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A microbial partnership thriving in an acidic hot spring in Yellowstone National Park has surrendered some of its lifestyle secrets to researchers at ORNL.
This presentation provides an overview of the Borrego Springs community microgrid.
The Great Basin region of the western USA is capable of generating much greater amounts of geothermal energy than currently produced. Most geothermal resources in this region are blind, and thus the favorable characteristics for geothermal activity must be synthesized and methodologies developed to discover new commercial-grade systems. The geothermal play fairway concept involves integration of multiple parameters indicative of geothermal activity as a means of identifying promising areas for new development. In the Nevada play fairway project, nine geologic, geochemical, and geophysical parameters were initially synthesized to produce a new geothermal potential map of 96,000 km2. Granite Springs Valley in western Nevada is a particularly promising site selected for detailed study. It contains several favorable structural settings, including terminations of major Quaternary normal faults and fault intersections. Geologic, geophysical, and geochemical techniques were employed to define the most likely sites for high permeability and select drilling targets for temperature-gradient holes. Local and intermediate permeability models were revised to reflect results of detailed analyses and generate new detailed play fairway maps of the area. The most promising site lies in the northeastern part of the basin directly east of Adobe Flat, where the horse-tailing termination of a major normal fault (as revealed by new gravity data), opaline sinter deposits, warm shallow wells, and a low-resistivity anomaly are collocated. Geothermometry suggests a blind system with temperatures as high as ~130°C in this area. Four new temperature-gradient holes document temperatures of ~80°C at ~150 m depth. Lessons learned in the detailed studies of this project include: 1) initially identified sites commonly include multiple favorable settings at a finer scale; 2) promising sites in Cenozoic basins cannot be well defined without detailed geophysical surveys; and 3) play fairway analysis is critical at multiple scales, providing a means to select regional prospects as well as vectoring into drilling targets at individual sites.
Subsurface data analysis, reservoir modeling, and machine learning (ML) techniques have been applied to the Brady Hot Springs (BHS) geothermal field in Nevada, USA to further characterize the subsurface and assist with optimizing reservoir management. Hundreds of reservoir simulations have been conducted in TETRAD-G and CMG STARS to explore different injection and production fluid flow rates and allocations and to develop a training data set for ML. This process included simulating the historical injection and production since 1979 and prediction of future performance through 2040. ML networks were created and trained using TensorFlow based on multilayer perceptron (MLP), long short-term memory (LSTM), and convolutional neural network (CNN) architectures. These networks took as input selected flow rates, injection temperatures, and historical field operation data and produced estimates of future production temperatures. This approach was first successfully tested on a simplified single fracture doublet system, followed by the application to the BHS reservoir. Using an initial BHS dataset with 37 simulated scenarios, the trained and validated network predicted the production temperature for 6 production wells with the mean absolute percentage error of less than 8%. In a complementary analysis effort, the principal component analysis applied to 13 BHS geological parameters revealed that vertical fracture permeability shows the strongest correlation with fault density and fault intersection density. A new BHS reservoir model was developed considering the fault intersection density as proxy for permeability. This new reservoir model helps to explore under-exploited zones in the reservoir. A data gathering plan to obtain additional subsurface data was developed; it includes temperature surveying for three idle injection wells, at which the reservoir simulations indicate high bottom-hole temperatures. The collected data assist with calibrating the reservoir model and may lead to converting these wells to producers to access under-exploited zones in the reservoir. Data gathering activities are planned for the first quarter of 2021.
