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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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At least 1,405 records · Page 78
All sourcesNASA NTRSDOE OSTI
DOE OSTI2022

Overall Performance Losses and Activated Mechanisms in Double Glass and Glass-backsheet Photovoltaic Modules with Monofacial and Bifacial PERC Cells, under Accelerated Exposures

Commercial PV modules have various packaging choices nowadays, which influence their long-term reliability. This study compared the degradation behaviors of sixteen module variants from two brands with varying encapsulant materials (EVA or POE), encapsulant types, module architectures (GB or DG), and cell types (monofacial or bifacial) using null hypothesis testing to determine statistical significant findings. The modules were exposed for 2,520 hours under two accelerated exposures: modified damp heat (mDH) and modified damp heat with full-spectrum light (mDH+FSL). For both brands, two DG module variants with UV-Cutoff rear encapsulant are found to have significantly lower average power loss than the module variants of EVA+GB with opaque rear encapsulant after each accelerated exposure. Metallization interconnect corrosion is identified as the primary degradation mechanism. Furthermore, unsupervised hierarchical clustering finds that the degradation behaviors of modules from one brand with a more strict manufacturing quality control depends on module architectures only.

14 SOLAR ENERGY↗
DOE OSTI2021

Fuzzified PaCcET for Economic-Emission Scheduling of Microgrids

In this paper, a new approach is proposed to solve a multi-objective economic-emission scheduling problem in microgrids (MGs) by simultaneously minimizing the energy and emission costs of the MG with various distributed energy resources (DERs). The proposed approach is an extension of a computationally effective multiobjective optimization technique, Pareto concavity elimination transformation (PaCcET). The proposed approach, referred to as Fuzzified-PaCcET, employs a fuzzy logic controller to dynamically revise crossover and mutation rates in the original PaCcET leading to the faster convergence of the solution. The proposed approach finds the best Pareto front, also referred to as a Non-dominated set (NDS) of solutions, instead of finding a single optimal solution. In order to find the solutions on concave areas of the Pareto front, an iterative objective space transformation is performed in the PaCcET algorithm to allow a linear combination of objective functions (in the transformed objective space). The proposed Fuzzified-PaCcET-based scheduling is implemented on a MG with various dispatchable and non-dispatchable DERs to find the set of optimal solutions according to the total fuel cost of DERs, as well as the most optimum environmental cost. In order to extract the best compromise solution (BCS) among NDS of solutions, a fuzzy-based method is implemented. The comparison of the simulation results of the Fuzzified-PaCcET with that of PaCcET shows that Fuzzified-PaCcET can generate better solution with less computational burden.

Gautam, Mukesh↗
DOE OSTI2021

Global patterns of forest autotrophic carbon fluxes

Carbon (C) fixation, allocation, and metabolism by trees set the basis for energy and material flows in forest ecosystems and define their interactions with Earth’s changing climate. However, we lack a cohesive synthesis on how forest carbon fluxes vary globally with respect to climate and one another. Here, we draw upon 1,319 records from the Global Forest Carbon Database (ForC), representing all major forest types and the nine most significant autotrophic carbon fluxes, to comprehensively explore how C cycling in mature, undisturbed forests varies with latitude and climate on a global scale. We show that, across all flux variables analyzed, C cycling decreases continuously with absolute latitude – a finding that confirms multiple previous studies but contradicts the idea that net primary productivity of temperate forests rivals that of tropical forests. C flux variables generally displayed similar trends across latitude and multiple climate variables, with no differences in allocation detected at this global scale. Temperature variables in general, and mean annual temperature and temperature seasonality in particular, were the best univariate predictors of C flux, explaining 19 - 71% of variation in the C fluxes analyzed. The effects of temperature were modified by moisture availability, with C flux reduced under hot and dry conditions and sometimes under very high precipitation. C fluxes increased with growing season length, but this was never the best univariate predictor. Within the growing season, the influence of climate on C cycling was small but significant for a number of flux variables. These findings clarify how forest C flux varies with latitude and climate on a global scale. In a period of accelerating climatic change, this improved understanding of the fundamental climatic controls on forest C cycling sets a foundation for understanding patterns of change.

