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DOE OSTI2016

Partitioning CO2 fluxes with isotopologue measurements and modeling to understand mechanisms of forest carbon sequestration

1. Objectives This project combines automated in situ observations of the isotopologues of CO2 with root observations, novel experimental manipulations of belowground processes, and isotope-enabled ecosystem modeling to investigate mechanisms of below- vs. aboveground carbon sequestration at the Harvard Forest Environmental Measurements Site (EMS). The proposed objectives, which have now been largely accomplished, include: A. Partitioning of net ecosystem CO2 exchange (NEE) into photosynthesis and respiration using long-term continuous observations of the isotopic composition of NEE, and analysis of their dynamics ; B. Investigation of the influence of vegetation phenology on the timing and magnitude of carbon allocated belowground using measurements of root growth and indices of belowground autotrophic vs. heterotrophic respiration (via trenched plots and isotope measurements); C. Testing whether plant allocation of carbon belowground stimulates the microbial decomposition of soil organic matter, using in situ rhizosphere simulation experiments wherein realistic quantities of artificial isotopically-labeled exudates are released into the soil; and D. Synthesis and interpretation of the above data using the Ecosystem Demography Model 2 (ED2). 2. Highlights Accomplishments: • Our isotopic eddy flux record has completed its 5th full year and has been used to independently estimate ecosystem-scale respiration and photosynthesis. • Soil surface chamber isotopic flux measurements were carried out during three growing seasons, in conjunction with a trenching manipulation. Key findings to date (listed by objective): A. Partitioning of Net Ecosystem Exchange: 1. Ecosystem respiration is lower during the day than at night—the first robust evidence of the inhibition of leaf respiration by light (the “Kok effect”) at the ecosystem scale. 2. Because it neglects the Kok effect, the standard NEE partitioning approach overestimates ecosystem photosynthesis (by ~25%) and daytime respiration (by ~100%) in the first half of the growing season at our site, and portrays ecosystem photosynthetic light-use efficiency as declining when in fact it is stable until autumnal senescence. B. Vegetation Phenology and belowground allocation: Findings: 1. Autotrophic respiration (Ra) showed a seasonal pattern, peaking in mid-summer when trees were most active. 2. The effective age of the substrate for belowground respiration is less than 2 weeks. 3. Above and belowground phenology are more synchronous in deciduous hardwood stands than evergreen hemlock stands. 4. The decline in root respiration rates in the fall is related to temperature rather than acclimation of root respiration or substrate limitations. Methodological Issues: 5. The isotopic signatures of autotrophic and heterotrophic respiration are too similar for isotopic partitioning of belowground respiration into these two components at our site—in keeping with the recent findings of Bowling et al. (2015) in a subalpine conifer forest. 6. Artifacts of the trenching method, such as changes in soil moisture and increased carbon substrate from the newly severed roots, are significant and need to be quantified when determining daily to annual estimates of autotrophic and heterotrophic respiration. C. Effects of simulated exudates on priming of microbial decomposition: The stoichiometry of root exudates influences both the amount and the mechanism by which priming occurs. At low C:N, SOC loss is caused by an increase in microbial efficiency. At high C:N, SOC loss is caused by an increase in microbial biomass. D. Modeling with the Ecosystem Demography Model (ED2): 1. Incorporation of 13C tracking to create an isotopically-enabled Ecosystem Demography v2 model (ED2) 2. State-of-the-art parameter optimization methodology developed for improving ED2 model predictions and parameters. 3. Significantly improved model predictions of growth- and maintenance-related carbon fluxes and 13C fluxes

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2021

Low-intensity frequent fires in coniferous forests transform soil organic matter in ways that may offset ecosystem carbon losses

