Search NASA⌕ Search

SEARCH · Search NASA

Results for “resolution process”

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.

Quote a phrase for an exact phrase match. Source license links do not imply unrestricted reuse.

At least 631 records · Page 35

Multidimensional visualization of the dynamic evolution of Li metal via in situ/operando methods

The growing demands for high-energy density electrical energy storage devices stimulate the coupling of conversion-type cathodes and lithium (Li) metal anodes. While promising, the use of these “Li-free” cathodes brings new challenges to the Li anode interface, as Li needs to be dissolved first during cell operation. In this study, we have achieved a direct visualization and comprehensive analysis of the dynamic evolution of the Li interface. The critical metrics of the interfacial resistance, Li growth, and solid electrolyte interface (SEI) distribution during the initial dissolution/deposition processes were systematically investigated by employing multidimensional analysis methods. They include three-electrode impedance tests, in situ atomic force microscopy, scanning electrochemical microscopy, and cryogenic scanning transmission electron microscopy. The high-resolution imaging and real-time observations show that a loose, diffuse, and unevenly distributed SEI is formed during the initial dissolution process. This leads to the dramatically fast growth of Li during the subsequent deposition, deviating from Fick’s law, which exacerbates the interfacial impedance. The compactness of the interfacial structure and enrichment of electrolyte species at the surface during the initial deposition play critical roles in the long-term stability of Li anodes, as revealed by operando confocal Raman spectroscopic mapping. In conclusion, our observations relate to ion transfer, morphological and structural evolution, and Li (de)solvation at Li interfaces, revealing the underlying pathways influenced by the initial dissolution process, which promotes a reconsideration of anode investigations and effective protection strategies.

25 ENERGY STORAGE↗

Rapid QSTS Simulations for High-Resolution Comprehensive Assessment of Distributed PV

The rapid increase in penetration of distributed energy resources on the electric power distribution system has created a need for more comprehensive interconnection modeling and impact analysis. Unlike conventional scenario-based studies, quasi-static time-series (QSTS) simulations can realistically model time-dependent voltage controllers and the diversity of potential impacts that can occur at different times of year. However, to accurately model a distribution system with all its controllable devices, a yearlong simulation at 1-second resolution is often required, which could take conventional computers a computational time of 10 to 120 hours when an actual unbalanced distribution feeder is modeled. This computational burden is a clear limitation to the adoption of QSTS simulations in interconnection studies and for determining optimal control solutions for utility operations. The solutions we developed include accurate and computationally efficient QSTS methods that could be implemented in existing open-source and commercial software used by utilities and the development of methods to create high-resolution proxy data sets. This project demonstrated multiple pathways for speeding up the QSTS computation using new and innovative methods for advanced time-series analysis, faster power flow solvers, parallel processing of power flow solutions and circuit reduction. The target performance level for this project was achieved with year-long high-resolution time series solutions run in less than 5 minutes within an acceptable error.

24 POWER TRANSMISSION AND DISTRIBUTION↗

A High-resolution Regional Wave Resource Characterization For The U.S. West Coast

Objectives/Scope: Wave resource characterization is a critical step for wave energy converter deployment in the coastal ocean and relies on long-term, high-resolution wave datasets. This study presents a detailed modeling study of the wave resource along the U.S. West Coast (Washington, Oregon, and California), a coastal region that was identified with high wave energy potential in earlier studies. Methods, Procedures, Process: The wave hindcast covers a 32-year period from 1979 to 2010 and is based on a multi-resolution, unstructured-grid SWAN model framework. Model configuration closely follows and meets the requirements recommended by the International Electrotechnical Commission Technical Specification (IEC TS) for wave energy resource assessment and characterization (Class 2 - feasibility study). The model domain covers the entire U.S. Exclusive Economic Zone (EEZ) in the West Coast and has a spatial resolution varying from ~300 m in the nearshore region (20 km from the shoreline) to ~2500 m within the EEZ and ~5000 m at the open boundary, which extends beyond the EEZ. The model was forced by hourly 2-D wave spectra produced by a two-way nested WaveWatch III model, which covers the global ocean domain and the broader U.S. West Coast region domain with spatial resolutions of 0.5 degree and 10 arc-minutes, respectively. Both wave models are forced by hourly, 0.5-degree wind forcing obtained from NCEP’s Climate Forecast System Reanalysis (CFSR) product. Results, Observations, Conclusions: The standard model output for the SWAN model includes 3-hourly output for the six IEC wave resource parameters (e.g., omnidirectional wave power) at each grid point and hourly 2-D spectra at more than 50 NDBC buoys. Extensive model validation was achieved by comparing the six model-predicted IEC parameters with those derived from field observations at representative NDBC buoys. The error statistics indicated the model’s satisfactory performance. Further analyses were conducted to systematically evaluate the temporal and spatial distributions of wave energy potential and wave climate along the U.S. West Coast. Results suggest that Washington and Oregon coasts have similar nearshore wave resource, which is significantly higher than resources in Southern California. Strong seasonal variations are also observed, e.g., high wave energy tends to occur in the winter months. In summary, this study produced the first high-resolution, comprehensive dataset on wave energy distribution along the U.S. West Coast. Novel/Additive Information: The results are being used by the National Renewable Energy Laboratory to update the MHK Atlas, which was originally derived from NOAA’s 4-arc-minute WaveWatch III model output. In addition, the monthly averaged wave energy climatology dataset can be readily shared to support a variety of research and application efforts within the EEZ of the U.S. West Coast.

