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At least 145 records · Page 8

Ecosystems and Networks Integrated with Genes and Molecular Assemblies (Final Scientific/Technical Report)

The ENIGMA science focus area (SFA) is a multi-disciplinary, multi-institutional research effort focused on addressing foundational knowledge gaps in environmental microbial communities by studying groundwater and sediment microbiomes in the shallow subsurface at the contaminated Oak Ridge Field Research Site (FRC). We seek to discover and characterize the reciprocal interactions between the microbial communities and the geochemical and geophysical parameters of the shallow subsurface within the contamination plume. The goal of the Fields lab is to help manage and conduct laboratory experiments informed by field observations using ecological and physiological approaches to study microbial populations in situ as well as ex situ (in the laboratory). In particular, we aim to study and characterize the impact of hydrological constraints on free-living and biofilm biomass and activity with increasing spatial and temporal resolution under static and flow conditions. We also aim to help characterize novel microbial groups that are present and active under relevant field conditions, including the development of molecular techniques for in situ detection as well as metabolic interactions that underlie pertinent physiology and ecology.

59 BASIC BIOLOGICAL SCIENCES↗

Assessment of Methods to Control Invasive Reed Canarygrass (Phalaris arundinacea) in Tidal Freshwater Wetlands

Controlling non-native invasive species is a significant challenge facing natural area managers in North America and around the world. Reed canarygrass (Phalaris arundinacea), is invasive in temperate freshwater wetlands throughout the United States and Canada. While methods for the prevention or elimination of reed canarygrass are generally well established, methods suitable for the unique conditions in tidal wetlands remain poorly understood. Namely, prolonged inundation of tidal wetlands for control purposes may only be accomplished with a concomitant loss of habitat connectivity and other functions. Restoration practitioners aiming to design self-sustaining wetlands in the lower Columbia River and estuary, on the northwestern Pacific Coast, have found that reed canarygrass is widespread and quick to establish throughout the 176-river-kilometer tidal freshwater floodplain. Here we report the results of a comprehensive effort to develop the knowledge base for control in tidal wetlands, through systematic review of the scientific literature, interviews with experienced practitioners, and field observations at nine Pacific Northwest sites. The review framework incorporated practical considerations and key environmental conditions: elevation related to hydrologic regime, salinity, shade, and nutrient availability. The results support implementation of multiple methods for a minimum of five years, on the largest possible area, ideally the watershed scale. Applicable methods include control in advance of restoration, topographic modification such as scrape-downs and mounds; establishing strong native competitors; and periodic, targeted control. Formal field experiments are needed to evaluate factors that influence control. Developing science-based, effective, practicable approaches to control reed canarygrass should improve restoration outcomes in natural areas.

intertidal, invasive, Phalaris arundinacea, reed c↗

Mitigating contamination in LSS surveys: a comparison of methods

ABSTRACT Future large-scale structure surveys will measure the locations and shapes of billions of galaxies. The precision of such catalogues will require meticulous treatment of systematic contamination of the observed fields. We compare several existing methods for removing such systematics from galaxy clustering measurements. We show how all the methods, including the popular pseudo-Cℓ Mode Projection and Template Subtraction methods, can be interpreted under a common regression framework and use this to suggest improved estimators. We show how methods designed to mitigate systematics in the power spectrum can be used to produce clean maps, which are necessary for cosmological analyses beyond the power spectrum, and we extend current methods to treat the next-order multiplicative contamination in observed maps and power spectra, which reduced power spectrum errors from $\Delta \chi ^2_{\rm C_\ell }\simeq 10$ to ≃ 1 in simulated analyses. Two new mitigation methods are proposed, which incorporate desirable features of current state-of-the-art methods while being simpler to implement. Investigating the performance of all the methods on a common set of simulated measurements from Year 5 of the Dark Energy Survey, we test their robustness to various analysis cases. Our proposed methods produce improved maps and power spectra when compared to current methods, while requiring almost no user tuning. We end with recommendations for systematics mitigation in future surveys, and note that the methods presented are generally applicable beyond the galaxy distribution to any field with spatial systematics.