The impact of shifting disturbance regimes on soil carbon (C) storage is a key uncertainty in global change research. Wildfires in coniferous forests are becoming more frequent in many regions, potentially causing large C emissions. Repeated low-intensity prescribed fires can mitigate wildfire severity, but repeated combustion may decrease soil C unless compensatory responses stabilize soil organic matter. Here, we tested how 30 years of decadal prescribed burning affected C and nitrogen (N) in plants, detritus, and soils in coniferous forests in the Sierra Nevada mountains, USA. Tree basal area and litter stocks were resilient to fire, but fire reduced forest floor C by 77% (-36.4 Mg C/ha). In mineral soils, fire reduced C that was free from minerals by 41% (-4.4 Mg C/ha) but not C associated with minerals, and only in depths ≤ 5 cm. Fire also transformed the properties of remaining mineral soil organic matter by increasing the proportion of C in a pyrogenic form (from 3.2% to 7.5%) and associated with minerals (from 46% to 58%), suggesting the remaining soil C is more resistant to decomposition. Laboratory assays illustrated that fire reduced microbial CO2 respiration rates by 55% and the activity of eight extracellular enzymes that degrade cellulosic and aromatic compounds by 40–66%. Lower decomposition was correlated with lower inorganic N (-49%), especially ammonium, suggesting N availability is coupled with decomposition. The relative increase in forms of soil organic matter that are resistant to decay or stabilized onto mineral surfaces, and the associated decline in decomposition suggest that low-intensity fires may promote mineral soil C storage in pools with long mean residence times in coniferous forests.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS1998

A Method to Access Absolute fIPAR fo Vegetation in Spatially Complex Ecosystems

Arid and semi-arid lands compose a large fraction of the earth's terrestrial vegetation, and thereby contribute significantly to global atmospheric-biospheric interactions. The thorny shrubs and small trees in these semi-arid shrub lands have counterparts throughout much of the world's tropical and subtropical zones and have captured substantial areas of the world's former grasslands. The objective of our field and remotely sensed measurements in the semi-arid shrublands of Texas is to monitor interannual variability and directional change in landscape structure, ecosystem processes and atmosphere-biosphere exchanges. To understand the role ecosystems play in controlling the composition of the atmosphere, it is necessary to quantify processes such as photosynthesis and primary production, decomposition and soil carbon storage, and trace gas exchanges. Photosynthesis is the link whereby surface-atmosphere exchanges such as the radiation balance and exchange of heat, moisture, and gas can be inferred. It also describes the efficiency of carbon dioxide exchange and is directly related to the primary production of vegetation. Our efforts in this paper focus on the indirect, quantification of photosynthesis, and thereby carbon flux and net primary production, via remote sensing and direct measurements of intercepted photosynthetically active radiation (IPAR).

Wessman, Carol A.↗

DOE OSTI2013

Expectation-maximization algorithms for learning a finite mixture of univariate survival time distributions from partially specified class values

Heterogeneity exists on a data set when samples from di erent classes are merged into the data set. Finite mixture models can be used to represent a survival time distribution on heterogeneous patient group by the proportions of each class and by the survival time distribution within each class as well. The heterogeneous data set cannot be explicitly decomposed to homogeneous subgroups unless all the samples are precisely labeled by their origin classes; such impossibility of decomposition is a barrier to overcome for estimating nite mixture models. The expectation-maximization (EM) algorithm has been used to obtain maximum likelihood estimates of nite mixture models by soft-decomposition of heterogeneous samples without labels for a subset or the entire set of data. In medical surveillance databases we can find partially labeled data, that is, while not completely unlabeled there is only imprecise information about class values. In this study we propose new EM algorithms that take advantages of using such partial labels, and thus incorporate more information than traditional EM algorithms. We particularly propose four variants of the EM algorithm named EM-OCML, EM-PCML, EM-HCML and EM-CPCML, each of which assumes a specific mechanism of missing class values. We conducted a simulation study on exponential survival trees with five classes and showed that the advantages of incorporating substantial amount of partially labeled data can be highly signi cant. We also showed model selection based on AIC values fairly works to select the best proposed algorithm on each specific data set. A case study on a real-world data set of gastric cancer provided by Surveillance, Epidemiology and End Results (SEER) program showed a superiority of EM-CPCML to not only the other proposed EM algorithms but also conventional supervised, unsupervised and semi-supervised learning algorithms.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Unitarity methods in AdS/CFT

