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DOE OSTI2022

Data for Metabolic Engineering of Rhodotorula toruloides IFO0880 Improves C16 and C18 Fatty Alcohol Production from Synthetic Media

The oleaginous, carotenogenic yeast Rhodotorula toruloides has been increasingly explored as a platform organism for the production of terpenoids and fatty acid derivatives. Fatty alcohols, a fatty acid derivative widely used in the production of detergents and surfactants, can be produced microbially with the expression of a heterologous fatty acyl-CoA reductase. Due to its high lipid production, R. toruloides has high potential for fatty alcohol production, and in this study several metabolic engineering approaches were investigated to improve the titer of this product. Fatty acyl-CoA reductase from Marinobacter aqueolei was co-expressed with SpCas9 in R. toruloides IFO0880 and a panel of gene overexpressions and Cas9-mediated gene deletions were explored to increase the fatty alcohol production. Two overexpression targets (ACL1 and ACC1, improving cytosolic acetyl-CoA and malonyl-CoA production, respectively) and two deletion targets (the acyltransferases DGA1 and LRO1) resulted in significant (1.8 to 4.4-fold) increases to the fatty alcohol titer in culture tubes. Combinatorial exploration of these modifications in bioreactor fermentation culminated in a 3.7 g/L fatty alcohol titer in the LRO1Δ mutant. As LRO1 deletion was not found to be beneficial for fatty alcohol production in other yeasts, a lipidomic comparison of the DGA1 and LRO1 knockout mutants was performed, finding that DGA1 is the primary acyltransferase responsible for triacylglyceride production in R. toruloides , while LRO1 disruption simultaneously improved fatty alcohol production, increased diacylglyceride and triacylglyceride production, and increased glucose consumption. The fatty alcohol titer of fatty acyl-CoA reductase-expressing R. toruloides was significantly improved through the deletion of LRO1, or the deletion of DGA1 combined with overexpression of ACC1 and ACL1. Disruption of LRO1 surprisingly increased both lipid and fatty alcohol production, creating a possible avenue for future study of the lipid metabolism of this yeast.

Conversion↗

NASA NTRS1999

Automated Flight Dynamics Product Generation for the EOS AM-1 Spacecraft

As part of NASA's Earth Science Enterprise, the Earth Observing System (EOS) AM-1 spacecraft is designed to monitor long-term, global, environmental changes. Because of the complexity of the AM-1 spacecraft, the mission operations center requires more than 80 distinct flight dynamics products (reports). To create these products, the AM-1 Flight Dynamics Team (FDT) will use a combination of modified commercial software packages (e.g., Analytical Graphic's Satellite ToolKit) and NASA-developed software applications. While providing the most cost-effective solution to meeting the mission requirements, the integration of these software applications raises several operational concerns: (1) Routine product generation requires knowledge of multiple applications executing on variety of hardware platforms. (2) Generating products is a highly interactive process requiring a user to interact with each application multiple times to generate each product. (3) Routine product generation requires several hours to complete. (4) User interaction with each application introduces the potential for errors, since users are required to manually enter filenames and input parameters as well as run applications in the correct sequence. Generating products requires some level of flight dynamics expertise to determine the appropriate inputs and sequencing. To address these issues, the FDT developed an automation software tool called AutoProducts, which runs on a single hardware platform and provides all necessary coordination and communication among the various flight dynamics software applications. AutoProducts, autonomously retrieves necessary files, sequences and executes applications with correct input parameters, and deliver the final flight dynamics products to the appropriate customers. Although AutoProducts will normally generate pre-programmed sets of routine products, its graphical interface allows for easy configuration of customized and one-of-a-kind products. Additionally, AutoProducts has been designed as a mission-independent tool, and can be easily reconfigured to support other missions or incorporate new flight dynamics software packages. After the AM-1 launch, AutoProducts will run automatically at pre-determined time intervals . The AutoProducts tool reduces many of the concerns associated with the flight dynamics product generation. Although AutoProducts required a significant effort to develop because of the complexity of the interfaces involved, its use will provide significant cost savings through reduced operator time and maximum product reliability. In addition, user satisfaction is significantly improved and flight dynamics experts have more time to perform valuable analysis work. This paper will describe the evolution of the AutoProducts tool, highlighting the cost savings and customer satisfaction resulting from its development. It will also provide details about the tool including its graphical interface and operational capabilities.

