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All sources NASA NTRS DOE OSTI

DOE OSTI2021

Achieving 5,000-h and 8,000-h Low-PGM Electrode Durability on Automotive Drive Cycles

Whereas total Pt loading in anode and cathode catalysts below 0.125 mg cm −2 is required to meet the stringent cost target for automotive fuel cell systems (FCS) for light duty vehicles, low-loaded cathode catalysts are susceptible to unacceptable aging-related performance losses at high current densities. A framework model, validated by accelerated stress test data, has identified cell voltage, relative humidity (RH) and temperature as the key operating variables that affect degradation of a high-activity d-PtCo/C cathode catalyst with 0.1 mg cm −2 Pt loading. Drive cycle simulations indicate that these can be controlled by properly selecting the minimum FCS power, compressor-expander module (CEM) turndown, and stack coolant temperature. The optimum system parameters are 4-kW e minimum power for an 80-kW e FCS, CEM turndown of 12.5, and 66 °C average coolant exit temperature that combine to limit the maximum cell voltage to 850 mV and outlet RH to 90%–100%. Depending on Pt loading, the mismatch between actual and allowable degradation for 10% power loss over 5,000-h lifetime requires the stack to be oversized by 2.4%–5%, resulting in 8.4%–41% lower Pt utilization and 7.1%–20.5% penalty in stack cost. The corresponding results for 8,000-h lifetime are 10.3%-14% stack oversizing, 23%–51.8% lower Pt utilization, and 24.1%–35.4% stack cost penalty.

08 HYDROGEN↗

DOE OSTI2021

Using heterogeneous data to identify signatures of dengue outbreaks at fine spatio-temporal scales across Brazil

Dengue virus remains a significant public health challenge in Brazil, and seasonal preparation efforts are hindered by variable intra- and interseasonal dynamics. Here, we present a framework for characterizing weekly dengue activity at the Brazilian mesoregion level from 2010–2016 as time series properties that are relevant to forecasting efforts, focusing on outbreak shape, seasonal timing, and pairwise correlations in magnitude and onset. In addition, we use a combination of 18 satellite remote sensing imagery, weather, clinical, mobility, and census data streams and regression methods to identify a parsimonious set of covariates that explain each time series property. The models explained 54% of the variation in outbreak shape, 38% of seasonal onset, 34% of pairwise correlation in outbreak timing, and 11% of pairwise correlation in outbreak magnitude. Regions that have experienced longer periods of drought sensitivity, as captured by the “normalized burn ratio,” experienced less intense outbreaks, while regions with regular fluctuations in relative humidity had less regular seasonal outbreaks. Both the pairwise correlations in outbreak timing and outbreak trend between mesoresgions were best predicted by distance. Our analysis also revealed the presence of distinct geographic clusters where dengue properties tend to be spatially correlated. Forecasting models aimed at predicting the dynamics of dengue activity need to identify the most salient variables capable of contributing to accurate predictions. Our findings show that successful models may need to leverage distinct variables in different locations and be catered to a specific task, such as predicting outbreak magnitude or timing characteristics, to be useful. This advocates in favor of “adaptive models” rather than “one-size-fits-all” models. The results of this study can be applied to improving spatial hierarchical or target-focused forecasting models of dengue activity across Brazil.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2026

Comparative Performance of Gaussian Plume and Backward Lagrangian Stochastic Models for Near-Field Methane Emission Estimation Using a Single Controlled Release Experiment