We develop a systematic unitarity method for loop-level AdS scattering amplitudes, dual to non-planar CFT correlators, from both bulk and boundary perspectives. We identify cut operators acting on bulk amplitudes that put virtual lines on shell, and show how the conformal partial wave decomposition of the amplitudes may be efficiently computed by gluing lower-loop amplitudes. A central role is played by the double discontinuity of the amplitude, which has a direct relation to these cuts. We then exhibit a precise, intuitive map between the diagrammatic approach in the bulk using cutting and gluing, and the algebraic, holographic unitarity method of [1] that constructs the non-planar correlator from planar CFT data. Our analysis focuses mostly on four-point, one-loop diagrams — we compute cuts of the scalar bubble, triangle and box, as well as some one-particle reducible diagrams — in addition to the five-point tree and four-point double-ladder. Analogies with S-matrix unitarity methods are drawn throughout.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2017

Isovector charges of the nucleon from 2+1-flavor QCD with clover fermions

Here, we present high-statistics estimates of the isovector charges of the nucleon from four 2 + 1-flavor ensembles generated using Wilson-clover fermions with stout smearing and tree-level tadpole improved Symanzik gauge action at lattice spacings 𝑎 ≈ 0.127 and 0.09 fm and with 𝑀 𝜋 ≈ 280 and 170 MeV. The truncated solver method with bias correction and the coherent source sequential propagator construction are used to cost-effectively achieve 𝑂⁡(1⁢0 5 ) measurements on each ensemble. Using these data, the analysis of two-point correlation functions is extended to include four states in the fits, and of three-point functions to three states. Control over excited-state contamination in the calculation of the nucleon mass, the mass gaps between excited states, and in the matrix elements is demonstrated by the consistency of estimates using this multistate analysis of the spectral decomposition of the correlation functions and from simulations of the three-point functions at multiple values of the source-sink separation. The results for all three charges, 𝑔 𝐴 , 𝑔 𝑆 , and 𝑔 𝑇 , are in good agreement with calculations done using the clover-on-HISQ lattice formulation with similar values of the lattice parameters.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2021

Data for “Fast-decaying plant litter enhances soil carbon in temperate forests, but not through microbial physiological traits”

This data package contains data and code used in the paper “Fast-decaying plant litter enhances soil carbon in temperate forests, but not through microbial physiological traits”. This paper details results from two studies: 1) a laboratory leaf litter incubation experiment (lab experiment) and 2) a multi-site observational field study (field study). Both studies were designed to test the relationships among litter quality, microbial physiological traits, and mineral-associated soil carbon (C). In the lab experiment, we incubated 16 temperate tree litters of differing chemical quality with isotopically distinct soil, measuring microbial physiological traits and the flow of litter-derived C into the mineral-associated soil C pool. In the field study, we sampled soils (0-5 cm) across six eastern US temperate forests, measuring microbial physiological traits, soil abiotic properties, and leaf litter chemistry. The analysis data are provided in two .csv files corresponding to either the lab experiment or field study. Both files contain data on litter chemistry, microbial physiological traits (growth and turnover rates, and carbon use efficiency [CUE]), and the mineral-associated soil C pool. The lab experiment dataset additionally contains litter-derived versus soil-derived soil C, respiration, and litter decomposition parameters. The field study dataset additionally contains site-level climatic information, ectomycorrhizal dominance of plots, and plot-level soil properties. Also provided is the R code and output reproducing the results in the related publication. Analyses were originally performed using R version 3.6.1 using the package "lavaan" and the packages listed on lines 5-7 in the file "data.R".

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2026

Biobased Polybenzoxazine Derived from Furfurylamine and Piceol with Low Cure Temperature and Advanced Properties for Composite Matrices

A novel benzoxazine made from furfurylamine, paraformaldehyde, and piceol, Bz-FA-HA, is assessed for applications in fiber reinforced (FR) composites. Piceol is a biobased phenolic compound derived from the roots of Norwegian spruce trees and contains a methyl ketone group at the para position. Bz-FA-HA is a liquid at room temperature, has a viscosity of < 1 Pa.s at temperatures above 90 °C, and a Tonset of cure at 132 °C. The carbonyl is found to react with the furan ring, yielding a crosslinking reaction, when cured above 180 °C as indicated by differential scanning calorimetry and thermogravimetric analysis coupled with Fourier transform infrared spectroscopy. Poly(Bz-FA-HA) has a Tg > 350 °C, attributed to the crosslinking reaction. Furthermore, the storage modulus is > 3 GPa, regardless of cure temperature. Poly(Bz-FA-HA) has a char yield at 800 °C of 65.0 % (62.3 % at 1000 °C), and a Tonset of decomposition of 357 °C in nitrogen. The resulting carbon formed during pyrolysis shrinks during the carbonization reaction and scanning electron microscopy imaging shows a cross-section with micro cracks. The high processability, advanced mechanical properties, and exceptional char yield make it a promising candidate as the matrix for FR composites.