Wang, Taiping↗

In Vivo Entombment of Bacteria and Fungi during Calcium Oxalate, Brushite, and Struvite Urolithiasis

Human kidney stones form via repeated events of mineral precipitation, partial dissolution, and reprecipitation, which are directly analogous to similar processes in other natural and manmade environments, where resident microbiomes strongly influence biomineralization. High-resolution microscopy and high-fidelity metagenomic (microscopy-to-omics) analyses, applicable to all forms of biomineralization, have been applied to assemble definitive evidence of in vivo microbiome entombment during urolithiasis. Stone fragments were collected from a randomly chosen cohort of 20 patients using standard percutaneous nephrolithotomy (PCNL). Fourier transform infrared (FTIR) spectroscopy indicated that 18 of these patients were calcium oxalate (CaOx) stone formers, whereas one patient formed each formed brushite and struvite stones. This apportionment is consistent with global stone mineralogy distributions. Stone fragments from seven of these 20 patients (five CaOx, one brushite, and one struvite) were thin sectioned and analyzed using brightfield (BF), polarization (POL), confocal, super-resolution autofluorescence (SRAF), and Raman techniques. DNA from remaining fragments, grouped according to each of the 20 patients, were analyzed with amplicon sequencing of 16S rRNA gene sequences (V1–V3, V3–V5) and internal transcribed spacer (ITS1, ITS2) regions. Bulk-entombed DNA was sequenced from stone fragments in 11 of the 18 patients who formed CaOx stones, and the patients who formed brushite and struvite stones. These analyses confirmed the presence of an entombed low-diversity community of bacteria and fungi, including Actinobacteria, Bacteroidetes, Firmicutes, Proteobacteria, and Aspergillus niger. Bacterial cells approximately 1 μm in diameter were also optically observed to be entombed and well preserved in amorphous hydroxyapatite spherules and fans of needle-like crystals of brushite and struvite. In conclusion, these results indicate a microbiome is entombed during in vivo CaOx stone formation. Similar processes are implied for brushite and struvite stones. This evidence lays the groundwork for future in vitro and in vivo experimentation to determine how the microbiome may actively and/or passively influence kidney stone biomineralization.

59 BASIC BIOLOGICAL SCIENCES↗

Neutron-capture Element Abundances of 491 Stars in Milky Way Dwarf Satellite Galaxies from Medium-resolution Spectra

The chemical compositions of evolved stars in Local Group dwarf spheroidal galaxies (dSphs) provide insight into the galaxy’s past star formation and nucleosynthesis. Neutron-capture element abundances are especially interesting. In particular, s-process elements can provide a third chemical clock for resolving star formation histories in addition to core-collapse and Type Ia supernovae. Likewise, the primary sites of the r-process are still areas of extensive research. Until now, the number of stars with neutron-capture element abundances in dSphs has been limited by the need for stars bright enough for high-resolution spectroscopy. We present abundance measurements of the neutron-capture elements Sr, Y, Ba, and Eu with errors <0.4 dex—as well as new measurements of Mg—in 491 stars in Sculptor, Fornax, Draco, Sextans, and Ursa Minor. The large number of stars in our sample is possible because we used medium-resolution spectra from the DEIMOS spectrograph, assembling the largest homogeneous set of neutron-capture abundances in dSphs to date. By utilizing the abundances of both s- and r-process elements, we find evidence of an s-process contribution at early times in Sculptor from our measurements of [Ba/Fe]. This is a potential signature of s-process nucleosynthesis in fast-rotating massive stars. By comparing our measurements of [Eu/Fe] with [Mg/Fe], we show the need for an r-process source that has a short delay time to enrich stars in the dSphs. Thus, neutron star mergers are likely not the sole source of r-process material in dSphs.

