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At least 307 records · Page 17

Subsurface Biogeochemical Research: Watershed System Science for Energy

The Subsurface Biogeochemical Research (SBR) program within the U.S. Department of Energy’s (DOE) Office of Biological and Environmental Research is strategically aligned with DOE’s mission to ensure U.S. security and prosperity through watershed system science. Water resources critical for energy production are under pressure from growing water demand, contamination, drought, flooding, and saltwater intrusion. Sustainable management of watershed systems and their coupling with the built environment rely on understanding the hydrological and biogeochemical processes that control watershed system dynamics and water availability and quality. Next-generation science-based models of watershed systems are needed to address many U.S. energy and environmental challenges, including contaminant cleanup, clean water availability, safe storage of energy and nuclear byproducts in the subsurface, nutrient availability for sustainable biofuel crops, and recovery of subsurface energy resources.

09 BIOMASS FUELS↗

Design and scale-up of 3D printed bat houses with biomass-derived polymer composites

Biomass (e.g., pine sawdust, especially high–ash content pine sawdust) is commonly disposed of as waste. Combining biomass with polymers to make composite feedstocks for 3D printing has been explored as a method to reduce or repurpose the biomass waste. Although not all biocomposite properties are known, the wood-based polylactic acid (PLA) composite has promising qualities for applications in ecological settings. In this work, pine wood–PLA composite feedstock was used to 3D print supplemental roost structures for endangered tree-roosting bats, which often face a paucity of suitable naturally occurring roosts. This material combination was selected because it is estimated to degrade faster than the synthetic material systems that are used widely in supplemental bat roosting structures to aid in the conservation of tree roosting bats. The layered, rough surface created by the 3D printing process serves as a surface that bats can grip while roosting. Computer-aided design (CAD) models were generated based on natural roost structures, and a full-size bat house was successfully additively manufactured using a pellet-fed large-scale 3D printing system. The 3D printed hexagon exhibited a tensile strength of 22–23 MPa and a Young’s modulus of 3202–3218 MPa in the x-direction. It has been demonstrated that the 3D printed bat house can be installed on a tree in a stable fashion. This successful demonstration of a bat roost manufactured using a bioderived composite should promote its use in other fish and wildlife structures and broader industrial applications such as construction and automobiles.

3D printing↗

Interannual fires as a source for subarctic summer decadal climate variability mediated by permafrost thawing

Climate model simulations run under the Coupled Model Intercomparison Project Phase 6 (CMIP6) use an inhomogeneous biomass burning aerosol (BBA) emission dataset, which exhibits pronounced interannual variability from 1997–2014 due to the infusion of satellite data. Using the Community Earth System Model version 2 Large Ensemble (CESM2-LE) with original and smoothed CMIP6 BBA forcings, we show that the CMIP6 data inhomogeneity causes spurious decadal subarctic land warming. During years with reduced aerosol concentrations, increased solar radiation can trigger abrupt subarctic permafrost thawing, increased soil water drainage, upper soil drying, and subsequent surface warming. This slow process, which is further amplified by nonlinear cloud-aerosol interactions, cannot be completely offset during years of increased aerosol fluxes, thereby reddening surface temperature spectra in response to large-amplitude interannual aerosol forcing. More generally, our CESM2 experiments identify a pathway for generating decadal variability in high latitudes, involving interannual shortwave forcing and slow nonlinear soil responses.

54 ENVIRONMENTAL SCIENCES↗

An Open-Source Framework for the Computational Analysis and Design of Autothermal Chemical Processes

