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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 397 records · Page 22
All sourcesNASA NTRSDOE OSTI
DOE OSTI2021

Metabolic Source Isotopic Pair Labeling and Genome-Wide Association Are Complementary Tools for the Identification of Metabolite-Gene Associations in Plants

The optimal extraction of information from untargeted metabolomics analyses is a continuing challenge. Here, we describe an approach that combines stable isotope labeling, liquid chromatography– mass spectrometry (LC–MS), and a computational pipeline to automatically identify metabolites produced from a selected metabolic precursor. Here, we identified the subset of the soluble metabolome generated from phenylalanine (Phe) in Arabidopsis thaliana, which we refer to as the Phe-derived metabolome (FDM) In addition to identifying Phe-derived metabolites present in a single wild-type reference accession, the FDM was established in nine enzymatic and regulatory mutants in the phenylpropanoid pathway. To identify genes associated with variation in Phe-derived metabolites in Arabidopsis, MS features collected by untargeted metabolite profiling of an Arabidopsis diversity panel were retrospectively annotated to the FDM and natural genetic variants responsible for differences in accumulation of FDM features were identified by genome-wide association. Large differences in Phe-derived metabolite accumulation and presence/absence variation of abundant metabolites were observed in the nine mutants as well as between accessions from the diversity panel. Many Phe-derived metabolites that accumulated in mutants also accumulated in non-Col-0 accessions and was associated to genes with known or suspected functions in the phenylpropanoid pathway as well as genes with no known functions. Overall, we show that cataloguing a biochemical pathway’s products through isotopic labeling across genetic variants can substantially contribute to the identification of metabolites and genes associated with their biosynthesis.

09 BIOMASS FUELS↗
DOE OSTI2024

On the nature of apparent transient sources on the National Geographic Society–Palomar Observatory Sky Survey glass copy plates

Abstract We examine critically recent claims for the presence of above-atmosphere optical transients in publicly available digitized scans of Schmidt telescope photographic plate material derived from the National Geographic Society–Palomar Observatory Sky Survey. We employ the publicly available SuperCOSMOS Sky Survey catalogues to examine statistically the morphology of the sources. We develop a simple, objective, and automated image classification scheme based on a random forest decision tree classifier. We find that the putative transients are likely to be spurious artefacts of the photographic emulsion. We suggest a possible cause of the appearance of these images as resulting from the copying procedure employed to disseminate glass copy survey atlas sets in the era before large-scale digitization programmes.

Hambly, N. C. (ORCID:0000000299019064)↗
DOE OSTI2023

A global perspective on bacterial diversity in the terrestrial deep subsurface

While recent efforts to catalogue Earth’s microbial diversity have focused upon surface and marine habitats, 12–20% of Earth’s biomass is suggested to exist in the terrestrial deep subsurface, compared to ~1.8% in the deep subseafloor. Metagenomic studies of the terrestrial deep subsurface have yielded a trove of divergent and functionally important microbiomes from a range of localities. However, a wider perspective of microbial diversity and its relationship to environmental conditions within the terrestrial deep subsurface is still required. Our meta-analysis reveals that terrestrial deep subsurface microbiota are dominated by Betaproteobacteria, Gammaproteobacteria and Firmicutes, probably as a function of the diverse metabolic strategies of these taxa. Evidence was also found for a common small consortium of prevalent Betaproteobacteria and Gammaproteobacteria operational taxonomic units across the localities. This implies a core terrestrial deep subsurface community, irrespective of aquifer lithology, depth and other variables, that may play an important role in colonizing and sustaining microbial habitats in the deep terrestrial subsurface. An in silico contamination-aware approach to analysing this dataset underscores the importance of downstream methods for assuring that robust conclusions can be reached from deep subsurface-derived sequencing data. Understanding the global panorama of microbial diversity and ecological dynamics in the deep terrestrial subsurface provides a first step towards understanding the role of microbes in global subsurface element and nutrient cycling.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2026

Dark Energy Survey Year 6 results: Redshift calibration of the MagLim++ lens sample

