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Safety-Related Instrumentation & Control Pilot Upgrade Initiation Phase Implementation Report

This research report (1) describes the process followed and products developed during the SR I&C Pilot Project Initial Scoping Phase, and (2) captures lessons learned. Exelon Generation and LWRS collaborated to develop a Digital Transformation Strategy as part of a larger Advanced Concept of Operations. The proposed SR I&C Pilot Upgrade provides a foundation stone for this Digital Transformation that will improve plant safety, reliability, and operational performance while lowering plant Total Cost of Ownership (TCO). Initial Scoping Phase activities for this Pilot Project have been performed in accordance with industry processes that have been adapted to better support digital upgrades. These processes include IP-ENG-001, Standard Design Process (SDP) [Reference 2], NISP-EN-04, Standard Digital Engineering Process (SDEP) [Reference 3], and Electric Power Research Institute (EPRI) Report 3002011816, Digital Engineering Guide (DEG). Completing Initial Scoping Phase Engineering and Operations, Licensing, and Project Management Activities was necessary to sufficiently bound the scope, schedule, and estimated cost of the Project to enable utility management to authorize moving into the Conceptual Design Phase. A significant finding of the Business Case Analysis (BCA) methodology developed and applied as part of this effort was that the growth rate of material costs for sustaining the operation of obsolete SR I&C equipment is accelerating. This directly contributed to the Project Economic Analysis created to justify continuing the Project. Project Initial Scoping Phase lessons learned have also been captured to assist the larger industry in understanding the Digital Transformation Strategy and SR I&C Pilot Project Initial Scoping Phase efforts. This is in keeping with the public/private partnership that has been established between the Department of Energy (DOE) and Exelon for this effort with engagement from the NRC. By addressing first-of-a-kind (FOAK) risks and capturing lessons learned, the SR I&C Pilot Upgrade Project addresses technical, regulatory, and business risks to enable subsequent implementers of similar upgrades.

22 GENERAL STUDIES OF NUCLEAR REACTORS↗

Task 12 Sustainability - Methodological Guidelines on Net Energy Analysis of Photovoltaic Electricity (2nd Edition)

Net Energy Analysis (NEA) is a structured, comprehensive method of quantifying the extent to which a given energy source is able to provide a net energy gain (i.e., an energy surplus) to the end user, after accounting for all the energy losses occurring along the chain of processes that are required to exploit it (i.e., for its extraction, processing and transformation into a usable energy carrier, and delivery to the end user), as well as for all the additional energy 'investments' that are required in order to carry out the same chain of processes. However, this general framework leaves the individual practitioner with a range of choices that can affect the results and thus, the conclusions of a NEA study. The current IEA PVPS guidelines were developed to provide guidance on assuring consistency, balance, and quality to enhance the credibility and reliability of the results from photovoltaic (PV) NEAs. The guidelines represent a consensus among the authors - PV NEA experts in North America and Europe - for assumptions made on PV performance, process inputs and outputs, methods of analysis, and reporting of the results. Guidance is given on photovoltaic-specific parameters used as inputs in NEA and on choices and assumptions in inventory data analysis and on implementation of modelling approaches. A consistent approach towards system modelling, the functional unit, the system boundaries and allocation aspects enhance the credibility of PV electricity NEA studies and enables balanced NEA-based comparisons. Specifically, "apples-to-oranges" comparisons of different energy carriers (e.g., fuels vs. electricity) are not methodologically sound and are to be avoided in all cases; also, any comparison across renewable and non-renewable electricity generation technologies must clearly point out the intrinsically short-term nature of the NEA viewpoint, which does not capture the long-term sustainability implications of renewable vs. non-renewable primary energy harvesting and use: non-renewable primary energy resources are depleted and finally exhausted (irrespective of the size of the EROI), while renewable primary energy resources are not. This document provides an in-depth discussion of a common metric of NEA, namely the energy return on investment (EROI), and how this is to be interpreted vis-a-vis the deceptively similar-sounding metrics in the field of Life Cycle Assessment (LCA): cumulative energy demand (CED) and non-renewable cumulative energy demand (nr-CED) per unit output. Specifically, a number of key differences are highlighted between these metrics as applied to electricity production systems, which are listed in Table S-1.

