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At least 451 records · Page 25

Soil microbial legacies differ following drying-rewetting and freezing-thawing cycles

Climate change alters frequencies and intensities of soil drying-rewetting and freezing-thawing cycles. These fluctuations affect soil water availability, a crucial driver of soil microbial activity. While these fluctuations are leaving imprints on soil microbiome structures, the question remains if the legacy of one type of weather fluctuation (e.g., drying-rewetting) affects the community response to the other (e.g., freezing-thawing). As both phenomenons give similar water availability fluctuations, we hypothesized that freezing-thawing and drying-rewetting cycles have similar effects on the soil microbiome. We tested this hypothesis by establishing targeted microcosm experiments. We created a legacy by exposing soil samples to a freezing-thawing or drying-rewetting cycle (phase 1), followed by an additional drying-rewetting or freezing-thawing cycle (phase 2). We measured soil respiration and analyzed soil microbiome structures. Across experiments, larger CO 2 pulses and changes in microbiome structures were observed after rewetting than thawing. Drying-rewetting legacy affected the microbiome and CO 2 emissions upon the following freezing-thawing cycle. Conversely, freezing-thawing legacy did not affect the microbial response to the drying-rewetting cycle. Our results suggest that drying-rewetting cycles have stronger effects on soil microbial communities and CO 2 production than freezing-thawing cycles and that this pattern is mediated by sustained changes in soil microbiome structures.

59 BASIC BIOLOGICAL SCIENCES↗

Importance of Site Diversity and Connectivity in Electrochemical CO Reduction on Cu

Electrochemical CO 2 reduction on Cu is a promising approach to produce value-added chemicals using renewable feedstocks, yet various Cu preparations have led to differences in activity and selectivity toward single and multicarbon products. Here, we find, surprisingly, that the effective catalytic activity toward ethylene improves when there is a larger fraction of less active sites acting as reservoirs of *CO on the surface of Cu nanoparticle electrocatalysts. In an adaptation of chemical transient kinetics to electrocatalysis, we measure the dynamic response of a gas diffusion electrode (GDE) cell when the feed gas is abruptly switched between Ar (inert) and CO. When switching from Ar to CO, CO reduction (COR) begins promptly, but when switching from CO to Ar, COR can be maintained for several seconds (delay time) despite the absence of the CO reactant in the gas phase. A three-site microkinetic model captures the observed dynamic behavior and shows that Cu catalysts exhibiting delay times have a less active *CO reservoir that exhibits fast diffusion to active sites. The observed delay times and the estimated *CO reservoir sizes are affected by catalyst preparation, applied potential, and microenvironment (electrolyte cation identity, electrolyte pH, and CO partial pressure). Notably, we estimate that the *CO reservoir surface coverage can be as high as 88 ± 7% on oxide-derived Cu (OD-Cu) at high overpotentials (–1.52 V vs SHE) and this increases in reservoir coverage coincide with increased turnover frequencies to ethylene. We also estimate that *CO can travel substantial distances (up to 10s of nm) prior to desorption or reaction. It appears that active C–C coupling sites by themselves do not control selectivity to C 2+ products in electrochemical COR; the supply of CO to those sites is also a crucial factor. More generally, the overall activity of Cu electrocatalysts cannot be approximated from linear combinations of individual site activities. Future designs must consider the diversity of the catalyst network and account for intersite transportation pathways.

30 DIRECT ENERGY CONVERSION↗

Effects of CELF Pretreatment Severity on Lignin Structure and the Lignin-Based Polyurethane Properties