Matusow, Carla↗

NASA NTRS2003

Snow and Ice Products from the Moderate Resolution Imaging Spectroradiometer

Snow and sea ice products, derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument, flown on the Terra and Aqua satellites, are or will be available through the National Snow and Ice Data Center Distributed Active Archive Center (DAAC). The algorithms that produce the products are automated, thus providing a consistent global data set that is suitable for climate studies. The suite of MODIS snow products begins with a 500-m resolution, 2330-km swath snow-cover map that is then projected onto a sinusoidal grid to produce daily and 8-day composite tile products. The sequence proceeds to daily and 8-day composite climate-modeling grid (CMG) products at 0.05 resolution. A daily snow albedo product will be available in early 2003 as a beta test product. The sequence of sea ice products begins with a swath product at 1-km resolution that provides sea ice extent and ice-surface temperature (IST). The sea ice swath products are then mapped onto the Lambert azimuthal equal area or EASE-Grid projection to create a daily and 8-day composite sea ice tile product, also at 1 -km resolution. Climate-Modeling Grid (CMG) sea ice products in the EASE-Grid projection at 4-km resolution are planned for early 2003.

Hall, Dorothy K.↗

NASA NTRS1997

The Climate Signal in Regional Moisture Fluxes: A Comparison of Three Global Data Assimilation Products

This study assesses the quality of estimates of climate variability in moisture flux and convergence from three assimilated data sets: two are reanalysis products generated at the Goddard Data Assimilation Office (DAO) and the National Centers for Environmental Prediction/National Centers for Atmospheric Research (NCEPJNCAR), and the third consists of the operational analyses generated at the European Center for Medium Range Forecasts (ECMWF). The regions under study (the United States Great Plains, the Indian monsoon region, and Argentina east of the Andes) are characterized by frequent low level jets (LLJs) and other interannual low level wind variations tied to the large-scale flow. While the emphasis is on the reanalysis products, the comparison with the operational product is provided to help assess the improvements gained from a fixed analysis system. All three analyses capture the main moisture flux anomalies associated with selected extreme climate (drought and flood) events during the period 1985-93. The correspondence is strongest over the Great Plains and weakest over the Indian monsoon region reflecting differences in the observational coverage. For the reanalysis products, the uncertainties in the lower tropospheric winds is by far the dominant source of the discrepancies in the moisture flux anomalies in the middle latitude regions. Only in the Indian Monsoon region, where interannual variability in the low level winds is comparatively small, does the moisture bias play a substantial role. In contrast, the comparisons with the operational product show differences in moisture which are comparable torhe differences in the wind in all three regions. Compared with the fluxes, the anomalous moisture convergences show substantially larger differences among the three products. The best agreement occurs over the Great Plains region where all three products show vertically-integrated moisture convergence during the floods and divergence during the drought with differences in magnitude of about 25%. The reanalysis products, in particular, show good agreement in depicting the different roles of the mean flow and transients during the flood and drought periods. Differences between the three products in the other two regions exceed 100% reflecting differences in the low level jets and the large scale circulation patterns. The operational product tends to have locally larger amplitude convergence fields which average out in area-mean budgets: this appears to be at least in part due to errors in the surface pressure fields and aliasing from the higher resolution of the original ECMWF fields. On average, the reanalysis products show higher coherence with each other than with the operational product in the estimates of interannual variability. This result is less clear in the Indian monsoon region where differences in the input observations appears to be an important factor. The agreement in the anomalous convergence patterns is, however, still rather poor even over relatively data dense regions such as the United States Great Plains. These differences are attributed to deficiencies in the assimilating GCM's representations of the planetary boundary layer and orography, and a global observing system incapable of resolving the highly confined low level winds associated with the climate anomalies.

Min, Wei↗

NASA NTRS2011

Contribution of Near Real Time MODIS-Based Forest Disturbance Detection Products to a National Forest Threat Early Warning System