14 SOLAR ENERGY↗

A Review and Outlook on Experimental Advances and Innovations in Geological CO 2 Storage: Insights from Depleted Gas Reservoirs and Saline Aquifers

Geological storage of carbon dioxide (CO 2 ) in depleted gas reservoirs and deep saline aquifers is a key part of global decarbonization efforts. As carbon capture and storage advances toward commercial-scale deployment, the credibility and scalability of laboratory experiments are increasingly vital for guiding safe and effective field implementation. This review offers a comprehensive, cross-scale evaluation of experimental methodologies, including core flooding, high-pressure, high-temperature systems, microfluidic visualization, and emerging systems such as multilayer commingled/compartmentalized core flooding, 3D-printed micromodels, and AI-powered digital twins. These innovations are demonstrated to enhance representativeness, reproducibility, and real-time insight, thereby addressing the limitations of conventional workflows. A critical analysis of methodological gaps, such as inconsistent pressure–temperature conditions, oversimplified brine chemistry, and a lack of standardization, reveals experimental sources of scale translation errors and performance uncertainty. By comparing the unique challenges of depleted gas reservoirs (such as low water saturation and legacy well leakage) to those of saline aquifers (including pressure buildup and caprock integrity), this review identifies formation-specific priorities for experimental design. Novel contributions include a synthesis of best practices, integration strategies for model calibration, and recommendations for standardizing core handling, saturation procedures, and reporting protocols. Furthermore, this work serves as a guide for developing robust, field-relevant experimental strategies that can increase the deployment and regulatory acceptance of CO 2 storage technologies at scale.

58 GEOSCIENCES↗

Ligand Control of Oxidation and Crystallographic Disorder in the Isolation of Hexavalent Uranium Mono-Oxo Complexes

Here, the development of high-valent transuranic chemistry requires robust methodologies to access and fully characterize reactive species. We have recently demonstrated that the reducing nature of imidophosphorane ligands supports the two-electron oxidation of U 4+ to U 6+ and established the use of this ligand to evaluate the inverse-trans-influence (ITI) in actinide metal-ligand multiple bond (MLMB) complexes. To extend this methodology and analysis to transuranic complexes, new small-scale synthetic strategies and lower-symmetry ligand derivatives are necessary to improve crys-tallinity and reduce crystallographic disorder. To this end, the synthesis of two new imidophosphorane ligands, [N=P t Bu(pip) 2 ]¯ (NPC 1 ) and [N=P t Bu(pyrr) 2 ]¯ (NPC 2 ) (pip = piperidinyl; pyrr = pyrrolidinyl) is presented, which break pseudo-C 3 axes in the tetravalent complexes, U[NPC 1 ] 4 and U[NPC 2 ] 4 . The reaction of these complexes with two-electron oxygen atom transfer reagents (N 2 O, trimethylamine N-oxide (TMAO) and 2,3:5,6-dibenzo-7-azabicyclo[2.2.1]hepta-2,5-diene (dbabhNO)) yields the U 6+ mono-oxo complexes U(O)[NPC 1 ] 4 and U(O)[NPC 2 ] 4 . This methodology is optimized for direct translation to transuranic elements. Of the two ligands, the NPC 2 framework is most suitable for facilitating detailed bonding analysis and assessment of the ITI. Theoretical evaluation of the U–(NPC) bonding confirms a substantial difference between axially and equatorially-bonded N atoms, revealing mark-edly more covalent U–N ax interactions. The U 6d+5f combined contribution for U–N ax is nearly double that of U–N eq , accounting for ITI shortening and increased bond order of the axial bond. Two distinct N-atom hybridizations in the pyrrolidine/piperidine rings are noted across the complexes, with approximate sp 2 and sp 3 configurations describing the slightly shorter P–N “planar” and slightly longer P–N “pyramidal” bonds, respectively. In all complexes, the NPC 2 ligands feature more planar N atoms than NPC 1 , in accordance with a higher electron-donating capacity of the former.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Consensus and Disagreement in Atmospheric River Detection: ARTMIP Global Catalogues

