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DOE OSTI2022

Soil temperature mitigation due to vegetation biophysical feedbacks

Understanding the interactions between temperature regimes and vegetation cover is one of the key scientific topics in global environmental change and land surface process research. Recently, the prominent global greening trend has inspired considerable interest in examining climate feedbacks to vegetation changes. However, the impacts of recent widespread vegetation cover changes on soil temperature have been less documented and have received insufficient attention. Here, a high-resolution regional climate model was used to examine the potential impact of vegetation cover changes over the past 37 years, obtained as satellite observational data, on regional air and soil temperatures across the Heilong-Amur River Basin. Our sensitivity experiments indicated that the 1.85% increase in the regional fractional vegetation cover (FVC) from 1982 to 2018 cooled the air temperature by 0.045°C and the soil temperature by 0.19°C and that this cooling effect would continue in the near future, from 2016-2018 to 2051-2053. We found that soil temperatures were more sensitive to vegetation cover changes than air temperatures, particularly in mid-high latitude forest ecosystems; this finding helps to explain the nonsignificant decrease in soil temperatures in forest ecosystems over the past 40 years detected in the ERA5-Land reanalysis. Further, our results also suggest that vegetation restoration in forest ecosystems could mitigate the effects of climate change on permafrost environments by increasing the number of soil freezing days.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2020

Advances in PFAS Monitoring and Remediation Using a Functionalized Material Approach

The growing global concerns about the effects to public health from human exposure to per- and polyfluoroalkyl substances (PFAS) motivates the development of strategies for reliable monitoring of PFAS in environmental streams, as well as for their rapid, effective removal if detected. For the continuous PFAS monitoring, an inexpensive, field-deployable, in situ sensor is urgently needed; yet the prevalent in situ techniques often struggle to strike a balance between the practical sensitivity and selectivity demands of the real world. Similarly, for effective PFAS removal, strategies for their fast, selective, and quantitative capture are desired, yet the present commercially available sorbents are unable to meet the requirements of rapid, quantitative capture of all PFAS components, and are notably inefficient in removing the more toxic smaller chains. To address these twin challenges, Pacific Northwest National Laboratory is developing strategies for improved detection and remediation of PFAS. For the rapid, selective, quantitative removal of PFAS from environmental streams, the strategy relies on designing capture probes with exclusively tailored electronic and spatial affinities for the PFAS that are able to selectively capture them from environmental streams. For the in situ detection and quantification of PFAS in complex, multicomponent matrices such as groundwater, the approach relies on the targeted capture of specific PFAS by these PFAS-specific capture probes immobilized on a platform. The platform acts as an electrode to directly measure PFAS concentration through a proportional change in electrical response upon their capture. A combination of optimization of platform design and incorporation of additional, sensitive detection modalities have allowed us to achieve detection limits as low as 0.5 ng/L for detection of PFAS compounds (compared to the 70 ng/L Health Advisory Limit of the U.S. Environmental Protection Agency).

Per- and poly-fluorinated alkyl substances (PFAS),↗

DOE OSTI2020

Advances in PFAS Monitoring and Remediation Using a Functionalized Material Approach - 20080

47 OTHER INSTRUMENTATION↗

DOE OSTI2024

Solid-State Mixed-Potential Electrochemical Sensors for Natural Gas Leak Detection and Quality Control (Final Technical Report)

Mitigation of methane emissions are a critical factor to limiting the impact of the natural gas industry on global climate change. Throughout the period of 2020-2024, the University of New Mexico and its commercialization partner and subcontractor, SensorComm Technologies, Inc. (SCT), have worked together to develop a low-cost Artificial Intelligence (AI)-driven Internet of Things (IoT)-based multi-gas sensor platform for methane emissions detection. In the final year of the project, we extended this work to include hydrogen detection in support of a transition to a hydrogen economy where hydrogen could be transported through existing natural gas infrastructure. Mixed potential electrochemical sensors were first prototyped by ceramic additive manufacturing and then transitioned to conventional ceramic manufacturing tape casting and screen-printing technologies in preparation for mass production. Demonstrated limits of detection of 5 ppm of methane in natural gas and 1 ppm of hydrogen were measured. These limits of detection are among the lowest of solid-state electrochemical sensors that have been reported in the literature or available in the industry. Machine learning algorithms were developed to identify natural gas mixtures with > 98% accuracy level and quantify methane concentrations at 97% accuracy. The presence of hydrogen could also be identified, and its concentration quantified at these accuracy levels. These algorithms were optimized for running on portable computing hardware which enabled > 1 Hz processing rates. A portable packaged IoT system was integrated with the electrochemical sensor in collaboration with SCT. The package consists of readout electronics with < 1 mV resolution, sensor temperature control, and data transmission over cellular wireless and/or Wi-Fi networks. Field testing was performed in two rounds at Colorado State University’s Methane Emissions Technology Evaluation Center (CSU METEC). The first round of testing demonstrated successful measurements of methane from an underground natural gas leak of 20 standard liters per minute (SLPM), which agreed with previously published literature using more sophisticated and expensive analytical equipment. The second round of testing showed that an above ground leak of 2 SLPM of hydrogen could be detected at 32 ft. This project has resulted in six published peer reviewed journal articles, over ten presentations at professional conferences, and one full patent application filed in 2023. Future work on this project includes increased sensitivity, higher production yields, and applications in the hydrogen safety and flare emissions monitoring spaces.