Conversion of technical lignin into performance biopolymers such as polyurethane offers environmental and economic advantages when combined with production of biofuels from biomass sugars, presenting significant interest toward studying the role of pretreatment on lignin structure and functionality. Co-solvent enhanced lignocellulosic fractionation (CELF) pretreatment, employing acidic aqueous tetrahydrofuran (THF) mixtures, was developed to effectively break down the lignin-carbohydrate matrix and promote extraction of lignin from lignocellulosic biomass with desirable purity and yield. In this study, we report the effects of CELF pretreatment reaction severity on the molecular structure of CELF-extracted lignin and its impact toward the mechanical properties of the resulting lignin-based polyurethanes. Reaction temperature was found to play the most significant role, compared to reaction time and acidity, in manipulating structural features such as molecular weight, functionality and intra-polymer structure. At the severe reaction conditions at 180°C, the order of reactivity for primary lignin interlinkages characterized by semiquantitative HSQC NMR analysis were found to be β-ether > phenylcoumaran (β−5′) > resinol (β−β′) facilitating a high degree of depolymerization and yielding a high frequency of free phenolics and reduced aliphatic hydroxyl groups. All side-chain interlinkages were depleted converting guaiacyl subunits into condensed forms, while still retaining uncondensed syringyl subunits. Under the mild 150°C temperature reaction, CELF lignin had higher molecular weight and retained more β-ether interlinkages. The results from CELF lignin-based polyurethane synthesis indicated that the tensile properties depended on the miscibility of CELF lignin with other components and low molecular weight cuts improved the dispersion of lignin in the polyurethane network. Pre-mixing of CELF with poly(ethylene glycol) (PEG) reduced the brittleness and improved the ductility of the CELF lignin-PEG polyurethanes.

59 BASIC BIOLOGICAL SCIENCES↗

Kinetic Modeling Analysis of Ar Addition to Atmospheric Pressure N 2 –H 2 Plasma for Plasma-Assisted Catalytic Synthesis of NH 3

Zero-dimensional kinetic modeling of atmospheric pressure Ar–N 2 –H 2 nonthermal plasma was carried out to gain mechanistic insights into plasma-assisted catalytic synthesis of ammonia. Ar dilution is a common technique for tailoring plasma discharge properties and has been shown to enhance NH 3 formation when added to N 2 –H 2 plasma. The kinetic model was developed for a coaxial dielectric barrier discharge quartz wool-packed bed reactor operating at near room temperature using a kHz-frequency plasma source. With 30% Ar mixed in a 1:1 N 2 –H 2 plasma at 760 Torr, we find that NH 3 production is dominated by Eley–Rideal (E-R) surface reactions, which heavily involve surface NH x species derived from N and H radicals in the gas phase, while the influence of excited N 2 molecules is negligible. This is contrary to the commonly proposed mechanism that excited N 2 molecules created by Penning excitation of N 2 by Ar(4s) and Ar(4p) play a significant role in assisting NH 3 formation. Our model shows that the enhanced NH 3 formation upon Ar dilution is unlikely due to the interactions between Ar and H species, as excited Ar atoms have a weak effect on H radical formation through H 2 dissociation compared to electrons. We find that excited Ar atoms contribute to 28% of the N radical production in the gas phase via N 2 dissociation, while the rest are dominated by electron-impact dissociation. Furthermore, Ar species play a negligible role in the product NH 3 dissociation. N 2 conversion sensitivity analyses were carried out for electron number density (ne) and reduced electric field (E/N), and contributions from Ar to gas-phase N radical production were quantified. Finally, the model can provide guidance on potential reasons for observing enhanced NH 3 formation upon Ar dilution in N 2 –H 2 plasma beyond changes in the discharge characteristics.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Adaptive harnessing damping in hydrokinetic energy conversion by two rough tandem-cylinders using flow-induced vibrations

Alternating lift technology (ALT) harnesses hydrokinetic energy from currents and tides and is different from conventional steady lift technologies (turbines). ALT is still under development with an important research issue being the mitigation of wake effect on downstream cylinders in Flow Induced Oscillations (FIO) of multi-cylinder Current Energy Converters (CEC). Rather than adjust the configuration/parameters of the converter, a more direct and effective way is to actively adjust the harnessed power. In this paper, a hydrokinetic energy converter using FIO of two cylinders in tandem in one-degree-of-freedom oscillators, with nonlinear adaptive damping and linear spring stiffness, is tested experimentally. FIO include Vortex Induced Vibrations (VIV), galloping, and their coexistence. Introducing adaptive damping into the tandem cylinders overcomes the shielding effect, which previous research on two tandem cylinders has shown to reduce power output by the downstream cylinder. Shielding along with fixed damping result either in ceasing motion due to excessive damping, or in low harnessed energy due to insufficient damping. In this experimental study, damping-to-velocity rate, linear spring-stiffness, cylinder spacing, and flow-velocity are the parameters with Reynolds number 30,000 ≤ Re ≤ 120,000. Comparison to linear-oscillators in FIO shows that this nonlinear converter, with velocity-proportional damping coefficient, is more effective over the entire FIO range but especially in galloping, where both flow and cylinder speeds are higher. Experimental results for energy harvesting, efficiency and instantaneous energy of the converter are presented and discussed supported by amplitude and frequency response data. Here the results show that the nonlinear, adaptive, velocity-proportional damping coefficient is an effective way to increase the overall harnessed power and the power of downstream cylinder. The harnessed power in the VIV to galloping transition increases by up to 94%. The most significant improvement is in the galloping region, where the increase in harnessed power and efficiency is around 33%.