Methane (CH 4 ) is a major component of natural gas and a potent greenhouse gas. Increasing atmospheric methane concentrations are attributed to emissive anthropogenic activities by an average of 13 ppb per yr since 2020 and are linked to a changing global climate. Mitigating CH 4 emissions from oil and gas production sites has recently become a target to reduce overall greenhouse gas emissions; however, monitoring the efficacy of mitigation strategies depends on accurate quantification of CH 4 emissions at the facility-level. Near-field quantification of methane (CH 4 ) emissions from oil and gas (O&G) facilities remains challenging due to the effects of atmospheric variability and sensor configuration on atmospheric dispersion models. This study evaluates the performance of two atmospheric dispersion models, the Gaussian plume (GP) and backward Lagrangian stochastic (bLS), by comparing calculated CH 4 emissions to controlled single-point emissions between 0.4 and 5.2 kg CH 4 h −1 . Emissions were calculated by both models using 121 individual sets of measurements comprising five-minute averaged downwind methane mixing ratios and matching meteorological data. The comparison shows that the bLS approach achieved a higher proportion of emission estimates within a factor of two (FAC2) of the known emission rates compared to the GP approach. The emissions calculated by the bLS model also had a lower multiplicative error and reduced bias relative to GP. Other error-based metrics further confirmed the bLS model performed better, as it yielded lower RMSE and MAE than GP. Statistical analysis of the emission data shows that the lateral and vertical alignment of the source and the sensor plays a critical role in emission estimations, as measurements made closer to the plume centerline and at a distance between 40 and 80 m downwind yielded the best FAC2 agreement. High wind meander degraded the ability of both approaches to generate representative emissions, particularly with the GP approach, as it violates the modeling approach’s assumption of steady-state emissions. Data suggest emissions calculated by the bLS model are comprehensively in better agreement, but the computational demands of the modeling approach and integration into fenceline systems limit real-time applicability. While these results provide insight into model performance under controlled near-field conditions, their applicability to more complex or heterogeneous oil and gas production environments (e.g., the regions Marcellus or Unita Basins) remains limited and uncertain.

gaussian plume↗

DOE OSTI2025

A Pentavalent HIV-1 Subtype C Vaccine Containing Computationally Selected gp120 Strains Improves the Breadth of V1V2 Region Responses

Background: HIV-1 envelope (Env) variable loops 1 and 2 (V1V2) directed non-neutralizing antibodies were a correlate of decreased transmission risk in the RV144 vaccine trial. Thus, the elicitation and breadth of antibody responses against the V1V2 of HIV-1 Env are important considerations for HIV-1 vaccine candidates. The V1V2 region’s highly variable nature and the extensive diversity of subtype C HIV-1 Envelopes (Envs) make the V1V2 response breadth a high priority for HIV-1 vaccine regimens aiming for V1V2-mediated protection in Southern Africa. Here, we determined whether the breadth of the anti-V1V2 vaccine response can be broadened by including HIV-1 Env strains computationally designed to enhance the coverage of subtype C V1V2 sequence diversity. Methods: Three subtype C Env strains were selected to maximize antibody binding coverage while complementing subtype C vaccine gp120s that were given in human clinical trials in South Africa, as well as to improve epitope accessibility. Humoral immunogenicity of a novel trivalent gp120 vaccine immunogen, a bivalent gp120 boost already in clinical trials (1086C and TV1), and a pentavalent (all five gp120s combined) were evaluated in a preclinical immunization study in guinea pigs. The pentavalent combination was further evaluated with alum versus glucopyranosyl lipid adjuvants formulated in squalene-in-water emulsion (GLA-SE) adjuvants in non-human primates. The breadth of the anti-V1V2 response was assessed using an array of cross-subtype variable loops 1&2 (V1V2) scaffold proteins and linear V2 peptides. Results: The breadth of the IgG response against V1V2 antigens of the trivalent and pentavalent groups was comparable, and both were greater than the breadth of the bivalent group. Linear epitope mapping showed that two linear epitopes in V2 were targeted by the vaccinated animals: the V2 hotspot focused at 169K that potentially correlated with decreased HIV-1 risk in RV144 and the V2.2 site (179LDV/I181) that is part of the integrin α4β7 binding site. The bivalent vaccine elicited a significantly higher magnitude of binding to the V2 hotspot compared to the trivalent vaccine whereas the trivalent vaccine elicited significantly higher binding to the V2.2 epitope compared to the bivalent vaccine, while the pentavalent recognized both regions. Conclusions: These results demonstrate that the three new computationally selected subtype C Envs successfully complemented 1086C and TV1 for broader V1V2 antibody responses, and, in concert with adjuvants that stimulate V1V2 responses, can be considered as part of a rationale immunogen design to improve V1V2 IgG coverage in future vaccine trials in South Africa.