Atmospheric rivers (ARs) constitute an important mechanism for water vapor transport, but research on their characteristics and impacts has relied on a diverse assortment of detection methodologies, complicating comparisons. The AR Tracking Method Intercomparison Project (ARTMIP) provides a platform for comparing such methodologies, but analysis of ARTMIP catalogues has heretofore focused primarily on specific regions. Here we investigate ARs as detected by an ensemble of algorithms with global coverage. We find that the frequency of occurrence of the majority–consensus ARs produces a robust distribution, featuring five hot spots over the extratropical oceans, against which we compare individual algorithm results. We further explore the underlying similarities and differences via two case studies of AR evolution. The dominant source of disagreement between detection methodologies globally consists of detections (or lack thereof) of weak features, and the algorithms otherwise tend to agree remarkably well on the footprints of ARs.

54 ENVIRONMENTAL SCIENCES↗

Column separation of tetravalent cerium fission products from trivalent rare earth radio-isotopes

Rapid and efficient isolation of individual rare earth element (REE) radioisotopes from complex mixtures is necessary to support the fields of nuclear forensics, medical isotope production and nuclear physics measurements. The separations must be robust and generate sufficiently high purity samples for subsequent radiological analysis. Current methodologies utilize a laborious two step Ce(IV)-iodate precipitation followed by Ce(IV)-nitrate di-(2-ethylhexyl)phosphoric acid/n-heptane extraction. This work reports an alternative method to isolate Ce fission product isotopes equilibrated with milligrams of cold carrier, from the remaining REE’s using a Ce(IV)/LN-resin (Eichrom Technologies) based separation. Optimization of Ce(IV) loading, REE(III) elution volume and subsequent Ce(III) stripping step utilized 166m Ho tracer. Mixed fission product experiments provided a further test of this LN-resin method, with analysis of purified 141/144 Ce, 147 Nd and 91 Y. Overall, while decontamination factors were lower for the LN-resin method, (vs. the combined precipitation/extraction) the simplicity of the technique and the satisfactory fission product analysis results point to the efficacy of this method.

38 RADIATION CHEMISTRY, RADIOCHEMISTRY, AND NUCLEA↗

Low-Temperature Geothermal Play Fairway Analysis for the Denver Basin

This project is part of a national initiative to showcase the benefits of incorporating low-temperature geothermal resource assessment into the deployment of geothermal heating, combined heat and power (CHP), and geothermal direct-use (GDU) technologies. The initiative was established to accelerate the country's decarbonization efforts by identifying potential for low-temperature geothermal resource utilization (<150 degrees C, e.g., CHP and GDU) in selected sedimentary basins with numerous population centers. The play fairway analysis (PFA) methodologies in this study were adapted from previous PFA investigations of sedimentary basin geothermal play types (SBGPTs) that evaluated the potential for low-temperature resources (<150 degrees C). Workflows, relevant datasets, a new Python library, and common and composite geological criteria maps are utilized to develop low-temperature geothermal resource favorability maps for the Denver Basin, a sedimentary basin spanning Colorado, Nebraska, and Wyoming. The replication of these methodologies in other SBGPTs can evaluate potential for low-temperature resources. To facilitate future assessment of low-temperature geothermal resources in SBGPTs, this project provides PFA workflows, data, tools, and favorability maps that will ultimately support the utilization of low-temperature geothermal resources in sedimentary basins.