13 HYDRO ENERGY↗

EXTRACTING HUMAN RELIABILITY FINDINGS FROM HUMAN FACTORS STUDIES IN THE HUMAN SYSTEMS SIMULATION LABORATORY

Modernization of U.S. nuclear power plants (NPPs) is widespread, with most plants currently replacing and transitioning equipment, control systems, and human system interfaces (HSI)s from analog to digital displays. This conversion remedies the obsolescence of analog parts along with needs for increased intuitiveness of design, safety, and capabilities. The Human Factors and Reliability team at Idaho National Laboratory (INL) carried out twelve control room modernization studies in the newly designed Human Systems Simulation Laboratory (HSSL) over nine years. The HSSL was constructed as a testbed for evaluating human factors techniques and performance measures, HSI frameworks, and cutting-edge operational concepts in NPPs. Installing a full-scope training simulator enabled direct design and evaluation work on the same instrumentation and control (I&C) and HSIs located at U.S. plants. The subsequent addition of glass top bays afforded crews opportunities to implement operations via the simulator using full-scale representations of their home NPP. Additionally, functional HSI prototypes were created, providing an environment for operator-in-the-loop benchmark studies. The HSSL has assisted in upgrades of six commercial NPP control rooms and served as an invaluable proving ground for new NPP operations technology. Human reliability analysis (HRA) was not originally the focus of the studies; however, data relating to HRA such as type and frequency of human errors can be extracted from the studies. INL is currently extracting data from the HSSL study reports to apprise how information gathered from simulation, HSI, and other related studies can create a broad look across different data sources to help inform HRA methods.

99 GENERAL AND MISCELLANEOUS↗

System and technoeconomic analysis of solar thermochemical hydrogen production

Hydrogen is a promising energy carrier that can be obtained from various feedstocks using renewable energy sources. Direct solar thermochemical hydrogen (STCH) production by water splitting can utilize the full spectrum of solar radiation and has the potential to achieve high solar energy conversion efficiencies. Currently STCH research areas focus on material discovery. This paper evaluates the performance of various STCH materials in the context of a system platform to assess techno-economic benefits and gaps in the path to STCH scale-up. Additionally, to analyze the hydrogen production cost, a concentrating solar thermal (CST) system is introduced as a platform for integrating STCH materials and accommodating generalized thermochemical processes. The thermochemical process is based on a two-step STCH cycle using metal oxide that consists of a high temperature step for metal oxide reduction, followed by an oxidation step for water splitting at a lower temperature. A preferred configuration is to have the high temperature step occurring in a directly irradiated solar receiver reactor. To this end, we conceptualized a receiver design and associated solar field layout and investigated STCH operational boundaries, component costs and sensitivity parameters on the $2/kgH 2 goal of hydrogen production. The study explored system-related variables and factors associated with scaling up. The CST platform allows more comprehensive studies that encompass aspects of STCH materials and systems such as cost, hydrogen productivity and replacement frequency, alongside other system components like heliostat field, tower, and potential receiver costs.

