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At least 109 records · Page 6

Microstructural and Micro-Chemical Evolutions in the Irradiated UCO Fuel Kernels of AGR-1 and AGR-2 TRISO Fuel Particles

AGR-1 and AGR-2 TRISO fuel particles were fabricated with slightly different fuel kernel chemical compositions, modified fabrication processes, different fuel kernel diameters, and changed 235U enrichments. To correlate those differences with the fuel kernel responses to neutron irradiations in terms of irradiated fuel microstructure, fission products chemical and physical states, and fission gas bubble evolutions, extensive microstructural and analytical characterizations were conducted. The studies used a state of art transmission electron microscopy (TEM) equipped with Energy-dispersive X-ray spectroscopy (EDS) of four silicon solid-state detectors which have super sensitivity and fast speed. The TEM specimens were prepared from selected AGR-1 and AGR-2 irradiated fuel kernels exposed to safety testing after irradiation. The particles were chosen to represent a representative irradiation conditions with a fuel burnup within the range from 10.8 to 18.6% FIMA, and the time-average volume-average temperatures vary from 1070 to 1287°C. The 235U enrichment was 19.74 wt.% for the AGR1 fuel kernels and 14.03 wt.% for the AGR-2 fuel kernels. The TEM results show that there were significant microstructural reconstructions in the irradiated fuel kernels for both the AGR-1 and AGR-2 fuels. There are four major phases including fuel matrix of UO2 and UC, U2RuC2, and UMoC2 in the irradiated AGR2 fuel kernel. Zr and Nb form solid solution in the UC phase. UMoC2 phase often shows a detectable concentration of Tc. Pd was found to mainly locate in the buffer layer or to be associated with fission gas bubble within the UMoC2 phase. The EDS maps qualitatively show that the rare-earth fission products (Nb, et al.) preferentially reside in the UO2 phase. In contrast, in the irradiated AGR1 fuel kernel, no U2RuC2 or UMoC2 precipitates were positively identified. Instead, there is a high number of rod-shape precipitates enriched with Ru, Tc, Rh, and Pd observed in the fuel kernel center and edge zone. The difference of microstructural and micro-chemical evolutions in irradiated fuel kernels between the AGR-1 and AGR-2 TRISO fuel particle may result from a combined factor of irradiation temperature, fuel geometry and chemical composition. However, the irradiation temperature probably play a more deterministic role. Limited electron energy loss spectroscopy (EELS) characterizations on the AGR2 fuel kernel show that there is nearly no carbon in the UO2 phase while a small fraction of oxygen was detected in the UC/UMoC2 phase.

11 NUCLEAR FUEL CYCLE AND FUEL MATERIALS↗

Harnessing Biomineralization Potential of Metal-Sequestering Bacteria for Rare Earth Elements (REE) Material Synthesis

Extremophilic methylotrophs, such as Methylotuvimicrobium alcaliphilum 20ZR are known for their natural ability to carry out REE capture and uptake. It has been predicted that proteins associated with surface layers facilitate transport and homeostasis of essential metals. Indeed, electron microscopic analysis coupled with antibody staining revealed that cell envelop of metal-grown M. alcaliphilum 20ZR contains metal-binding proteins in the base of the cup-shaped structures of S-layers. While less explored, the proteins associated with S-layers are also predicted to contribute to scavenging of other minerals essential for core metabolism. Here, we employed bottom-up proteomic study to compare the protein content of S-layer fractions of M. alcaliphilum 20ZR cultures grown in the presence and absence trace metals to identify putative components REE-scavenging machinery.

36 MATERIALS SCIENCE↗

Shape-Controlled Synthesis of Copper Nanocrystals for Plasmonic, Biomedical, and Electrocatalytic Applications