combined heat and power↗

Low-Temperature Geothermal Play Fairway Analysis for the Denver Basin: Preprint

This project is part of a national initiative to showcase the benefits of incorporating low-temperature geothermal resource assessment into the deployment of geothermal heating and cooling (GHC), combined heat and power (CHP), and geothermal direct use (GDU) technologies. The initiative was established to accelerate the country's decarbonization efforts by identifying potential for low-temperature geothermal resource utilization (< 150 Degrees Celsius, i.e., GHC, CHP, and GDU) in selected sedimentary basins with numerous population centers. The Play Fairway Analysis (PFA) methodologies in this study were adapted from previous PFA investigations of sedimentary basin geothermal play types (SBGPTs) that evaluated the potential for low-temperature resources (< 150 Degrees Celsius). Workflows, relevant datasets, python code, common and composite geological criteria maps are utilized to develop low-temperature geothermal resource favorability maps for the Denver Basin, a sedimentary basin spanning Colorado, Nebraska, and Wyoming. The replication of these methodologies in other SBGPTs can evaluate potential for low-temperature resources. To facilitate future assessment of low-temperature geothermal resources in SBGPTs, this project provides PFA workflows, data, tools, and favorability maps that will ultimately support the utilization of low-temperature geothermal resources in sedimentary basins.

Denver Basin↗

Dam-Break Flow Measurements of Liquid–Granular Mixtures in a Channelized Reservoir

Dam-break flows of granular materials exhibit a complex non-Newtonian rheology, which is strongly influenced by various factors, such as the characteristics of the granular material, the degree of initial compaction, and saturation level of the granular matrix. Specially adapted nonintrusive techniques are required to investigate these flows in the laboratory. This paper investigated the nonintrusive technique of image analysis. The methodologies used in the measurement of bulk flow parameters, such as flow depth, front velocity, and flow rate, and the extraction of detailed flow characteristics such as velocity profiles, were discussed in the context of a series of granular dam-break flow experiments. These experiments were performed under three types of initial conditions: dry, saturated (water filling the pore space), and submerged (a layer of saturated granular material submerged under water) using four types of granular materials—PET pellets, crushed walnut shells, urea, and sand—with grain sizes ranging from 200 μm to 2.9 mm. High-speed cameras were used to capture the evolution and local properties of the flow, such as velocity fields using particle image velocimetry (PIV). Bulk properties of the flow were obtained by tracking the surface profile of the granular matrix and the water table. The extracted profiles were used to measure the evolution of the volume of the granular matrix and the fluid phase separately upstream and downstream of the gate, which allowed measuring the dilatancy (increase in pore space). The study showed that the image analysis techniques are versatile and can be adapted to measure different flow parameters in a variety of granular flows to better understand and analyze their complex behavior. Finally, the advantages and drawbacks of each image analysis technique were discussed and best-practice recommendations were provided.

42 ENGINEERING↗

DEEPEN 3D PFA Weights for Exploration Datasets in Magmatic Environments

DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments. As part of the development of the DEEPEN 3D play fairway analysis (PFA) methodology for magmatic plays (conventional hydrothermal, superhot EGS, and supercritical), weights needed to be developed for use in the weighted sum of the different favorability index models produced from geoscientific exploration datasets. This GDR submission includes those weights. The weighting was done using two different approaches: one based on expert opinions, and one based on statistical learning. The weights are intended to describe how useful a particular exploration method is for imaging each component of each play type. They may be adjusted based on the characteristics of the resource under investigation, knowledge of the quality of the dataset, or simply to reduce the impact a single dataset has on the resulting outputs. Within the DEEPEN PFA, separate sets of weights are produced for each component of each play type, since exploration methods hold different levels of importance for detecting each play component, within each play type. The weights for conventional hydrothermal systems were based on the average of the normalized weights used in the DOE-funded PFA projects that were focused on magmatic plays. This decision was made because conventional hydrothermal plays are already well-studied and understood, and therefore it is logical to use existing weights where possible. In contrast, a true PFA has never been applied to superhot EGS or supercritical plays, meaning that exploration methods have never been weighted in terms of their utility in imaging the components of these plays. To produce weights for superhot EGS and supercritical plays, two different approaches were used: one based on expert opinion and the analytical hierarchy process (AHP), and another using a statistical approach based on principal component analysis (PCA). The weights are intended to provide standardized sets of weights for each play type in all magmatic geothermal systems. Two different approaches were used to investigate whether a more data-centric approach might allow new insights into the datasets, and also to analyze how different weighting approaches impact the outcomes. The expert/AHP approach involved using an online tool (https://bpmsg.com/ahp/) with built-in forms to make pairwise comparisons which are used to rank exploration methods against one-another. The inputs are then combined in a quantitative way, ultimately producing a set of consensus-based weights. To minimize the burden on each individual participant, the forms were completed in group discussions. While the group setting means that there is potential for some opinions to outweigh others, it also provides a venue for conversation to take place, in theory leading the group to a more robust consensus then what can be achieved on an individual basis. This exercise was done with two separate groups: one consisting of U.S.-based experts, and one consisting of Iceland-based experts in magmatic geothermal systems. The two sets of weights were then averaged to produce what we will from here on refer to as the "expert opinion-based weights," or "expert weights" for short. While expert opinions allow us to include more nuanced information in the weights, expert opinions are subject to human bias. Data-centric or statistical approaches help to overcome these potential human biases by focusing on and drawing conclusions from the data alone. More information on this approach along with the dataset used to produce the statistical weights may be found in the linked dataset below.