Banbury Morgan, Rebecca↗
DOE OSTI2022

Responsiveness of miscanthus and switchgrass yields to stand age and nitrogen fertilization: A meta‐regression analysis

Abstract Optimal management of the perennial bioenergy crops, miscanthus and switchgrass, requires an understanding of their responsiveness to nitrogen (N) fertilizer at different maturity stages across locations and growing conditions. Earlier studies that have examined the yield response of these crops to N and stand age using field experiments or meta‐analysis techniques provide mixed evidence. We extend earlier studies by applying a multi‐level mixed‐effects (MLME) meta‐regression model to conduct a more extensive multivariate regression of yield response of these crops to N and stand age, while controlling for climate and location conditions and unobserved factors related to study design. Our findings are based on 1403 and 2811 yield observations for miscanthus and switchgrass, respectively, from experiments conducted between 2002 and 2019 across the rainfed region in the United States. We find statistically significant evidence that an additional year of maturity increases miscanthus and switchgrass yields but at a decreasing rate; yields peak at the 7th and 6th year respectively, for the observed range of applied N rates and stands. We also find that an increase in N application increases yield by a statistically significant level, but at a declining rate; the magnitude of the yield response to N is, however, small and varies with the age of the crop. The impact of N is larger on older compared to younger and middle‐aged stands of miscanthus. In contrast, the impact of N on switchgrass is larger on middle‐aged compared to younger and older stands of switchgrass. We do not find a statistically significant effect of soil productivity on yield for either crop. This analysis provides a basis for developing N application recommendations and optimal rotation age for miscanthus and switchgrass and shows that these energy crops can grow just as productively on low productivity land as on high productivity land.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Determining spatially varying profit‐maximizing management practices for miscanthus and switchgrass production in the rainfed United States

Abstract Determining optimal management practices for the profitable production of perennial energy crops is critical for scaling up production beyond experimental levels. Although many experimental field studies have examined the effects of management practices on the performance of miscanthus and switchgrass, there are no recommendations for economically optimal nitrogen (N) application rates and how they should vary spatially and with the age of the energy crop as well as on optimal rotation age of the energy crop to maximize profits. We develop a modeling framework to determine economically optimal crop management decisions and simulate the variability under various scenarios for miscanthus and switchgrass production across 2287 counties in the rainfed United States. We find that profit‐maximizing N recommendations for these crops vary across maturity stages and regions and can increase the landowner's profits compared with a uniform N rate across ages and regions. We also find that the optimal rotation for these crops is shorter than the productive physical lifespan (15–20 and 10 years for miscanthus and switchgrass, respectively). Specifically, the N rate that maximizes the economic returns is negligible for miscanthus and 111 kg ha −1 for switchgrass production at age 2. The mean profit‐maximizing N rate increases with age for miscanthus, peaking at 151 kg ha −1 at age 11 before declining to 114 kg ha −1 at the optimal rotation age of 13 years while that for switchgrass is 150 kg ha −1 for middle‐aged stands and declines to 114 kg ha −1 at the optimal rotation of 8–9 years. We find that miscanthus is the most profitable energy crop in the northern region of the rainfed United States while switchgrass is most profitable in the south of the rainfed United States. Our findings are useful for improving assessments of the profitability of energy crops and guiding future management decisions by landowners.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2024

Chemical signature characterization with hyperspectral imagery: novel deep learning model architectures and physically-motivated data augmentation techniques

The high spectral resolution afforded by Hyperspectral Imaging (HSI) sensors is poised to bring unprecedented advancements to signature characterization applications. Thus far, much of the research in the machine learning field devoted to HSI applications has focused on a few specific tasks like land-use land-cover classification. In land classification tasks, spatial information is very important, and model architectures are often designed to leverage spatial contexts. However, it is unclear how well these spatially-tuned models will translate to tasks where spectral information is critical, like the detection and characterization of chemicals. In this work, we compare spectral models (inputs are 1D spectra) and spatial-spectral models (inputs are 3D cubes) in the context of predicting chemical concentration maps. We find that spatial-spectral models perform the best, though we find a wide range in performance across the different architectures tested. Additionally, we find that model performance is impacted by the availability of training data, particularly in scenarios where the training data doesn't fully capture the true variance of real-world conditions. We find that data augmentation can help mitigate sparse coverage of observed parameter space (e.g., seasonal or geographic variability in ground cover), and present augmentation strategies that are tailored to hyperspectral data.