In this work, we derive and calibrate the redshift distribution of the MagLim++ lens galaxy sample used in the Dark Energy Survey Year 6 (DES Y6) 3 x 2pt cosmology analysis. The 3 x 2pt analysis combines galaxy clustering from the lens galaxy sample and weak gravitational lensing. The redshift distributions are inferred using the SOMPZ method - a Self-Organizing Map framework that combines deep-field multi-band photometry, wide-field data, and a synthetic source injection ( B alrog) catalog. Key improvements over the DES Year 3 (Y3) calibration include a noise-weighted SOM metric, an expanded Balrog catalogue, and an improved scheme for propagating systematic uncertainties, which allows us to generate O(10 8 ) redshift realizations that collectively span the dominant sources of uncertainty. These realizations are then combined with independent clustering-redshift measurements via importance sampling. The resulting calibration achieves typical uncertainties on the mean redshift of 1-2%, corresponding to a 20-30% average reduction relative to DES Y3. We compress the n(z) uncertainties into a small number of orthogonal modes for use in cosmological inference. Marginalizing over these modes leads to only a minor degradation in cosmological constraints. Here, this analysis establishes the MagLim++ sample as a robust lens sample for precision cosmology with DES Y6 and provides a scalable framework for future surveys.

dark energy↗
DOE OSTI2022

Analytic Gaussian covariance matrices for galaxy N-point correlation functions

Here, we derive analytic covariance matrices for the N-point correlation functions (NPCFs) of galaxies in the Gaussian limit. Our results are given for arbitrary N and projected onto the isotropic basis functions given by spherical harmonics and Wigner 3j symbols. A numerical implementation of the 4PCF covariance is compared to the sample covariance obtained from a set of lognormal simulations, Quijote dark matter halo catalogues, and MultiDark-Patchy galaxy mocks, with the latter including realistic survey geometry. The analytic formalism gives reasonable predictions for the covariances estimated from mock simulations with a periodic-box geometry. Furthermore, fitting for an effective volume and number density by maximizing a likelihood based on Kullback-Leibler divergence is shown to partially compensate for the effects of a nonuniform window function. Our result is recently shown to facilitate NPCF analysis on a realistic survey data.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

A consensus protocol for the recovery of mercury methylation genes from metagenomes

Abstract Mercury (Hg) methylation genes ( hgcAB ) mediate the formation of the toxic methylmercury and have been identified from diverse environments, including freshwater and marine ecosystems, Arctic permafrost, forest and paddy soils, coal‐ash amended sediments, chlor‐alkali plants discharges and geothermal springs. Here we present the first attempt at a standardized protocol for the detection, identification and quantification of hgc genes from metagenomes. Our Hg‐cycling microorganisms in aquatic and terrestrial ecosystems (Hg‐MATE) database, a catalogue of hgc genes, provides the most accurate information to date on the taxonomic identity and functional/metabolic attributes of microorganisms responsible for Hg methylation in the environment. Furthermore, we introduce “marky‐coco”, a ready‐to‐use bioinformatic pipeline based on de novo single‐metagenome assembly, for easy and accurate characterization of hgc genes from environmental samples. We compared the recovery of hgc genes from environmental metagenomes using the marky‐coco pipeline with an approach based on coassembly of multiple metagenomes. Our data show similar efficiency in both approaches for most environments except those with high diversity (i.e., paddy soils) for which a coassembly approach was preferred. Finally, we discuss the definition of true hgc genes and methods to normalize hgc gene counts from metagenomes.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2024

Rev1 overexpression accelerates N -methyl- N -nitrosourea (MNU)-induced thymic lymphoma by increasing mutagenesis

Rev1 has two important functions in the translesion synthesis pathway, including dCMP transferase activity, and acts as a scaffolding protein for other polymerases involved in translesion synthesis. However, the role of Rev1 in mutagenesis and tumorigenesis in vivo remains unclear. We previously generated Rev1-overexpressing (Rev1-Tg) mice and reported that they exhibited a significantly increased incidence of intestinal adenoma and thymic lymphoma (TL) after N-methyl-N-nitrosourea (MNU) treatment. In this study, we investigated mutagenesis of MNU-induced TL tumorigenesis in wild-type (WT) and Rev1-Tg mice using diverse approaches, including whole-exome sequencing (WES). In Rev1-Tg TLs, the mutation frequency was higher than that in WT TL in most cases. However, no difference in the number of nonsynonymous mutations in the Catalogue of Somatic Mutations in Cancer (COSMIC) genes was observed, and mutations involved in Notch1 and MAPK signaling were similarly detected in both TLs. Mutational signature analysis of WT and Rev1-Tg TLs revealed cosine similarity with COSMIC mutational SBS5 (aging-related) and SBS11 (alkylation-related). Interestingly, the total number of mutations, but not the genotypes of WT and Rev1-Tg, was positively correlated with the relative contribution of SBS5 in individual TLs, suggesting that genetic instability could be accelerated in Rev1-Tg TLs. Finally, we demonstrated that preleukemic cells could be detected earlier in Rev1-Tg mice than in WT mice, following MNU treatment. In conclusion, Rev1 overexpression accelerates mutagenesis and increases the incidence of MNU-induced TL by shortening the latency period, which may be associated with more frequent DNA damage-induced genetic instability.