79 ASTRONOMY AND ASTROPHYSICS↗

Thermal scanning probe and laser lithography for patterning nanowire based quantum devices

Semiconductor nanowire (NW) quantum devices offer a promising path for the pursuit and investigation of topologically-protected quantum states, and superconducting and spin-based qubits that can be controlled using electric fields. Theoretical investigations into the impact of disorder on the attainment of dependable topological states in semiconducting nanowires with large spin–orbit coupling and g-factor highlight the critical need for improvements in both growth processes and nanofabrication techniques. In this work, we used a hybrid lithography tool for both the high-resolution thermal scanning probe lithography and high-throughput direct laser writing of quantum devices based on thin InSb nanowires with contact spacing of 200 nm. Electrical characterization demonstrates quasi-ballistic transport. The methodology outlined in this study has the potential to reduce the impact of disorder caused by fabrication processes in quantum devices based on 1D semiconductors.

36 MATERIALS SCIENCE↗

Time-Resolved Geometric Feature Tracking Elucidates Laser-Induced Keyhole Dynamics

In this report, during laser melting of metals, localized metal evaporation resulting in the formation of a keyhole shaped cavity can occur if processing conditions are chosen with high power density. An unstable keyhole can have deleterious effects in certain applications (e.g., laser powder bed fusion) as it increases the likelihood of producing defects such as porosity. In this work, we propose a pipeline that enables complete segmentation and extraction of various geometric features in keyholing conditions. In situ synchrotron high-speed X-ray visualization at the Advanced Photon Source provides large datasets of experimental images with a high spatio-temporal resolution across a range of laser parameters for Ti-6Al- 4 V. Computer vision image processing techniques were used to extract time-resolved quantitative geometric features (e.g., depth, width, front wall angle) throughout keyhole evolution which were subsequently analyzed to understand the relationship between the variation of local keyhole geometry and processing conditions. This analysis is the first to employ a data-driven approach to further our understanding of the keyholing process regime.

36 MATERIALS SCIENCE↗

Quantifying rupture characteristics of microearthquakes in the Parkfield Area using a high-resolution borehole network

It is well known that large earthquakes often exhibit significant rupture complexity such as well separated subevents. With improved recording and data processing techniques, small earthquakes have been found to exhibit rupture complexity as well. Studying these small earthquakes offers the opportunity to better understand the possible causes of rupture complexities. Specifically, if they are random or are related to fault properties. We examine microearthquakes (M < 3) in the Parkfield, California, area that are recorded by a high-resolution borehole network. We quantify earthquake complexity by the deviation of source time functions and source spectra from simple circular (omega-square) source models. We establish thresholds to declare complexity, and find that it can be detected in earthquakes larger than magnitude 2, with the best resolution above M2.5. Comparison between the two approaches reveals good agreement (>90 per cent), implying both methods are characterizing the same source complexity. For the two methods, 60–80 per cent (M 2.6–3) of the resolved events are complex depending on the method. The complex events we observe tend to cluster in areas of previously identified structural complexity; a larger fraction of the earthquakes exhibit complexity in the days following the M w 6 2004 Parkfield earthquake. Ignoring the complexity of these small events can introduce artefacts or add uncertainty to stress drop measurements. Focusing only on simple events however could lead to systematic bias, scaling artefacts and the lack of measurements of stress in structurally complex regions.

58 GEOSCIENCES↗

Atomic resolution scanning transmission electron microscopy at liquid helium temperatures for quantum materials

Fundamental quantum phenomena in condensed matter, ranging from correlated electron systems to quantum information processors, manifest their emergent characteristics and behaviors predominantly at low temperatures. This necessitates the use of liquid helium (LHe) cooling for experimental observation. Atomic resolution scanning transmission electron microscopy combined with LHe cooling (cryo-STEM) provides a powerful characterization technique to probe local atomic structural modulations and their coupling with charge, spin and orbital degrees-of-freedom in quantum materials. However, achieving atomic resolution in cryo-STEM is exceptionally challenging, primarily due to sample drifts arising from temperature changes and noises associated with LHe bubbling, turbulent gas flow, etc. In this work, we demonstrate atomic resolution cryo-STEM imaging at LHe temperatures using a commercial side-entry LHe cooling holder. Firstly, we examine STEM imaging performance as a function of He gas flow rate, identifying two primary noise sources: He-gas pulsing and He-gas bubbling. Secondly, we propose two strategies to achieve low noise conditions for atomic resolution STEM imaging: either by temporarily suppressing He gas flow rate using the needle valve or by acquiring images during the natural warming process. Lastly, we show the applications of image acquisition methods and image processing techniques in investigating structural phase transitions in Cr 2 Ge 2 Te 6 , CuIr 2 S 4 , and CrCl 3 . In conclusion, our findings represent an advance in the field of atomic resolution electron microscopy imaging for quantum materials and devices at LHe temperatures, which can be applied to other commercial side-entry LHe cooling TEM holders.