Benzoxazine↗

DOE OSTI2024

Integrating the full four-loop negative geometries and all-loop ladder-type negative geometries in ABJM theory

The decomposition of the four-point ABJM amplituhedron into negative geometries produces compact integrands of logarithmic of amplitudes such that the infrared divergence only comes from the last loop integration, from which we can compute the cusp anomalous dimension of the ABJM theory. In this note, we integrate L – 1 loop momenta of the L-loop negative geometries for all four-loop negative geometries and a special class of all-loop ladder-type negative geometries by a method based on Mellin transformation, and from these finite quantities we extract the corresponding contribution to the cusp anomalous dimension. We find that the infrared divergence of a box-type negative geometry at L = 4 is weaker than other negative geometries, then only tree-type negative geometries contribute to the cusp anomalous dimension at L = 4. For the all-loop ladder-type negative geometries, we prove and conjecture some recursive structures as integral equations in Mellin space and find that they cannot contribute zeta values like ζ 3 , ζ 5 to the cusp anomalous dimension.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2023

Mechanism and kinetic study of rare earth extraction from allanite by direct acid leaching

Direct acid leaching was conducted to recover rare earth elements (REEs) from an allanite ore assaying 9,861.4 ppm of REEs. The effects of operational variables such as acid type, sulfuric acid (H 2 SO 4 ) concentration, temperature, solid/liquid (S/L) ratio, and particle size on the total REE (TREE) recovery were systematically examined. The REE mineralogy and the involved leaching mechanisms were investigated by microscopic characterization and residue re-leaching tests. It was found that approximately 80% of REEs was extracted using 1 M H 2 SO 4 at 75 °C for 2 h. Increasing temperature significantly improved the REE extraction, while changing acid type, H 2 SO 4 concentration, and particle size did not. The TREE recovery also gradually decreased at higher S/L ratios. The low fraction of Si leached (<4.0%) suggested that the extraction did not significantly alter the crystal structure of the dominant mineral. The leaching kinetics of REEs were fast within the first 10 min, followed by a much slower stage (i.e., 10-120 min). The kinetic modeling results showed that each stage may be controlled by both chemical reaction and diffusion (i.e., mix control). The activation energies for REE leaching using 1 M H 2 SO 4 in the 0-10 min and 10-120 min were determined to be 20.3 and 10.8 kJ/mol, respectively. Finally, the residue re-leaching results suggested that the fast leaching kinetics at the beginning may be explained by the preferential decomposition of metamict allanite rather than the formation of silica gel, while the following slower leaching stage was due to the dissolution of difficult-to-leach REE-bearing minerals such as well-crystallized allanite.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2020

Mechanisms of Asymmetric Membrane Formation in Nonsolvent-Induced Phase Separation

We report the first simulations of nonsolvent-induced phase separation (NIPS) that predict membrane microstructures with graded asymmetric pore size distribution. In NIPS, a polymer solution film is immersed in a nonsolvent bath, enriching the film in nonsolvent, and leading to phase separation that forms a solid polymer-rich membrane matrix and polymer-poor membrane pores. We demonstrate how mass-transfer-induced spinodal decomposition, thermal fluctuations, and glass-transition dynamics implemented with mobility contrast between the polymer-rich and polymer-poor phases are essential to the formation of asymmetric membrane microstructures. Specifically, we show that the competition between the propagation of the phase-separation and glass-transition fronts determines the degree of pore-size asymmetry. In conclusion, we also explore the sensitivity of these microstructures to the initial film composition, and compare their formation in 2D and 3D.