60 APPLIED LIFE SCIENCES↗
DOE OSTI2021

The tundra phenology database: more than two decades of tundra phenology responses to climate change

Observations of changes in phenology have provided some of the strongest signals of the effects of climate change on terrestrial ecosystems. The International Tundra Experiment (ITEX), initiated in the early 1990s, established a common protocol to measure plant phenology in tundra study areas across the globe. Today, this valuable collection of phenology measurements depicts the responses of plants at the colder extremes of our planet to experimental and ambient changes in temperature over the past decades. The database contains 150 434 phenology observations of 278 plant species taken at 28 study areas for periods of 1–26 years. Here we describe the full data set to increase the visibility and use of these data in global analyses and to invite phenology data contributions from underrepresented tundra locations. Portions of this tundra phenology database have been used in three recent syntheses, some data sets are expanded, others are from entirely new study areas, and the entirety of these data are now available at the Polar Data Catalogue (https://doi.org/10.21963/13215).

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Algorithms in Diffraction Profile Analysis

This chapter introduces several approaches to crystallographic structure refinement from diffraction profile data including the Rietveld method, global optimization methods, and Bayesian modeling. First, the Rietveld method and related nonlinear least squares approaches to analyzing diffraction profiles are briefly discussed. We then review the most common algorithms within global optimization as alternative methods of structure solution: grid search, simulated annealing, and genetic algorithms. As the Rietveld method is the standard tool for analyzing diffraction profile data, we catalogue its challenges and limitations. A Bayesian approach to diffraction profile analysis is presented as an alternative, along with several sampling algorithms including Gibbs sampling, variants of Metropolis sampling, Hamiltonian Monte Carlo, and approximate Bayesian computing. These sampling algorithms are applied to the fitting of a neutron diffraction profile from a National Institute of Standards and Technology silicon standard reference material, and their results are compared.

Singh, Susheela↗
DOE OSTI2020

Tidal Disruption Event Galaxy Binner

This software simulates astronomical survey detections of tidal disruptions of stars by super-massive black holes. It begins with the synthetic galaxy catalogue described in van Velzen 2008 (https://arxiv.org/abs/1707.03458). The stellar disruption rate in each galaxy is estimated based on Stone & Metzger 2016 (https://arxiv.org/abs/1410.7772). Based on these rates, and the present-day stellar mass function in the galaxy, disruptions are randomly sampled, and the properties of the resulting flares are sampled based on empirical distributions. The code also accounts for obscuration by dust in the host galaxy. Finally, the survey selection effects are applied. The detectable simulated flares are stored in a database, allowing histograms of their properties to be created.

Roth, NathanielJ.↗
DOE OSTI2020

Earth microbial co-occurrence network reveals interconnection pattern across microbiomes

Microbial interactions shape the structure and function of microbial communities; microbial association networks in specic environments have been widely developed to explore these complex systems, but their wired pattern across microbiomes in various environments at the global scale remains unexplored. Here we have inferred an Earth microbial association network from a communal catalogue with 23,595 samples and 12,646 exact sequence variants from 14 environments in the Earth Microbiome Project dataset. Results: This non-random scale-free Earth microbial association network consisted of 8 taxonomy distinct modules linked with dierent environments, which featured environment specic microbial associations. Dierent topological features of subnetworks inferred from datasets trimmed into uniform size indicate distinct association patterns in the microbiomes of various environments. The proportions of specialist edges, which ranged from 43.0% to 65.7%, highlight that environmental specic microbial associations are essential features of microbiomes in various environments. Based on edge-overlap similarity, the microbiomes of various environments were clustered into two groups, which were mainly bridged by the microbiomes of plant and animal surface. Acidobacteria Gp2 and Nisaea were identied as hubs in most of subnetworks. Negative edges proportions ranged from 1.9% in the soil subnetwork to 48.9% the non-saline surface subnetwork, suggesting various environments experience distinct intensities of competition or niche dierentiation. Conclusion: This investigation provides a new resource for examining Earth microbial association patterns across environments and emphasizes the network perspective for comprehensively understanding unique microbiome features. Keywords: Association pattern; Earth microbiomes; Genelist edges; Network hubs; Negative associations; Specialist edges; Topological properties