36 MATERIALS SCIENCE↗

Generating Emissions Inventory for Carbon Capture and Storage Analysis for Carbon-Intensive Industrial Sectors

Decarbonizing the industrial sector is critical to achieve carbon dioxide (CO2) emissions reductions goals of the Biden Administration. Currently available decarbonization options include electrification, fuel switching to zero carbon fuels like green hydrogen (H2) and carbon capture and storage (CCS). Application of post-combustion carbon capture (PCCC) technology in the power sector, as well as research at the U.S. Department of Energy's Fossil Energy and Carbon Management (FECM) Office has shown that its application in the industrial sector could have co-benefits in the form of emissions reductions of non-CO2 regulated pollutants. For example, solvent based PCCC systems require pre-conditioning of flue gas to remove sulfur and particulate matter (PM) upstream of the CO2 absorber. However, there is a lack of understanding about the type of non-CO2 pollutants which can be captured and the amount of reduction possible. PCCC application differs across industrial sectors as it depends on the availability of decarbonization options, characteristics of industrial processes and the amount and composition of pollutant flows. Certain facilities can also have multiple effluent flows with or without a CO2 stream. As such, understanding industrial processes and their effluent flows in detail is required to quantify the co-benefits opportunities presented by PCCC. Considering this requirement, the goal of this analysis is to develop a high-resolution inventory of effluent flows from facilities of 8 industrial sectors in the U.S. These industrial sectors - ethanol, ammonia, cement, steel, natural gas processing, hydrogen, petroleum refining and wood and pulp products - have carbon-intensive effluent flows, and thus are prime candidates for PCCC applications. In this study, we map the composition of pollutant flow from flue stacks across the identified facilities. Using data available in three Environmental Protection Agency (EPA) databases - the Green House Gas Reporting Program (GHGRP), the National Emissions Inventory (NEI) and the Toxic Release Inventory (TRI), we create a combined inventory which lists the type, amount, and concentration of pollutant flows. Using total weight of the pollutant flow back calculated from observed data for CO2 concentrations in flue gas for individual sectors, we calculate the concentration of each pollutant in the flue gas stream. Thus, the resultant emissions inventory includes the following details for each facility in the sector: facility-level and if possible, process-level pollutant flows, concentrations of pollutants in the flue gas, and geographical coordinates of the facilities. A detailed statistical analysis and summary allows us to search for erroneous data and remove them from the final inventory. The generation of the inventory is achieved using a python-based framework which can recreate this inventory for other industrial sectors as well as using newer releases of emission inventories from EPA. The statistical analysis performed on the inventory is also calibrated and automated to identify outliers efficiently.

air pollutants↗

The Anatomy of an Unusual Edge-on Protoplanetary Disk. I. Dust Settling in a Cold Disk

As the earliest stage of planet formation, massive, optically thick, and gas-rich protoplanetary disks provide key insights into the physics of star and planet formation. When viewed edge-on, high-resolution images offer a unique opportunity to study both the radial and vertical structures of these disks and relate this to vertical settling, radial drift, grain growth, and changes in the midplane temperatures. In this work, we present multi-epoch Hubble Space Telescope and Keck scattered light images, and an Atacama Large Millimeter/submillimeter Array 1.3 mm continuum map for the remarkably flat edge-on protoplanetary disk SSTC2DJ163131.2–242627, a young solar-type star in ρ Ophiuchus. We model the 0.8 μm and 1.3 mm images in separate Markov Chain Monte Carlo (MCMC) runs to investigate the geometry and dust properties of the disk using the MCFOST radiative transfer code. In scattered light, we are sensitive to the smaller dust grains in the surface layers of the disk, while the submillimeter dust continuum observations probe larger grains closer to the disk midplane. An MCMC run combining both data sets using a covariance-based log-likelihood estimation was marginally successful, implying insufficient complexity in our disk model. The disk is well characterized by a flared disk model with an exponentially tapered outer edge viewed nearly edge-on, though some degree of dust settling is required to reproduce the vertically thin profile and lack of apparent flaring. A colder than expected disk midplane, evidence for dust settling, and residual radial substructures all point to a more complex radial density profile to be probed with future, higher-resolution observations.