This presentation discusses an effort to compute and post weekly MODIS forest change products for the conterminous US (CONUS), as part of national forest threat early warning system (EWS) known as the U.S. Forest Change Assessment Viewer (FCAV). The US Forest Service, NASA, USGS, and ORNL are working collaboratively to contribute weekly change products to this EWS. Large acreages of the nation's forests are being disturbed by a growing multitude of biotic and abiotic threats that can act either singularly or in combination. When common at regional scales, such disturbances can pose hazards and threats to floral and faunal bio-diversity, ecosystem sustainability, ecosystem services, and human settlements across the conterminous US. Regionally evident forest disturbances range from ephemeral periodic canopy defoliation to stand replacement mortality events due to insects, disease, fire, hurricanes, tornadoes, ice, hail, and drought. Mandated by the Healthy Forest Restoration Act of 2003, this forest threat EWS has been actively developed since 2006 and on-line since 2010. This FCAV system employs 250-meter MODIS NDVI-based forest change products as a key element of the system, providing regional and CONUS scale products in near real time every 8 days. Each forest change product in FCAV is based on current versus historical 24 day composite NDVI data gridded at 231.66 meter resolution. Current NDVI is derived from USGS eMODIS expedited products. MOD13 NDVI is used for constructing historical baselines. CONUS change products are computed for all forests as % change in the current versus historical NDVI. Change products are computed according to previous year, previous 3 years and previous 8 year historical baselines. The use of multiple baselines enables disturbance anomaly phenology to be more fully assessed. CONUS forest change products are posted each week on the FCAV, a web mapping service maintained by the National Environmental Modeling and Analysis Center. The FCAV EWS has been used to aid multiple Federal and State agency forest management activities, including aerial disturbance detection surveys, as well as rapid response preliminary assessments of timber loss due to tornadoes, regional drought studies, and fire damage assessments. The FCAV allows end-users to assess the context of apparent forest vegetation change with respect to ancillary data, such as land cover, topography, hydrology, climate variables, and administrative boundaries. Such change products are being evaluated through case studies involving comparison with higher spatial resolution satellite, aerial, and field data. The presentation will include multiple examples in which regionally evident forest disturbances were successfully detected and monitored with the MODIS-based change products, as part of the FCAV. FCAV's MODIS forest change products enable end-users (e.g., resource managers) to monitor forest hazards at regional scales throughout the year and across the nation.

Spruce, Joseph P.↗

NASA NTRS2013

Development of Hybrid Product Breakdown Structure for NASA Ground Systems

The Product Breakdown Structure is traditionally a method of identification of the products of a project in a tree structure. It is a tool used to assess, plan, document, and display the equipment requirements for a project. It is part of a product based planning technique, and attempts to break down all components of a project in as much detail as possible, so that nothing is overlooked. The PBS for ground systems at the Kennedy Space Center is being developed to encompass the traditional requirements including the alignment of facility, systems, and components to the organizational hierarchy. The Ground Operations Product Breakdown Structure is a hybrid in nature in that some aspects of a work breakdown structure will be incorporated and merged with the Architecture Concept of Operations, Master Subsystem List, customer interface, and assigned management responsibility. The Ground Operations Product Breakdown Structure needs to be able to identify the flexibility of support differing customers (internal and external) usage of ground support equipment within the Kennedy Space Center launch and processing complex. The development of the Product Breakdown Structure is an iterative activity Initially documenting the organization hierarchy structure and relationships. The Product Breakdown Structure identifies the linkage between the customer program requirements, allocation of system resources, development of design goals, and identification logistics products. As the Product Breakdown Structure progresses the incorporation of the results of requirement planning for the customer occurs identifying facility needs and systems. The mature Product Breakdown Structure is baselined with a hierarchical drawing, the Product Breakdown Structure database, and an associated document identifying the verification of the data through the life cycle of the program/product line. This paper will document, demonstrate, and identify key aspects of the life cycle of a Hybrid Product Breakdown Structure. The purpose is to show how a project management and system engineering approach can be utilized for providing flexible customer service in an evolving manned space flight launch processing environment.

Monaghan, Mark W.↗

NASA NTRS2013

Development of Hybrid Product Breakdown Structure for NASA Ground Systems

Monaghan, Mark W.↗

NASA NTRS2016

Soil Moisture Active Passive Mission L4_SM Data Product Assessment (Version 2 Validated Release)