Surface thermal features, most notably hot springs and geysers are increasingly being recognized for their importance to ecosystems, indigenous cultures, and in some cases agriculture, recreation, and tourism. Geothermal project development poses a potential risk to these natural features but current regulatory requirements for assessing and managing these risks during exploration, permitting and monitoring are somewhat inconsistent and unpredictable across different geothermal fields. This has resulted in uncertainty and increases in exploration risk for geothermal energy developers that have led to costly project delays, cancellations, or hesitation to commit. Varying regulatory requirements may also influence public perception, fostering confusion, distrust and ultimately opposition to geothermal projects, further contributing to project delays or cancellations. At a time when there is an increasing urgency for reliable baseload clean energy, geothermal is a net-zero, renewable solution that additionally provides access to more equitable and environmentally just clean power. Continued integration of geothermal energy into the national energy roadmap can be facilitated through consistent and predictable permitting, providing regulators the framework they need, developers a clear path forward, and transparency that the public deserves. This project, currently in its beginning phases, seeks to address this important issue by providing a technical basis from which to build a preliminary protocol for assessing and managing potential impacts from new or existing geothermal energy projects to surface thermal features and their associated ecosystems. Development of this preliminary protocol will be informed by (1) a literature review of well-documented case studies in the western U.S. and New Zealand to understand the range of conditions that exemplify geothermal-surface thermal systems; (2) development of generic illustrative conceptual-numerical models to quantify, understand, and predict the first-order controls (e.g., pressure and permeability) on surface flows; and (3) additional independent and scientifically rigorous evaluations of geothermal-surface thermal system case studies from the Basin and Range Province that incorporate publicly available data as well as data provided by industry through data-sharing agreements. Learning from the successes of the process used to develop the Induced Seismicity Management Protocol (ISMP), we ultimately aim to use these initial efforts as a springboard for establishing a surface thermal feature management working group that will work collaboratively to finalize the protocol as well as co-create recommended best practices for implementation. We envision that the working group will primarily be composed of representatives from regulatory entities, government agencies, Tribes, academia, national laboratories, and industry, and will include early and regular engagement with community organizations and environmental groups. This will help ensure broad acceptance and implementation of the protocol, which will facilitate a more consistent, predictable, and standardized regulatory process, and help to ensure that geothermal energy continues to provide a reliable source of clean energy, and a pathway to achieving greater energy equity in the U.S.
Abstract Globally, populations of diverse taxa have altered phenology in response to climate change. However, most research has focused on a single population of a given taxon, which may be unrepresentative for comparative analyses, and few long‐term studies of phenology in ectothermic amniotes have been published. We test for climate‐altered phenology using long‐term studies (10–36 years) of nesting behavior in 14 populations representing six genera of freshwater turtles ( Chelydra , Chrysemys , Kinosternon , Malaclemys , Sternotherus , and Trachemys ). Nesting season initiation occurs earlier in more recent years, with 11 of the populations advancing phenology. The onset of nesting for nearly all populations correlated well with temperatures during the month preceding nesting. Still, certain populations of some species have not advanced phenology as might be expected from global patterns of climate change. This collection of findings suggests a proximate link between local climate and reproduction that is potentially caused by variation in spring emergence from hibernation, ability to process food, and thermoregulatory opportunities prior to nesting. However, even though all species had populations with at least some evidence of phenological advancement, geographic variation in phenology within and among turtle species underscores the critical importance of representative data for accurate comprehensive assessments of the biotic impacts of climate change.
Abstract Background Seaweed oligosaccharides are environmentally‐friendly natural products and their use for disease control in sustainable agriculture is extremely promising. Enzymatic digestion to prepare seaweed oligosaccharides has drawn considerable interest. However, the study of enzymatically degraded products of carrageenan is still in its infancy compared with that of other hydrocolloids such as agar and alginate. To prepare degraded carrageenan on a commercial scale, it is necessary to select superior producer bacterial strains to improve the yield and thermostability of carrageenases. Results The carrageenan‐degrading bacterium Bacillus sp. HT19 was isolated from sediment of a hot spring in Indonesia, and a κ‐carrageenase with high activity was purified from the culture supernatant. The purified enzyme, named Car19, had maximum activity (538 U mg −1 ) at 60 °C and pH 7.0. Notably, the enzyme retained >90% of its initial activity after incubation at 60 °C for 24 h. The Ca 2+ obviously improved the thermostability of Car19 at 70 °C. The K m and V max values of purified Car19 were 0.061 mg mL −1 and 115.13 U mg −1 , respectively, with κ‐carrageenan as substrate. Thin‐layer chromatography and electrospray ionization mass‐spectrometry analysis of hydrolysates indicated that the enzyme exolytically depolymerized κ‐carrageenan to neo‐carrabiose. The hydrolysate enhanced the resistance of cucumber to cucumber mosaic virus and increased the activity of antioxidant enzymes in infected plants. Conclusion To our knowledge, Car19 is the most thermostable κ‐carrageenase reported so far. Its high optimal reaction temperature and thermostability, and unitary hydrolysate constituent, makes Car19 a promising candidate for the preparation of carrageenan oligosaccharides with plant protection activity. © 2018 Society of Chemical Industry
Abstract We examined the efficacy of a one-generation (five brood years: 1997–2001) captive broodstock program for spring Chinook Salmon Oncorhynchus tshawytscha by comparing survival rates of captive broodstock progeny (CBP; F2) with that of hatchery-origin fish (HOR) from a conservation hatchery supplementation program in which both groups were derived from the Tucannon River (Washington State) population for the 2000–2006 brood years. Survival rates compared were egg to fry, fry to smolt, egg to smolt, total (ages 3–5) and adult (ages 4+) smolt-to-adult-return (SAR) survival, and total (ages 3–5) and adult (ages 4+) progeny-to-parent (P:P) ratio. Total escapement and adult P:P ratios were also examined to determine if observed demographic benefits to the population continued after the captive broodstock program ended. The CBP group had lower within-hatchery survival than the HOR group, with significant differences in survival at the egg-to-fry and egg-to-smolt stages due to poor egg viability. Mean untransformed total and adult SARs for the CBP were half those of the HOR group; however, SARs did not differ significantly. The CBP also had significantly lower total and adult P:P ratios than the HOR group and were below replacement for six of the seven brood years. While the captive broodstock provided additional fish for release that would not have been available otherwise, overall the CBP performed poorly and below expectations compared with the HOR group, both within the hatchery and after release. The captive broodstock program provided a short-term demographic boost, most notable in the 2008–2010 return years, but the benefit did not carry over after the program ended.