The main project object was to develop software tools for simulating non-equilibrium autothermal processes, improving the prospects for identifying and designing such systems. The project demonstrates the use of these tools to simulate autothermal pyrolysis, a process recently developed at the pilot-plant scale at Iowa State University. In such process, instead of externally heating a reactor to pro-vide the enthalpy of pyrolysis, sufficient oxygen in the form of air is introduced into the reactor to support partial oxidation of reactants and products with the exothermic energy released supporting endothermic pyrolysis reactions. A fluidized bed is used to assure good mixing of biomass and oxidant and provide an isothermal reaction environment. The amount of oxygen required depends upon the kind of biomass being pyrolyzed and parasitic heat losses from the reactor. For example, for woody biomass pyrolyzed under conditions that simulate adiabatic operation, equivalence ratios can be as low as 0.06, compared to 0.20 or higher for autothermal gasifiers. By removing the heat transfer bottleneck of conventional pyrolysis, operation in autothermal mode allowed a significant increase in reactor throughput process, approaching five times the throughput of the conventionally operated pyrolyzer. Different simulation strategies were considered and developed: a zero-dimensional chemistry model was used to verify the applicability of kinetic schemes to predict biomass fast pyrolysis in autothermal conditions. Conventional chemical reactor models such as the plug flow reactor and the partially stirred reactor were used to investigate the role of mixing in the fluidized bed pyrolyzer and to establish the impact of mixing time on the gas-phase reactions. A comprehensive multiphase computational fluid dynamics (mCFD) framework, including polydisperse granular phase modeling and detailed chemical kinetics was formulated and used to model the experimental setup for autothermal biomass fast pyrolysis at ISU. Multiphase CFD was also used to investigate the role of biomass feed positioning on the mixing of biomass in the pyrolizer. Finally, a reduced order model (ROM), suitable to be implemented in process simulators was obtained. Both the mCFD and the ROM were validated against experiments.

09 BIOMASS FUELS↗

Biomethanation to Upgrade Biogas to Pipeline Grade Methane

NREL is working closely with DOE, Electrochaea GmbH, and Southern California Gas Company (SoCalGas) to reduce costs of a biomethanation process capable of megawatt-scale deployment that upgrades organic biogas waste streams to produce pipeline quality renewable natural gas (RNG). Biomethanation is a two-step process using a single-celled methanogenic archaea that converts low-carbon low-cost hydrogen (H2) and waste carbon dioxide (CO2) to produce renewable methane (CH4). The process upgrades the biogenic CO2 - while allowing the CH4 to pass through - from biogas sources like dairies, wastewater treatment plants, and landfills. The CH4 produced is a drop-in direct replacement fuel and producers can participate in the growing number of carbon markets; like California's Low Carbon Fuel Standard and the Federal Renewable Fuel Standard. NREL and Argonne National Laboratory have completed a life cycle analysis using the GREET model to show that the biomethanation process produces RNG that is carbon negative even when H2 production via low-temperature water electrolysis is driven by the existing carbon intensity of California's electricity grid. And of course, even further carbon negative (-233 kg CO2e/kWh) when the electricity is produced from low-carbon sources like wind and solar. Leveraging lessons learned from operating SoCalGas' 700L 18-bar bioreactor system, NREL is designing and building a flexible RD&D platform that will enable field trials at biogas and other CO2 sources. A custom 16' long trailer will house a 20L 18-bar bioreactor, 3 - 25 kW proton exchange membrane electrolyzer, and dosing, thermal, and controls systems to support operations with only power, biogas, and water feedstocks required by the field locations. The end-of-project goal is to demonstrate pipeline quality RNG production (> 95% CH4, < 4% H2, <1% CO2, < 0.2% O2 and < 4 parts per million H2 sulfide) using real biogas feedstocks - thereby recycling both greenhouse gases for injection into the natural gas network or to be used onsite.

biogas upgrading↗

Tracking Aerosol Convection Interactions Experiment (TRACER) Field Campaign Report