79 ASTRONOMY AND ASTROPHYSICS↗

Mechanism of Microseismic Generation During Hydraulic Fracturing - With Evidence From HFTS 2 Observations

The objective of this study is to understand how microseismic events are generated during hydraulic fracturing, as well as the role of geomechanical conditions (i.e., stress and mechanical stratigraphy) in this process. In the industry, microseismic event clouds have been generally used as an “outer-boundary” of the “stimulated reservoir volume” (SRV). However, by comparing with other surveillance data (Low frequency Distributed Acoustic Sensing, or LF-DAS strain) in the Hydraulic Fracturing Test Site (HFTS) 2 experiment, we show that this assumption is fundamentally flawed. The HFTS 2 data has three unique observations that have not been commonly observed in other datasets: 1. Due to influence of offset pad depletion, microseismic data shows that hydraulic fractures from the child well can propagate over 3000 feet into the depleted low stress zone. 2. By comparing microseismic and horizontal fiber LF-DAS strain data, we observe that microseismic event cloud does not necessarily reflect the created hydraulic fracture volume. Particularly, the extent of microseismic event clouds near heel stages are much shorter than what is shown with LF-DAS strain data. 3. Microseismic event magnitudes are larger in the depleted regions. Through geomechanical analysis, we demonstrate that the “bedding-plane-slip” model is likely the mechanism for microseismic generation during hydraulic fracturing. Furthermore, this model successfully explains the above field observations from HFTS 2 experiment. We also provide a quantitative relationship connecting the microseismic event magnitude with fracture width increment and layer mechanical property contrast.

58 GEOSCIENCES↗

Interpretation of HFTS 2 Microseismic Data Using Bedding-Plane-Slip Mechanism

Summary The objective of this study is to understand how microseismic events are generated during hydraulic fracturing, as well as the role of geomechanical conditions (i.e., stress and mechanical stratigraphy) in this process. In the industry, microseismic event clouds have been generally used as an “outer boundary” of the “stimulated reservoir volume” (SRV). However, by comparing with other surveillance data (low-frequency distributed acoustic sensing, or LF-DAS, strain) in the Hydraulic Fracturing Test Site (HFTS) 2 experiment, we show that this assumption is fundamentally flawed. The HFTS 2 data have three unique observations that have not been commonly observed in other datasets: (1) Due to the influence of offset pad depletion, microseismic data show that hydraulic fractures from the child well can propagate over 3,000 ft into the depleted low-stress zone. (2) By comparing microseismic and horizontal fiber LF-DAS strain data, we observe that the microseismic event cloud does not necessarily reflect the created hydraulic fracture volume. Particularly, the extent of microseismic event clouds near heel stages is much shorter than what is shown with LF-DAS strain data. (3) Microseismic event magnitudes are larger in the depleted regions. Through geomechanical analysis, we demonstrate that the “bedding-plane-slip” model is likely the mechanism for microseismic generation during hydraulic fracturing. This model successfully explains the above field observations from the HFTS 2 experiment. We also provide a quantitative relationship connecting the microseismic event magnitude with fracture width increment and layer mechanical property contrast.

Engineering↗

Characterization of carbonaceous aerosols during TRACER-CAT

Absorbing aerosols (AA) have an important impact on the global radiation budget and cloud properties. The composition and properties of AA can vary substantially throughout the atmosphere, depending on the particle source and the influence of chemical aging. Uncertainties associated with the radiative effects of AA remain substantial. A key contributor to this uncertainty is understanding the extent to which coatings in general, and water uptake especially, alters absorption by AA particles and how this depends on particle composition. We deployed new and existing experimental tools during the Tracking Aerosol Convection Interactions Experiment (TRACER) campaign in Houston, TX as part of the Carbonaceous Aerosols Thrust (CAT) to provide detailed characterization of aerosol optical, chemical, and physical properties. Our TRACER-CAT measurements complemented and expanded on the planned TRACER instrumentation, allowing for more detailed characterization of aerosol properties of relevance to cloud development (a core focus of TRACER), such as the composition of particles that can act as cloud condensation nuclei, than would otherwise be available. Our measurements have allowed for assessment of the relationship(s) between AA optical properties (with a focus on absorption) and the chemical and physical characteristics (including the mixing state of black carbon (BC) containing particles). These field observations occurred in collaboration with Los Alamos National Laboratory in summer 2022 during the TRACER intensive operating period. The instrumentation we co-deployed provided for measurement of (i) multi-wavelength dry aerosol absorption, scattering, and extinction, (ii) the size-dependent composition and abundance of sub-micron aerosol, differentiating between those particles that do and do not contain BC, (iii) BC-specific concentrations and size distributions, (iv) particle size, and (v) the first field measurements at an ARM site of the influence of RH on multi-wavelength absorption by ambient AA. We have leveraged the natural variability of the atmosphere and of aerosol sources in the Houston region to (i) specifically disentangle contributions to light absorption from BC, absorbing organic carbon (brown carbon), and coatings on BC, (ii) characterize the mixing state of BC and assess the factors that give rise to compositional differences between BC-containing and BC-free aerosol, and (iii) establish how water uptake influences absorption and how any such effect depends on particle composition and BC mixing state. Overall, our study contributed to the mission of the Atmospheric System Research program in multiple ways. Through the deployment of complementary, advanced instrumentation for characterization of a wide range of aerosol properties our work helped to maximize the scientific impact of the TRACER campaign. Our work also allowed for development of new insights into the relationship(s) between aerosol composition, hygroscopicity, and the mixing state of BC with aerosol optical properties. Through this, our work has provided knowledge that can improve understanding and model representation of aerosol processes as they affect the Earth’s radiation budget.