Changes in characteristics of snowfall and spring freeze–thaw-cycle (FTC) events under the warming climate make it critical to understand biophysical controls on soil CO2 efflux (RS) in seasonally snow-covered ecosystems. We conducted a snow removal experiment and took year-round continuous automated measurements of RS, soil temperature (T5) and soil volumetric water content at the 5 cm depth (W5) with a half-hour interval in a Chinese temperate forest in 2010–2011. Our objectives were to: (1) develop statistical models to describe the seasonality of RS in this forest; (2) quantify the contribution of seasonal RS to the annual budget; (3) examine biophysical effects of snowpack on RS; and (4) test the hypothesis that an FTC-induced enhancement of RS is jointly driven by biological and physical processes.
Temperate and boreal conifer forests are dormant for many months during the cold season. Climate change is altering the winter environment, with increased temperature, altered precipitation, and earlier snowmelt in many locations. If significant enough, these changes may alter patterns of dormancy and activity of evergreens. Here we studied the factors limiting photosynthetic activity of a high-elevation subalpine forest that has undergone substantial warming in recent decades. We tested the hypothesis that this warming has been significant enough to allow photosynthesis during sunny warm days in winter. Using thermal imagery, we found that foliage in winter was sometimes near the temperature optimum for photosynthesis, but no net carbon gain occurred for most of the cold season. Water transport was limited by blockage of sap transport by frozen boles, but not by frozen soils. Foliar carotenoid content was much higher during winter, driven largely by increases in the pool size of the photoprotective xanthophyll cycle. There was no seasonal change in chlorophyll or lutein content. Net carbon uptake began only as boles thawed, with no difference in timing among tree species, and the spring increase in canopy-level photosynthetic capacity occurred before sap transport was detected. The seasonality of gross primary productivity (GPP) was strongly linked to seasonality of xanthophyll cycle deepoxidation state in all species. Seasonality of GPP was detectable with two metrics of canopy color – the Green Chromatic Coordinate and Green-Red Vegetation Index (a proxy for the newly proposed MODIS-based chlorophyll/carotenoid index or CCI). Both indices were significantly correlated with GPP. Together these results indicate the potential for airborne or near-surface remote sensing of leaf color to serve as a metric of photosynthetic activity in evergreen forests, and to monitor physiological changes associated with the progression in and out of winter dormancy.
Accurate models are important to predict how global climate change will continue to alter plant phenology and near-term ecological forecasts can be used to iteratively improve models and evaluate predictions that are made a priori. The Ecological Forecasting Initiative's National Ecological Observatory Network (NEON) Forecasting Challenge, is an open challenge to the community to forecast daily greenness values, measured through digital images collected by the PhenoCam Network at NEON sites before the data are collected. For the first round of the challenge, which is presented here, we forecasted canopy greenness throughout the spring at eight deciduous broadleaf sites to investigate when, where, and for what model type phenology forecast skill is highest. A total of 192,536 predictions were submitted, representing eighteen models, including a persistence and a day of year mean null models. We found that overall forecast skill was highest when forecasting earlier in the greenup curve compared to the end, for shorter lead times, for sites that greened up earlier, and when submitting forecasts during times other than near budburst. The models based on day of year historical mean had the highest predictive skill across the challenge period. In this first round of the challenge, by synthesizing across forecasts, we started to elucidate what factors affect the predictive skill of near-term phenology forecasts.