Immunology↗

NASA NTRS1998

Pursuit Latency for Chromatic Targets

The temporal dynamics of eye movement response to a change in direction of stimulus motion has been used to compare the processing speeds of different types of stimuli (Mulligan, ARVO '97). In this study, the pursuit response to colored targets was measured to test the hypothesis that the slow response of the chromatic system (as measured using traditional temporal sensitivity measures such as contrast sensitivity) results in increased eye movement latencies. Subjects viewed a small (0.4 deg) Gaussian spot which moved downward at a speed of 6.6 deg/sec. At a variable time during the trajectory, the dot's direction of motion changed by 30 degrees, either to the right or left. Subjects were instructed to pursue the spot. Eye movements were measured using a video ophthalmoscope with an angular resolution of approximately 1 arc min and a temporal sampling rate of 60 Hz. Stimuli were modulated in chrominance for a variety of hue directions, combined with a range of small luminance increments and decrements, to insure that some of the stimuli fell in the subjects' equiluminance planes. The smooth portions of the resulting eye movement traces were fit by convolving the stimulus velocity with an exponential having variable onset latency, time constant and amplitude. Smooth eye movements with few saccades were observed for all stimuli. Pursuit responses to stimuli having a significant luminance component are well-fit by exponentials having latencies and time constants on the order of 100 msec. Increases in pursuit response latency on the order of 100-200 msec are observed in response to certain stimuli, which occur in pairs of complementary hues, corresponding to the intersection of the stimulus section with the subjects' equiluminant plane. Smooth eye movements can be made in response to purely chromatic stimuli, but are slower than responses to stimuli with a luminance component.

Mulligan, Jeffrey B.↗

NASA NTRS2014

A Framework for Dimensioning VDL-2 Air-Ground Networks

This paper describes a framework developed at MITRE for dimensioning a Very High Frequency (VHF) Digital Link Mode 2 (VDL-2) Air-to-Ground network. This framework was developed to support the FAA's Data Communications (Data Comm) program by providing estimates of expected capacity required for the air-ground network services that will support Controller-Pilot-Data-Link Communications (CPDLC), as well as the spectrum needed to operate the system at required levels of performance. The Data Comm program is part of the FAA's NextGen initiative to implement advanced communication capabilities in the National Airspace System (NAS). The first component of the framework is the radio-frequency (RF) coverage design for the network ground stations. Then we proceed to describe the approach used to assess the aircraft geographical distribution and the data traffic demand expected in the network. The next step is the resource allocation utilizing optimization algorithms developed in MITRE's Spectrum ProspectorTM tool to propose frequency assignment solutions, and a NASA-developed VDL-2 tool to perform simulations and determine whether a proposed plan meets the desired performance requirements. The framework presented is capable of providing quantitative estimates of multiple variables related to the air-ground network, in order to satisfy established coverage, capacity and latency performance requirements. Outputs include: coverage provided at different altitudes; data capacity required in the network, aggregated or on a per ground station basis; spectrum (pool of frequencies) needed for the system to meet a target performance; optimized frequency plan for a given scenario; expected performance given spectrum available; and, estimates of throughput distributions for a given scenario. We conclude with a discussion aimed at providing insight into the tradeoffs and challenges identified with respect to radio resource management for VDL-2 air-ground networks.

Aviation↗

NASA NTRSDate not supplied

TPSAS-NF1676L-11363-DND

The key to the vicarious calibration of historical satellites relies on invariant targets, such as the moon, Dome C, and deserts. Deep convective clouds (DCC) also show promise of being a stable invariant or predictable target viewable by all satellites, since they behave as solar diffusers. However DCC have not been well characterized for calibration. Ten years of well-calibrated MODIS is now available. DCC can easily be identified using IR thresholds, where the IR calibration can be traced to the onboard blackbodies. The natural variability of DCC albedo will be analyzed geographically and seasonally, especially difference of convection initiated over land or ocean.