54 ENVIRONMENTAL SCIENCES↗

SOSAT: Geohazard Risk Assessment in Carbon Sequestration Operations

Like all operations in which fluids are injected into the subsurface, geologic carbon storage (GCS) presents inherit risks that must be assessed and mitigated to successfully deploy such technology in the field. For example, alterations to pore pressure and the stress state due to fluid injection may trigger certain geohazards, such as potential fault activation and induced seismicity or unintentional hydraulic fracturing. Here we present capabilities for assessing these potential risks using the State of Stress Analysis Tool (SOSAT): a Python library and web-based application capable of probabilistically estimating the subsurface state of stress informed by various field observations. Using posterior distributions of principal stress components, SOSAT can assess the risk of fault activation within the injection formation for either a critically oriented fault or a fault with a user-prescribed orientation. Additionally, SOSAT can estimate the probability of unintentional hydraulic fracturing of the intact reservoir rock. Here, we demonstrate these SOSAT capabilities using a hypothetical GCS site. This type of risk assessment can assist with the effective deployment of GCS technology in the field by informing safe design and management practices.

Haagenson, Ryan J.↗

A reporting format for field measurements of soil respiration

Field observations of the soil-to-atmosphere CO2 flux–soil respiration, RS–are a prime example of ‘long tail’ data that historically have had neither centralized databases nor an agreed-upon reporting format. This has hindered scientific transparency, analytical reproducibility, and novel syntheses with respect to this globally-important component of the carbon cycle. Here we propose a new data and metadata reporting format for RS data, based on engagement with a wide range of researchers in the field as well as expert advisory panels. Our goal was a reporting format that would be relevant and useful for synthesis activities, and optimizing data discoverability and usability while not placing an undue burden on data contributors. We describe previous RS data collection efforts, lessons learned from related databases and data-oriented networks (e.g. FLUXNET) in earth and ecological sciences, and the process of community consultation. The proposed reporting format focuses on chamber-level data and metadata, specifying measurement conditions and, for a given measurement period defined by beginning and ending timestamps, a mean RS flux (or CO2 concentration) and associated ancillary measurements. Fundamentally, this format aims to enable findable, accessible, interoperable, and reusable data, while providing ‘future-proofing’ capabilities to support reanalyses using as yet unknown algorithms or approaches. Finally, this proposed RS reporting format is available online, and is intended to be a dynamic document, subject to further community feedback and/or change in the future.

Bond-Lamberty, Benjamin↗

Magnetotail Variability During Magnetospheric Substorms

Abstract In this work, we present a statistical study of substorms covering a five‐year period 2016–2020. Substorm phases were identified from time series of the SuperMAG AL (SML) index using a list of 5,077 previously identified substorm onsets, the SML peak value marking transition from expansion to recovery phase, and the recovery identified as return to activity less than −100 nT in the SML index. Magnetic field observations from THEMIS, RBSP, and MMS missions were used to study the magnetotail characteristics during the substorm evolution. A superposed epoch analysis indicates that the substorm onset occurs almost simultaneously with a few minutes of uncertainty throughout the magnetotail, ranging from geostationary orbit to 20 RE. The onset in the transition region precedes the ground onset by a few minutes. The peak SML time coincides with the peak of the outer transition region Δ B Z , which suggests that the field‐aligned currents driving the SML activity arise from the outer transition region. Analysis of 2D maps of the tail magnetic field shows that the magnetotail current changes are limited to the center of the tail within | Y | < 10 R E . The substorm recovery is fastest in the inner transition region and lasts longer when moving further out. We did not find major asymmetries in the substorm signatures associated with IMF B Y or B Z .