During the post-launch SMAP calibration and validation (Cal/Val) phase there are two objectives for each science data product team: 1) calibrate, verify, and improve the performance of the science algorithm, and 2) validate the accuracy of the science data product as specified in the science requirements and according to the Cal/Val schedule. This report provides an assessment of the SMAP Level 4 Surface and Root Zone Soil Moisture Passive (L4_SM) product specifically for the product's public Version 2 validated release scheduled for 29 April 2016. The assessment of the Version 2 L4_SM data product includes comparisons of SMAP L4_SM soil moisture estimates with in situ soil moisture observations from core validation sites and sparse networks. The assessment further includes a global evaluation of the internal diagnostics from the ensemble-based data assimilation system that is used to generate the L4_SM product. This evaluation focuses on the statistics of the observation-minus-forecast (O-F) residuals and the analysis increments. Together, the core validation site comparisons and the statistics of the assimilation diagnostics are considered primary validation methodologies for the L4_SM product. Comparisons against in situ measurements from regional-scale sparse networks are considered a secondary validation methodology because such in situ measurements are subject to up-scaling errors from the point-scale to the grid cell scale of the data product. Based on the limited set of core validation sites, the wide geographic range of the sparse network sites, and the global assessment of the assimilation diagnostics, the assessment presented here meets the criteria established by the Committee on Earth Observing Satellites for Stage 2 validation and supports the validated release of the data. An analysis of the time average surface and root zone soil moisture shows that the global pattern of arid and humid regions are captured by the L4_SM estimates. Results from the core validation site comparisons indicate that "Version 2" of the L4_SM data product meets the self-imposed L4_SM accuracy requirement, which is formulated in terms of the ubRMSE: the RMSE (Root Mean Square Error) after removal of the long-term mean difference. The overall ubRMSE of the 3-hourly L4_SM surface soil moisture at the 9 km scale is 0.035 cubic meters per cubic meter requirement. The corresponding ubRMSE for L4_SM root zone soil moisture is 0.024 cubic meters per cubic meter requirement. Both of these metrics are comfortably below the 0.04 cubic meters per cubic meter requirement. The L4_SM estimates are an improvement over estimates from a model-only SMAP Nature Run version 4 (NRv4), which demonstrates the beneficial impact of the SMAP brightness temperature data. L4_SM surface soil moisture estimates are consistently more skillful than NRv4 estimates, although not by a statistically significant margin. The lack of statistical significance is not surprising given the limited data record available to date. Root zone soil moisture estimates from L4_SM and NRv4 have similar skill. Results from comparisons of the L4_SM product to in situ measurements from nearly 400 sparse network sites corroborate the core validation site results. The instantaneous soil moisture and soil temperature analysis increments are within a reasonable range and result in spatially smooth soil moisture analyses. The O-F residuals exhibit only small biases on the order of 1-3 degrees Kelvin between the (re-scaled) SMAP brightness temperature observations and the L4_SM model forecast, which indicates that the assimilation system is largely unbiased. The spatially averaged time series standard deviation of the O-F residuals is 5.9 degrees Kelvin, which reduces to 4.0 degrees Kelvin for the observation-minus-analysis (O-A) residuals, reflecting the impact of the SMAP observations on the L4_SM system. Averaged globally, the time series standard deviation of the normalized O-F residuals is close to unity, which would suggest that the magnitude of the modeled errors approximately reflects that of the actual errors. The assessment report also notes several limitations of the "Version 2" L4_SM data product and science algorithm calibration that will be addressed in future releases. Regionally, the time series standard deviation of the normalized O-F residuals deviates considerably from unity, which indicates that the L4_SM assimilation algorithm either over- or under-estimates the actual errors that are present in the system. Planned improvements include revised land model parameters, revised error parameters for the land model and the assimilated SMAP observations, and revised surface meteorological forcing data for the operational period and underlying climatological data. Moreover, a refined analysis of the impact of SMAP observations will be facilitated by the construction of additional variants of the model-only reference data. Nevertheless, the “Version 2” validated release of the L4_SM product is sufficiently mature and of adequate quality for distribution to and use by the larger science and application communities.

SMAP L4_SM↗

NASA NTRS2016

Production of Peroxy Nitrates in Boreal Biomass Burning Plumes over Canada During the BORTAS Campaign