D R Doelling↗

DOE OSTI2019

Compositionally Graded High Entropy Alloy with a Strong front and ductile base

Material components with variable properties can be ideal for many advanced applications due to their seamless nature of microstructural transition, cost reduction and high resistance of failure. A compositionally graded AlXCoCrFeNi (x=0.3-0.7) high entropy alloy composite build was additively manufactured using laser engineered net shaping (LENSTM). In this high throughput production process, the elemental composition of Al-Co-Cr-Fe-Ni powders in the hoppers were varied and the feed rates were shifted to create a laminate of Al0.3CoCrFeNi and Al0.7CoCrFeNi layers, with a 500 µm wide transition zone of intermediary composition. The energy-dispersive X-ray spectroscopy along the build direction verified the elemental composition matching closely with the targeted compositions. X-ray diffraction revealed the Al0.3CoCrFeNi to be a single-phase fcc structure whereas Al0.7CoCrFeNi had dual phase fcc + B2/ bcc. Scanning electron microscopy was used to capture the microstructural features in the two layers as well as the transition zone. The massive shift in mechanical properties of hardness, dynamic strength and work hardening rates in this graded composite have been discussed. With this endeavor, the microstructural complexity of HEAs has been combined with the unique advantage of LENSTM to achieve an ingenious path to fabricate materials suited applications demanding variable strength and ductility/toughness.

Gwalani, Bharat↗

DOE OSTI2024

Detecting axion dark matter with black hole polarimetry

The axion, as a leading dark matter candidate, is the target of many ongoing and proposed experimental searches based on its coupling to photons. Ultralight axions that couple to photons can also cause polarization rotation of light which can be probed by the cosmic microwave background. In this work, we show that a large axion field is inevitably developed around black holes due to the Bose-Einstein condensation of axions, enhancing the induced birefringence effects. Therefore, measuring the modulation of supermassive black hole imaging polarization angles is a strong probe to the axion-photon coupling due to the formation of the axion condensation (axion star) which enhances the axion field. The oscillating axion field around black holes induces polarization rotation on the black hole image, which is detectable and distinguishable from astrophysical effects on the polarization angle, as it exhibits distinctive temporal variability and frequency invariability. In this work, we perform the theoretical calculation on the axion star formation rate and correspondingly the enhanced axion field value near supermassive black holes. Then, we present the range of axion-photon couplings within the axion mass range 10 − 21 – 10 − 16 eV that can be probed by the Event Horizon Telescope. The axion parameter space probed by black hole polarimetry will expand with the improvement in sensitivity on the polarization measurement and more black hole polarimetry targets with determined black hole masses. Published by the American Physical Society 2024

72 PHYSICS OF ELEMENTARY PARTICLES AND FIELDS↗

DOE OSTI2019

Rosette core fungal resistance in Arabidopsis thaliana

Main conclusion: Unlike rosette leaves, the mature Arabidopsis rosette core can display full resistance to Botrytis cinerea revealing the importance for spatial and developmental aspects of plant fungal resistance. Abstract: Arabidopsis thaliana is a model host to investigate plant defense against fungi. However, many of the reports investigating Arabidopsis fungal defense against the necrotrophic fungus, Botrytis cinerea, utilize rosette leaves as host tissue. Here we report organ-dependent differences in B. cinerea resistance of Arabidopsis. Although wild-type Arabidopsis rosette leaves mount a jasmonate-dependent defense that slows fungal growth, this defense is incapable of resisting fungal devastation. In contrast, as the fungus spreads through infected leaf petioles towards the plant center, or rosette core, there is a jasmonate- and age-dependent fungal penetration blockage into the rosette core. In this paper, we report evidence for induced and preformed resistance in the rosette core, as direct rosette core inoculation can also result in resistance, but at a lower penetrance relative to infections that approach the core from infected leaf petioles. The Arabidopsis rosette core displays a distinct transcriptome relative to other plant organs, and BLADE ON PETIOLE (BOP) transcripts are abundant in the rosette core. The BOP genes, with known roles in abscission zone formation, are required for full Arabidopsis rosette core B. cinerea resistance, suggesting a possible role for BOP-dependent modifications that may help to restrict fungal susceptibility of the rosette core. Finally, we demonstrate that cabbage and cauliflower, common Brassicaceae crops, also display leaf susceptibility and rosette core resistance to B. cinerea that can involve leaf abscission. Thus, spatial and developmental aspects of plant host resistance play critical roles in resistance to necrotrophic fungal pathogens and are important to our understanding of plant defense mechanisms.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2015