08 HYDROGEN↗

A Climatology of Marine Boundary Layer Cloud and Drizzle Properties derived from Ground-based Observations over the Azores

In this study, more than four years of ground-based observations and retrievals were collected and analyzed to investigate the seasonal and diurnal variations of single-layered MBL (with three subsets: non-drizzling, virga and rain) cloud and drizzle properties, as well as their vertical and horizontal variations. The annual mean drizzle frequency was ~55%, with ~70% in winter and ~45% in summer. The cloud-top (-base) height for rain clouds was the highest (lowest), resulted in the deepest cloud layer (0.8 km), which is four (two) times of non-drizzling (virga) clouds. The retrieved cloud-droplet effective radii (rc) were the largest (smallest) for rain (non-drizzling) clouds, and the nighttime values were greater than the daytime values. Drizzle number concentration (Nd) and liquid water content (LWCd) were three and one order(s) lower than their cloud counterparts. The rc and LWCc increased from the cloud base to ???? = ~0.75 by condensational growth, while drizzle median radii (rd) increased from the cloud top downwards the cloud base by collision-coalescence. The adiabaticity values monotonically increased from the cloud top to the cloud base with maxima of ~0.7 (0.3) for non-drizzling (rain) clouds. The drizzling process decreases the adiabaticity by 0.25 to 0.4, and the cloud-top entrainment mixing impacts as deep as upper 40% of the cloud layers. Cloud and drizzle homogeneities decreased with increased horizontal sampling lengths. Cloud homogeneity increases with increasing cloud fraction. These results can serve as baselines for studying MBL cloud-to-rain conversion and growth processes over the Azores.

Wu, Peng↗

Contrasting Carbon–Water–Energy Dynamics in Perennial and Annual Bioenergy Agroecosystems Using Eddy Covariance and Interpretable Machine Learning

Understanding how agroecosystems respond to environmental variability is fundamental to predicting productivity and sustainability under a changing climate. We analyzed 55 site-years of high-frequency eddy covariance observations from five agroecosystems—two perennial grasses (miscanthus and switchgrass), two annual rotation systems (maize–soybean and sorghum–soybean), and a restored native prairie—to examine ecosystem-scale carbon, water, and energy fluxes. Using an interpretable machine-learning framework with regression tree ensembles, Shapley Additive Explanations, and Accumulated Local Effects, we quantified how environmental and temporal factors regulate gross primary productivity (GPP), evapotranspiration (ET), water-use efficiency, and the Bowen ratio. Perennials exhibited stronger physiological buffering and maintained fluxes across a broader range of temperature and moisture conditions, reflecting deeper rooting and persistent canopy cover. Annuals, in contrast, showed greater short-term variability and stronger coupling to atmospheric demand, with GPP and ET declining rapidly under low humidity or soil moisture. Differences in temperature sensitivity of Bowen ratio further revealed that perennials sustained proportionally greater sensible heat flux under cool conditions, whereas annuals exhibited constrained energy exchange when evaporative demand was low. Together, these results demonstrate that crop life cycle and canopy structure are fundamental determinants of ecosystem-scale carbon–water–energy coupling. By integrating long-term flux observations with interpretable machine learning, this study identifies the environmental drivers that shape agroecosystem function and highlights how conversion from annual to perennial feedstocks can enhance climatic resilience and alter land–atmosphere energy feedbacks. These findings provide a data-driven basis for improving crop and Earth-system models and for guiding bioenergy landscape design under future climate scenarios.

Accumulated Local Effects↗

Microscopic subsurface characterization of layered magnetic materials using magnetic resonance force microscopy

This project resulted in the following accomplishments: 1) The invention of scanned probe ferromagnetic resonance microscopy. Upon implementation and refinement this approach was used to measure static and dynamic magnetic resonance properties of ferromagnets with an unprecedented combination of spectral and spatial resolution. 2) Demonstration and study of spin pumping in a pristine ferromagnet across a boundary defined entirely by a magnetic field gradient, and so free of materials discontinuities. 3) First demonstrated highly efficient dynamic spin injection from Y 3 Fe 5 O 12 (YIG) into NiO, an antiferromagnetic (AF) insulator and robust spin propagation in AF NiO over distances up to 100-nm thickness; both spin injection and spin transport are mediated by the AF spin correlations. 4) Demonstration of exceptionally high efficiency conversion of spin current to charge current achieved in spin pumping from the dynamic magnetization of a ferromagnetic insulator into a variety of adjacent metal films. 5) Seminal study of the nature of spin-orbit coupling in d-electron metals that revealed the dominant sensitivity of the d-orbital moment to the d-electron count and revealing the important roles of both d-electron configuration and atomic number in the physics of the spin Hall effect. 6) Demonstration of observation of FMR by means of optically-detected NV diamond relaxometry that provided a highly sensitive, spatially resolved FMR detection method and revealed spin pumping across 100-nm length scales by means of dipolar coupling. 7) Using magnetic field localization, developed for FMR imaging, demonstrated a novel approach to discretizing spin wave modes to improve the characteristics of auto-oscillators driven by pure spin currents produced by the spin Hall effect. 8) We demonstrated large spin pumping signals from propagating high wavevector spinwaves in thin film YIG find that the spin pumping efficiency was insensitive to wavevector thus emphasizing the promise of thin YIG films for spinwave-based spintronics by allowing for predictable down-scaling of device dimensions and enabling a broad range of operational frequencies.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗

Hydrodynamics and Load Shedding Behavior of a Variable-Geometry Oscillating Surge Wave Energy Converter (OSWEC)

In order to improve their long-term viability, wave energy converters (WECs) need to be able to shed loads when a threshold wave condition is exceeded. As shown by Tom et al. (2016) [1], provision of adjustable flaps within the body of an oscillating surge wave energy converter (OSWEC) allows wave energy to pass through the device. A control system may then be able to open and close the flaps when waves approaching the device exceed preset thresholds. The variable-geometry OSWEC (VG-OSWEC) concept studied in this paper is a bottom-hinged, rectangular wave paddle with five flaps of elliptical cross-section embedded into the face of the paddle. System ID tests were conducted on this VG-OSWEC device at a 1:14 scale in a wave basin. Free decay tests showed that the damping was distinctly nonlinear when the flaps were fully open, and the natural frequency increased by 40% when compared with the flaps in a fully closed configuration. Tests with regular wave conditions were used to develop the response amplitude operator for the rotational motion about the hinge. These response amplitude operator results when compared with numerical simulations run using WEC-Sim/WAMIT and ANSYS AQWA, show strong agreement with the flap open and closed conditions. The regular-wave condition measurements also show that the wave excitation moment about the hinge was reduced by up to 60% when the flaps were fully open. The experiments serve to demonstrate the potential of the variable geometry design to shed loads and survive harsh ocean environments.

load shedding↗

Modular Isolated Soft-Switching Medium Voltage String Inverter for Large-Scale PV Farm

This paper presents a single-stage modular isolated soft-switching medium voltage string inverter (MVSI) with tri-port configuration to interconnect PV and storage to medium voltage (MV) grid. The modular MVSI provides advanced functionalities such as energy storage elements integration without additional converters, connection to MV grid resulting in lower distribution losses in the PV farm, high-frequency galvanic isolation, independent control of PV, storage and grid power, high modularity and scalability. The topology of the MVSI, operation principle and model-predictive priority-switching (MPPS) control to achieve fast dynamic balancing across stacked modules are discussed. The independent power control is validated in PLECS simulation and the operation of stacked MVSI with MPPS control is verified through Hardware-in-the-loop (HIL) simulation. Here, the hardware prototype of 25 kVA MVSI building block is developed. 18 kW experimental results of single building block verifying tri-ports operation and 20 kW experimental results of two modules stacked operation are presented. A clean sinusoidal waveform with negligibly low THD in both tests is obtained. A low dv/dt of <; 1kV/us and soft-switching are achieved.