15 GEOTHERMAL ENERGY↗

DEEPEN Global Standardized Categorical Exploration Datasets for Magmatic Plays

DEEPEN stands for DE-risking Exploration of geothermal Plays in magmatic ENvironments. As part of the development of the DEEPEN 3D play fairway analysis (PFA) methodology for magmatic plays (conventional hydrothermal, superhot EGS, and supercritical), weights needed to be developed for use in the weighted sum of the different favorability index models produced from geoscientific exploration datasets. This was done using two different approaches: one based on expert opinions, and one based on statistical learning. This GDR submission includes the datasets used to produce the statistical learning-based weights. While expert opinions allow us to include more nuanced information in the weights, expert opinions are subject to human bias. Data-centric or statistical approaches help to overcome these potential human biases by focusing on and drawing conclusions from the data alone. The drawback is that, to apply these types of approaches, a dataset is needed. Therefore, we attempted to build comprehensive standardized datasets mapping anomalies in each exploration dataset to each component of each play. This data was gathered through a literature review focused on magmatic hydrothermal plays along with well-characterized areas where superhot or supercritical conditions are thought to exist. Datasets were assembled for all three play types, but the hydrothermal dataset is the least complete due to its relatively low priority. For each known or assumed resource, the dataset states what anomaly in each exploration dataset is associated with each component of the system. The data is only a semi-quantitative, where values are either high, medium, or low, relative to background levels. In addition, the dataset has significant gaps, as not every possible exploration dataset has been collected and analyzed at every known or suspected geothermal resource area, in the context of all possible play types. The following training sites were used to assemble this dataset: - Conventional magmatic hydrothermal: Akutan (from AK PFA), Oregon Cascades PFA, Glass Buttes OR, Mauna Kea (from HI PFA), Lanai (from HI PFA), Mt St Helens Shear Zone (from WA PFA), Wind River Valley (From WA PFA), Mount Baker (from WA PFA). - Superhot EGS: Newberry (EGS demonstration project), Coso (EGS demonstration project), Geysers (EGS demonstration project), Eastern Snake River Plain (EGS demonstration project), Utah FORGE, Larderello, Kakkonda, Taupo Volcanic Zone, Acoculco, Krafla. - Supercritical: Coso, Geysers, Salton Sea, Larderello, Los Humeros, Taupo Volcanic Zone, Krafla, Reyjanes, Hengill. **Disclaimer: Treat the supercritical fluid anomalies with skepticism. They are based on assumptions due to the general lack of confirmed supercritical fluid encounters and samples at the sites included in this dataset, at the time of assembling the dataset. The main assumption was that the supercritical fluid in a given geothermal system has shared properties with the hydrothermal fluid, which may not be the case in reality. Once the datasets were assembled, principal component analysis (PCA) was applied to each. PCA is an unsupervised statistical learning technique, meaning that labels are not required on the data, that summarized the directions of variance in the data. This approach was chosen because our labels are not certain, i.e., we do not know with 100% confidence that superhot resources exist at all the assumed positive areas. We also do not have data for any known non-geothermal areas, meaning that it would be challenging to apply a supervised learning technique. In order to generate weights from the PCA, an analysis of the PCA loading values was conducted. PCA loading values represent how much a feature is contributing to each principal component, and therefore the overall variance in the data.