The observations collected during the BOReal forest fires on Tropospheric oxidants over the Atlantic using Aircraft and Satellites (BORTAS) campaign in summer 2011 over Canada are analysed to study the impact of forest fire emissions on the formation of ozone (O3 and total peroxy nitrates (sigma)PNs, (sigma)ROONO2. The suite of measurements on board the BAe-146 aircraft, deployed in this campaign, allows us to calculate the production of O3 and of (sigma)PNs, a long-lived NOx reservoir whose concentration is supposed to be impacted by biomass burning emissions.In fire plumes, profiles of carbon monoxide (CO), which is a well-established tracer of pyrogenic emission, show concentration enhancements that are in strong correspondence with a significant increase of concentrations of (sigma)PNs, where as minimal increase of the concentrations of O3 and NO2 is observed. The (sigma)PN and O3 productions have been calculated using the rate constants of the first- and second-order react Pions of volatile organic compound (VOC) oxidation. The (sigma)PN and O3 productions have also been quantified by 0-D model simulation based on the Master Chemical Mechanism. Both methods show that in fire plumes the average production of (sigma)PNs and O3 are greater than in the background plumes, but the increase of (sigma)PN production is more pronounced than the O3 production. The average (sigma)PN production in fire plumes is from 7 to 12 times greater than in the background, whereas the average O3 production in fire plumes is from 2 to 5 times greater than in the background. These results suggest that, at least for boreal forest fires and for the measurements recorded during the BORTAS campaign,fire emissions impact both the oxidized NOy and O3;but (1)(sigma)PN production is amplified significantly more thanO3 production and (2) in the forest fire plumes the ratio between the O3 production and the (sigma)PN production is lower than the ratio evaluated in the background air masses, thus confirming that the role played by the (sigma)PNs produced during biomass burning is significant in the O3 budget. The implication of these observations is that fire emissions in some cases, for example boreal forest fires and in the conditions reported here, may influence more long-lived precursors of O3than short-lived pollutants, which in turn can be transported and eventually diluted in a wide area.

biomass burning↗

NASA NTRS2017

Development and Assessment of the SMAP Enhanced Passive Soil Moisture Product

Launched in January 2015, the National Aeronautics and Space Administration (NASA) Soil Moisture Active Passive (SMAP) observatory was designed to provide frequent global mapping of high-resolution soil moisture and freeze-thaw state every two to three days using a radar and a radiometer operating at L-band frequencies. Despite a hardware mishap that rendered the radar inoperable shortly after launch, the radiometer continues to operate nominally, returning more than two years of science data that have helped to improve existing hydrological applications and foster new ones.Beginning in late 2016 the SMAP project launched a suite of new data products with the objective of recovering some high-resolution observation capability loss resulting from the radar malfunction. Among these new data products are the SMAP Enhanced Passive Soil Moisture Product that was released in December 2016, followed by the SMAPSentinel-1 Active-Passive Soil Moisture Product in April 2017.This article covers the development and assessment of the SMAP Level 2 Enhanced Passive Soil Moisture Product (L2_SM_P_E). The product distinguishes itself from the current SMAP Level 2 Passive Soil Moisture Product (L2_SM_P) in that the soil moisture retrieval is posted on a 9 km grid instead of a 36 km grid. This is made possible by first applying the Backus-Gilbert optimal interpolation technique to the antenna temperature (TA) data in the original SMAP Level 1B Brightness Temperature Product to take advantage of the overlapped radiometer footprints on orbit. The resulting interpolated TA data then go through various correctioncalibration procedures to become the SMAP Level 1C Enhanced Brightness Temperature Product (L1C_TB_E). The L1C_TB_E product, posted on a 9 km grid, is then used as the primary input to the current operational SMAP baseline soil moisture retrieval algorithm to produce L2_SM_P_E as the final output. Images of the new product reveal enhanced visual features that are not apparent in the standard product. Based on in situ data from core validation sites and sparse networks representing different seasons and biomes all over the world, comparisons between L2_SM_P_E and in situ data were performed for the duration of April 1, 2015 October 30, 2016. It was found that the performance of the enhanced 9 km L2_SM_P_E is equivalent to that of the standard 36 km L2_SM_P, attaining a retrieval uncertainty below 0.040 m(exp 3)/m(exp 3) unbiased root-mean-square error (ubRMSE) and a correlation coefficient above 0.800. This assessment also affirmed that the Single Channel Algorithm using the V-polarized TB channel (SCA-V) delivered the best retrieval performance among the various algorithms implemented for L2_SM_P_E, a result similar to a previous assessment for L2_SM_P.

Enhanced↗

DOE OSTI2023

Chemical looping combustion oxygen carrier production cost study

The objective of this study was to estimate the cost of commercial production of oxygen carriers (OCs) for large-scale application in a mature, chemical looping combustion (CLC) power generation industry. Estimates of cost were made for two production facility scenarios: 1) build and operate an on-site, OC production facility located at a 550 MW CLC power plant site; and 2) build and operate a central production facility to produce and distribute OCs to the U.S. CLC power generation industry. Two OC production techniques were addressed: mechanical mixing and co-precipitation. Representative OCs that have production raw materials with sufficient commercial availability to support a CLC industry are ilmenite, a natural OC, and four engineered OC types, Fe 2 O 3 -based, CuO-based, NiO-based, and CuFeAlO 4 -based, with candidate OC support materials Al 2 O 3 and TiO 2 . The costs of the OC production raw materials represent the major portion of the OC product cost; the OC production cost, in dollars per kg, has been found to be nearly a linear function of the OC raw materials cost, in dollars per kg. In conclusion, the estimated OC product costs can be used to estimate the maximum OC loss rate yielding a designated CLC power plant cost-of-electricity (COE) target as a development guide, and it has been found that the maximum OC makeup rate, in kg per hour, achieving a designated COE reduction goal relative to a conventional pulverized coal (PC) power plant, will be nearly inversely proportional to the OC production raw materials cost, in dollars per kg.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2021