Kumar, S.↗

Correlating Surface Processing of Nb Superconducting RF Cavities with the Evolution of Surface Electronic States

Superconducting-radio frequency (RF) cavities provide an efficient way to accelerate particle beams with extremely high acceleration gradients while generating very small power dissipation. The few nanometers of the surface play a critical role in defining the RF performance of superconducting Nb based cavities. Over the past two decades, several pioneering surface treatment and processing methods have emerged, enabling remarkable improvements in superconducting cavity performance by simultaneously achieving high quality factors with increasing maximum acceleration gradients. These processing approaches include chemical polishing, distinct multi-step thermal treatments under ultra-high vacuum (UHV) conditions over low to high temperature regimes, as well as high-temperature treatments under controlled nitrogen atmospheres. Beyond their macroscopic impact on RF performance, these methods produce distinct surface oxide configurations characterized by different valence states, oxide thicknesses, chemical uniformity, and oxygen concentration profiles extending into the near-surface bulk of niobium. In this work, we are trying to understand how the surface-processing methods and the resulting oxide/oxygen profiles affect the electronic structure of surface and the mechanism of superconductivity. Using a combination of X-ray photoemission and X-ray absorption spectroscopies, we investigate how the valence-band structure and the electronic density of states (DoS) near the Fermi level evolve under different surface treatments. By employing tunable photon energies across multiple elemental absorption edges, we use resonant photoemission to disentangle and identify the elemental contributions to specific valence-band features. Our observations show that different surface-processing methods lead to distinct temperature evolutions of the DoS and valence-band states near the Fermi level. Our results suggest variations in different Nb-O orbital hybridizations in distinct processes and point towards the possibility of different underlying mechanisms of superconductivity governed by surface chemistry and oxide configuration. We also correlate these distinct superconducting mechanisms with RF cavity performance, specifically focusing on measured surface resistance, the nature of the Q-slope, and quench fields observed in superconducting RF measurements. These results will enable us to identify the potential limiting factors and relevant controllable parameters that can be further optimized to improve the performance of superconducting RF cavities.

Tripathi, Malvika [Fermilab] (ORCID:00000001989251↗

Bio-fuel effects and seasonal fuel property variations related to abnormal combustion occurrences observed in the field

Since 2015, the automotive industry has regularly observed sharp increases in customer complaints of poor driveability and increased warranty claims during the months of September and October. These persistent seasonal complaint increases have been tracked to occur from increased abnormal combustion events that coincide with the seasonal transition from summer to winter fuel volatility, beginning on September 15th annually. The Reid Vapor Pressure (RVP) of gasoline during this seasonal transition has been found to be the primary property attributed to this annual issue. It’s hypothesized that an increase in volatile butanes and pentanes from advanced petroleum recovery techniques and hydrofracking production has hastened the transition from summer to winter fuel volatility in the marketplace, rather than the gradual increase of the RVP over time as historically intended. At worst, mid-winter fuel, with an RVP ranging from 12 to 16 psi, depending on location in the U.S., enters the market while ambient temperatures can still be above average for the winter season. This combination of high volatility fuel with unseasonably warm weather will increase fuel system flash boiling, injector spray cavitation, and spray collapse inside the engine’s combustion chamber, ultimately linking fuel property variations to abnormal engine combustion processes. This CRADA program will investigate these known knowledge gaps by coupling with two national laboratories, Oak Ridge National Laboratory, and the National Renewable Energy Laboratory to employ both unique tools and expertise throughout the industry to provide the insight, knowledge, and data critical to understand the observed interactions. Overall findings of this work are that fuel wall retention increased SPI proportionally, and fuels with an increased distillation (i.e. energy fraction) above the wall temperature increased fuel retention. Likewise fuels with increased enthalpy of vaporization (HoV) increased fuel retention proportional to the temperature reduction from the HoV (~13K reduction in this work). Thus, fuel with increased HoV and increased fuel distillation above the linear temperature also exhibited increased SPI rates. Fuel with high RVP did exhibit increased fuel spray collapse form spray imaging measurements, but in SPI testing the high volatility of these fuels at the tested conditions did not necessarily increase SPI rates despite exhibiting increased spray collapse in injector imaging and increased spray-wall impingement measured in fired engine testing. It was also found that spray imaging showed collapse was possible at throttled conditions, but this was not relevant to high boost pressures relevant to SPI conditions, however, under transient load and or speed encountered in real-world operation fuel spray collapse could affect fuel retention and real-world SPI that were not probed in the automated high load test sequence of this work.