03 NATURAL GAS↗

DOE OSTI2021

La 3+ and Y 3+ interactions with the carboxylic acid moiety at the liquid/vapor interface: Identification of binding complexes, charge reversal, and detection limits

Specific interactions of yttrium and lanthanum ions with a fatty acid Langmuir monolayer were investigated using vibrational sum frequency spectroscopy. The trivalent ions were shown to interact with the charged form of the carboxylic acid group from nanomolar concentrations (<300 nM). Analysis of the spectral features from both the symmetric and the asymmetric carboxylate modes reveals the presence of at least three distinct coordination structures linked to specific binding configurations. Although the same species were identified for both La 3+ and Y 3+ , they display a different concentration dependence, highlighting the ion-specificity of the interaction. From the analysis of the response of interfacial water molecules, the reversal of the surface charge, as well as the formation of yttrium hydroxide complexes, were detected upon increasing the amount of salt in solution. The binding interaction and kinetics of absorption are sensitive to the solution pH, showing a distinct ion speciation in the interfacial region when compared to the bulk. Changing the subphase pH or adding a monovalent background electrolyte that promotes deprotonation of the carboxylic acid headgroup could further improve the detection limit of La 3+ and Y 3+ to concentrations < 100 nM. These findings demonstrate that nM concentrations of trace metals contaminants, typically found on monovalent salts, can significantly influence the binding structure and kinetics in Langmuir monolayers.

01 COAL, LIGNITE, AND PEAT↗

DOE OSTI2023

Long–short-term memory encoder–decoder with regularized hidden dynamics for fault detection in industrial processes

The ability of recurrent neural networks (RNN) to model nonlinear dynamics of high dimensional process data has enabled data-driven RNN-based fault detection algorithms. Previous studies have focused on detecting faults by identifying the discrepancies in data distribution between the faulty and normal data, as reflected in prediction errors generated by RNN models. However, in industrial processes, variations in data distribution can also result from changes in normal control setpoints and compensatory control adjustments in response to disturbances, making it hard to differentiate between normal and faulty conditions. This paper proposes a fault detection method utilizing a long short-term memory (LSTM) encoder–decoder structure with regularized hidden dynamics and reversible instance normalization (RevIN) to compactly represent high-dimensional measurements for effective monitoring. During training, the hidden states of the model are regularized to form a low-dimensional latent space representation of the original multivariate time series data. As a result, the prediction errors of the latent states can be used to monitor the abnormal dynamic variations, while the reconstruction errors of the measured variables are used to monitor the abnormal static variations. Furthermore, the proposed indices can reflect operating conditions, even when the distribution of test data changes, which helps distinguish faults from normal adjustments and disturbances that controllers can settle. Here, data from numerical simulation and the Tennessee Eastman process are used to illustrate the effectiveness of the proposed fault detection method.

42 ENGINEERING↗

DOE OSTI2020

Differentiation strategies of soil rare and abundant microbial taxa in response to changing climatic regimes

Despite the important roles of soil microbes, especially the most diverse rare taxa in maintaining community diversity and multifunctionality, how different climate regimes alter the stability and functions of the rare microbial biosphere remains unknown. We reciprocally transplanted field soils across a latitudinal gradient to simulate climate change and sampled the soils annually after harvesting the maize over the following 6 years (from 2005 to 2011). By sequencing microbial 16S ribosomal RNA gene amplicons, we found that changing climate regimes significantly altered the composition and dynamics of soil microbial communities. A continuous succession of the rare and abundant communities was observed. Rare microbial communities were more stable under changing climatic regimes, with lower variations in temporal dynamics, and higher stability and constancy of diversity. More nitrogen cycling genes were detected in the rare members than in the abundant members, including amoA, napA, nifH, nirK, nirS, norB and nrfA. Random forest analysis and receiver operating characteristics analysis showed that rare taxa may act as potential contributors to maize yield under changing climatics. The study indicates that the taxonomically and functionally diverse rare biosphere has the potential to increase functional redundancy and enhance the ability of soil communities to counteract environmental disturbances. With ongoing global climate change, exploring the succession process and functional changes of rare taxa may be important in elucidating the ecosystem stability and multifunctionality that are mediated by microbial communities.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2024