Convective clouds serve a critical role in the Earth’s energy and water cycles through their transport of heat, moisture, momentum, and chemical species through the troposphere driving the global circulation (e.g., Hartmann et al. 1984, Del Genio et al. 2012, Su et al. 2014). On more local scales, convective clouds impact the atmospheric heating profile through diabatic heating effects, removal of water from the atmospheric column through precipitation, and conditioning of the local environment impacting further development of clouds (e.g., Sullivan and Voigt 2021). These critical roles underscore the importance of realistic representation of convective processes across scales of models from large-eddy simulation (LES), to convection-permitting models (CPM; e.g., Kendon et al. 2020, Marinescu et al. 2021), to numerical weather prediction (NWP) models used for operational weather forecasting, to Earth system models used to predict climate sensitivity (Sanderson et al. 2011, Sherwood et al. 2014, Tomassini et al. 2014, Zhao et al. 2016, Cronin et al. 2017). A key component of improving model representation of convective clouds is better quantification and parameterization of updraft microphysics and dynamics, including their interactions with the surrounding environment and storm organization (Bony et al. 2015, Hagos and Houze 2016, Donner et al. 2016, Morrison et al. 2020). Aerosol is an important environmental factor that could affect convective clouds and precipitation since cloud droplet and ice formation processes are initiated by it. Andrae et al. (2004) hypothesized that aerosols associated with increased biomass burning particles acting as cloud condensation nuclei (CCN) result in smaller and more monodisperse cloud droplets leading to suppression of warm rain formation, ultimately leading to more cloud water being lofted above the freezing level based on observations in the Amazon region. The subsequent increase in latent heat release increases the buoyancy of rising convective parcels invigorating the deep convection. This work was followed by a description of the theoretical basis for this “cold-phase invigoration” by Rosenfeld et al. (2008), who argued that it could have a significant effect for deep convective clouds with warm cloud-bases. Several modeling studies (e.g., Khain et al. 2005, 2009, van den Heever et al. 2006, Fan et al. 2007, 2009, 2012, Lee et al. 2008, Storer et al. 2010, Lebo et al. 2012, Storer and van den Heever 2013, Chen et al. 2020, Dagan et al. 2022) have investigated these aerosol-convection interactions and the environmental factors that influence their relative importance and magnitude. More recently, several studies have indicated that “warm-phase invigoration”, the enhancement of convection through condensational heating, also appears to play a role in enhancing both shallow cumuli (Seiki and Nakajima 2014, Saleeby et al 2015) and deeper tropical convection (Lebo and Seinfeld 2011, Khain et al. 2012, Sheffield et al 2015, Fan et al. 2018, Igel and van den Heever 2021), as well as Houston thunderstorms (Fan et al. 2007, 2020). However, still other studies have provided additional evidence of systematic biases in simulated convective outflow ice size distribution properties, which are consistent with a lack of poorly understood secondary ice production within convective updrafts (e.g., Fridlind et al. 2017). To help address these critical gaps in our understanding of cloud processes, aerosol processes and aerosol-cloud interactions, the Tracking Aerosol Convection Interactions Experiment was designed building upon efforts by the Aerosol, Cloud, Precipitation and Climate (ACPC) Initiative (http://acpcintiative.org/), a joint effort of the International Geosphere-Biosphere Programme (IGBP) and the World Climate Research Program (WCRP) that focused on resolving uncertainties in the interactions between aerosol and clouds towards better understanding the role that these interactions play in the climate system. The TRACER campaign was motivated by recommendations from a number of pilot studies undertaken by ACPC (van den Heever et al. 2017, Fridlind et al. 2019, Hu et al. 2019, Fan et al. 2020, Marinescu et al. 2021, Hernandez-Deckers et al. 2022) that pointed towards the southeastern Texas region as a locale where aerosol-convection interactions could be studied owing to the copious occurrence of isolated convection during the summer months accompanied by diverse and significant sources of aerosols from both anthropogenic and natural sources. The TRACER campaign began on 01 October 2021 and extended through 30 September 2022 with an intensive operational period (IOP) during June-September 2022. Three main sites (Table 1) were managed by the U.S. Department of Energy (DOE) Atmospheric Radiation Measurement (ARM) user facility.

54 ENVIRONMENTAL SCIENCES↗

Integration of LIBS with Machine Learning for Real-Time Monitoring of Feedstock in H 2 Gasification Applications

This project, funded by the U.S. Department of Energy (DOE) – Office of Fossil Energy under Award Number DE-FE0032177, aimed to assess the feasibility of an integrated Laser-Induced Breakdown Spectroscopy (LIBS) system with advanced machine learning (ML) models for real-time characterization and potential control of hydrogen gasifiers running on waste materials as feedstocks. This was a multidisciplinary effort that encompassed the acquisition and standardized analysis of individual and blended feedstocks—comprising biomass, coal waste, and plastic waste, followed by the development of a dynamic LIBS bench system for material sample analysis and development of predictive ML models. Comprehensive laboratory testing enabled the creation of a robust elemental dataset that served as the foundation for ML model training. Techniques such as Random Forest, Gradient Boosting, Support Vector Regression, and Neural Networks were employed to predict key feedstock properties, including higher heating value (HHV), moisture content, thermal conductivity, and ash composition with high accuracy. The results were validated against experimental data and demonstrated strong potential for real-time application in gasifier control systems. The project concluded with a study on the integration of the LIBS+ML approach for gasifier control and a techno-economic analysis of the implementation of the approach into hydrogen (H 2 ) gasification systems. Dissemination of results was carried out at a DOE meeting. This work establishes a scalable framework for automated, in-line feedstock quality assessment, offering significant implications for process optimization and emissions reduction in hydrogen production.