37 INORGANIC, ORGANIC, PHYSICAL, AND ANALYTICAL CH↗

DOE OSTI2015

Survey and analysis of multiresolution methods for turbulence data

This paper compares the effectiveness of various multi-resolution geometric representation methods, such as B-spline, Daubechies, Coiflet and Dual-tree wavelets, curvelets and surfacelets, to capture the structure of fully developed turbulence using a truncated set of coefficients. The turbulence dataset is obtained from a Direct Numerical Simulation of buoyancy driven turbulence on a 512 3 mesh size, with an Atwood number, A = 0.05, and turbulent Reynolds number, Re t = 1800, and the methods are tested against quantities pertaining to both velocities and active scalar (density) fields and their derivatives, spectra, and the properties of constant density surfaces. The comparisons between the algorithms are given in terms of performance, accuracy, and compression properties. The results should provide useful information for multi-resolution analysis of turbulence, coherent feature extraction, compression for large datasets handling, as well as simulations algorithms based on multi-resolution methods. In conclusion, the final section provides recommendations for best decomposition algorithms based on several metrics related to computational efficiency and preservation of turbulence properties using a reduced set of coefficients.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Local SU(2) × U(1) quark flavor symmetry in the RS bulk

We propose a model of quark flavor based on an additional SU(2) × U(1) local symmetry in a warped extra dimensional bulk. In contrast to other works, we break the additional gauge symmetry in the bulk via two complex scalars which acquire bulk vevs, rather than relying on brane-localized symmetry breaking. A gauge-covariant Kaluza-Klein decomposition of a theory with a bulk spontaneously broken gauge symmetry is performed, and exact expressions for the bulk profiles of all physical particles in such systems are given. The SM quark masses and mixings are then recreated using gauge-covariant bulk quark mass terms and Yukawa-like couplings to the new bulk scalars. A numerical sampling of points in the model parameter space that recreate the quark masses and mixings is performed at a KK scale of M KK = 5 TeV. We then compute the ΔF = 2 4-quark operators arising from our new flavor gauge bosons and scalars, and those arising from Kaluza-Klein modes of SM gauge bosons. By decoupling one of our bulk scalar fields to all quark fields except the right-handed up-like sector, we find that it is possible to greatly suppress tree-level contributions to the highly constrained Kaon mixing parameters. Instead, the dominant constraints on the model emerge from neutral Bd and D meson mixing. These constraints are explored with our numerical sampling of the model parameter space, and the specific contribution of the new flavor gauge bosons and scalars is discussed. We find that for a significant range of realistic flavor gauge couplings, the new gauge bosons compete with the normally dominant gluon flavor-changing currents, but flavor-changing operators emerging from the bulk scalar fields are highly suppressed. Finally, we briefly comment on flavor constraints that are independent of the flavor gauge sector arising from the Z$\overline{b}$ L b L coupling and rare top decays.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

NASA NTRS1991

Vegetation Biochemistry: What Can Imaging Spectrometry Tell Us About Canopies?

Changes in ecosystem processes such as productivity and decomposition may be expressed in the canopy foliar chemistry resulting from altered carbon allocation patterns, metabolic processes and nutrient availability. Understanding carbon balance on land over large regions requires quantitative determination of leaf constituents such as lignin and total nitrogen from remote sensing imaging systems. Results from spectral reflectance measurements of stacked leaves in the laboratory show that spectrum matching techniques are applicable to the derivation of the equivalent liquid water thickness in plants as well as to the extraction of dry leaf matter reflectance spectra from spectra of green leaves. The residual spectra derived by subtracting water spectra from the spectra of green leaves shows a feature at 1.72 micrometers that can be related to the lignin content of the leaves. Oak leaves have a deeper residual absorption feature than do cotton leaves which is consistent with their relative lignin content. Similar results are achieved when deriving the residuals from images taken over areas of grass and pine trees. Imaging spectrometry provides promise in developing images of various foliar biochemical constituents.