A Statistical Evaluation of Combining Human Productivity Metrics in the Indoor Environment

The potential of improving human productivity by providing healthy indoor environments has been a consistent interest in the building field for decades. This research field's long-standing challenge is to measure human productivity given the complex nature of office work. Previous studies have diversified productivity metrics, allowing greater flexibility in collecting human data; however, this diversity complicates the ability to combine productivity metrics from disparate studies within a meta-analysis. This study aims to categorize existing productivity metrics and statistically assess which categories show similar behavior when used to measure the impacts of indoor environmental quality. The 106 productivity metrics compiled were grouped into six productivity metric categories: neurobehavioral speed, accuracy, neurobehavioral response time, call handling time, self-reported productivity, and performance score. Then, this study set neurobehavioral speed as the baseline category given its fitness to the efficiency-based definition of productivity (i.e., output versus input) and conducted three statistical analyses with the other categories to evaluate their similarity. As results, the categories of neurobehavioral response time, self-reported productivity, and call handling time were found to have statistical similarity with neurobehavioral speed. This study contributes to creating a constructive research environment for future meta-analyses to understand which human productivity metrics can be combined with each other.

32 ENERGY CONSERVATION, CONSUMPTION, AND UTILIZATI↗

DOE OSTI2022

Assessing the Potential Impact of River Chemistry on Arctic Coastal Production

The Arctic coastal margin receives a disproportionately large fraction of the global river discharge. The bio-geochemistry of the river water as it empties into the marine environment reflects inputs and processes that occur as the water travels from its headwaters. Climate-induced changes to Arctic vegetation and permafrost melt may impact river chemistry. Understanding the impact of river nutrients on coastal marine production, and how this may change in the future, are important for resource managers and community members who monitor and rely on coastal food resources. Using the Energy Exascale Earth System Model we explore the impact of timing and river nutrient concentrations on primary production in each coastal Arctic region and then assess how this influences secondary production and particle fluxes supporting the benthic food web. Our results indicate that while the concentration of Arctic river nitrogen can have a significant impact on annual average nitrogen and primary production in the coastal Arctic, with production increases of up to 20% in the river influenced interior Seas, the timing of the river nutrient inputs into the marine environment appears less important. Bloom timing and partitioning between small and large phytoplankton were minimally impacted by both river nutrient concentration and timing, suggesting that in general, coastal Arctic ecosystem dynamics will continue to be primarily driven by light availability, rather than nutrients. Under a doubling river nutrient scenario, the percentage increase in the POC flux to the benthos on river influenced Arctic coastal shelves was 2-4 times the percentage increase in primary production, suggesting changes to the river nutrient concentration has the potential to modify the Arctic food web structure and dynamics. Generally, the nutrient-induced changes to primary production were smaller than changes previously simulated in response to ice reduction and temperature increase. However, in the Laptev Sea, the production increase resulting from a doubling of river nutrients exceeded the production increase simulated with an atmospheric warming scenario. Dissolved organic carbon is presently poorly represented in the model so its impact on production is hard to simulate. Applying established relationships between modeled DOC, total DOC, and light absorption we illustrate that DOC could play a very important role in modulating production. Our findings highlight the importance of developing more realistic river nutrient and discharge forcing for Earth System Models such that their impact on the critical Arctic coastal domain can be more adequately resolved.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2020