01 COAL, LIGNITE, AND PEAT↗

Carbon Capture Design and Costing: Phase 2 (C3DC2) (Final Project Report)

ION Clean Energy’s (ION) advanced solvent is one of the leading solvent systems currently under development for post-combustion carbon dioxide (CO 2 ) capture. ION has partnered with Nebraska Power Public District (NPPD), Sargent & Lundy, Koch Modular Process Systems, and Siemens to design a commercial-scale (700 MW) capture system utilizing ION’s advanced solvent, ICE-21, retrofitted onto NPPD’s Gerald Gentleman Station in Sutherland, Nebraska, USA. The capture system was designed to take full advantage of the solvent benefits including an efficient physical plant layout, reduced energy requirements, less solvent degradation, lower emissions, and lower capital costs relative to systems built with DOE BBS case benchmark solvents. This Front-End Engineering Design (FEED) study also included an investigation of utilizing biomass co-combustion with the aim of reaching near-zero emissions for this coal-fired power generating unit. The targeted biomass was from local resources in Nebraska tied to the production of ethanol.

01 COAL, LIGNITE, AND PEAT↗

A primer on forest structure measurement with lidar for ecologists

Light detection and ranging (lidar) technology has fundamentally advanced the way we measure forest structure, facilitating new insights into ecological processes. Lidar for forest ecology applications is deployed on multiple types of platforms that operate from the ground, air, or space, and each has associated strengths and limitations. Ideally, the choice of what kind of lidar to use in a particular study should be guided by the ecological question of interest; however, practical considerations of cost, data availability, and processing tools can be equally important. This synthesis is a practical introduction to how different lidar platforms characterize forest structure (e.g., tree size/location, wood volume, branching structure, aboveground biomass, leaf properties), designed for a general audience of ecologists (not remote sensing scientists) seeking an accessible introduction to the use of lidar. We also provide examples of novel ecological insights from recent lidar research and describe current limitations and areas of expected improvement. Last, we include an appendix of data collected from terrestrial, mobile, unoccupied aerial system, airplane, and satellite lidar platforms within a common temperate forest area, with associated code to allow new lidar users to visualize and manipulate data in R.

Cushman, KC [ORNL] (ORCID:0000000234641151)↗

Development of spirulina for the manufacture and oral delivery of protein therapeutics

The use of the edible photosynthetic cyanobacterium Arthrospira platensis (spirulina) as a biomanufacturing platform has been limited by a lack of genetic tools. Here we report genetic engineering methods for stable, high-level expression of bioactive proteins in spirulina, including large-scale, indoor cultivation and downstream processing methods. Following targeted integration of exogenous genes into the spirulina chromosome (chr), encoded protein biopharmaceuticals can represent as much as 15% of total biomass, require no purification before oral delivery and are stable without refrigeration and protected during gastric transit when encapsulated within dry spirulina. Oral delivery of a spirulina-expressed antibody targeting campylobacter—a major cause of infant mortality in the developing world—prevents disease in mice, and a phase 1 clinical trial demonstrated safety for human administration. Spirulina provides an advantageous system for the manufacture of orally delivered therapeutic proteins by combining the safety of a food-based production host with the accessible genetic manipulation and high productivity of microbial platforms.

59 BASIC BIOLOGICAL SCIENCES↗

Production and Catalytic Upgrading of 2,3-Butanediol Fermentation Broth into Sustainable Aviation Fuel Blendstock and Fuel Properties Measurement