We present a reservoir geophysics study, including rock physics modeling and seismic inversion, of a carbon dioxide sequestration site in Southwestern Wyoming, namely the Rock Springs Uplift, and build a petrophysical model for the potential injection reservoirs for carbon dioxide sequestration. Our objectives include the facies classification and the estimation of the spatial model of porosity and permeability for two sequestration targets of interest, the Madison Limestone and the Weber Sandstone. The available dataset includes a complete set of well logs at the location of the borehole available in the area, a set of 110 core samples, and a seismic survey acquired in the area around the well. The proposed study includes a formation evaluation analysis and facies classification at the well location, the calibration of a rock physics model to link petrophysical properties and elastic attributes using well log data and core samples, the elastic inversion of the pre-stack seismic data, and the estimation of the reservoir model of facies, porosity and permeability conditioned by seismic inverted elastic attributes and well log data. In particular, the rock physics relations are facies-dependent and include granular media equations for clean and shaley sandstone, and inclusion models for the dolomitized limestone. The permeability model has been computed by applying a facies-dependent porosity-permeability relation calibrated using core sample measurements. Finally, the study shows that both formations show good storage capabilities. The Madison Limestone includes a homogeneous layer of high-porosity high-permeability dolomite; the Weber Sandstone is characterized by a lower average porosity but the layer is thicker than the Madison Limestone.
In recent years, the number of floods following unprecedented rainfall events have increased in Iran during early spring (March 21st to April 20th, referred to in Iran as the month of “Farvadin”). While numerous studies have addressed changes in climate extremes and precipitation trends at different temporal scales from daily to annual across the country, analyses of short-duration and heavy precipitation, especially during recent years, are rarely considered. Furthermore, most studies investigate the variations in extremes and total precipitation using a limited number of synoptic weather stations across Iran. Here this study assesses the variations in heavy precipitation (precipitation with intensities greater than or equal to 3 mm/3 h) at 0.04° spatial and 3-hourly temporal resolution during the month of Farvardin. In addition, the effect of atmospheric river conditions over Iran and their possible link to intensifying heavy precipitation is explored. For this purpose, the CONNected-objECT (CONNECT) algorithm is applied on a precipitation dataset, Precipitation Estimation from Remotely Sensed Information Using Artificial Neural Networks-Cloud Classification System (PERSIANN-CCS), and an Integrated Water Vapor Transport (IVT) dataset from the NASA Modern-Era Retrospective Analysis for Research and Applications Version-2 (MERRA-2). The results suggest that the increase in the number of floods in recent years is related to the increase in the intensity and volume of heavy precipitation events, although the frequency and duration of heavy precipitation events have not changed significantly. Furthermore, the results show that atmospheric river conditions over the country are present during the same window as each year’s most extreme events. It is found that 8 out of 13 of the largest ARs over Iran come from moisture plumes with pathways over the African and Red Sea.
Three thermophilic Nanoarchaeota-Crenarchaeota symbiotic systems have been described. We obtained another stable anaerobic enrichment culture at 80 °C, pH 6.0 from a New Zealand hot spring. The nanoarchaeote (Ncl-1) and its host (NZ3 T ) were isolated in co-culture and their genomes assembled. The small (~200 nm) flagellated cocci were often attached to larger cocci. Based on 16S rRNA gene similarity (88.4%) and average amino acid identity (52%), Ncl-1 is closely related to Candidatus Nanopusillus acidilobi. Their genomes both encode for archaeal flagella and partial glycolysis and gluconeogenesis pathways, but lack ATP synthase genes. Like Nanoarchaeum equitans, Ncl-1 has a CRISPR-Cas system. Ncl-1 also relies on its crenarchaeotal host for most of its biosynthetic needs. The host NZ3 T was isolated and grows on proteinaceous substrates but not on sugars, alcohols, or fatty acids. NZ3 T requires thiosulfate and grows best at 82 °C, pH 6.0. NZ3 T is most closely related to the Desulfurococcaceae, Ignisphaera aggregans (~92% 16S rRNA gene sequence similarity, 45% AAI). Based on phylogenetic, physiological and genomic data, Ncl-1 and NZ3T represent novel genera in the Nanoarchaeota and the Desulfurococcaceae, respectively, with the proposed names Candidatus Nanoclepta minutus and Zestosphaera tikiterensis gen. nov., sp. nov., type strain NZ3 T (=DSMZ 107634 T = OCM 1213 T ).