As a metal that can occur in nature in the elemental form, copper (Cu) has been used by humans since ca. 8000 BC. With most properties matching those of Ag and Au, Cu has played a more significant role in commercial applications owing to its much higher (the 25th among all elements) abundance in Earth’s crust and thus more affordable price. In addition to its common use as a conductor of heat and electricity, it is a constituent of various metal alloys for hardware, coins, strain gauges, and thermocouples. Bulk Cu is also widely utilized as a building material. When downsized to the nanoscale, Cu and Cu-based structures have found widespread use in applications ranging from electronics to optoelectronics, plasmonics, catalysis, sensing, and biomedicine. Besides Ag and Au, for example, Cu is another metal known for its localized surface plasmon resonance (LSPR) in the visible and near-infrared regions when prepared as nanocrystals. As a potential replacement for indium–tin oxide (ITO) films, polymer coatings containing Cu nanowires are strong candidates for the fabrication of transparent and flexible electrodes key to touchscreen display and related applications. The commercial catalysts for water–gas shift and gas detoxification reactions are also based on Cu nanoparticles. Most recently, Cu nanocrystals have attracted considerable interest for their superior selectivity toward hydrocarbons and multicarbon species during the electrochemical reduction of CO 2 . The success of all these applications critically depends on our ability to control the shape and surface structure of the nanocrystals. Relative to Ag and Au, it is more challenging to generate Cu-based nanocrystals using colloidal methods due to its lower reduction potential and greater vulnerability to oxidation. Here, in this account, we discuss recent progress in the colloidal synthesis of Cu nanocrystals with controlled shapes for plasmonic, biomedical, and catalytic applications. With glucose serving as a reducing agent, Cu nanocrystals bearing a twinned or single-crystal structure can be synthesized using an aqueous system with the assistance of hexadecylamine (HDA). In this synthetic protocol, HDA not only passivates the surface to protect the nanocrystals from oxidation but also manipulates the reduction kinetics of Cu(II) precursor through coordination and an increase of solution pH. Typical products include nanocubes and penta-twinned nanowires whose surfaces are dominated by {100} facets. When seeds produced either in situ or ex situ are introduced, Cu-based nanocrystals featuring a singly twinned, core–shell, or Janus structure can be readily synthesized. Aside from segmented structures, Cu-based alloys with various noble metals can be synthesized through coreduction or a galvanic replacement reaction with preformed Cu nanocrystals. By controlling the size and/or shape of Cu nanocrystals, their LSPR peaks can be tuned into the near-infrared region, making them promising candidates for optical imaging contrast enhancement and photothermal treatment. The inclusion of the 64 Cu isotope makes them immediately useful in positron emission tomography and thus image-guided therapy. The surface structure, elemental distribution, and valence state of Cu-based nanocrystals can all be tailored to augment their electrocatalytic performance. It is hoped that this Account will inspire more studies into the development of rational methods capable of producing Cu-based nanocrystals with diverse and well-controlled shapes, internal structures, and compositions for a broader range of applications.

36 MATERIALS SCIENCE↗

Development of a high current density, high temperature superconducting cable for pulsed magnets

Abstract A low AC loss Rare Earth Barium Copper Oxide (REBCO) cable, based on the VIPER cable technology has been developed by Commonwealth Fusion Systems for use in high field, REBCO based tokamaks. The new cable is composed of partitioned and transposed copper ‘petals’ shaped to fit together in a circular pattern with each petal containing a REBCO tape stack and insulated from each other to reduce AC losses. A stainless steel jacket adds mechanical robustness—also serving as a vessel for solder impregnation—while a tube runs through the middle for cooling purposes. Additionally, fiber optic sensors are placed under the tape stacks for quench detection. To qualify this design, a series of experiments were conducted as part of the SPARC tokamak Central Solenoid Model Coil program—to retire the risks associated with full scale, fast ramping, high flux HTS Central Solenoid (CS) and Poloidal Field (PF) coils for tokamak fusion power plants and net energy demonstrators. These risk study and risk reduction experiments include (1) AC loss measurement and model validation in the range of ~5 T/s, (2) an IxB electromagnetic loading of over 850 kN/m at the cable level and up to 300 kN/m at the stack level, (3) a transverse compression resilience of over 350 MPa, (4) manufacturability at tokamak relevant speeds and scales, (5) cable to cable joint performance, (6) fiber optic based quench detection speed, accuracy, and feasibility, and (7) overall winding pack integration and magnet assembly. The result is a cable technology, now referred to as PIT VIPER, with AC losses that measure fifteen times lower (at ~5 T/s) than its predecessor technology; a 2% or lower degradation of critical current (Ic) at high IxB electromagnetic loads; no detectable Ic degradation up to 570 MPa of transverse compression on the cable unit cell; end to end magnet manufacturing, consistently producing Ic values within 7% of the model prediction; cable to cable joint resistances at 20 K on the order of ~15 nΩ; and fast, functional quench detection capabilities that do not involve voltage taps. This cable technology will be tested comprehensively in a Central Solenoid Model Coil to prove its readiness for compact, high field tokamak operation.