With the increasing demand for sustainable supplies of aviation fuel and need to address climate change, new conversion technologies are needed to efficiently process biomass, produce high quality jet fuel blendstock, and meet carbon emission targets. This study demonstrates the synthesis, conditioning, and catalytic upgrading of 2,3-butanediol (BDO) fermentation broth into a jet fuel blendstock candidate. A high-titer 2,3-BDO fermentation broth (i.e., ~90 g/L) was produced at a 100-L scale and pretreated via nanofiltration to decrease the impurities level in the broth from 4.6 to 0.6 wt%. A novel process for catalytic upgrading of aqueous 2,3-BDO into a jet fuel blendstock candidate was developed, and each step was efficiently demonstrated. The catalytic steps include 1) 2,3-BDO dehydration into methyl ethyl ketone (MEK) over AlPO4, 2) MEK conversion into olefins over Zn1Zr10Ox, 3) oligomerization of olefins over a zeolite beta, and 4) hydrogenation over platinum/carbon. Both the model feed and real 2,3-BDO fermentation broth were tested for upgrading 2,3-BDO to MEK. With the real feed, a continuous loss of conversion (i.e., >50% loss over ~140 h time-on-stream [TOS]) was partly attributed to reversible deactivation from coking species. However, the conversion remained stable with the model feed, which demonstrates the efficiency of the first step for converting aqueous 2,3-BDO (10 wt% in water). For upgrading MEK to olefins, high selectivity to olefins (i.e., 82.5%) was obtained at high conversion levels (i.e., 93-98%) with stable conditions being achieved for > 70-hours TOS. Oligomerization of light olefins, which was demonstrated for > 270 h TOS, mainly led to the formation of dimers (C8-10) and trimers (C13-14). The oligomerized product was hydrogenated and distilled to recover the jet fraction (35 mass% or 40.9% carbon based yield), which consists mostly of desired isoalkanes (31.7 wt%), n-alkanes (24.5 wt%), and cycloalkanes (29.6 wt%). While some improvement is still needed to meet ASTM D7566 specifications for viscosity and final boiling point temperature, freezing point, density, aromatics content, and sulfur content of the jet blendstock candidate were within acceptable ranges, thus highlighting the potential of this process for production of jet fuel blendstock.

ADVANCED PROPULSION SYSTEMS,BIOMASS FUELS↗

Life Cycle Analysis of Electrofuels: Fischer–Tropsch Fuel Production from Hydrogen and Corn Ethanol Byproduct CO 2

Electrofuels from renewable H 2 and waste CO 2 streams are of increasing interest because of their CO 2 emissions reduction potentials compared to fossil counterparts. This study evaluated the well-to-wheel (WTW) greenhouse gas (GHG) emissions of Fischer-Tropsch (FT) fuels from various electrolytic H 2 pathways and CO 2 sources, using various process designs (i.e., with and without H 2 recycle) and system boundaries. Two systems with different boundaries were considered: a stand-alone plant (with CO 2 from any source) and an integrated plant with corn ethanol production (supplying CO 2 ). The FT fuel synthesis process was modeled using Aspen Plus, which showed that 45% of the carbon in CO 2 can be fixed in the FT fuel, with a fuel production energy efficiency of 58%. Using nuclear or solar/wind electricity, the stand-alone FT fuel production from various plant designs can reduce WTW GHG emissions by 90-108%, relative to petroleum fuels. When integrating the FT fuel production process with corn ethanol production, the WTW GHG emissions of FT fuels are 57-65% lower compared to petroleum counterparts. This study highlights the sensitivity of the carbon intensity of FT fuels to the system boundary selection (i.e., stand-alone vs integrated), which has different implications under various GHG emission credit frameworks.