09 BIOMASS FUELS↗

Vegetation transect surveys from 2022 and 2023 within the Kougarok Fire Complex (KFC) on the Seward Peninsula in Alaska, USA

This dataset contains recorded vegetation classifications from 16 transects within the Kougarok Fire Complex (KFC) area in Alaska. Each transect is 50 meters long, and vertical vegetation profiles were sampled every 50cm, resulting in 101 points recorded for each transect. At each point, a vertical rod was inserted in the ground and any living plant or substrate touching the rod was recorded from top to bottom. For each plant, the plant functional type (PFT) and species name was identified and recorded. The file "flmd.xlsx" provides file level meta data for all other included files. The file (transect_metadata.csv) contains descriptive information about each of the 16 transects (field observation year and date; latitude and longitude GPS measurements of the 0, 25, and 50 meter points; and whether that area burned during the 1971, 1997, 2002, 2015, and/or 2019 fires). The files (PFT_names.csv and species_names.csv) map the short hand labels for the plant function type (PFT) and species used in the transect surveys to their full names. The remaining files are named for each transect, and contain the results of the vegetation survey for each transect. These files contain the plant functional type and the species identified at each point. Points along the transect with more than one species at that point are listed vertically from top to bottom in these 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↗

Building Intelligent Cyberinfrastructure to Learn Iteratively from both Observations and Models for Understanding Watershed Dynamics

Focal Area(s): Predictive modeling through the use of AI techniques and AI-derived model components; the use of AI and other tools to design a prediction system comprising of a hierarchy of models (e.g., AI-driven model/component/parameterization selection). Science Challenge: Watershed processes, such as the fate and transport of sediment, carbon and nutrients across landscapes and their fluxes to water bodies (e.g., streams, rivers and lakes), have important implications for global and regional carbon and nutrient dynamics, biogeochemical functioning of terrestrial ecosystems, and soil functions. The magnitude of lateral surface/subsurface transport and fluxes of sediment, carbon and nutrients are key factors controlling the vulnerability of watersheds to climate extremes such as droughts, wildfires, and floods. Recent field observations and other scientific evidence suggest that the magnitudes of lateral transport and fluxes of sediment, carbon and nutrients are governed primarily by the spatial and vertical heterogeneity of landscape and soil properties and by pedogenic processes. However, the current generation of land surface and watershed models do not mechanistically couple the terrestrial and hydrologic systems, nor do they represent sufficiently the spatial and vertical heterogeneity of land surface and subsurface properties. On the other hand, increasing complexity of coupled watershed and land surface models requires more data to parameterize, calibrate and validate. Remote sensing (RS) provides a means to acquire spatial data and characterize their heterogeneity at the watershed scale, overcoming a major limitation associated with conventional point measurements. To improve the representation of land-surface and surface/subsurface process coupling and sub-grid heterogeneity in watershed models, it is essential to build our predictive understanding by learning from both the multi-scale multi-process modeling and diverse multi-scale data while leveraging powerful artificial intelligence (AI) techniques.