• Artificial intelligence (AI) / machine learning ↗
DOE OSTI2015

MO-F-CAMPUS-T-03: Continuous Dose Delivery with Gamma Knife Perfexion

Purpose: We propose continuous dose delivery techniques for stereotactic treatments delivered by Gamma Knife Perfexion using inverse treatment planning system that can be applied to various tumour sites in the brain. We test the accuracy of the plans on Perfexion’s planning system (GammaPlan) to ensure the obtained plans are viable. This approach introduces continuous dose delivery for Perefxion, as opposed to the currently employed step-and-shoot approaches, for different tumour sites. Additionally, this is the first realization of automated inverse planning on GammaPlan. Methods: The inverse planning approach is divided into two steps of identifying a quality path inside the target, and finding the best collimator composition for the path. To find a path, we select strategic regions inside the target volume and find a path that visits each region exactly once. This path is then passed to a mathematical model which finds the best combination of collimators and their durations. The mathematical model minimizes the dose spillage to the surrounding tissues while ensuring the prescribed dose is delivered to the target(s). Organs-at-risk and their corresponding allowable doses can also be added to the model to protect adjacent organs. Results: We test this approach on various tumour sizes and sites. The quality of the obtained treatment plans are comparable or better than forward plans and inverse plans that use step- and-shoot technique. The conformity indices in the obtained continuous dose delivery plans are similar to those of forward plans while the beam-on time is improved on average (see Table 1 in supporting document). Conclusion: We employ inverse planning for continuous dose delivery in Perfexion for brain tumours. The quality of the obtained plans is similar to forward and inverse plans that use conventional step-and-shoot technique. We tested the inverse plans on GammaPlan to verify clinical relevance. This research was partially supported by Elekta, Sweden (vendor of Gamma Knife Perfexion)

60 APPLIED LIFE SCIENCES↗
DOE OSTI2016

Reducing false positives of microcalcification detection systems by removal of breast arterial calcifications

Purpose: In the past decades, computer-aided detection (CADe) systems have been developed to aid screening radiologists in the detection of malignant microcalcifications. These systems are useful to avoid perceptual oversights and can increase the radiologists’ detection rate. However, due to the high number of false positives marked by these CADe systems, they are not yet suitable as an independent reader. Breast arterial calcifications (BACs) are one of the most frequent false positives marked by CADe systems. In this study, a method is proposed for the elimination of BACs as positive findings. Removal of these false positives will increase the performance of the CADe system in finding malignant microcalcifications. Methods: A multistage method is proposed for the removal of BAC findings. The first stage consists of a microcalcification candidate selection, segmentation and grouping of the microcalcifications, and classification to remove obvious false positives. In the second stage, a case-based selection is applied where cases are selected which contain BACs. In the final stage, BACs are removed from the selected cases. The BACs removal stage consists of a GentleBoost classifier trained on microcalcification features describing their shape, topology, and texture. Additionally, novel features are introduced to discriminate BACs from other positive findings. Results: The CADe system was evaluated with and without BACs removal. Here, both systems were applied on a validation set containing 1088 cases of which 95 cases contained malignant microcalcifications. After bootstrapping, free-response receiver operating characteristics and receiver operating characteristics analyses were carried out. Performance between the two systems was compared at 0.98 and 0.95 specificity. At a specificity of 0.98, the sensitivity increased from 37% to 52% and the sensitivity increased from 62% up to 76% at a specificity of 0.95. Partial areas under the curve in the specificity range of 0.8–1.0 were significantly different between the system without BACs removal and the system with BACs removal, 0.129 ± 0.009 versus 0.144 ± 0.008 (p<0.05), respectively. Additionally, the sensitivity at one false positive per 50 cases and one false positive per 25 cases increased as well, 37% versus 51% (p<0.05) and 58% versus 67% (p<0.05) sensitivity, respectively. Additionally, the CADe system with BACs removal reduces the number of false positives per case by 29% on average. The same sensitivity at one false positive per 50 cases in the CADe system without BACs removal can be achieved at one false positive per 80 cases in the CADe system with BACs removal. Conclusions: By using dedicated algorithms to detect and remove breast arterial calcifications, the performance of CADe systems can be improved, in particular, at false positive rates representative for operating points used in screening.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2019