The INNs and outs of antibody nonproprietary names

An important step in drug development is the assignment of an International Nonproprietary Name (INN) by the World Health Organization (WHO) that provides healthcare professionals with a unique and universally available designated name to identify each pharmaceutical substance. Monoclonal antibody INNs comprise a –mab suffix preceded by a substem indicating the antibody type, e.g., chimeric (-xi-), humanized (-zu-), or human (-u-). The WHO publishes INN definitions that specify how new monoclonal antibody therapeutics are categorized and adapts the definitions to new technologies. However, rapid progress in antibody technologies has blurred the boundaries between existing antibody categories and created a burgeoning array of new antibody formats. Thus, revising the INN system for antibodies is akin to aiming for a rapidly moving target. The WHO recently revised INN definitions for antibodies now to be based on amino acid sequence identity. These new definitions, however, are critically flawed as they are ambiguous and go against decades of scientific literature. A key concern is the imposition of an arbitrary threshold for identity against human germline antibody variable region sequences. This leads to inconsistent classification of somatically mutated human antibodies, humanized antibodies as well as antibodies derived from semi-synthetic/synthetic libraries and transgenic animals. Such sequence-based classification implies clear functional distinction between categories (e.g., immunogenicity). However, there is no scientific evidence to support this. Dialog between the WHO INN Expert Group and key stakeholders is needed to develop a new INN system for antibodies and to avoid confusion and miscommunication between researchers and clinicians prescribing antibodies.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2017

Feedback control design for non-inductively sustained scenarios in NSTX-U using TRANSP

This paper examines a method for real-time control of non-inductively sustained scenarios in NSTX-U by using TRANSP, a time-dependent integrated modeling code for prediction and interpretive analysis of tokamak experimental data, as a simulator. The actuators considered for control in this work are the six neutral beam sources and the plasma boundary shape. To understand the response of the plasma current, stored energy, and central safety factor to these actuators and to enable systematic design of control algorithms, simulations were run in which the actuators were modulated and a linearized dynamic response model was generated. A multi-variable model-based control scheme that accounts for the coupling and slow dynamics of the system while mitigating the effect of actuator limitations was designed and simulated. Simulations show that modest changes in the outer gap and heating power can improve the response time of the system, reject perturbations, and track target values of the controlled values.

70 PLASMA PHYSICS AND FUSION TECHNOLOGY↗

DOE OSTI2013

ASTEROSEISMIC CLASSIFICATION OF STELLAR POPULATIONS AMONG 13,000 RED GIANTS OBSERVED BY KEPLER

Of the more than 150,000 targets followed by the Kepler Mission, about 10% were selected as red giants. Due to their high scientific value, in particular for Galaxy population studies and stellar structure and evolution, their Kepler light curves were made public in late 2011. More than 13,000 (over 85%) of these stars show intrinsic flux variability caused by solar-like oscillations making them ideal for large-scale asteroseismic investigations. We automatically extracted individual frequencies and measured the period spacings of the dipole modes in nearly every red giant. These measurements naturally classify the stars into various populations, such as the red giant branch, the low-mass (M/M{sub Sun} {approx}< 1.8) helium-core-burning red clump, and the higher-mass (M/M{sub Sun} {approx}> 1.8) secondary clump. The period spacings also reveal that a large fraction of the stars show rotationally induced frequency splittings. This sample of stars will undoubtedly provide an extremely valuable source for studying the stellar population in the direction of the Kepler field, in particular when combined with complementary spectroscopic surveys.