54 ENVIRONMENTAL SCIENCES↗

Small field campaign: aerosol – ice formation closure pilot study. Final Report

Prediction of atmospheric ice formation from aerosol particles by heterogeneous nucleation represents one of the grand challenges in atmospheric science. Our insufficient predictive understanding of primary ice formation is the reason that climate models typically do not include heterogeneous ice nucleation with subsequent effects on climate uncertainty. Mixed-phase clouds, where supercooled water droplets and ice crystals coexist play globally an important role regulating climate. This is especially the case for the Arctic region that experiences the greatest warming due to climate change compared to other regions in the world. Immersion freezing initiated by ice-nucleating particles (INPs) in supercooled water droplets is recognized as the dominant primary ice formation pathway in mixed-phase cloud regimes. For this reason, it is crucial to evaluate our capability to predict immersion freezing for a given ambient aerosol population. The goal of this project is conducting a field-based pilot study at the U.S. DOE Atmospheric Radiation Measurement (ARM) user facility at Southern Great Plains (SGP) to evaluate our capability to predict the number concentration of aerosol particles that serve as INPs in the immersion freezing mode. Successful prediction of INP number concentrations is also termed “closure”. This field-observational approach represents a first-of-its kind attempt of an aerosol–ice formation closure study (AEROICESTUDY). Very few closure studies related to INPs have been conducted, and to our knowledge, none using robust size-resolved ambient aerosol composition measurements as a starting point. Achievement of aerosol–ice formation closure relies on our ability to characterize the ambient aerosol population with respect to particles size and composition and to determine INP number concentrations for specified freezing temperatures. This requires numerous online and offline instrumentation resulting in this pilot field campaign being a multi-institutional and community-collaborative effort. We chose the ARM SGP megasite for this first aerosol-ice formation closure pilot study due to its significant measurement capabilities available to obtain detailed physical characterization of the local aerosol population including size distribution, mass loading, and chemical composition of non-refractory aerosol particles. The overall objective of this project is to identify ice nucleation parameterizations that produce the most robust predictions of INP numbers and thus are best suited to be included in cloud and climate models. This objective includes the following goals for this field and laboratory-based project: i) What are the crucial aerosol physicochemical property measurements needed to accurately guide ice nucleation representations in models and long-term INP measurements? ii) What level of parameter details needs to be known to achieve aerosol–ice formation closure? iii) What are the leading causes for climate model bias in INP predictions? We found that the advances in our understanding of immersion freezing garnered over the last 20 years allowed us to yield partial and full closures of atmospheric immersion freezing from ambient aerosol particles. When the aerosol population is physicochemically complex and parameterizations for representative INP types are not yet available, we still struggle to accurately predict INP number concentrations. This project clearly demonstrates that with more laboratory and field measurements that are accompanied by particle composition analysis, the necessary datasets to achieve aerosol–ice formation closure for various locations will emerge, thus providing a robust foundation for guiding the representation of INPs in cloud and climate models.

54 ENVIRONMENTAL SCIENCES↗

Sensitivity of Optical Satellites to Estimate Windthrow Tree-Mortality in a Central Amazon Forest

Windthrow (i.e., trees broken and uprooted by wind) is a major natural disturbance in Amazon forests. Images from medium-resolution optical satellites combined with extensive field data have allowed researchers to assess patterns of windthrow tree-mortality and to monitor forest recovery over decades of succession in different regions. Although satellites with high spatial-resolution have become available in the last decade, they have not yet been employed for the quantification of windthrow tree-mortality. Here, we address how increasing the spatial resolution of satellites affects plot-to-landscape estimates of windthrow tree-mortality. We combined forest inventory data with Landsat 8 (30 m pixel), Sentinel 2 (10 m), and WorldView 2 (2 m) imagery over an old-growth forest in the Central Amazon that was disturbed by a single windthrow event in November 2015. Remote sensing estimates of windthrow tree-mortality were produced from Spectral Mixture Analysis and evaluated with forest inventory data (i.e., ground true) by using Generalized Linear Models. Field measured windthrow tree-mortality (3 transects and 30 subplots) crossing the entire disturbance gradient was 26.9 ± 11.1% (mean ± 95% CI). Although the three satellites produced reliable and statistically similar estimates (from 26.5% to 30.3%, p < 0.001), Landsat 8 had the most accurate results and efficiently captured field-observed variations in windthrow tree-mortality across the entire gradient of disturbance (Sentinel 2 and WorldView 2 produced the second and third best results, respectively). As expected, mean-associated uncertainties decreased systematically with increasing spatial resolution (i.e., from Landsat 8 to Sentinel 2 and WorldView 2). However, the overall quality of model fits showed the opposite pattern. We suggest that this reflects the influence of a relatively minor disturbance, such as defoliation and crown damage, and the fast growth of natural regeneration, which were not measured in the field nor can be captured by coarser resolution imagery. Our results validate the reliability of Landsat imagery for assessing plot-to-landscape patterns of windthrow tree-mortality in dense and heterogeneous tropical forests. Satellites with high spatial resolution can improve estimates of windthrow severity by allowing the quantification of crown damage and mortality of lower canopy and understory trees. However, this requires the validation of remote sensing metrics using field data at compatible scales.