Surface Water Microbial Community Response to the Biocide 2,2-Dibromo-3-Nitrilopropionamide, Used in Unconventional Oil and Gas Extraction

Production of unconventional oil and gas continues to rise, but the effects of high-density hydraulic fracturing (HF) activity near aquatic ecosystems are not fully understood. A commonly used biocide in HF, 2,2-dibromo-3-nitrilopropionamide (DBNPA), was studied in microcosms of HF-impacted (HF+) versus HF-unimpacted (HF-) surface water streams to (i) compare the microbial community response, (ii) investigate DBNPA degradation products based on past HF exposure, and (iii) compare the microbial community response differences and similarities between the HF biocides DBNPA and glutaraldehyde. The microbial community responded to DBNPA differently in HF-impacted versus HF-unimpacted microcosms in terms of the number of 16S rRNA gene copies quantified, alpha and beta diversity, and differential abundance analyses of microbial community composition through time. The differences in microbial community changes affected degradation dynamics. HF-impacted microbial communities were more sensitive to DBNPA, causing the biocide and by-products of the degradation to persist for longer than in HF-unimpacted microcosms. A total of 17 DBNPA by-products were detected, many of them not widely known as DBNPA by-products. Many of the brominated by-products detected that are believed to be uncharacterized may pose environmental and health impacts. Similar taxa were able to tolerate glutaraldehyde and DBNPA; however, DBNPA was not as effective for microbial control, as indicated by a smaller overall decrease of 16S rRNA gene copies/ml after exposure to the biocide, and a more diverse set of taxa was able to tolerate it. These findings suggest that past HF activity in streams can affect the microbial community response to environmental perturbation such as that caused by the biocide DBNPA. IMPORTANCE Unconventional oil and gas activity can affect pH, total organic carbon, and microbial communities in surface water, altering their ability to respond to new environmental and/or anthropogenic perturbations. These findings demonstrate that 2,2-dibromo-3-nitrilopropionamide (DBNPA), a common hydraulic fracturing (HF) biocide, affects microbial communities differently as a consequence of past HF exposure, persisting longer in HF-impacted (HF+) waters. These findings also demonstrate that DBNPA has low efficacy in environmental microbial communities regardless of HF impact. These findings are of interest, as understanding microbial responses is key for formulating remediation strategies in unconventional oil and gas (UOG)-impacted environments. Moreover, some DBNPA degradation by-products are even more toxic and recalcitrant than DBNPA itself, and this work identifies novel brominated degradation by-products formed.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2016

Proteome Remodeling in Response to Sulfur Limitation in “ Candidatus Pelagibacter ubique”

“ Ca . Pelagibacter ubique” is a key driver of marine biogeochemistry cycles and a model for understanding how minimal genomes evolved in free-living anucleate organisms. This study explores the unusual sulfur acquisition strategy that has evolved in these cells, which lack assimilatory sulfate reduction and instead rely on reduced sulfur compounds found in oxic marine environments to meet their cellular quotas. Our findings demonstrate that the sulfur acquisition systems are constitutively expressed but the enzymatic steps leading to the essential sulfur-containing amino acid methionine are regulated by a unique array of riboswitches and genes, many of which are encoded in a rapidly evolving genome region. These findings support mounting evidence that streamlined cells have evolved regulatory mechanisms that minimize transcriptional switching and, unexpectedly, localize essential sulfur acquisition genes in a genome region normally associated with adaption to environmental variation.