79 ASTRONOMY AND ASTROPHYSICS↗

DOE OSTI2013

Impact of variable RBE on proton fractionation

Purpose: To explore the impact of variable proton relative biological effectiveness (RBE) on dose fractionation for clinically relevant situations. A generic RBE = 1.1 is generally used for isoeffect calculations, while experimental studies showed that proton RBE varies with tissue type, dose, and linear energy transfer (LET). Methods: An analytical expression for the LET and {alpha}/{beta} dependence of the linear-quadratic (LQ) model has been used for proton simulations in parallel with the assumption of a generic RBE = 1.1. Calculations have been performed for ranges of LET values and fractionation sensitivities to describe clinically relevant cases, such as the treatment of head and neck and prostate tumors. Isoeffect calculations were compared with predictions from a generic RBE value and reported clinical results. Results: The generic RBE = 1.1 appears to be a reasonable estimate for the proton RBE of rapidly growing tissues irradiated with low LET radiation. However, the use of a variable RBE predicts larger differences for tissues with low {alpha}/{beta} (both tumor and normal) and at low doses per fraction. In some situations these differences may appear in contrast to the findings from photon studies highlighting the importance of accurate accounting for the radiobiological effectiveness of protons. Furthermore, the use of variable RBE leads to closer predictions to clinical results. Conclusions: The LET dependence of the RBE has a strong impact on the predicted effectiveness of fractionated proton radiotherapy. The magnitude of the effect is modulated by the fractionation sensitivity and the fractional dose indicating the need for accurate analyses both in the target and around it. Care should therefore be employed for changing clinical fractionation patterns or when analyzing results from clinical studies for this type of radiation.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2023

Drivers of stability and transience in composition-functioning links during serial propagation of litter-decomposing microbial communities

ABSTRACT Biotic factors that influence the temporal stability of microbial community functioning are an emerging research focus for the control of natural and engineered systems. The discovery of common features within community ensembles that differ in functional stability over time is a starting point to explore biotic factors. We serially propagated a suite of soil microbial communities through five generations of 28-day microcosm incubations to examine microbial community compositional and functional stability during plant litter decomposition. Using dissolved organic carbon (DOC) abundance as a target function, we hypothesized that microbial diversity, compositional stability, and associated changes in interactions would explain the relative stability of the ecosystem function between generations. Communities with initially high DOC abundance tended to converge towards a “low DOC” phenotype within two generations, but across all microcosms, functional stability between generations was highly variable. By splitting communities into two cohorts based on their relative DOC functional stability, we found that compositional shifts, diversity, and interaction network complexity were associated with the stability of DOC abundance between generations. Further, our results showed that legacy effects were important in determining compositional and functional outcomes, and we identified taxa associated with high DOC abundance. In the context of litter decomposition, achieving functionally stable communities is required to utilize soil microbiomes to increase DOC abundance and long-term terrestrial DOC sequestration as one solution to reduce atmospheric carbon dioxide concentrations. Identifying factors that stabilize function for a community of interest may improve the success of microbiome engineering applications. IMPORTANCE Microbial community functioning can be highly dynamic over time. Identifying and understanding biotic factors that control functional stability is of significant interest for natural and engineered communities alike. Using plant litter–decomposing communities as a model system, this study examined the stability of ecosystem function over time following repeated community transfers. By identifying microbial community features that are associated with stable ecosystem functions, microbial communities can be manipulated in ways that promote the consistency and reliability of the desired function, improving outcomes and increasing the utility of microorganisms.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2018

