situ transmission electron microscopy (TEM), X-ray diffraction, Mn K-edge X-ray absorption near edge structure (XANES) and extended X-ray absorption fine structure (EXAFS) measurements. The elucidated mechanism is fundamentally different from the previously proposed Zn 2+ insertion or conversion reactions. These findings provide a foundation for developing dissolution- deposition chemistries suitable for scalable stationary energy storage with aqueous electrolyte.
25 ENERGY STORAGE↗
TRACER-VOC: Speciated Volatile Organic Compounds at the Tracking Aerosol Convection Interactions Experiment Field Campaign Report
Formation of secondary organic aerosol (SOA) is responsible for the growth of particles into cloud condensation nuclei (CCN)-relevant sizes and accounts for a substantial fraction of aerosol mass in the troposphere. Despite its wide abundance and importance, capturing SOA in regional and climate models is still challenging due to complex chemical transformations involved in production of SOA. Oxidation products of biogenic hydrocarbons, such as isoprene, monoterpenes, and sesquiterpenes account for the largest fraction of SOA mass over the continents. As such, biogenic SOA is an important source of continental CCN, and has been recently shown to nucleate ice in the deposition mode. To better account for the processes involved in SOA formation in global and regional climate models, we need better measurements of sources and transformations of volatile organic compounds (VOCs), the precursors to SOA formation in the atmosphere. Understanding aerosol-deep convection interactions is an important science driver of the Tracking Aerosol Convection Interactions Experiment (TRACER), requiring a characterization of the critical controls on aerosol properties and processes, and how those properties and processes vary spatially and temporally in the Houston area. In that environment, the atmospheric photo-oxidative chemistry that drives the evolution and transformation of aerosol properties and processes is strongly impacted by the emission of VOCs, which have both anthropogenic (e.g., industrial, urban, transportation, biomass burning) and biogenic (e.g., marine) sources in the region. Understanding (and disentangling) the complex role of VOCs in such a heterogenous region requires high-time-resolution, speciated VOC measurements that are spatially resolved. To meet these measurement requirements, the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) user facility’s time-of-flight proton transfer reaction-mass spectrometer (ToF-PTR-MS) was deployed during the TRACER intensive operational period (IOP) from June to September, 2022 at the ancillary site (ANC), which was sited to provide a characterization of the rural atmospheric environment in contrast to the main site.
54 ENVIRONMENTAL SCIENCES↗
Turbulent Processes that Influence Boundary-Layer Cloud Structure (Final Technical Report)
Many models of the atmosphere simulate vertical profiles of observable fields, such as temperature, moisture, and vertical velocity. To assess the realism of such model output, it is important to evaluate the modeled profiles against observations. However, many extant evaluations consist of comparing time averaged profiles from the model and the observations. Such time averages can smooth out unrealistic features that appear in instantaneous profiles. In this way, the time averages may obscure certain model errors from detection. For instance, many models misrepresent turbulent processes, leading to profiles that are too smoothed out or too noisy. E.g., if a model has coarse vertical resolution and overly strong diffusion, then the model may be unable to produce observed sharp peaks. On the other hand, a model may have artificial approximations that produce spurious jumps in the vertical. Much can be learned by browsing through instantaneous snapshots of model output. But the volume of output produced by a global model is far too great to rely purely on visual inspection. In addition, we need a way to statistically characterize the profiles, so that anomalies can be detected more conveniently.
54 ENVIRONMENTAL SCIENCES↗