15 GEOTHERMAL ENERGY↗

Cybersecurity Vulnerability Mitigation Framework through Empirical Paradigm: Enhanced Prioritized Gap Analysis

Existing cybersecurity vulnerability assessment tools were designed based on the policies and standards defined by organizations such as the U.S. Department of Energy and the National Institute of Standards and Technology (NIST). Frameworks such as the cybersecurity capability maturity model (C2M2) and the NIST Cybersecurity Framework (CSF) are often used by the critical infrastructure owners and operators to determine the cybersecurity maturity of their facility. Although these frameworks are exceptional at performing qualitative cybersecurity analysis and identifying vulnerabilities, they do not provide a means to perform prioritized mitigation of those vulnerabilities in order to achieve a desired cybersecurity maturity. To address that challenge, we developed a framework and software application called the cybersecurity vulnerability mitigation framework through empirical paradigm (CyFEr). This paper presents the detailed architecture of CyFEr’s enhanced prioritized gap analysis (EPGA) methodology and its application to CSF. The efficacy of the presented framework is demonstrated by comparing against existing similar models and testing against the cyber injects from a real-world cyber-attack that targeted industrial control systems (ICS) in critical infrastructures.

Gourisetti, Sri Nikhil G.↗

Assessment of coated cladding impact on large-break LOCA with TRACE-DAKOTA

Since 2011, the U.S. Department of Energy has launched new research and development (R&D) programs for developing new accident tolerant fuels (ATFs). These new fuel concepts are expected to bring several advancements in terms of plant safety. However, development, licensing, as well as deployment of ATF require a substantial investment among fuel vendors, operating utilities, and regulatory authorities. For ATF to be economically feasible, credited safety benefits may be necessary to provide an economic incentive for transition of nuclear power plants from Zr/UO2-based fuel technologies to ATFs. As a result, it is essential to evaluate the economic viability of ATF by conducting a comprehensive safety benefits study informed by R&D and demonstration studies. In the present work, based on the best estimate plus uncertainty methodology, sensitivity analysis and uncertainty quantification for key safety quantities under LB-LOCA are performed for the Peach Bottom boiling water reactor (BWR) with GE14 nuclear fuel design adopting the ATF concepts. A coupled TRACE-DAKOTA analysis framework is adopted to perform the uncertainty quantification. Based on the computational results and obtained statistics, the coping time increase, fuel performance improvement as well as the most dominating phenomena during the accident for Cr-coated cladding are investigated in detail. Overall, the results obtained are useful for subsequent plant PRA study and support a move to more modernized performance-based regulatory requirements to realize plant economic benefits.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗

Sub-Sampled Imaging for STEM: Maximising Image Speed, Resolution and Precision Through Reconstruction Parameter Refinement

Sub-sampling during image acquisition in scanning transmission electron microscopy (STEM) has been shown to provide a means to increase the overall speed of acquisition while at the same time providing an efficient means to control the dose, dose rate and dose overlap delivered to the sample. In this paper, we discuss specifically the parameters used to reconstruct sub-sampled images and highlight their effect on inpainting using the beta-process factor analysis (BPFA) methodology. The selection of the main control parameters can have a significant effect on the resolution, precision and sensitivity of the final inpainted images, and here we demonstrate a method by which these parameters can be optimised for any image in STEM. As part of this paper, we also provide a link to open source code and a tutorial on its use, whereby these parameters can be tested for any datasets. When coupled with the hardware necessary to rapidly sub-sample images in STEM, this approach can have significant implications for imaging beam sensitive materials and dynamic processes.