Here we implemented the Gaussian charge-on-spring (GCOS) version of the original self-consistent field implementation of the Gaussian Charge Polarizable water model and test its accuracy to represent the polarization behavior of the original model involving smeared charges and induced dipole moments. Moreover, for that purpose we adapted the recently developed multiple-particle-move (MPM) within the Gibbs and isochoric-isothermal ensembles Monte Carlo methods for the efficient simulation of polarizable fluids. We also assessed the accuracy of the GCOS representation by a direct comparison of the resulting vapor-liquid phase envelope, microstructure, and relevant microscopic descriptors of water polarization along the orthobaric curve against the corresponding quantities from the actual GCP water model.
The influence of mixed-phase stratiform clouds on the surface shortwave irradiance is examined using unique spectral shortwave irradiance measurements made during the Indirect and Semi-Direct Aerosol Campaign (ISDAC), supported by the U.S. Department of Energy Atmospheric Radiation Measurement (ARM) program. An Analytical Spectral Devices (ASD, Inc.) spectroradiometer measured downwelling spectral irradiance from 350 to 2200 nm in one-minute averages throughout April-May 2008 from the ARM Climate Research Facility's North Slope of Alaska (NSA) site at Barrow. This study examines spectral irradiance measurements made under single-layer, overcast cloud decks having geometric thickness < 3000 m. Cloud optical depth is retrieved from irradiance in the interval 1022-1033 nm. The contrasting surface radiative influences of mixed-phase clouds and liquid-water clouds are discerned using irradiances in the 1.6-{micro}m window. Compared with liquid-water clouds, mixed-phase clouds during the Arctic spring cause a greater reduction of shortwave irradiance at the surface. At fixed conservative-scattering optical depth (constant optical depth for wavelengths {lambda} < 1100 nm), the presence of ice water in cloud reduces the near-IR surface irradiance by an additional several watts-per-meter-squared. This additional reduction, or supplemental ice absorption, is typically {approx}5 W m{sup -2} near solar noon over Barrow, and decreases with increasing solar zenith angle. However, for some cloud decks this additional absorption can be as large as 8-10 W m{sup -2}.
Laboratory measurements including gas (N 2 ) porosity and permeability, time-domain nuclear magnetic resonance, thin section, and scanning electron microscopy analysis were conducted to obtain petrographical and petrophysical descriptions of the Weber Sandstone and Madison Limestone at the Rock Spring Uplift, a potential carbon dioxide storage site in Southwestern Wyoming. The relationships between pore structures, such as pore geometry, pore-size distribution, pore network, and porosity/permeability are investigated. First, using thin sections combined with scanning electron microscopy for pore structures description, all samples are described in detail from the geological, petrographysical, and diagenetic viewpoint. Results show that within the Madison Limestone, pore types include intercrystalline, vuggy, moldic, or mixed (combination of all other pore types). Both moldic and vuggy pore types are associated with samples of high porosity and permeability. Nuclear magnetic resonance relaxation time distributions show either bimodal or multimodal distributions. Large relaxation time components are associated with samples with large pores, whereas small components are dominated by small pores. The T 2 geometric mean correlates well with gas permeability. Additionally, short-time diffusion coefficients (D) were measured by pulsed field gradient method using a series of gradient strengths. We found that diffusion coefficient distributions correlate with the corresponding T 2 distributions for macropores. By comparing the dominant peak position of T 2 distributions and their corresponding diffusion coefficient distributions, we predicted the surface relaxivity of different rock types. We found that surface relaxivities of Weber Sandstone samples can be well predicted, while for Madison Limestone samples, surface relaxivities are overestimated due to diffusive pore coupling effect.
Brady Hot Springs geothermal field has exhibited subsidence, as measured by interferometric synthetic aperture radar (InSAR). Previous studies have examined both the temporal evolution of the deformation from 2004 through 2016 and the spatial extent of the deformation, directly relating the observed subsidence to volumetric changes below the surface. We extend the modeling at Brady to analyze a data set of interferometric pairs spanning from the end of 2003 through 2018. We examine spatial and temporal trends in the observed deformation by time–series analysis of each of the 1656 cubic voxels in a parameterized elastic dislocation model to identify areas where the subsurface volume changes as a function of time. Joint time–series analysis of Global Positioning System and InSAR pairs confirm significant changes in rates of volume change during time intervals when well operations were varied. Here, the rate of subsidence increases with increased injection, consistent with the identification of thermal contraction of the rock matrix as the dominant driving mechanism. Conversely, the modeled volume increases when pumping ceases, suggesting thermal expansion of the rock matrix.