54 ENVIRONMENTAL SCIENCES↗

Acoustic and electrical properties of Fe-Ti oxides with application to the deep lunar mantle

The overturn of titanium-rich mantle cumulates has been invoked to explain the structure and dynamics of the Moon. These dense cumulates are stable at the core-mantle boundary (CMB) and could explain field observations inferred from geophysical studies. Here, we report acoustic and electrical experiments on natural ilmenite-rutile aggregates up to 4.5 GPa and 1920 K. Seismic velocities show a weak pressure and temperature dependence, with Vs ~ 4.2 (+/-0.2) km/s and Vp ~8.0 (+/-0.2) km/s at the CMB conditions. Conductivity increases by a factor of 10 4 from 373 to 1920 K and is >10(3) S/m above 1573 K. Seismic and electrical models for the lunar mantle based on our results, considering mixtures of Fe-Ti oxides and olivine, indicate that field velocity and conductivity estimates are reproduced satisfactorily with 3-16 vol.% Fe-Ti oxides and 20 vol.% melt. Interactions between a Ti-rich, melt-bearing layer and the adjacent core likely affect the cooling and magnetic history of the Moon.

58 GEOSCIENCES↗

Tomographic galaxy clustering with the Subaru Hyper Suprime-Cam first year public data release

We analyze the clustering of galaxies in the first public data release of the HSC Subaru Strategic Program. Despite the relatively small footprints of the observed fields, the data are an excellent proxy for the deep photometric datasets that will be acquired by LSST, and are therefore an ideal test bed for the analysis methods being implemented by the LSST DESC. We select a magnitude limited sample with i<24.5 and analyze it in four redshift bins covering 0.15≲z≲1.5. We carry out a Fourier-space analysis of the two-point clustering of this sample, including all auto- and cross-correlations. We demonstrate the use of map-level deprojection methods to account for fluctuations in the galaxy number density caused by observational systematics. Through an HOD analysis, we place constraints on the characteristic halo masses of this sample, finding a good fit up to scales k max = 1Mpc –1 , including both auto- and cross-correlations. Our results show monotonically decreasing average halo masses, which can be interpreted in terms of the drop-out of red galaxies at high redshifts for a flux-limited sample. In terms of photometric redshift systematics, we show that additional care is needed in order to marginalize over uncertainties in the redshift distribution in galaxy clustering, and that these uncertainties can be constrained by including cross-correlations. We are able to make a ~3σ detection of lensing magnification in the HSC data. Our results are stable to variations in σ 8 and Ω c and we find constraints that agree well with measurements from Planck and low-redshift probes. Lastly, we use our pipeline to study the clustering of galaxies as a function of limiting flux, and provide a simple fitting function for the linear galaxy bias for magnitude limited samples as a function of limiting magnitude and redshift.

79 ASTRONOMY AND ASTROPHYSICS↗

Measurements and Prediction of Ash Deposition in a Cyclone-Fired Boiler Operating under Variable Load Conditions

Measurements of ash deposition rates were made between the secondary superheater and reheater sections of a 450 MW cyclone-fired lignite boiler as the operational load varied from 33 to 100%. Significant reductions in deposition rates with a decrease in operational load were observed. To uncover the causative mechanisms behind these observations, operational data from the power plant were used to carry out computational fluid dynamic (CFD) simulations of the boiler. After ascertaining that the gas temperatures and velocities at various sections within the boiler were being represented adequately, decoupled simulations of the ash deposition process on the deposit probe were carried out using a finely resolved boundary layer mesh. Fly ash particle size distribution (PSD) and its concentration for the decoupled calculations were determined from stand-alone cyclone barrel simulations. The ash partitioning (mass %) between the fly ash and slag was found to be ~50:50, which was in line with previous field observations, and it did not vary significantly across different cyclone loads. The predicted PSD of the deposit ash was concentrated in the size range 10–30 microns, which was in agreement with cross-sectional images of the deposit obtained from the measurements. At lower loads, sharp variations in the deposition rates were predicted in the gas temperature range 950–1150 K. The particle kinetic energy—particle viscosity-based capture methodology utilized in this study in conjunction with appropriate ash compositions, ash viscosity models and gas temperature estimates can help estimate slagging propensities at different loads reasonably well in these systems.

Krishnamoorthy, Gautham (ORCID:0000000255205092)↗