47 OTHER INSTRUMENTATION↗

In Situ X-ray Scattering Reveals Coarsening Rates of Superlattices Self-Assembled from Electrostatically Stabilized Metal Nanocrystals Depend Nonmonotonically on Driving Force

Self-assembly of colloidal nanocrystals (NCs) into superlattices (SLs) is an appealing strategy to design hierarchically organized materials with promising functionalities. Mechanistic studies are still needed to uncover the design principles for SL self-assembly, but such studies have been difficult to perform due to the fast time and short length scales of NC systems. To address this challenge, we developed an apparatus to directly measure the evolving phases in situ and in real time of an electrostatically stabilized Au NC solution before, during, and after it is quenched to form SLs using small-angle X-ray scattering. By developing a quantitative model, we fit the time-dependent scattering patterns to obtain the phase diagram of the system and the kinetics of the colloidal and SL phases as a function of varying quench conditions. The extracted phase diagram is consistent with particles whose interactions are short in range relative to their diameter. We find the degree of SL order is primarily determined by fast (subsecond) initial nucleation and growth kinetics, while coarsening at later times depends nonmonotonically on the driving force for self-assembly. We validate these results by direct comparison with simulations and use them to suggest dynamic design principles to optimize the crystallinity within a finite time window. The combination of this measurement methodology, quantitative analysis, and simulation should be generalizable to elucidate and better control the microscopic self-assembly pathways of a wide range of bottom-up assembled systems and architectures.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

Dynamic Life-Cycle Analysis of Fast Pyrolysis Biorefineries: Impacts of Feedstock Moisture Content and Particle Size

The commercialization of biorefineries has been met with significant obstacles due to the technical difficulties of handling solid biomass feedstocks, which are highly variable in physical properties and chemical compositions. An understanding of the principles of unit operations along the supply chain is key to the success of the biofuel industry. This study applies a dynamic life-cycle analysis (DLCA) methodology by developing quantitative relationships between the inputs and outputs for each unit operation based on scientific understanding of the causal effects. Using the DLCA, we assessed system sustainability of drop-in fuel production from fast pyrolysis of pine residues followed by hydro-processing. Life-cycle greenhouse gas (GHG) emissions were calculated for 4641 runs involving two key feedstock parameters: moisture content after field drying and particle size of the feed to pyrolyzer. Moisture contents varied between 25% and 35%, while particle sizes varied between 0.5 and 5 mm in these runs. The life-cycle GHG emissions of these cases vary from 22 to 40 g/MJ. Close examination of each unit operation's contribution to the total GHG emissions reveals that low moisture content after field drying produces savings in energy consumption during feedstock transportation and on-site drying. However, although small particle size leads to overall higher fuel yield, it also requires a significant amount of energy for feedstock size reduction and fuel production. The energy penalty outweighs the benefit of increased fuel yields, especially when fine particles (<1 mm) are used for pyrolysis; thus, small particle size leads to increased GHG emissions overall. The results highlight the trade-offs between the energy demand for preprocessing and the conversion yields, which can be addressed with DLCA.

09 BIOMASS FUELS↗

Biogeochemistry of upland to wetland soils, sediments, and surface waters across Mid-Atlantic and Great Lakes coastal interfaces

Transferable and mechanistic understanding of cross-scale interactions is necessary to predict how coastal systems respond to global change. Cohesive datasets across geographically distributed sites can be used to examine how transferable a mechanistic understanding of coastal ecosystem control points is. To address the above research objectives, data were collected by the EXploration of Coastal Hydrobiogeochemistry Across a Network of Gradients and Experiments (EXCHANGE) Consortium – a regionally distributed network of researchers that collaborated on experimental design, methodology, collection, analysis, and publication. The EXCHANGE Consortium collected samples from 52 coastal terrestrial-aquatic interfaces (TAIs) during Fall of 2021. At each TAI, samples collected include soils from across a transverse elevation gradient (i.e., coastal upland forest, transitional forest, and wetland soils), surface waters, and nearshore sediments across research sites in the Great Lakes and Mid-Atlantic regions (Chesapeake and Delaware Bays) of the continental USA. The first campaign measures surface water quality parameters, bulk geochemical parameters on water, soil, and sediment samples, and physicochemical parameters of sediment and soil.

54 ENVIRONMENTAL SCIENCES↗