Sanabria, Charlie (ORCID:0000000150175309)↗

Rapid consolidation method for preparing bulk metastable iron-rich materials

Interstitially modified compounds of rare earth element-containing, iron-rich compounds may be synthesized with a ThMn 12 tetragonal crystal structure such that the compounds have useful permanent magnet properties. It is difficult to consolidate particles of the compounds into a bulk shape without altering the composition and magnetic properties of the metastable material. A combination of thermal analysis and crystal structure analysis of each compound may be used to establish heating and consolidation parameters for sintering of the particles into useful magnet shapes.

Zhou, Chen↗

Development of inter-grid-cell lateral unsaturated and saturated flow model in the E3SM Land Model (v2.0)

Abstract. The lateral transport of water in the subsurface is important in modulating terrestrial water energy distribution. Although a few land surface models have recently included lateral saturated flow within and across grid cells, it is not a default configuration in the Climate Model Intercomparison Project version 6 experiments. In this work, we developed the lateral subsurface flow model within both unsaturated and saturated zones in the Energy Exascale Earth System Model (E3SM) Land Model version 2 (ELMv2.0). The new model, called ELMlat, was benchmarked against PFLOTRAN, a 3D subsurface flow and transport model, for three idealized hillslopes that included a convergent hillslope, divergent hillslope, and tilted V-shaped hillslope with variably saturated initial conditions. ELMlat showed comparable performance against PFLOTRAN in terms of capturing the dynamics of soil moisture and groundwater table for the three benchmark hillslope problems. Specifically, the mean absolute errors (MAEs) of the soil moisture in the top 10 layers between ELMlat and PFLOTRAN were within 1 %±3 %, and the MAEs of water table depth were within ±0.2 m. Next, ELMlat was applied to the Little Washita experimental watershed to assess its prediction of groundwater table, soil moisture, and soil temperature. The spatial pattern of simulated groundwater table depth agreed well with the global groundwater table benchmark dataset generated from a global model calibrated with long-term observations. The effects of lateral groundwater flow on the energy flux partitioning were more prominent in lowland areas with shallower groundwater tables, where the difference in simulated annual surface soil temperature could reach 0.3–0.4 ∘C between ELMv2.0 and ELMlat. Incorporating lateral subsurface flow in ELM improves the representation of the subsurface hydrology, which will provide a good basis for future large-scale applications.

58 GEOSCIENCES↗

River sinuosity describes a continuum between randomness and ordered growth

River channels are among the most common landscape features on Earth. An essential characteristic of channels is sinuosity: their tendency to take a circuitous path, which is quantified as along-stream length divided by straight-line length. River sinuosity is interpreted as a characteristic that either forms randomly at channel inception or develops over time as meander bends migrate. Studies tend to assume the latter and thus have used river sinuosity as a proxy for both modern and ancient environmental factors including climate, tectonics, vegetation, and geologic structure. But no quantitative criterion for planform expression has distinguished between random, initial sinuosity and that developed by ordered growth through channel migration. This ambiguity calls into question the utility of river sinuosity for understanding Earth’s history. We propose a quantitative framework to reconcile these competing explanations for river sinuosity. Using a coupled analysis of modeled and natural channels, we show that while a majority of observed sinuosity is consistent with randomness and limited channel migration, rivers with sinuosity ≥1.5 likely formed their geometry through sustained, ordered growth due to channel migration. This criterion frames a null hypothesis for river sinuosity that can be applied to evaluate the significance of environmental interpretations in landscapes shaped by rivers. The quantitative link between sinuosity and channel migration further informs strategies for preservation and restoration of riparian habitat and guides predictions of fluvial deposits in the rock record and in remotely sensed environments from the seafloor to planetary surfaces.