A portable application framework for energy management and information systems (EMIS) solutions using Brick semantic schema

This paper introduces a portable framework for developing, scaling and maintaining energy management and information systems (EMIS) applications using an ontology-based approach. Key contributions include an interoperable layer based on Brick schema, the formalization of application constraints pertaining metadata and data requirements, and a field demonstration. The framework allows for querying metadata models, fetching data, preprocessing, and analyzing data, thereby offering a modular and flexible workflow for application development. Its effectiveness is demonstrated through a case study involving the development and implementation of a data-driven anomaly detection tool for the photovoltaic systems installed at the Politecnico di Torino, Italy. During eight months of testing, the framework was used to tackle practical challenges including: (i) developing a machine learning-based anomaly detection pipeline, (ii) replacing data-driven models during operation, (iii) optimizing model deployment and retraining, (iv) handling critical changes in variable naming conventions and sensor availability (v) extending the pipeline from one system to additional ones.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗

DOE OSTI2020

Safeguards Modeling for Advanced Nuclear Facility Design.

Future nuclear fuel cycle facilities will see a significant benefit from considering materials accountancy requirements early in the design process. The Material Protection, Accounting, and Control Technologies (MPACT) working group is demonstrating Safeguards and Security by Design (SSBD) for a notional electrochemical reprocessing facility as part of a 2020 Milestone. The idea behind SSBD is to consider regulatory requirements early in the design process to provide more optimized systems and avoid costly retrofits later in the design process. Safeguards modeling, using single analyst tools, allows the designer to efficiently consider materials accountancy approaches that meet regulatory requirements. However, safeguards modeling also allows the facility designer to go beyond current regulations and work toward accountancy designs with rapid response and lower thresholds for detection of anomalies. This type of modeling enables new safeguards approaches and may inform future regulatory changes. The Separation and Safeguards Performance Model (SSPM) has been used for materials accountancy system design and analysis. This paper steps through the process of designing a Material Control and Accountancy (MC&A) system, presents the baseline system design for an electrochemical reprocessing facility, and provides performance metrics from the modeling analysis. The most critical measurements in the electrochemical facility are the spent fuel input, electrorefiner salt, and U/TRU product output measurements. Finally, material loss scenario analysis found that measurement uncertainties (relative standard deviations) for Pu would need to be at 1% (random and systematic error components) or better in order to meet domestic detection goals or as high as 3% in order to meet international detection goals, based on a 100 metric ton per year plant size.

98 NUCLEAR DISARMAMENT, SAFEGUARDS, AND PHYSICAL P↗

DOE OSTI2023

A sensitive high repetition rate arrival time monitor for X-ray free electron lasers

X-ray free-electron laser sources enable time-resolved X-ray studies with unmatched temporal resolution. To fully exploit ultrashort X-ray pulses, timing tools are essential. However, new high repetition rate X-ray facilities present challenges for currently used timing tool schemes. Here we address this issue by demonstrating a sensitive timing tool scheme to enhance experimental time resolution in pump-probe experiments at very high pulse repetition rates. Our method employs a self-referenced detection scheme using a time-sheared chirped optical pulse traversing an X-ray stimulated diamond plate. By formulating an effective medium theory, we confirm subtle refractive index changes, induced by sub-milli-Joule intense X-ray pulses, that are measured in our experiment. The system utilizes a Common-Path-Interferometer to detect X-ray-induced phase shifts of the optical probe pulse transmitted through the diamond sample. Owing to the thermal stability of diamond, our approach is well-suited for MHz pulse repetition rates in superconducting linear accelerator-based free-electron lasers.