Evaluation of long-term Northern Hemisphere snow water equivalent products

Nine gridded Northern Hemisphere snow water equivalent (SWE) products were evaluated as part of the European Space Agency (ESA) Satellite Snow Product Intercomparison and Evaluation Exercise (SnowPEx). Three categories of datasets were assessed: (1) those utilizing some form of reanalysis (the NASA Global Land Data Assimilation System version 2 – GLDAS-2; the European Centre for Medium-Range Weather Forecasts (ECMWF) interim land surface reanalysis – ERA-Interim/Land and ERA5; the NASA Modern-Era Retrospective Analysis for Research and Applications version 1 (MERRA) and version 2 (MERRA-2); the Crocus snow model driven by ERA-Interim meteorology – Crocus); (2) passive microwave remote sensing combined with daily surface snow depth observations (ESA GlobSnow v2.0); and (3) stand-alone passive microwave retrievals (NASA AMSR-E SWE versions 1.0 and 2.0) which do not utilize surface snow observations. Evaluation included validation against independent snow course measurements from Russia, Finland, and Canada and product intercomparison through the calculation of spatial and temporal correlations in SWE anomalies. The stand-alone passive microwave SWE products (AMSR-E v1.0 and v2.0 SWE) exhibit low spatial and temporal correlations to other products and RMSE nearly double the best performing product. Constraining passive microwave retrievals with surface observations (GlobSnow) provides performance comparable to the reanalysis-based products; RMSE over Finland and Russia for all but the AMSR-E products is ∼50 mm or less, with the exception of ERA-Interim/Land over Russia. Using a seven-dataset ensemble that excluded the stand-alone passive microwave products reduced the RMSE by 10 mm (20 %) and increased the correlation from 0.67 to 0.78 compared to any individual product. The overall performance of the best multiproduct combinations is still at the margins of acceptable uncertainty for scientific and operational requirements; only through combined and integrated improvements in remote sensing, modeling, and observations will real progress in SWE product development be achieved.

Northern Hemisphere snow water equivalent (SWE) pr↗

DOE OSTI2023

Resource Characterization to Estimate Potential for Electricity Co-Production at Blackburn Oil Field, Nevada

The U.S. Department of Energy estimates that an annual average of 25 billion barrels of hot water are produced from oil and gas wells within the United States. The thermal energy available in the co-produced water stream is usually discarded, as the produced waters are considered an inconvenience by the operators and are disposed of using injection wells. However, utilizing organic Rankine cycle (ORC) generators, a vast amount of thermal energy can be captured and converted into electricity (albeit at relatively low efficiency due to the low temperatures). The National Renewable Energy Laboratory (NREL), in collaboration with Transitional Energy and Grant Canyon Oil & Gas, evaluated the feasibility of geothermal co-production of electricity by utilizing existing oil wells in Blackburn oil field in Nevada. The once prolific Blackburn oil field is located in Pine Valley, approximately 45 miles east-southeast of Elko, Nevada. Currently, the wells targeting the highly fractured Devonian Nevada dolomite reservoir are operating at a water cut ratio of more than 99%, with individual fluid (oil and water) production rates reaching 7.4 L/s (4,021 BBL/day). Analysis of publicly available data showed that the combination of the suitable wells' maximum historical production rates reached 22.90 L/s. The production from these wells occurs naturally and the wells are choked (and even shut down) by the operator to mitigate excessive water production, indicating a strong reservoir recharge and future opportunity to increase the water production for geothermal electricity generation. The main goal of this study was to evaluate the productivity of the existing wells, the performance of the reservoir, the surface network, and the operational constraints in order to achieve 1 MWe of electricity production from the field's water production. Utilizing the GEOPHIRES tool, we have determined that a twofold to threefold increase in the total fluid production, compared to the historical production under artificial restraint (choke), is required to reach a 1-MWe net target output for a low-temperature ORC system with air-cooled condensers. Lower flow rates would be required when utilizing water-based condensers instead of air-cooled condensers. However, that would require a constant supply of cold water, which may be challenging given the arid environment of the project site.

Blackburn↗

DOE OSTI2025

Functional but not taxonomic diversity increases productivity of Populus in the southeastern United States

Plant interactions like competition and facilitation impact ecosystem function and resilience. Improving our understanding of the relationships between these interactions and community productivity has important implications for managers of production systems in forestry and agriculture as well as conservation science. Populus spp. are an excellent model system for exploring how inter‐ and intraspecific interactions impact ecosystem functions, such as productivity, in forest plantations. In this study, we compared aboveground productivity of six Populus clones from three different taxa grown in monoclonal and mixed‐clonal plots. The different mixture treatments were intended to experimentally test aboveground biomass response to contrasting levels of taxonomic diversity and functional diversity based on nitrogen use characteristics of Populus clones. We hypothesize that functional diversity would be more important than taxonomic diversity in increasing aboveground productivity of mixed‐clonal plantings compared to monocultures. In addition, a subset of treatments was carried out on additional sites representing a productivity gradient in order to determine if the relationship between biodiversity and productivity in these systems diminished at more productive sites as suggested by the stress‐gradient hypothesis. We found that functionally diverse mixtures of clones had greater yield of aboveground biomass than the average of their constituent monocultures, while more taxonomically diverse mixes of clones did not differ from the average of their constituent monocultures. However, when reestablished on sites with extremely high or low productivity, the best performing clone mixture also did not differ from the average of its constituent monocultures. Our results suggest that intimate clone mixtures of Populus have the potential to significantly increase productivity, but results vary by mixture and by site. To capitalize on positive biodiversity effects on yield in production systems, targeted mixtures based on divergent functional traits linked to different use and acquisition strategies for site‐specific limiting resources are most likely to be successful.