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2022

Analyzing Stochastic Computer Models: A Review with Opportunities

In modern science, computer models are often used to understand complex phenomena and a thriving statistical community has grown around analyzing them. This review aims to bring a spotlight to the growing prevalence of stochastic computer models-providing a catalogue of statistical methods for practitioners, an introductory view for statisticians (whether familiar with deterministic computer models or not), and an emphasis on open questions of relevance to practitioners and statisticians. Gaussian process surrogate models take center stage in this review, and these, along with several extensions needed for stochastic settings, are explained. The basic issues of designing a stochastic computer experiment and calibrating a stochastic computer model are prominent in the discussion. Instructive examples, with data and code, are used to describe the implementation of, and results from, various methods.

agent based model↗
DOE OSTI2021

AbacusSummit Halo Light Cone Catalogs

This is a set of halo light cone catalogs from the AbacusSummit suite of cosmological N-body simulations (abacussummit.readthedocs.io/). They are a value-added data product provided by post-processing the simulation output. The main application of the halo light cone catalogs is the construction of realistic mock galaxy catalogues and weak lensing maps on the sky. The algorithm (described in Hadzhiyska et al. 2021) associates CompaSO halos from 29 redshift epochs spanning z = 0.1-2.5 with their particles at the time of light-cone crossing. It then records the halo and particle information into an easily accessible product, which can be read with the CompaSO reader. The 25 base resolution boxes at fiducial cosmology have a halo light cone catalog covering an octant of the sky to z approx 0.8 and about 2000 deg2 extending to z approx 2.4. The huge boxes provide light cone information of the full sky until z approx 2.18 and extend further towards the corners of the box (available until z = 2.25). Galaxy mock catalogs on the sky can be generated easily though the AbacusHOD script providing an extended HOD framework (see Yuan et al. 2021, for details), which has been modified to work with the halo light cone catalogs. The available tracers are luminous red galaxies (LRGs), emission-line galaxies (ELGs), and quasi-stellar objects (QSOs).

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2022

CO2 pipeline data catalog

This "Data Catalog" is an excel spreadsheet of collected and catalogued spatial and non-spatial public datasets in relevance to and support of CO2 transport (pipelines) infrastructure development and risk modeling. Includes data associated with CO2 sources, sinks, and transportation.

CO2↗
DOE OSTI2021

Reconstruction of Pre- and Post-Test Surfaces at the U-20az BARNWELL Site, Nevada National Security Site

Technical report on results of photogrammetric reconstruction task at NNSS. Modern photogrammetric methods were applied to historic aerial photographs taken six days before and four days after the BARNWELL underground nuclear explosion (UNE) to recreate the pre-UNE topography and the fresh post-UNE surface. The surfaces were compared to each other to characterize surface effects of the BARNWELL UNE. Topographic changes between the pre-UNE and post-UNE surfaces were limited to minor rock fall and intentional changes related to construction activities. Methods developed in this study could potentially be used across a much wider area to discover and catalogue as yet undescribed subtle underground nuclear explosion surface effects.

58 GEOSCIENCES↗
DOE OSTI2022

Mining G.O.L.D. (Geothermal Opportunities Leveraged Through Data): Exploring Synergies Between the Geothermal and Mining Industries

This report analyzes potential collaborations between the geothermal and locatable mineral industries (focused on the portion of the Basin and Range Province within Nevada, United States of America). The objectives of this study included analyzing: 1. The type and quality of data collected by the locatable mineral industry to determine feasibility for geothermal resource exploration; 2. The regulatory pathways and potential barriers that could prevent development of geothermal resources discovered via a mining claim (and vice versa) in the United States; 3. The historical development of geothermal resources discovered via mineral exploration data in the United States and illustrations of co-located mining and geothermal power projects; 4. The value propositions for both the locatable mineral and the geothermal industries to collaborate. This article concludes that many of the data collected by the mining industry as part of locatable mineral exploration (e.g., copper, gold, lithium) would also be useful for identifying and developing previously unknown geothermal resources (and in some notable cases, already have led to geothermal resource development). In addition, for minimal costs, the mining industry could catalogue these data and potentially monetize the data itself or use the data in the future to develop a geothermal project. Leveraging these locatable mineral data to develop geothermal resources and/or co-located minerals and geothermal resources would represent significant cost savings when compared to developing geothermal resources under a business-as-usual scenario as well as compared to current generating technologies (e.g., diesel-powered generators) employed at remote mining operations. Ultimately, leveraging mining industry data, knowledge, and expertise serves to effectively expand the geothermal exploration workforce, increase the rate of geothermal resource discovery, and potentially reduce geothermal electricity's levelized cost of energy (LCOE) by 23%-29%.