47 OTHER INSTRUMENTATION↗

Sub-Sampled Imaging for STEM: Maximising Image Speed, Resolution and Precision Through Reconstruction Parameter Refinement

Sub-sampling during image acquisition in scanning transmission electron microscopy (STEM) has been shown to provide a means to increase the overall speed of acquisition while at the same time providing an efficient means to control the dose, dose rate and dose overlap delivered to the sample. In this paper, we discuss specifically the parameters used to reconstruct sub-sampled images and highlight their effect on inpainting using the beta-process factor analysis (BPFA) methodology. The selection of the main control parameters can have a significant effect on the resolution, precision and sensitivity of the final inpainted images, and here we demonstrate a method by which these parameters can be optimised for any image in STEM. As part of this paper, we also provide a link to open source code and a tutorial on its use, whereby these parameters can be tested for any datasets. When coupled with the hardware necessary to rapidly sub-sample images in STEM, this approach can have significant implications for imaging beam sensitive materials and dynamic processes.

47 OTHER INSTRUMENTATION↗

NSO Processing Scripts (NSO wind loading data set processing scripts) [SWR-23-86]

NREL conducted comprehensive field measurements of the atmospheric turbulent wind conditions and the resulting structural wind loads on parabolic troughs at the Nevada Solar One plant from October 2021 to June, 2023. The measurement set-up included meteorological masts and structural load sensors on four trough rows. Additionally, NREL commissioned a lidar scanning the horizontal plane over the trough field. The high-resolution data set, characterizing the complex flow field and resulting structural loads, is available at https://data.openei.org/submissions/5938. The processing routines published here were used to create the data from the instruments' raw data.

Egerer, Ulrike↗

Order-disorder in room-temperature ionic liquids probed via methyl quantum tunneling

Room-temperature ionic liquids are promising candidates for applications ranging from electrolytes for energy storage devices to lubricants for food and cellulose processing to compounds for pharmaceutics, biotransformation, and biopreservation. Due to the ion complexity, many room-temperature ionic liquids readily form amorphous phases upon cooling, even at modest rates. Here, we investigate two commonly studied imidazolium-based room-temperature ionic liquids, 1-ethyl-3-methylimidazolium tetrafluoroborate and 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide, as well as their mixtures, to demonstrate how the complex interplay between the crystalline and amorphous phases is affected by the processing conditions, such as thermal history, liquid mixing, and applied pressure. We show that quantum tunneling in the cation methyl groups, measured by high-resolution inelastic neutron scattering, can be used to probe the order-disorder in room-temperature ionic liquids (crystalline vs amorphous state) that develops as a result of variable processing conditions.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Self-consistent analysis for the η c → γ γ process

The next-to-next-to-leading-order (NNLO) perturbative QCD (pQCD) predictions for both the decay width and the transition form factor in the η c → γ γ process, based on nonrelativistic QCD (NRQCD), deviate from precise experimental measurements. These significant discrepancies have cast doubt on the applicability of NRQCD to charmonium processes. In this paper, we analyze the η c → γ γ process by applying the principle of maximum conformality (PMC), a systematic method for eliminating renormalization scheme-and-scale ambiguities. The PMC renormalization scales are determined by absorbing the nonconformal β -terms that govern the behavior of the QCD running coupling via the renormalization group equation. We obtain the PMC scale Q ⋆ = 4.49 m c for the η c → γ γ decay width. Even after using the PMC method, the convergence of the pQCD series is still poor, which indicates the importance of uncalculated next-to-next-to-next-to-leading-order and higher-order terms. The resulting value for Γ η c → γ γ is in agreement with the Particle Data Group’s reported value of Γ η c → γ γ = 5.1 ± 0.4 keV within the bounds of uncertainties. Moreover, the transition form factor obtained using the PMC is also in good agreement with precise experimental measurements. The application of the PMC suggests a potential resolution to η c → γ γ puzzle and supports the applicability of NRQCD to charmonium processes. Published by the American Physical Society 2025

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

Role of Ocean and Atmosphere Variability in Scale-Dependent Thermodynamic Air-Sea Interactions