BEF↗

DOE OSTI2022

The Global LAnd Surface Satellite (GLASS) evapotranspiration product Version 5.0: Algorithm development and preliminary validation

An accurate estimation of spatially and temporally continuous global terrestrial evapotranspiration (ET) is essential in the assessment of surface energy, water and carbon cycles. The Global LAnd Surface Satellite (GLASS) ET product Version 4.0 (v4.0) based on the Bayesian model averaging (BMA) method was generated to estimate global terrestrial ET. However, certain uncertainty for the GLASS ET product v4.0 limits its application. In this study, we introduced the deep neural networks (DNN) merging framework to improve terrestrial ET estimation for GLASS ET product Version 5.0 (v5.0) generation by integrating five satellite-derived ET products [Moderate Resolution Imaging Spectroradiometer (MODIS) ET product (MOD16), Shuttleworth–Wallace dual-source ET product (SW), Priestley–Taylor-based ET product (PT-JPL), modified satellite-based Priestley–Taylor ET product (MS-PT) and simple hybrid ET product (SIM)]. We compared the performance of DNN method against other merging methods, including GLASS ET algorithm v4.0 (BMA), the gradient boosting regression tree (GBRT) method and the random forest (RF) method, based on 195 global eddy covariance (EC) flux towers covering observations from 2000 through 2015. Validations indicated that the DNN had the highest accuracy among four merging methods across different land cover types, yielding the highest average determination coefficients (R 2 , 0.62), root-mean-squared-error (RMSE, 24.1 W/m 2 ) and Kling–Gupta efficiency (KGE, 0.77) with a of 99% confidence interval. Compared with GLASS ET algorithm v4.0, the DNN improved on the R 2 by approximately 7% (p < 0.01) and the KGE by 10%. Based on the DNN, we then generated 8-day GLASS ET product v5.0 globally with a 1 km spatial resolution from 2001 to 2015 driven by GLASS vegetation and surface net radiation (R n ) datasets and Modern-Era Retrospective Analysis for Research and Applications, Version 2 (MERRA2) datasets. Finally, this global terrestrial ET product provides a valuable dataset for monitoring regional and global water resources and environmental changes.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Introduction of NADH-dependent nitrate assimilation in Synechococcus sp. PCC 7002 improves photosynthetic production of 2-methyl-1-butanol and isobutanol

Cyanobacteria hold promise for renewable chemical production due to their photosynthetic nature, but engineered strains frequently display poor production characteristics. These difficulties likely arise in part due to the distinctive photoautotrophic metabolism of cyanobacteria. Here, in this work, we apply a genome-scale metabolic model of the cyanobacteria Synechococus sp. PCC 7002 to identify strain designs accounting for this unique metabolism that are predicted to improve the production of various biofuel alcohols (e.g. 2-methyl-1-butanol, isobutanol, and 1-butanol) synthesized via an engineered biosynthesis pathway. Using the model, we identify that the introduction of a large, non-native NADH-demand into PCC 7002's metabolic network is predicted to enhance production of these alcohols by promoting NADH-generating reactions upstream of the production pathways. To test this, we construct strains of PCC 7002 that utilize a heterologous, NADH-dependent nitrite reductase in place of the native, ferredoxin-dependent enzyme to create an NADH-demand in the cells when grown on nitrate-containing media. We find that photosynthetic production of both isobutanol and 2-methyl-1-butanol is significantly improved in the engineered strain background relative to that in a wild-type background. We additionally identify that the use of high-nutrient media leads to a substantial prolongment of the production curve in our alcohol production strains. The metabolic engineering strategy identified and tested in this work presents a novel approach to engineer cyanobacterial production strains that takes advantage of a unique aspect of their metabolism and serves as a basis on which to further develop strains with improved production of these alcohols and related products.

2-methyl-1-butanol↗