15 GEOTHERMAL ENERGY↗
DOE OSTI2023

Chromium Tolerant, Highly Active and Stable Electrocatalytic Internal Surface Coating for Cathode of Commercial SOFCs (Final Report)

This project is aimed to develop a chromium (Cr) tolerant, highly active, and stable coating layer on the internal surfaces of the porous composite cathode from commercially available SOFCs. Such coating layer was developed using the additive manufacturing process of Atomic Layer Deposition (ALD) and has been applied on the cathode consisting of either an electronic conductor of LaxSr 1-x MnyO 3-δ (LSM) or mixed ionic and electronic conducting La x Sr 1-x Co y Fe 1-y O 3-δ (LSCF). PI's work has demonstrated that the internal surface of cathode from the commercial cells, can be further tailored using ALD coating to dramatically enhance the cell performance. For instance, ALD layer consisting heterostructured nano composite of nano-Pt and nano-(Mn 0.8 Co 0.2 ) 3 O 4 oxide on the internal surface of porous LSM/YSZ cathode from SOFCs, has resulted in the large reduction of the cell polarizations resistance by up to 53%, and enormous increase of power density over 370%. For the cells with LSCF/Sm 2 O 3 doped CeO 2 (SDC) cathode, the conformal layer of nano-composite consisting of superjacent CoOx and subjacent minimum amount of Pt nano-grains has resulted in the power density enhancement by 126% for the large scale industry tubular cells at 750°C, and both the performance enhancement and nanostructure of the ALD layer are stable over ~ 2000 h continuous operation performed at industry test station. In the meanwhile, those ALD coating layer developed by PI's work is also inherently Cr-tolerant, and could act as physical barrier for preventing Cr diffusion into the cathode backbone, so as to mitigate the Cr poisoning effect on the cathode. In this project, the impact of Cr on the performance of those ALD coated commercial cells has been evaluated. Based on evolution of the cell performance, the ALD coating layer chemistry and ALD coating layer thickness has been optimized to maximize the overall Cr tolerance, cell power density and cell longevity. Different ALD coating has been applied onto the internal surface of LSM/YSZ and LSCF/SDC backbone respectively. The architecture/scaffold structures on the internal surface of different cathode, designed by this project, was catalogued and analyzed using High Resolution Transmission Electron Microscopy (HRTEM), and cell power/durability performance are assured via comprehensive electrochemical performance testing in the industry operation relevant conditions. The impact of the electrochemical operation current density, the water humidity, the cell operation temperature, and cell operation duration on the Cr tolerance of ALD coated cells has been systematically investigated. There is completely different nanostructure degradation mechanisms between LSM and LSCF cells induced by Cr contamination. For the LSCF/SDC baseline cell, With the Cr source, there is no apparent Sr surface segregation phase even for the baseline cell operated for 3000 h at 750 °C. With the Cr source, there is significant amorphous (SrCr)Ox phase accumulated in the original pore region. For the commercial baseline cells, Cr contaminants on the LSM electrode severely impacted the entire cell's electrochemical performance and nanostructure degradation. Those degradations include (1). Peak power density loss of 64 % after 109 h of operation. The dramatic increase in Rp (2). They are cracking at LSM/SSZ interface, LSM grains. SSZ remains intact but with (CrMn)Ox. By contrast, ALD coating (MnCo)Ox/Pt dramatically improves the Cr resistance, as follows (1). ALD-coated cell with a power density is 280-380 % of the baseline cell, depending on the ALD layer thickness. (2). For a cell with a 20 nm thick ALD layer, there is a large performance enhancement (> 200 % power density) induced by ALD coating of Cr-tolerant Mn 0.8 Co 0.2 Ox. (3). For a cell with a 20 nm thick ALD layer, after 168 h at 750 °C power density of the ALD-coated cell is ~ 600% of that baseline cell upon operation with Cr contamination for 109 h. The ALD coating on the internal surface of cathode developed by this project integrated multi-functions. Those multi-functions include (1). Dramatically improving the cell power density for the commercial cells; (2). Dramatically improving contamination resistance of the cathode, for being an excellent protection coating layer sealing off Cr contamination. (3). Dramatically increasing the cell longevity by potentially preventing the microstructure evolution and grain coarsening of the cathode. Overall, this project will provide a simple solution to simultaneously enhance power density and increase the reliability, robustness, and endurance of commercial SOFCs, over the entire operating temperature range of 650-800 °C. For the inherently functional SOFC, the ALD coating of LSM based cathode mitigate the Cr-contamination. Power density of ALD-coated cell is ~ 600% of that baseline cell upon operation with Cr contamination. In addition to SOFCs, the novel on-demand design approach and creation of multifunctional heterogeneous architecture on the electrode surface presented in this work opens further research for their application in other types of fuel cells, batteries, and sensors for which electrochemical reactions on the surface are similarly critical.