30 DIRECT ENERGY CONVERSION↗

Operating Stresses and Their Effects on Degradation of LSM-Based SOFC Cathodes

The performance of solid oxides fuel cells (SOFCs) with four different Mn excess of lanthanum strontium manganite (LSM) -based cathodes were examined under different temperatures (1,000 °C, 900 °C), current densities (0, 380, and 760 mA cm -2 ), and cathode atmospheres (p O 2 )=0.1,0.15,0.21) for durations ranging from 58 to 1,008 h. Each yttria-stabilized zirconia (YSZ) electrolyte-supported “button” cell had a porous Ni/YSZ composite anode and a porous LSM/YSZ composite cathode. The cells’ output voltage versus time were recorded and electrochemical impedance spectroscopy (EIS) and linear sweep voltammetry (LSV) measurements were performed every 24 hours. The total area specific resistance (ASR) was calculated from these measurements. The values of ASR from both EIS and LSV were comparable between each other but lower than that from durability test. Distribution of relaxation times (DRT) analysis was performed to investigate the electrochemical processes and their corresponding relaxation frequencies as well as their attributions to the total ASR. The series resistance and parallel resistance that obtained from the equivalent circuit fit of the Nyquist plot were higher at low temperature and low p O 2 regardless of LSM compositions. The area of the peaks derived from DRT analysis increased with time during individual tests. The microstructures of the tested cells were examined using scanning electron microscopy and energy-dispersive x-ray spectroscopy (SEM/EDS). Manganese oxide particles were observed near the cathode-electrolyte interface after prolonged (1,008 h) testing in air of a cell with LSM of 11% manganese excess, and after a short test (58 h) under low oxygen (p O 2 = 0.10) in a cell with LSM of 5% manganese excess. However, the role of MnOx in cell degradation is still unknown.

08 HYDROGEN↗

Hydrogen Adsorption, Reactivity, and Catalysis on Colloidal Iron Carbide Nanoparticles

Supported iron carbide particles have long served as catalysts for CO hydrogenation (the Fischer Tropsch synthesis, FTS) and continue to be attractive. Despite this, little is known about their chemistry. Reported here is a colloidal Fe x C nanoparticle (NP) model system that allows direct observation of surface hydrogen and CO, as well as quantification of the surface H. Dodecylamine-capped Fe x C NPs (DDA-Fe x C NPs) were synthesized through solution-phase carburization of Fe NPs and form stable colloids in low-polarity organic solvents. Treatment of these colloids with H 2 or D 2 produced highly hydrogenated materials, and FTIR spectra of DDA-Fe x C-D n showed that most of the D binds to carbides, with at least four distinct v(C-D) modes. The surface C-H(D) bonds were all reactive, transferring hydrogen to alkenes and other reagents in solution. Titration and ICP measurements showed a 0.17:1 ratio of added H:total Fe, or roughly. 40 H per 1.8 nm DDA-Fe x C NP. Conversely, CO was preferentially bound to surface Fe sites, with FTIR spectra showing a single broad v(CO) that shifted with CO coverage or co-adsorption of H 2 . The DDA-Fe x C NPs were active catalysts for both olefin hydrogenation and the FTS, under mild conditions and without catalyst pre-treatment. The CO hydrogenation reactions yielded a broad distribution of long-chain linear paraffins and olefins. Though quantitative comparisons with typical FTS results are not possible because of our use of sealed batch reactors and other factors, the observations of high catalytic reactivity demonstrate the relevance of this model system to iron-carbide catalysis. DFT calculations on model slab surfaces with varying iron carbide stoichiometries revealed that the thermodynamically preferred surface adsorption sites are C for H ads and Fe for CO ads . A variety of binding sites and binding energies were found for each adsorbate. We are unaware of previous studies indicating that a diverse array of C-H bonds is the primary source of reactive H on iron carbides. Experimentally, the diversity of *C-H sites was evident in reactions with H-atom donors and abstractors of different strengths, from both the reaction stoichiometries and IR spectra. The different surface–H binding energies correlate with the v(C-D) stretching frequencies. Furthermore, these insights into complex iron carbide surfaces and catalysis could assist catalyst design, and they showcase the importance of stoichiometric studies of reaction intermediates.

08 HYDROGEN↗

Comparison of Social Media, Syndromic Surveillance, and Microbiologic Acute Respiratory Infection Data: Observational Study