47 OTHER INSTRUMENTATION↗

DOE OSTI2022

Sleptonic SUSY: from UV framework to IR phenomenology

We study an attractive scenario, “Sleptonic SUSY”, which reconciles the 125 GeV Higgs scalar and the non-observation of superpartners thus far with potentially pivotal roles for slepton phenomenology: providing viable ongoing targets for LHC discovery, incorporating a co-annihilation partner for detectable thermal relic dark matter, and capable of mediating the potential muon g – 2 anomaly. This is accomplished by a modestly hierarchical spectrum, with sub-TeV sleptons and electroweakinos and with multi-TeV masses for the other new states. We study new elements in the UV MSSM realization of Sleptonic SUSY based on higher-dimensional sequestering and the synergy between the resulting gaugino-mediation, hypercharge D-term mediation and Higgs-mediation of SUSY-breaking, so as to more fully capture the range of possibilities. This framework stands out by harmoniously solving the flavor, CP and μ – Bμ problems of the supersymmetric paradigm. We discuss its extension to orbifold GUTs, including gauge-coupling and b-tau unification. We also develop a non-minimal model with extra Higgs fields, in which the electroweak vacuum is more readily cosmologically stable against decay to a charge-breaking vacuum, allowing a broader range of sleptonic spectra than in the MSSM alone. We survey the rich set of signals possible at the LHC and future colliders, covering both R-parity conservation and violation, as well as for dark matter detection. While the multi-TeV squarks imply a Little Hierarchy Problem, intriguingly, small changes in parameter space to improve naturalness result in dramatic phase transitions to either electroweak-preservation or charge-breaking. In a Multiverse setting, the modest unnaturalness may then be explained by the “principle of living dangerously”.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2024

Heuristic algorithms for design of integrated monitoring of geologic carbon storage sites

Designs for Risk Evaluation and Management (DREAM) is a tool developed under the National Risk Assessment Partnership (NRAP) to enhance geologic carbon storage safety and efficiency. Using potential leakage scenarios generated externally by the users preferred history-matching approach, DREAM constructs ideal combinations of sensor locations in the right place at the right time to detect as many leaks as possible, detect them as early as possible, and minimize cost. This user-friendly tool, developed in Java, features a window-based GUI for input and a 3D visualization tool for viewing the domain space and optimized monitoring plans. DREAM's latest version accommodates real-world usage by allowing for joint optimization of wellbore point sensor placements and surface geophysics survey geometries, and by using more efficient multi-objective optimization algorithms. We show an example where, these two improvements combined allow us to support containment assurance and go from detecting 80–90 % of the potential CO 2 leakage to +99.7 %, a step-change improvement that can make the deciding difference in whether a site is suitable for geologic carbon storage. Though developed for geologic carbon storage, this tool would be equally applicable in many surface or offshore environmental monitoring projects.

58 GEOSCIENCES↗

DOE OSTI2021

Proline hydroxylase domain-containing enzymes regulate calcium levels in cardiomyocytes by TRPA1 ion channel

Highlights: • PHD induces calcium release from cardiomyocytes through ryanodine channel. • PHD activates TRPA1 to induce extracellular calcium ions into the cell and further activate the ryanodine channel. • TRPA1 is involved in the regulation of PHD-Ca2+-AMPK signaling pathway. The proline hydroxylase domain-containing enzymes (PHDs) acts as cellular oxygen sensors, inducing a series of responses to hypoxia, especially during the regulation of metabolism and energy homeostasis. The increase of Ca{sup 2+} in cardiomyocytes, induced by the opening of PHD signaling pathway, is the key initiation signal necessary for the PHD-mediated regulation of the energy metabolism pathway, but the underlying molecular mechanism remains incompletely understood. This study used PHD inhibitors (PHIs) and PHD2-specific RNA interference (PHD2shRNA) to inhibit PHD signals in cardiomyocytes to explore whether transient receptor potential ankyrin 1 (TRPA1) is involved in the regulation of calcium ion influx in the PHD activation pathway associated with to AMP-activated protein kinase (AMPK). The Fluo-3AM probe was used to measure changes in free intracellular calcium ion concentrations, and Western blot analysis was used to detect the levels of phosphorylated (P)-AMPK, TRPA1, and P–Ca{sup 2+}/calmodulin-dependent protein kinase Ⅱ (CaMKⅡ) levels. The PHI-mediated inhibition of PHD resulted in an increase in free Ca{sup 2+} fluorescence in cardiomyocytes, which activated AMPK, TRPA1, and CaMKⅡ. The TRPA1 inhibitor HC030031, the CaMKII inhibitor KN93, and a ryanodine inhibitor (Ryanodine) were all able to inhibit the PHI-induced increase in intracellular Ca{sup 2+} and AMPK activation. Both PHIs and PHD2shRNA were able to effectively activate CaMKII and TRPA1. However, an inositol 1,4,5-triphosphate receptor (IP3R) inhibitor and the protein kinase A (PKA) inhibitor H89 did not significantly inhibit the PHI-induced increase in intracellular Ca{sup 2+} and AMPK activation. These results indicated that PHD might activate the CaMKⅡ pathway through the TRPA1 ion channel, inducing the release of calcium from the sarcoplasmic reticulum through ryanodine receptor 2 (RyR2), activating AMPK to initiate the protective effects of hypoxia in cardiomyocytes.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Large Individual Ion FTICR Measurements from the Mid-1990s Using Reactions for Charge Determination Mass Spectrometry