Smith, Daniel P.↗
DOE OSTI2017

Monte Carlo Glauber wounded nucleon model with meson cloud

We study the effect of the nucleon meson cloud on predictions of the Monte Carlo Glauber wounded nucleon model for AA, pA, and pp collisions. From the analysis of the data on the charged multiplicity density in AA collisions we find that the meson–baryon Fock component reduces the required fraction of binary collisions by a factor of ~2 for Au + Au collisions at √s = 0.2 TeV and ~1.5 for Pb + Pb collisions at √s = 2.76 TeV. For central AA collisions, the meson cloud can increase the multiplicity density by ~16–18%. We give predictions for the midrapidity charged multiplicity density in Pb + Pb collisions at √s = 5.02 TeV for the future LHC run 2. We find that the meson cloud has a weak effect on the centrality dependence of the ellipticity ϵ{sub 2} in AA collisions. For collisions of the deformed uranium nuclei at √s = 0.2 TeV, we find that the meson cloud may improve somewhat agreement with the data on the dependence of the elliptic flow on the charged multiplicity for very small centralities defined via the ZDCs signals. We find that the meson cloud may lead to a noticeable reduction of ϵ{sub 2} and the size of the fireball in pA and pp collisions.

73 NUCLEAR PHYSICS AND RADIATION PHYSICS↗
DOE OSTI2018

Likelihood analysis of the sub-GUT MSSM in light of LHC 13-TeV data

We describe a likelihood analysis using MasterCode of variants of the MSSM in which the soft supersymmetry-breaking parameters are assumed to have universal values at some scale M in below the supersymmet-ric grand unification scale M GUT , as can occur in mirage mediation and other models. In addition to M in , such ‘sub-GUT’ models have the 4 parameters of the CMSSM, namely a common gaugino mass m 1/2 , a common soft supersymmetry-breaking scalar mass m 0 , a common trilinear mixing parameter A and the ratio of MSSM Higgs vevs tan β, assuming that the Higgs mixing parameter μ> 0. We take into account constraints on strongly- and electroweakly-interacting sparticles from ~ 36/fb of LHC data at 13 TeV and the LUX and 2017 PICO, XENON1T and PandaX-II searches for dark matter scattering, in addition to the previous LHC and dark matter constraints as well as full sets of flavour and electroweak constraints. We find a preference for Min ~ 10 5 to 10 9 GeV, with M in ~ M GUT disfavoured by &Delta;χ 2 ~ 3 due to the BR(B s,d → μ + μ - ) constraint. The lower limits on strongly-interacting sparticles are largely determined by LHC searches, and similar to those in the CMSSM. We find a preference for the LSP to be a Bino or Higgsino with m$\mathbb -0\atop{X1} $ ~ 1 TeV, with annihilation via heavy Higgs bosons H/A and stop coannihilation, or chargino coannihilation, bringing the cold dark matter density into the cosmological range. We find that spin-independent dark matter scattering is likely to be within reach of the planned LUX-Zeplin and XENONnT experiments. We probe the impact of the (g - 2) μ constraint, finding similar results whether or not it is included.

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗
DOE OSTI2021

ArborX

ArborX library tackles a problem of efficiently finding geometric objects that are close in space. Variations of this problem, such as finding the nearest neighbors of a point, or finding all objects within a certain distance, are inherent components of applications in many fields. The data may be large so that solving the problem efficiently may require significant computational resources, such as multiple processors or accelerators such as general purpose GPUs. ArborX' main advantage in its ability to solve large problems efficiently utilizing a combination of distributed and on-node parallelism. ArborX can be run efficiently on a wide variety of hardware, including GPUs from different vendors, which distinguishes it from other available libraries which typically choose only few of these. The other advantage is that it supports both types of user problems: spatial problems (useful for intersections and finding objects within certain distance), and nearest neighbor problems. ArborX also supports flexible interface in its interaction with a user. Particularly, it allows a user to call user's own function on a positive match, a functionality not rarely available in other libraries. ArborX implements construction and traversal algorithms using efficient tree structures, such as bounding volume hierarchy (BVH). At its core, it uses linear BVH for its low construction cost and sufficient quality. ArborX is written using C++, and is parallelized using the message passing interface (MPI) for the distributed communication, and the Kokkos library for on-node parallelism. This approach allows ArborX to be run on a wide variety of hardware, from common laptops and desktops to supercomputers while using the same codebase. ArborX also implements several advanced algorithms using geometric search, such as density-based clustering algorithm DBSCAN.