CESM1(WACCM) Stratospheric Aerosol Geoengineering Large Ensemble Project

This paper describes the stratospheric aerosol geoengineering large ensemble (GLENS) project, which promotes the use of an unique model dataset, performed with Community Earth System Model, using the Whole Atmosphere Community Climate Model as its atmospheric component (CESM1(WACCM)), to investigate global and regional impacts of geoengineering. The performed simulations target multiple simultaneous climate goals unlike many earlier studies that targeted globally averaged surface temperature. This strategic approach is expected to reduce some of the previously found adverse effects of stratospheric aerosol geoengineering, including uneven cooling between the poles and equator and shifts in tropical precipitation. An ensemble of 20 members allows the identification of forced changes in global and regional climate variables in the coupled atmosphere, land, sea-ice, and ocean system in the presence of internal variability. Here, we invite the broader community to perform in-depth analysis of climate related impacts and to identify processes that lead to changes in the climate system as the result of a strategic application of stratospheric aerosol geoengineering. (Capsule Summary) A community project that enables analysis of robust global and regional changes resulting from strategic stratospheric aerosol geoengineering in the presence of internal climate variability.

58 GEOSCIENCES↗

DOE OSTI2025

Development of the Contamination Distribution Centered Toxics Mobility Vulnerability Index in the Beaumont–Port Arthur Region of Texas

This study advances the Toxics Mobility Inventory (TMI) and the Toxics Mobility Vulnerability Index (TMVI) to develop a new tool to assess the movement of hazardous substances and their implications for vulnerable communities. It emphasizes the need to include contamination distribution variables in such indices to address disproportionate impacts and more accurately reflect vulnerability. The study uses the TMI framework and TMVI methodology in the Beaumont–Port Arthur region of Texas, also integrating contamination distribution considerations into the analysis to develop a new framework and process. The new Contamination Distribution Centered Toxics Mobility Vulnerability Index (CDC-TMVI) consolidates climate change and topography variables into a broader built environment vulnerability category while introducing a contamination sources category. Using ArcGIS Pro and ToxPi tools, the study evaluates 27 geospatial variables across four categories: built environment vulnerability, social vulnerability, health outcomes, and contamination sources. The results indicate significant contributions from contamination and social vulnerability variables, highlighting areas with higher risks of flooding and air pollution. This article advocates for future research and policy efforts to enhance the integration of contamination sources and their spatial distributions into toxics mobility assessments to better protect vulnerable populations. Furthermore, the unique methodology and findings serve as a basis for developing targeted measures and strategic planning to improve environmental health.

contamination↗

DOE OSTI2023

Evaluation of global teleconnections in CMIP6 climate projections using complex networks

In climatological research, the evaluation of climate models is one of the central research subjects. As an expression of large-scale dynamical processes, global teleconnections play a major role in interannual to decadal climate variability. Their realistic representation is an indispensable requirement for the simulation of climate change, both natural and anthropogenic. Therefore, the evaluation of global teleconnections is of utmost importance when assessing the physical plausibility of climate projections. We present an application of the graph-theoretical analysis tool δ-MAPS, which constructs complex networks on the basis of spatio-temporal gridded data sets, here sea surface temperature and geopotential height at 500 hPa. Complex networks complement more traditional methods in the analysis of climate variability, like the classification of circulation regimes or empirical orthogonal functions, assuming a new non-linear perspective. While doing so, a number of technical tools and metrics, borrowed from different fields of data science, are implemented into the δ-MAPS framework in order to overcome specific challenges posed by our target problem. Those are trend empirical orthogonal functions (EOFs), distance correlation and distance multicorrelation, and the structural similarity index. δ-MAPS is a two-stage algorithm. In the first place, it assembles grid cells with highly coherent temporal evolution into so-called domains. In a second step, the teleconnections between the domains are inferred by means of the non-linear distance correlation. We construct 2 unipartite and 1 bipartite network for 22 historical CMIP6 climate projections and 2 century-long coupled reanalyses (CERA-20C and 20CRv3). Potential non-stationarity is taken into account by the use of moving time windows. The networks derived from projection data are compared to those from reanalyses. Our results indicate that no single climate projection outperforms all others in every aspect of the evaluation. But there are indeed models which tend to perform better/worse in many aspects. Differences in model performance are generally low within the geopotential height unipartite networks but higher in sea surface temperature and most pronounced in the bipartite network representing the interaction between ocean and atmosphere.

58 GEOSCIENCES↗