08 HYDROGEN↗

Recent Cryogenic Carbon Capture™ Field Test Results

Sustainable Energy Solutions (SES) has been developing Cryogenic Carbon Capture™ (CCC) since 2008. In that time, two processes have been developed, the External Cooling Loop and Compressed Flue Gas CCC processes (CCC-ECL and CCC-CFG, respectively). The CCC-ECL process cools the flue gas with an external refrigerant loop. This process currently captures up to 1 tonne of CO2 per day (TPD). SES has tested CCC-ECL on real flue gas slip streams from subbituminous coal, bituminous coal, biomass, natural gas, shredded tires, and municipal waste fuels at field sites that include utility power stations, heating plants, cement kilns, and pilot-scale research reactors. The CO2 concentrations from these tests ranged from 5 to 22% on a dry basis. CO2 capture ranged from 95-99+% during these tests. Several other condensable species were also captured including NO2, SO2 and PMxx at 95+%. NO was also captured at a modest rate. The CCC-CFG process has been scaled up to a 0.25 ton per day system. This system has been tested on real flue gas streams including subbituminous coal, bituminous coal, and natural gas at field sites that include utility power stations, heating plants, and pilot-scale research reactors. CO2 concentrations for these tests ranged from 5 to 15% on a dry basis. CO2 capture ranged from 95-99+% during these tests. Several other condensable species were also captured including NO2, SO2, and PMxx at 95+%. NO was also captured at 90+%. Hg capture was also verified and the resulting effluent from CCC-CFG was below a 1ppt concentration. This paper will focus on discussion of the capabilities of CCC generally, the results of CCC-ECL field testing, and future steps surrounding the development of this technology. Test results that will be presented have been collected during 9 months of testing at a commercial power plant under funding from the US Department of Energy (DOE) and the host utility. Testing of one of the systems at a commercial cement plant in the United States will also be discussed. During this testing, the system captured CO2 from the cement plant and stored the CO2 in pressurized tanks. These tanks were provided to a partner company that later used the CO2 in a CO2 utilization demonstration. The CO2 was utilized to cure concrete manufactured using cement from the same plant where the CO2 was captured. This integrated capture and utilization demonstration was the first time that the cement industry has shown in the field that it can sequester its CO2 emissions in its main product stream. This represents a potential game changing solution for industrial CO2 emissions. Operational data and host-site feedback indicate that the CCC process is ideally suited for deployment into a variety of commercial environments. A few areas of de-risking remain to make sure the technology can meet very strict industrial reliability standards. These areas of de-risking are identified and discussed. The product CO2 is shown to meet specification for many uses including industrial and merchant applications. The technology is nearing readiness for deployment at commercial scale and several initial target markets have been identified.

20 FOSSIL-FUELED POWER PLANTS↗

Prioritization of Early-Stage Research and Development of a Hydrogel-Encapsulated Anaerobic Technology for Distributed Treatment of High Strength Organic Wastewater

This study aims to support the prioritization of research and development (R&D) pathways of an anaerobic technology leveraging hydrogel-encapsulated biomass to treat high-strength organic industrial wastewaters, enabling decentralized energy recovery and treatment to reduce organic loading on centralized treatment facilities. To characterize the sustainability implications of early-stage design decisions and to delineate R&D targets, an encapsulated anaerobic process model was developed and coupled with design algorithms for integrated process simulation, techno-economic analysis, and life cycle assessment under uncertainty. Across the design space, a single-stage configuration with passive biogas collection was found to have the greatest potential for financial viability and the lowest life cycle carbon emission. Through robust uncertainty and sensitivity analyses, we found technology performance was driven by a handful of design and technological factors despite uncertainty surrounding many others. Hydraulic retention time and encapsulant volume were identified as the most impactful design decisions for the levelized cost and carbon intensity of chemical oxygen demand (COD) removal. Encapsulant longevity, a technological parameter, was the dominant driver of system sustainability and thus a clear R&D priority. Ultimately, we found encapsulated anaerobic systems with optimized fluidized bed design have significant potential to provide affordable, carbon-negative, and distributed COD removal from high strength organic wastewaters if encapsulant longevity can be maintained at 5 years or above.

Anaerobic Treatment↗

Harvesting Energy from Wastewater by Converting Sewage

This project aims were to develop and demonstrate a scalable, integrated process to convert sewage sludge into renewable natural gas (RNG), enabling wastewater treatment plants (WWTPs) to become net energy producers. The system proposal integrates autothermal hydrothermal liquefaction (AT-HTL), supercritical salt precipitation (SCSP), and hydrothermal gasification (HTG), collectively forming the Supercritical Sludge-to-Gas (SC-S2G) platform. Initially, batch hydrothermal liquefaction reactions were used to screen sewage sludge using AT-HTL (later termed RI-HTL) conversion to biocrude, aqueous and char phases compared to hydrothermal liquefaction (HTL). Significant improvement in biocrude yield using peroxide addition at O:C ratio of 0.05 and under conditions of 300°C for 10 minutes gave 57% biocrude yield and 85% fluid carbon yield (biocrude plus aqueous), while minimizing the loss of carbon to char solids (~7%). Hence, RI-HTL was shown to be effective for conversion of real sewage sludge. The corrosion of the alloy reactor tubes or vessels is an important factor when developing a process that includes an oxidant and a chemically complex feed like sewage sludge. We investigated the corrosion rates on metal alloys at 350°C for 240 hours. Corrosion rates of 0.21 and 0.26 mpy for 304L and 316L stainless steel were measured respectively. The corrosion information obtained in this investigation was utilized by PNNL for design, materials sourcing and construction of the pilot scale continuous flow system.