ECP↗
DOE OSTI2025

ArborX 2.0

ArborX library tackles a problem of efficiently finding geometric objects that are close in space. Variations of this problem, such as finding the nearest neighbors of a point, or finding all objects within a certain distance, are inherent components of applications in many fields. The data may be large so that solving the problem efficiently may require significant computational resources, such as multiple processors or accelerators such as general purpose GPUs. ArborX' main advantage in its ability to solve large problems efficiently utilizing a combination of distributed and on-node parallelism. ArborX can be run efficiently on a wide variety of hardware, including GPUs from different vendors, which distinguishes it from other available libraries which typically choose only few of these. The other advantage is that it supports both types of user problems: spatial problems (useful for intersections and finding objects within certain distance), and nearest neighbor problems. ArborX also supports flexible interface in its interaction with a user. Particularly, it allows a user to call user's own function on a positive match, a functionality not rarely available in other libraries. ArborX implements construction and traversal algorithms using efficient tree structures, such as bounding volume hierarchy (BVH). At its core, ArborX uses linear BVH for its low construction cost and sufficient quality. ArborX implements both spatial and nearest-neighbor traversal algorithms. ArborX also provides several clustering algorithms (minimum spanning tree, DBSCAN, HDBSCAN*), interpolation using minimum least squares and ray tracing. ArborX is written using C++, and is parallelized using the message passing interface (MPI) for the distributed communication, and the Kokkos library for on-node parallelism. This approach allows ArborX to be run on a wide variety of hardware, from common laptops and desktops to supercomputers while using the same codebase.

Prokopenko, Andrey [Oak Ridge National Laboratory ↗
DOE OSTI2020

A terminology for in situ visualization and analysis systems

The term "in situ processing" has evolved over the last decade to mean both a specific strategy for visualizing and analyzing data and an umbrella term for a processing paradigm. The resulting confusion makes it difficult for visualization and analysis scientists to communicate with each other and with their stakeholders. To address this problem, a group of over 50 experts convened with the goal of standardizing terminology. This paper summarizes their findings and proposes a new terminology for describing in situ systems. An important finding from this group was that in situ systems are best described via multiple, distinct axes: integration type, proximity, access, division of execution, operation controls, and output type. This paper discusses these axes, evaluates existing systems within the axes, and explores how currently used terms relate to the axes.

97 MATHEMATICS AND COMPUTING↗
DOE OSTI2019

The Value of {sup 99m}Tc-PSMA SPECT/CT-Guided Surgery for Identifying and Locating Lymph Node Metastasis in Prostate Cancer Patients

Background: This study evaluated the effect of technetium-99m ({sup 99m}Tc)-labeled prostate-specific membrane antigen (PSMA)-based image-guided surgery on the oncologic outcomes for patients with primary or recurrent prostate cancer (PCa). Methods: This study retrospectively analyzed 54 consecutive patients with PCa who underwent {sup 99m}Tc-labeled PSMA-based image-guided surgery between January 2016 and September 2017. These patients received a radical prostatectomy (RP) with pelvic lymph node dissection (PLND) or salvage lymph node dissection (sLND). The resected specimens were compared with findings of postoperative histologic analysis. The responses to the treatment were recorded during the follow-up period. Results: In 31 patients, PSMA single-photon emission computerized tomography (SPECT) and computed tomography (CT) could find 52 suspicious lymph node metastases (LNMs). With the help of PSMA SPECT/CT, 12 patients with recurrence received sLND, 19 primary PCa patients received RP with extended PLND, and 23 primary PCa patients received RP with standard PLND. The findings showed that PSMA SPECT/CT could detect LNMs with high sensitivity and specificity. In six patients, PSMA SPECT/CT could find more LNMs that were not found by MRI and help to modify the extent of lymphadenectomy. At the latest follow-up evaluation, 39 patients showed a biochemical response (BR), 9 patients showed a biochemical recurrence (BCR) after BR, and 6 patients never exhibited BR. The patients who received RP with standard PLND or extended PLND had a better prostate-specific antigen (PSA) response than the patients who received sLND. The patients with pelvic LNMs also had a better PSA response than the patients with retroperitoneal LNMs. Conclusions: This study showed that {sup 99m}Tc-PSMA SPECT/CT-guided surgery can remove more LNMs than conventional imaging with high sensitivity and specificity and delay disease progression in PCa patients.