Goetz, Alexander F. H.↗

DOE OSTI2012

Detection of long-term trends in carbon accumulation by forests in Northeastern U.S. and determination of causal factors (Final Report)

The overall project goal was to quantify the trends and variability for Net ecosystem exchange of CO 2 , H 2 O, and energy by northeastern forests, with particular attention to the role of succession, differences in species composition, legacies of past land use, and disturbances. Measurements included flux measurements and observations of biomass accumulation using ecosystem modeling as a framework for data interpretation. Continuation of the long-term record at the Environmental Measurement Site (EMS) Tower was a priority. The final quality-assured CO 2 -flux data now extend through 2010. Data through 2011 are collected but not yet finalized. Biomass observations on the plot array centered on the tower are extended to 2011. Two additional towers in a hemlock stand (HEM) and a younger deciduous stand (LPH) complement the EMS tower by focusing on stands with different species composition or age distribution and disturbance history, but comparable climate and soil type. Over the period since 1993 the forest has added 24.4 Mg-C ha -1 in the living trees. Annual net carbon uptake had been increasing from about 2 Mg-C ha -1 y -1 in the early 1990s to nearly 6 Mg-C ha -1 y -1 by 2008, but declined in 2009-2010. We attribute the increasing carbon uptake to a combination of warmer temperatures, increased photosynthetic efficiency, and increased influence by subcanopy hemlocks that are active in the early spring and late autumn when temperatures are above freezing but the deciduous canopy is bare. Not all of the increased carbon accumulation was found in woody biomass. Results from a study using data to optimize parameters in an ecosystem process model indicate that significant changes in model parameters for photosynthetic capacity and shifts in allocation to slow cycling soil organic matter are necessary for the model to match the observed trends. The emerging working hypothesis is that the pattern of increasing carbon uptake over the early 2000's represents a transient pulse that will eventually end as decomposition of the accumulated carbon catches up.

54 ENVIRONMENTAL SCIENCES↗

NASA NTRS2004

Ecosystem Impacts of Woody Encroachment In Texas: A Spatial Analysis Using AVIRIS

Woody encroachment, the increase of woody plant density relative to herbaceous vegetation, has been documented in drylands of Texas as well as worldwide (Archer 1994, Harrington and Harman 1995, Moleele et al. 2002). Over-grazing, fire suppression and climate change are implicated in the shift from open grasslands to ecosystems now populated by trees and shrubs (Scholes and Archer 1997, Archer et al. 2001), such as Prosopis glandulosa var. glandulosa (honey mesquite) in north Texas (Teague et al. 1997, Ansley et al. 2001, Asner et al. 2003a). Several studies have examined changes in ecosystem properties accompanying woody vegetation encroachment in the Southwest U.S., with research focused on increases in plant and soil carbon (C) and nitrogen (N) stores (Hoffman and Jackson 2000, Asner et al. 2003a), isotopic shifts in these pools (Boutton 1999, Archer et al. 2001), and increases in N cycling rates (Rundel et al. 1982, Hibbard et al. 2001). However, little is known regarding the impact of woody encroachment on N trace gas emissions from dryland regions such as Texas. NOx is produced in the soil during the processes of nitrification and denitrification (Firestone and Davidson 1989). The total N efflux from soils is most directly influenced by the internal cycling of N, which at a regionalscale, is controlled by the inputs and availability of N from vegetation via litterfall and subsequent decomposition (Robertson et al. 1989). Although plot-scale studies are critical to understanding controls over N oxide emissions, regionalization of the measurements is impeded by spatial variation in the factors contributing most to N cycling processes: soil properties (affecting soil moisture regimes and N stocks) and vegetation cover (affecting litter inputs and N uptake). While broad patterns in ecosystem structure and vegetation composition co-vary with general patterns of trace gas emissions (Matson 1997), there is no easily measured index of N availability that can be applied for regional-scale studies of N oxide fluxes. Remote sensing is arguably the only approach available to develop a spatially-explicit understanding of ecosystem processes. More specifically, remotely detectable spatial patterns in the distal controls over soil N properties, such as vegetation cover, land use and soil type (Robertson et al. 1989), should be exploited for regional studies of N oxide emissions. The woody encroachment phenomenon provides an opportunity to test the strength of the relationship between N oxide emissions and those factors controlling the fluxes that can be remotely measured. If such linkages can be firmly established, and if the spatial pattern of distal controls is relevant, then the combination of field measurements and remote sensing offers to improve regional-scale N oxide estimates. The paper presents the utility of linking field based sampling of soil NOx emissions with very high resolution remote sensing estimates of woody vegetation cover from the NASA AVIRIS, Airborne Visible-Infrared Imaging Spectrometer (Green et al. 1998, Asner and Green 2001) and automated spectral mixture analysis (Asner and Lobell 2000, Asner and Heidebrecht 2002) that provide a means to spatially extrapolate soil NOx emissions to the regional scale.