58 GEOSCIENCES↗

Effects of interlayer spacing and applied pressure on the lanthanide transport in MoS 2 -based two-dimensional channels

Rare-earth elements (REEs) are critical to modern industry but difficult to separate due to their subtle and monotonic changes in physicochemical properties. MoS 2 -based two-dimensional (2D) materials offer novel opportunities for enhancing REE separation, exhibiting a distinct volcano-shaped transport performance distribution that peaks at Sm 3+ . However, the specific contributions of thermodynamic and kinetic factors to ion transport within 2D confinement remain unclear. In this study, we conducted a series of non-equilibrium all-atom molecular dynamics (MD) simulations to explore the effects of interlayer spacing and external pressure on the transport of lanthanide ions in Å-scale acetate functionalized 2D MoS 2 (MoS 2 -COOH) channels. We examined ion entry and permeation rates, water flux, dehydration, and binding modes. The simulation results reveal that the transport trends of lanthanide ions are jointly driven by the dehydration degree and the relative-binding strengths of ions to water and to the acetate within the 2D channels. Notably, the dehydration pattern of lanthanide ions during permeation is closely linked to kinetic factors. Overall, this study provides a detailed atomistic understanding of the mechanisms underlying lanthanide ion transport under confinement. These findings point to the significant potential for tuning confinement and chemical functionalization within Å-scale channels for more efficient REE separation.

2D channels↗

Orthorhombic distortion drives orbital ordering in the antiferromagnetic 3$d$ 1 Mott insulator PrTiO 3

The orbital, which represents the shape of the electron cloud, very often strongly influences the manifestation of various exotic phenomena, e.g., magnetism, metal-insulator transition, colossal magnetoresistance, unconventional superconductivity, etc. in solid-state systems. The observation of the antiferromagnetism in $RE$TiO 3 ($RE$ = rare-earth) series has been puzzling since the celebrated Kugel-Khomskii model of spin-orbital superexchange predicts ferromagnetism in an orbitally degenerate $d$ 1 system. Further, the existence of the orbitally ordered vs. orbital liquid phase in both antiferromagnetic and paramagnetic phase have been unsettled issues thus far. To address these longstanding questions, we investigate single crystalline film of PrTiO 3 . Our synchrotron x-ray diffraction measurements confirm the retention of bulklike orthorhombic ($D_{2h}$) symmetry in the thin film geometry. We observe similar x-ray linear dichroism signal in both paramagnetic and antiferromagnetic phase, which can be accounted by ferro-orbital ordering (FOO). While the presence of $D_{2h}$ crystal field does not guarantee lifting of orbital degeneracy always, we find it to be strong enough in these rare-earth titanates, leading to the FOO state. Thus, our work demonstrates the orthorhombic distortion is the driving force for the orbital ordering of antiferromagnetic $RE$TiO 3 .

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

The Gaia–Kepler Stellar Properties Catalog. II. Planet Radius Demographics as a Function of Stellar Mass and Age

Studies of exoplanet demographics require large samples and precise constraints on exoplanet host stars. Using the homogeneous Kepler stellar properties derived using the Gaia Data Release 2 by Berger et al., we recompute Kepler planet radii and incident fluxes and investigate their distributions with stellar mass and age. We measure the stellar mass dependence of the planet radius valley to be dlogR{sub p}/dlogM{sub ⋆} = 0.26{sub −0.16}{sup +0.21}, consistent with the slope predicted by a planet mass dependence on stellar mass (0.24–0.35) and core-powered mass loss (0.33). We also find the first evidence of a stellar age dependence of the planet populations straddling the radius valley. Specifically, we determine that the fraction of super-Earths (1–1.8 R{sub ⊕}) to sub-Neptunes (1.8–3.5 R{sub ⊕}) increases from 0.61 ± 0.09 at young ages (<1 Gyr) to 1.00 ± 0.10 at old ages (>1 Gyr), consistent with the prediction by core-powered mass loss that the mechanism shaping the radius valley operates over Gyr timescales. Additionally, we find a tentative decrease in the radii of relatively cool (F {sub p} < 150 F{sub ⊕}) sub-Neptunes over Gyr timescales, which suggests that these planets may possess H/He envelopes instead of higher mean molecular weight atmospheres. We confirm the existence of planets within the hot sub-Neptunian “desert” (2.2 R {sub ⊕} < R {sub p} < 3.8 R{sub ⊕}, F {sub p} > 650 F{sub ⊕}) and show that these planets are preferentially orbiting more evolved stars compared to other planets at similar incident fluxes. In addition, we identify candidates for cool (F {sub p} < 20 F{sub ⊕}) inflated Jupiters, present a revised list of habitable zone candidates, and find that the ages of single and multiple transiting planet systems are statistically indistinguishable.