62 RADIOLOGY AND NUCLEAR MEDICINE↗
DOE OSTI2026

Data for Impact of Vertical and Seasonal Variation in Leaf Traits on Simulating Soybean Canopy Photosynthesis via 1D and 3D Modeling

Accurate modeling of photosynthesis is crucial for predicting crop productivity and quantifying the carbon cycle in agroecosystems. Leaf traits are essential inputs for modeling canopy photosynthesis. Yet, many existing models still use fixed plant functional type (PTF)-based values to parameterize leaf traits under a big-leaf or two-big-leaf assumption, neglecting their vertical profiles and seasonal changes. This simplification may introduce significant uncertainties in estimating gross primary productivity (GPP). In this study, we simulated soybean GPP and tested the effects of vertical and seasonal variation in three key leaf photosynthetic traits: the maximum carboxylation rate at 25 °C (Vcmax25), leaf chlorophyll content (LCC), and leaf mass per area (LMA) in the 1D-SCOPE and 3D-Helios models. Weekly field measurements were conducted during the growing season of 2024 to support the simulation. We designed ten leaf trait parameterization schemes by incorporating different combinations of vertical profiles and seasonal changes, while assuming homogeneous canopy architecture in both models. Our results revealed that Vcmax25 vertical and seasonal variation had the strongest influence on simulated GPP in both 1D and 3D models, while LCC and LMA effects were minimal. Particularly, the scheme with an empirically parameterized Vcmax25 profile achieved comparable performance to the scheme with the measured Vcmax25 profile. Both 1D-SCOPE and 3D-Helios accurately modeled GPP (SCOPE: R2 = 0.87, Bias = 0.55 µmol m⁻² s⁻¹; Helios: R2 = 0.9, Bias = 0.22 µmol m⁻² s⁻¹) under the most complex scheme, and their responses to vertical and seasonal variation in leaf traits were consistent, demonstrating the robustness of our findings. Based on our findings, we propose a scalable framework for parameterizing leaf traits to improve GPP simulations. This study contributes to improving the representation of leaf trait dynamics in canopy-level photosynthesis models, potentially enhancing our ability to predict crop productivity and understand agroecosystem carbon dynamics.

Photosynthesis↗
DOE OSTI2016

Toward an Understanding of the Environmental and Public Health Impacts of Unconventional Natural Gas Development: A Categorical Assessment of the Peer-Reviewed Scientific Literature, 2009-2015

The body of science evaluating the potential impacts of unconventional natural gas development (UNGD) has grown significantly in recent years, although many data gaps remain. Still, a broad empirical understanding of the impacts is beginning to emerge amidst a swell of research. The present categorical assessment provides an overview of the peer reviewed scientific literature from 2009–2015 as it relates to the potential impacts of UNGD on public health, water quality, and air quality. We have categorized all available original research during this time period in an attempt to understand the weight and direction of the scientific literature. Our results indicate that at least 685 papers have been published in peer-reviewed scientific journals that are relevant to assessing the impacts of UNGD. 84% of public health studies contain findings that indicate public health hazards, elevated risks, or adverse health outcomes; 69% of water quality studies contain findings that indicate potential, positive association, or actual incidence of water contamination; and 87% of air quality studies contain findings that indicate elevated air pollutant emissions and/or atmospheric concentrations. This paper demonstrates that the weight of the findings in the scientific literature indicates hazards and elevated risks to human health as well as possible adverse health outcomes associated with UNGD. There are limitations to this type of assessment and it is only intended to provide a snapshot of the scientific knowledge based on the available literature. However, this work can be used to identify themes that lie in or across studies, to prioritize future research, and to provide an empirical foundation for policy decisions.

03 NATURAL GAS↗