09 BIOMASS FUELS↗

Functional characterization of glycosyltransferases in duckweed to enable predictive biology

Glycosyltransferases (GTs) catalyze the formation of glycosidic linkages to produce almost all complex carbohydrates. This project used a multi-disciplinary, high-throughput (HTP) biochemical and computational biology approach focused on duckweed as a model energy crop, to study carbohydrate metabolic processes. To achieve this, developed and carried out out high-throughput (HTP) functional characterization of plant glycosyltransferases (GTs) role of enzymatic microenvironments be assessed through a combined proteomic and computational biology approach, and the combined data was used to populate deep-learning frameworks to predict plant GT function. Functional validation achieved through this research is being used to assign gene function and study plant processes at the systems level to efficiently link the genome sequence with gene function. Together, the combined approaches used within this study provide a foundation for how computational prediction, in combination with high-throughput functional validation, can be used to study plant processes at the systems level and translate knowledge gained to efficiently link genome sequence with gene function in a species agnostic manner.

09 BIOMASS FUELS↗

Regionalized Life-Cycle Water Impacts of Microalgal-Based Biofuels in the United States

While algal biofuels have the potential to reduce the national reliance on fossil fuels, high water consumption associated with algal biomass cultivation represents a major concern potentially compromising the sustainable commercialization of this technology. This study focuses on quantifying the water footprint (WF) and water scarcity footprint (WSF) of renewable diesel derived from algal biomass and provides insights into where algal cultivation is less water-intensive than traditional ethanol and biodiesel feedstocks. Results are generated with an engineering process model developed to predict the life-cycle water consumption, considering green, blue, and gray water, of algae facilities across the United States at a high spatiotemporal resolution. The total WFs for Florida and Arizona are determined to be 13.1 and 17.6 m 3 GJ –1 , respectively. The blue WF in Arizona is shown to be 8.5 times larger than in Florida, while the green WF is 4.5 times smaller, but when combined into a total WF, there is just a 26% difference between the two locations. The analysis reveals that the total life-cycle WFs of algal renewable diesel are smaller than the optimal WFs of corn ethanol and soybean biodiesel. Algal systems benefit from higher growth rates and offer the opportunity to manage wastewater streams, therefore generating smaller green and gray WFs than those of conventional biofuels. Here, the WSF analysis identifies the Gulf Coast as the most suitable region for algal cultivation, with cultivation in the western US shown to exacerbate local water stress levels.

54 ENVIRONMENTAL SCIENCES↗

Spectroscopy-based isotopic (δ 13 C) analysis for high spatial resolution of carbon exchange in the rhizosphere

The rhizosphere is a highly dynamic zone bridging plant roots with needed nutrient resources in soil. While the rhizosphere may be small, it has a disproportionally large impact on plant success and biomass production. A suite of rhizosphere-hosted microbial and geochemical interactions facilitate nutrient acquisition by plant roots, and, in turn, the roots stimulate these processes by supplying organic carbon into the rhizosphere. The small physical dimensions of the rhizosphere, however, can constrain efforts to elucidate key carbon exchange processes and their spatial extent and localization. We present a method for spatially resolved δ 13 C analysis of rhizosphere samples by coupling laser ablation (LA) sampling with isotopic analysis using capillary absorption spectroscopy (CAS) which differs from conventional mass spectrometer (MS) approaches. The CAS system has high sensitivity (requires fewer nanomoles of CO 2 per analysis) than comparable MS systems, which enables reduced sample size requirements to thereby improve spatial resolution (from 25 μm to as low as a projected 5 μm spatial resolution). We demonstrate the utility of CAS using rhizosphere samples from switchgrass plants exposed to 13 CO 2 . As a result, this technique will provide a capability for tracking the extent and spatial distribution of root exudate into the rhizosphere at highly detailed spatial scales.

59 BASIC BIOLOGICAL SCIENCES↗