79 ASTRONOMY AND ASTROPHYSICS↗

Terrestrial photosynthesis inferred from plant carbonyl sulfide uptake

Terrestrial photosynthesis, or gross primary production (GPP), is the largest carbon flux in the biosphere, but its global magnitude and spatiotemporal dynamics remain uncertain. The global annual mean GPP is historically thought to be around 120 PgC yr −1 , which is about 30–50 PgC yr −1 lower than GPP inferred from the oxygen-18 ( 18 O) isotope and soil respiration. This disparity is a source of uncertainty in predicting climate–carbon cycle feedbacks. Here, in this study, we infer GPP from carbonyl sulfide, an innovative tracer for CO 2 diffusion from ambient air to leaf chloroplasts through stomata and mesophyll layers. We demonstrate that explicitly representing mesophyll diffusion is important for accurately quantifying the spatiotemporal dynamics of carbonyl sulfide uptake by plants. From the estimate of carbonyl sulfide uptake by plants, we infer a global contemporary GPP of 157 (±8.5) PgC yr −1 , which is consistent with estimates from 18 O (150–175 PgC yr −1 ) and soil respiration ($149^{+29}_{-23}$) PgC yr −1 ), but with an improved confidence level. Our global GPP is higher than satellite optical observation-driven estimates (120–140 PgC yr –1 ) that are used for Earth system model benchmarking. This difference predominantly occurs in the pan-tropical rainforests and is corroborated by ground measurements, suggesting a more productive tropics than satellite-based GPP products indicated. As GPP is a primary determinant of terrestrial carbon sinks and may shape climate trajectories, our findings lay a physiological foundation on which the understanding and prediction of carbon–climate feedbacks can be advanced.

Lai, Jiameng↗

Factors controlling marine aerosol size distributions and their climate effects over the northwest Atlantic Ocean region

Abstract. Aerosols over Earth's remote and spatially extensive ocean surfaces have important influences on planetary climate. However, these aerosols and their effects remain poorly understood, in part due to the remoteness and limited observations over these regions. In this study, we seek to understand factors that shape marine aerosol size distributions and composition in the northwest Atlantic Ocean region. We use the GEOS-Chem model with the TwO-Moment Aerosol Sectional (TOMAS) microphysics algorithm model to interpret measurements collected from ship and aircraft during the four seasonal campaigns of the North Atlantic Aerosols and Marine Ecosystems Study (NAAMES) conducted between 2015 and 2018. Observations from the NAAMES campaigns show enhancements in the campaign-median number of aerosols with diameters larger than 3 nm in the lower troposphere (below 6 km), most pronounced during the phytoplankton bloom maxima (May/June) below 2 km in the free troposphere. Our simulations, combined with NAAMES ship and aircraft measurements, suggest several key factors that contribute to aerosol number and size in the northwest Atlantic lower troposphere, with significant regional-mean (40–60∘ N and 20–50∘ W) cloud-albedo aerosol indirect effect (AIE) and direct radiative effect (DRE) processes during the phytoplankton bloom. These key factors and their associated simulated radiative effects in the region include the following: (1) particle formation near and above the marine boundary layer (MBL) top (AIE: −3.37 W m−2, DRE: −0.62 W m−2); (2) particle growth due to marine secondary organic aerosol (MSOA) as the nascent particles subside into the MBL, enabling them to become cloud-condensation-nuclei-sized particles (AIE: −2.27 W m−2, DRE: −0.10 W m−2); (3) particle formation and growth due to the products of dimethyl sulfide, above and within the MBL (−1.29 W m−2, DRE: −0.06 W m−2); (4) ship emissions (AIE: −0.62 W m−2, DRE: −0.05 W m−2); and (5) primary sea spray emissions (AIE: +0.04 W m−2, DRE: −0.79 W m−2). Our results suggest that a synergy of particle formation in the lower troposphere (particularly near and above the MBL top) and growth by MSOA contributes strongly to cloud-condensation-nuclei-sized particles with significant regional radiative effects in the northwest Atlantic. To gain confidence in radiative effect magnitudes, future work is needed to understand (1) the sources and temperature dependence of condensable marine vapors forming MSOA, (2) primary sea spray emissions, and (3) the species that can form new particles in the lower troposphere and grow these particles as they descend into the marine boundary layer.