Internet data can be used to improve infectious disease models. However, the representativeness and individual-level validity of internet-derived measures are largely unexplored as this requires ground truth data for study. This study sought to identify relationships between Web-based behaviors and/or conversation topics and health status using a ground truth, survey-based dataset. This study leveraged a unique dataset of self-reported surveys, microbiological laboratory tests, and social media data from the same individuals toward understanding the validity of individual-level constructs pertaining to influenza-like illness in social media data. Logistic regression models were used to identify illness in Twitter posts using user posting behaviors and topic model features extracted from users’ tweets. Of 396 original study participants, only 81 met the inclusion criteria for this study. Of these participants’ tweets, we identified only two instances that were related to health and occurred within 2 weeks (before or after) of a survey indicating symptoms. It was not possible to predict when participants reported symptoms using features derived from topic models (area under the curve [AUC]=0.51; P=.38), though it was possible using behavior features, albeit with a very small effect size (AUC=0.53; P≤.001). Individual symptoms were also generally not predictable either. The study sample and a random sample from Twitter are predictably different on held-out data (AUC=0.67; P≤.001), meaning that the content posted by people who participated in this study was predictably different from that posted by random Twitter users. Individuals in the random sample and the GoViral sample used Twitter with similar frequencies (similar @ mentions, number of tweets, and number of retweets; AUC=0.50; P=.19). To our knowledge, this is the first instance of an attempt to use a ground truth dataset to validate infectious disease observations in social media data. The lack of signal, the lack of predictability among behaviors or topics, and the demonstrated volunteer bias in the study population are important findings for the large and growing body of disease surveillance using internet-sourced data.

59 BASIC BIOLOGICAL SCIENCES↗

Overlooked cooling effects of albedo in terrestrial ecosystems

Radiative forcing (RF) resulting from changes in surface albedo is increasingly recognized as a significant driver of global climate change but has not been adequately estimated, including by Intergovernmental Panel on Climate Change (IPCC) assessment reports, compared with other warming agents. Here, we first present the physical foundation for modeling albedo-induced RF and the consequent global warming impact (GWI Δα ). We then highlight the shortcomings of available current databases and methodologies for calculating GWI Δα at multiple temporal scales. There is a clear lack of comprehensive in situ measurements of albedo due to sparse geographic coverage of ground-based stations, whereas estimates from satellites suffer from biases due to the limited frequency of image collection, and estimates from earth system models (ESMs) suffer from very coarse spatial resolution land cover maps and associated albedo values in pre-determined lookup tables. Field measurements of albedo show large differences by ecosystem type and large diurnal and seasonal changes. As indicated from our findings in southwest Michigan, GWI Δα is substantial, exceeding the RF Δα values of IPCC reports. Inclusion of GWI Δα to landowners and carbon credit markets for specific management practices are needed in future policies. We further identify four pressing research priorities: developing a comprehensive albedo database, pinpointing accurate reference sites within managed landscapes, refining algorithms for remote sensing of albedo by integrating geostationary and other orbital satellites, and integrating the GWI Δα component into future ESMs.

54 ENVIRONMENTAL SCIENCES↗

Full wave modeling of radio-frequency beams in tokamaks in the electron cyclotron frequency range

Simulation of full wave, without paraxial approximation, high-resolution solution of wave equations in frequency domain in the electron cyclotron resonance (ECR) frequency range for realistic Tokamak plasma parameters became possible by using recently formulated hybrid iterative algorithm [Svidzinski et al., Phys. Plasmas 25, 082509 (2018)] for numerically solving discretized wave equations. This approach combines time evolution and iterative relaxation techniques into iteration cycles. This algorithm is implemented in 2D code FullWave, solving wave equations in Tokamaks in cold and hot plasma models, and it has been tested in 3D full wave iterative RF beams simulation tool, which is presently being developed to model 3D ECRH RF beams in fusion devices using dynamic grid adaptation. The results of 2D full wave modeling, assuming specified toroidal mode number, of ECRH RF beams in DIII-D plasma, performed in the cold and hot plasma models for outboard and top launch scenarios using FullWave are presented. Nonlocal hot plasma response model, based on accurate numerical solution of linearized Vlasov equation, is used to model beam propagation and absorption in the 2nd electron cyclotron harmonic region. Demonstration of capability of the hybrid iterative algorithm to model ECRH RF beams in 3D is made by simulating a substantial part of realistic beam in DIII-D, launched from outboard side of the machine. All relevant physics of RF beam propagation, most of which is not captured in paraxial approximation, such as beam's divergence, interference between the X and O modes in the beam, X-O mode conversion, beam splitting into the X and O mode beams, transformation of beam's cross section, and absorption at the 2nd electron cyclotron harmonic, is captured in the simulations. A numerical technique to find an optimal beam polarization at the launcher to launch a nearly pure X or O mode beam in plasma is developed and tested.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