This study investigates the influence of oceanic and atmospheric processes in extratropical thermodynamic air-sea interactions resolved by satellite observations (OBS) and by two climate model simulations run with eddy-resolving high-resolution (HR) and eddy-parameterized low-resolution (LR) ocean components. Here, in this work, spectral methods are used to characterize the sea surface temperature (SST) and turbulent heat flux (THF) variability and co-variability over scales between 50 and 10,000 km and 60 days to 80 years in the Pacific Ocean. The relative roles of the ocean and atmosphere are interpreted using a stochastic upper-ocean temperature evolution model forced by noise terms representing intrinsic variability in each medium, defined using climate model data to produce realistic rather than white spectral power density distributions. The analysis of all datasets shows that the atmosphere dominates the SST and THF variability over zonal wavelengths larger than ~2,000–2,500 km. In HR and OBS, ocean processes dominate the variability of both quantities at scales smaller than the atmospheric first internal Rossby radius of deformation (R 1 , ~600–2,000 km) due to a substantial ocean forcing coinciding with a weaker atmospheric modulation of THF (and consequently of SST) than at larger scales. The ocean forcing also induces oscillations in SST and THF with periods ranging from intraseasonal to multidecadal, reflecting a red spectrum response to ocean forcing similar to that driven by atmospheric forcing. Such features are virtually absent in LR due to a weaker ocean forcing relative to HR.

54 ENVIRONMENTAL SCIENCES↗

A New Method for High Resolution Surface Change Detection: Data Collection and Validation of Measurements from UAS at the Nevada National Security Site, Nevada, USA

The use of uncrewed aerial systems (UAS) increases the opportunities for detecting surface changes in remote areas and in challenging terrain. Detecting surface topographic changes offers an important constraint for understanding earthquake damage, groundwater depletion, effects of mining, and other events. For these purposes, changes on the order of 5–10 cm are readily detected, but sometimes it is necessary to detect smaller changes. An example is the surface changes that result from underground explosions, which can be as small as 3 cm. Previous studies that described change detection methodologies were generally not aimed at detecting sub-5-cm changes. Additionally, studies focused on high-fidelity accuracy were either computationally modeled or did not fully provide the necessary examples to highlight the usability of these workflows. Detecting changes at this threshold may be critical in certain applications, such as global security research and monitoring for high-consequence natural hazards, including landslides. Here we provide a detailed description of the methodology we used to detect 2–3 cm changes in an important applied research setting—surface changes related to underground explosions. This methodology improves the accuracy of change detection data collection and analysis through the optimization of pre-field planning, surveying, flight operations, and post-processing the collected data, all of which are critical to obtaining the highest output data resolution possible. We applied this methodology to a field study location, collecting 1.4 Tb of images over the course of 30 flights, and location data for 239 ground control points (GCPs). We independently verified changes with orthoimagery, and found that structure-from-motion, software-reported root mean square errors (RMSEs) for both control and check points underestimated the actual error. We found that 3 cm changes are detectable with this methodology, thereby improving our knowledge of a rock’s response to underground explosions.

47 OTHER INSTRUMENTATION↗

Multiple biomarkers highlight the importance of water column processes in treatment wetland organic matter cycling

A suite of biomarkers, including amino acids, pigments, and lignin phenols coupled with high resolution mass spectrometry were used to evaluate differences in the sources and fate of organic matter (OM) in Everglades treatment wetlands as a model for OM cycling in shallow water wetlands. Five components of the system (water column particulate organic matter, vertical traps, flocculent material, periphyton, and surface soil) were assessed for OM transformations down-profile (i.e. water column to soil) and between treatment cells dominated by emergent aquatic vegetation (EAV) and submerged aquatic vegetation (SAV), with comparisons to reference sites that resemble historic Everglades conditions. We found that OM cycling is fundamentally different between EAV and SAV wetlands, and that SAV wetlands have some shared characteristics with similar habitats in the Everglades. Other than locations densely populated by Typha spp., water column particulate organic C was derived from microbial/cryptomonad sources, rather than macroscopic sources (vascular plants and algal mats). Bacterial amino acid biomarkers were positively correlated with amino acid degradation indices and organic P (Po), respectively suggesting that microbial abundance is associated with "fresher" OM, and that further investigation into relationships between microbial biomass and Po is warranted. Overall, this multi-biomarker approach can evaluate the relative "freshness" of OM pools, identify sources of OM, and highlight the importance of water column processes in shallow water wetlands.

treatment wetlands, organic matter, Everglades, am↗