54 ENVIRONMENTAL SCIENCES↗

Storylines for the 1997 New Year’s Flood: The role of watershed antecedent conditions and future warming in shaping discharge in the Truckee River watershed

The 1997 New Year’s flood was among the most devastating floods in the Truckee River watershed located in western Nevada. This event resulted from complex interactions of flood drivers, such as extreme precipitation, wet antecedent watershed conditions, warm temperatures and rapid snowmelt. We leveraged simulated forcings from the regionally refined mesh capabilities of the Energy Exascale Earth System Model (RRM-E3SM) and a process-based hydrological model to recreate the 1997 New Year’s flood for the Truckee River watershed across four climate warming levels ranging from the current temperatures to + 4° C. For each scenario, we conducted ensemble simulations with the same forcing but with 100 different seasonal watershed antecedent conditions, which were randomly sampled from long-term hydrological simulations. The results show that the 1997 New Year’s flood can be reproduced or exceeded consistently only when the antecedent watershed conditions are wet, specifically when streamflows are above the 75th percentile of the climatological value. There is negligible change in ensemble mean peakflows for Truckee River near Reno; however, there are increases of 18% and 14% under the warming levels of + 3° C and + 4° C, respectively. The increases in peakflows under future climate warming are attributed to wetter antecedent watershed conditions and enhanced snowmelt. Furthermore, the largest increases in peakflows occur at small, high-elevation headwater basins along the Sierra Nevada crest. This study highlights that changes in extreme flood events will result from the complex interplay of multiple flood drivers. It also demonstrates the potential of storyline approaches to analyze future realizations of these extreme events under different climate scenarios.

Climate change impact study↗

Observations and Machine-Learned Models of Near-Surface Permafrost along the Koyukuk River, Alaska, USA

This dataset contains GeoTIFs (raster) and GeoPackages (vector) that map observations of near-surface permafrost and not-permafrost from a field campaign conducted near the village of Huslia, AK along the Koyukuk River and its floodplain in July 2018. These data were collected as part of a campaign to understand if and how permafrost impacts riverbank erosion. This problem cannot be assessed without knowing where permafrost exists. Permafrost was observed via frost probing (to a maximum depth of one meter), coring (to a maximum depth of two meters) and bank/bar excavations. An additional boat survey was performed wherein expert (Joel Rowland) judgment assessed the presence or absence of distinctive permafrost features (e.g., overhanging tundra mats, thermoerosional niching, ice wedges, active drainage of ice melt from soils). This dataset also contains the input features and results of two machine learning models (random forest and convolutional neural network) that extrapolate the observations to the full floodplain that may be useful for building, testing, or validating other machine-learned permafrost models. Permafrost data are provided as georasters of the same shape and geovectors (polylines/polygons) and are all projected into EPSG:32605. All data can be visualized with a GIS (QGIS, ArcGIS, etc.).

54 ENVIRONMENTAL SCIENCES↗

Inferring plant–plant interactions using remote sensing

Rapid technological advancements and increasing data availability have improved the capacity to monitor and evaluate Earth's ecology via remote sensing. However, remote sensing is notoriously ‘blind’ to fine-scale ecological processes such as interactions among plants, which encompass a central topic in ecology. Here, we discuss how remote sensing technologies can help infer plant–plant interactions and their roles in shaping plant-based systems at individual, community and landscape levels. At each of these levels, we outline the key attributes of ecosystems that emerge as a product of plant–plant interactions and could possibly be detected by remote sensing data. We review the theoretical bases, approaches and prospects of how inference of plant–plant interactions can be assessed remotely. At the individual level, we illustrate how close-range remote sensing tools can help to infer plant–plant interactions, especially in experimental settings. At the community level, we use forests to illustrate how remotely sensed community structure can be used to infer dominant interactions as a fundamental force in shaping plant communities. At the landscape level, we highlight how remotely sensed attributes of vegetation states and spatial vegetation patterns can be used to assess the role of local plant–plant interactions in shaping landscape ecological systems. Synthesis . Remote sensing extends the domain of plant ecology to broader and finer spatial scales, assisting to scale ecological patterns and search for generic rules. Robust remote sensing approaches are likely to extend our understanding of how plant–plant interactions shape ecological processes across scales—from individuals to landscapes. Combining these approaches with theories, models, experiments, data-driven approaches and data analysis algorithms will firmly embed remote sensing techniques into ecological context and open new pathways to better understand biotic interactions.