36 MATERIALS SCIENCE↗
DOE OSTI2023

Community Resilience Indicator Analysis: Commonly Used Indicators from Peer-Reviewed Research (Updated for Research Published 2003-2021)

In 2017, FEMA’s National Integration Center (NIC) Technical Assistance (TA) Branch identified a need to establish a data-driven basis for prioritizing locations for TA investment and guiding local emergency management planning. To achieve this goal, FEMA tasked Argonne National Laboratory (Argonne) with identifying commonly used indicators of community resilience across the landscape of published peer-reviewed research. FEMA and Argonne completed the first Community Resilience Indicator Analysis (CRIA) in 2018 and repeated the process in 2022. The CRIA process begins with a literature review and cataloguing of published peer-reviewed assessment methodologies on social vulnerability and community resilience. The literature review findings are then filtered by inclusion criteria established by the CRIA research team to ensure the methodologies are: (1) Quantitative, (2) Data and methodology are publicly available, (3) Calculated at the county level or lower, (4) Examine generalized hazard risk (rather than a singular hazard), and (5) Focused on pre-disaster community conditions. After this, the research team identifies the commonly used indicators across these methodologies and selects the best data source for each indicator. Finally, the research team bins the data for visual display, conducts a correlation analysis and creates a composite index, the FEMA Community Resilience Index (FEMA CRI). In 2018, the CRIA identified eight resilience and vulnerability assessment methodologies and 20 commonly used indicators (indicators used in three or more of the eight methodologies). The FEMA CRI in 2018 was created from these 20 indicators and was produced for at the county level. The 2022 CRIA updated the literature review to expand the list of methodologies examined and followed the same process, resulting in an analysis of 14 methodologies published between 2003 and 2021 and 22 indicators identified as commonly used (indicators used in five or more of the 14 methodologies). In 2022, the research team produced the FEMA CRI at the county and the census tract levels. To make the CRIA data more accessible and more actionable, each individual indicator and the FEMA CRI is binned and included in FEMA’s Resilience Analysis and Planning Tool (RAPT). RAPT enables emergency managers and community partners to quickly visualize relative differences in potential resilience by county, tribe and census tract. By reviewing the data for each of these 22 indicators individually, emergency managers can gain insights for targeted outreach strategies, planning, mitigation investments and response and recovery operations. Communities, regional governments and others can use this data to better understand potential challenges to resilience. As the social science field of examining and validating indicators of resilience evolves, FEMA will update RAPT to provide emergency managers and community partners with additional data and tools to inform planning, mitigation, response and recovery. It is important to understand that the role of the emergency manager is not to change or to “improve” the data, but to plan appropriately for the community characteristics reflected in the data. These datasets are community characteristics that researchers have identified as important considerations for resilience. For example, people with disabilities may have greater challenges to be resilient to disasters. If a community has a high population of people with disabilities, the emergency manager(s) may need to create tailored preparedness outreach programs and strategies to ensure those residents have support if evacuation is necessary. Rather than label these indicators as an absolute measure of resilience, FEMA considers “potential challenges to resilience” a better frame to understand these indicators. Everyone is vulnerable to disasters. While scholars theorize that certain characteristics may make an individual or a household more socially vulnerable, the data does not reflect measures that individuals and/or communities have taken to address potential challenges, such as emergency management planning and outreach or household preparedness measures. To aid emergency managers in understanding how to use these indicators, calling them potential challenges to resilience supports a more positive and strategic application of the data in all phases of emergency management.

99 GENERAL AND MISCELLANEOUS↗