This article discusses from a personal and present-day perspective the first studies of large highly charged individual molecular ions that were conducted using electrospray ionization (ESI) with Fourier transform ion cyclotron resonance (FTICR) MS in the mid-1990s. These studies are distinguished from current Charge Detection Mass Spectrometry (CDMS) research primarily by their use of individual ion charge state changes due to reactions. Here this work describes the key differences in technologies and methods with present CDMS, and the likely implications of these differences. I also comment on surprising individual ion behavior observed in some measurements involving increases in charge state, as well as their possible basis, and also briefly discuss the potential utility of the reaction-based mass measurement approach used in the context of what might more globally be referred to as ‘Charge Determination Mass Spectrometry’.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2021

Constraining and Characterizing the Size of Atmospheric Rivers: A Perspective Independent From the Detection Algorithm

Abstract Atmospheric rivers (AR) are large and narrow filaments of poleward horizontal water vapor transport. Because of its direct relationship with horizontal vapor transport, extreme precipitation, and overall AR impacts over land, the AR size is an important characteristic that needs to be better understood. Current AR detection and tracking algorithms have resulted in large uncertainty in estimating AR sizes, with areas varying over several orders of magnitude among different detection methods. We develop and implement five independent size estimation methods to characterize the size of ARs that make landfall over the west coast of North America in the 1980–2017 period and reduce the range of size estimation from ARTMIP. ARs that originate in the Northwest Pacific (WP) (100°−180°E) have larger sizes and are more zonally oriented than those from the Northeast Pacific (EP) (180°−240°E). ARs become smaller through their life cycle, mainly due to reductions in their width. They also become more meridionally oriented toward the end of their life cycle. Overall, the size estimation methods proposed in this study provide a range of AR areas (between 7 × 10 11 and 10 13 m 2 ), that is, several orders of magnitude narrower than current methods estimation. This methodology can provide statistical constraints in size and geometry for the AR detection and tracking algorithms, and an objective insight for future studies about AR size changes under different climate scenarios.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Observed increase in the peak rain rates of monsoon depressions

Most extreme precipitation in the densely populated region of central India is produced by atmospheric vortices called monsoon lows and monsoon depressions. Here we use satellite and gauge-based precipitation estimates with atmospheric reanalyses to assess 40-year trends in the rain rates of these storms, which have remained unknown. We show that rain rates increased in the rainiest quadrant of monsoon depressions, southwest of the vortex center; precipitation decreased in eastern quadrants, yielding no clear trend in precipitation averaged over the entire storm diameter. In an atmospheric reanalysis, ascent increased in the region of amplifying precipitation, but we could not detect trends in the intensity of rotational winds around the storm center. These storm changes occurred in a background environment where humidity increased rapidly over land while warming was more muted. Monsoon lows, which we show produce less precipitation than depressions, exhibit weaker trends that are less statistically robust.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

A switchable sensor and scavenger: detection and removal of fluorinated chemical species by a luminescent metal–organic framework

A robust In-MOF, In(tcpp), demonstrates sensitive detection of the fluorinated chemical species F − and PFOA via distinctly different luminescence signal change, and effective adsorption and removal of both species from aqueous solution.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2023

Understanding uncertainties in projections of western North Pacific tropical cyclogenesis

Reliable projections of tropical cyclone (TC) activities in the western North Pacific (WNP) are crucial for climate policy-making in densely-populated coastal Asia. Existing projections, however, exhibit considerable uncertainties with unclear sources. Here, based on future projections by the latest Coupled Model Intercomparison Project Phase 6 climate models, we identify a new and prevailing source of uncertainty arising from different TC identification schemes. Notable differences in projections of detected TCs and empirical genesis potential indices are found to be caused by inconsistent changes in dynamic and thermodynamic environmental factors affecting TC formations. While model uncertainty holds the secondary importance, we show large potential in reducing it through improved model simulations of present-day TC characteristics. Internal variability noticeably impacts near-term projections of the WNP tropical cyclogenesis, while the relative contribution of scenario uncertainty remains small. Our findings provide valuable insights into model development and TC projections, thereby aiding in adaptation decisions.

54 ENVIRONMENTAL SCIENCES↗