59 BASIC BIOLOGICAL SCIENCES↗

Influence of open ocean biogeochemistry on aerosol and clouds: Recent findings and perspectives

Aerosols and clouds are key components of the marine atmosphere, impacting the Earth’s radiative budget with a net cooling effect over the industrial era that counterbalances greenhouse gas warming, yet with an uncertain amplitude. Here we report recent advances in our understanding of how open ocean aerosol sources are modulated by ocean biogeochemistry and how they, in turn, shape cloud coverage and properties. We organize these findings in successive steps from ocean biogeochemical processes to particle formation by nucleation and sea spray emissions, further particle growth by condensation of gases, the potential to act as cloud condensation nuclei or ice nucleating particles, and finally, their effects on cloud formation, optical properties, and life cycle. We discuss how these processes may be impacted in a warming climate and the potential for ocean biogeochemistry—climate feedbacks through aerosols and clouds.

54 ENVIRONMENTAL SCIENCES↗

The influence of physical and algorithmic factors on simulated far-field waveforms and source–time functions of underground explosions using unsupervised machine learning

SUMMARY Characterizing explosion sources and differentiating between earthquake and underground explosions using distributed seismic networks becomes non-trivial when explosions are detonated in cavities or heterogeneous ground material. Moreover, there is little understanding of how changes in subsurface physical properties affect the far-field waveforms we record and use to infer information about the source. Simulations of underground explosions and the resultant ground motions can be a powerful tool to systematically explore how different subsurface properties affect far-field waveform features, but there are added variables that arise from how we choose to model the explosions that can confound interpretation. To assess how both subsurface properties and algorithmic choices affect the seismic wavefield and the estimated source functions, we ran a series of 2-D axisymmetric non-linear numerical explosion experiments and wave propagation simulations that explore a wide array of parameters. We then inverted the synthetic far-field waveform data using a linear inversion scheme to estimate source–time functions (STFs) for each simulation case. We applied principal component analysis (PCA), an unsupervised machine learning method, to both the far-field waveforms and STFs to identify the most important factors that control variance in the waveform data and differences between cases. For the far-field waveforms, the largest variance occurs in the shallower radial receiver channels in the 0–50 Hz frequency band. For the STFs, both peak amplitude and rise times across different frequencies contribute to the variance. We find that the ground equation of state (i.e. lithology and rheology) and the explosion emplacement conditions (i.e. tamped versus cavity) have the greatest effect on the variance of the far-field waveforms and STFs, with the ground yield strength and fracture pressure being secondary factors. Differences in the PCA results between the far-field waveforms and STFs could possibly be due to near-field non-linearities of the source that are not accounted for in the estimation of STFs and could be associated with yield strength, fracture pressure, cavity radius and cavity shape parameters. Other algorithmic parameters are found to be less important and cause less variance in both the far-field waveforms and STFs, meaning algorithmic choices in how we model explosions are less important, which is encouraging for the further use of explosion simulations to study how physical Earth properties affect seismic waveform features and estimated STFs.

58 GEOSCIENCES↗

Establishing robust correction schemes for improved and reliable ARM-AOS aerosol optical data products

Aerosol light absorption and scattering of solar radiation play an important role in the earth’s atmosphere in terms of direct and semi-direct radiative forcing. Optical parameters of importance to the US Department of Energy (DOE) climate models include absorption and scattering coefficients, single scattering albedo (SSA), absorption Angstrom exponents (AAE), and the asymmetry parameter (g). These parameters depend on aerosol size, shape and composition (refractive index), and are spectrally sensitive in the shortwave region. Additionally, these parameters have a complex dependency on the emission source, especially for carbonaceous aerosols. The DOE Atmospheric Radiation Measurement (ARM) user facility has deployed aerosol observing systems (AOS) containing several filter-based instruments to measure and constrain aerosol optical properties and related parameters at multiple sites worldwide. For measurement of aerosol light absorption, the AOS includes filter-based instruments (particle soot absorption photometer and tricolor absorption photometer) that infer particle-phase aerosol absorption coefficients at nominal red, green, and blue wavelength bands from the attenuation (ATN) of light passing through a particulate filter on which aerosols are deposited. Measurement of aerosol scattering is done in situ using nephelometers. By combining inferred absorption coefficients from filter-based ATN measurements and in situ scattering coefficients, value-added products (VAPs) such as SSA, AAE, and g are derived.

54 ENVIRONMENTAL SCIENCES↗