Martin, Roberta E.↗

DOE OSTI2023

The Effect of Rapid Development on Soil CO2 Efflux in a Cellulosic Biofuel Stand

As awareness of climate change increases, the need for carbon neutral fuel sources is growing. Lignocellulosic biofuel derived from pine trees has been suggested as one potential energy source; however, it requires more research before its efficacy for climate change mitigation can be determined. Due to the large share of forest carbon held in soils and the extensive area of pine plantations in the southeast U.S., a better understanding of plantation soil carbon dynamics is critical for biofuel carbon accounting. This study evaluated the effects of canopy development and productivity on soil CO2 efflux, a proxy for soil respiration (Rs), in an intensively managed loblolly pine (Pinus taeda) stand over a period from May 2015 to December 2019. We found that leaf area index (LAI) and gross ecosystem production (GEP), as well as meteorological variables, had significant effects on Rs, but that both overall Rs and soil carbon pools did not increase over the course of the study. We thus hypothesize that GEP and LAI had intra-annual effects on Rs, and that the lack of change in Rs is the result of an increase in autotrophic respiration (Ra) that offset a decrease in decomposition of the previous stand’s organic matter.

09 BIOMASS FUELS↗

DOE OSTI2021

Big Data For Operation and Maintenance Cost Reduction

The purpose of this research is to develop a first-of-a-kind framework for integrating Big Data capability into the daily activities of our current fleet of nuclear power plants. Big Data is traditionally defined as data sets with high volume, velocity, and heterogeneity, and the existing Big Data analytics capabilities are now widely popular in fields such as finance, weather, e-commerce, healthcare and sports. In the nuclear industry, while the volume and velocity of data may present computational challenges for existing analytics capabilities, data heterogeneity are seen to present the major challenge. This research project mainly focuses on incorporating the wide range of data heterogeneities in nuclear power plants into an integrated Big Data Analytics capability. The primary end-product of this project is a Big Data framework that is capable of dealing with the large volume and heterogeneity of the data found in nuclear power plants to extract timely and valuable information on equipment performance. The framework can generate system insights that are actionable relations between measurable impacts and the corresponding maintenance action plans and enable optimization of plant operation and maintenance based on the extracted information. The developed framework is capable of handling heterogeneous data including both image data and time-series sensor data. Specifically, this developed framework includes the following components. The first component is an overarching maintenance ontology which includes system insights required by maintenance optimization. The maintenance ontology interacts with other components in the developed framework. The second component handles Piping & Instrumentation Diagram (P&ID) data. It can be used to extract system components and their relations automatically from the P&IDs. This extracted information is stored in the first component, i.e., maintenance ontology, and is also used as input to the third component, i.e., a tool for generating the fault tree for the corresponding system. The generated fault tree in turn is stored in the ontology for assessing risk that is used as a criterion in maintenance policy optimization. The fourth component is a tool for inferring the parameters in the Markov degradation model for a nuclear system. It uses basic information from the ontology. The fifth component is a tool for assessing the degradation level using sensor measurement data, for example, pressure, flowrate. This tool can be used for determining corrective maintenance actions. The results obtained from components four and five are returned to the ontology. The sixth component of the framework is a tool for optimizing the maintenance policy for a nuclear system of interest. It takes certain basic information from the ontology, e.g., costs of maintenance actions and system failures, as input, and returns the optimal maintenance policy to the ontology. This tool can be used for determining predictive maintenance actions. A set of experiments have also been conducted to verify the algorithms developed in this project for nuclear system degradation monitoring. The experiments are based on four solenoid valves, similar to the ones used in nuclear power plants. The analyses based on the experimental data using two algorithms, i.e., the Randomized Window Decomposition (RWD) algorithm and the particle filtering algorithm, and the results are introduced in the report. The Big Data framework developed in this project can be used as a support tool in daily activities of plant operation and maintenance and will reduce current costs while maintaining or improving safety levels. Overall, the project will not only benefit existing reactors, however it will open new frontiers to realize the long overdue value of Big Data Analytics in the nuclear sphere.

46 INSTRUMENTATION RELATED TO NUCLEAR SCIENCE AND ↗