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At least 1,387 records · Page 77
All sourcesNASA NTRSDOE OSTI
DOE OSTI2024

Impact of survey spatial variability on galaxy redshift distributions and the cosmological 3 × 2-point statistics for the Rubin Legacy Survey of Space and Time (LSST)

We investigate the impact of spatial survey non-uniformity on the galaxy redshift distributions for forthcoming data releases of the Rubin Observatory Legacy Survey of Space and Time (LSST). Specifically, we construct a mock photometry data set degraded by the Rubin OpSim observing conditions, and estimate photometric redshifts of the sample using a template-fitting photo-z estimator, BPZ, and a machine learning method, FlexZBoost. We select the Gold sample, defined as $i\lt 25.3$ for 10 yr LSST data, with an adjusted magnitude cut for each year and divide it into five tomographic redshift bins for the weak lensing lens and source samples. We quantify the change in the number of objects, mean redshift, and width of each tomographic bin as a function of the coadd i-band depth for 1-yr (Y1), 3-yr (Y3), and 5-yr (Y5) data. In particular, Y3 and Y5 have large non-uniformity due to the rolling cadence of LSST, hence provide a worst-case scenario of the impact from non-uniformity. We find that these quantities typically increase with depth, and the variation can be $10\!-\!40~{{\rm per\ cent}}$ at extreme depth values. Using Y3 as an example, we propagate the variable depth effect to the weak lensing $3\times 2$ pt analysis, and assess the impact on cosmological parameters via a Fisher forecast. We find that galaxy clustering is most susceptible to variable depth, and non-uniformity needs to be mitigated below 3 per cent to recover unbiased cosmological constraints. There is little impact on galaxy–shear and shear–shear power spectra, given the expected LSST Y3 noise.

cosmology↗
DOE OSTI2023

Detection of the significant impact of source clustering on higher order statistics with DES Year 3 weak gravitational lensing data

We measure the impact of source galaxy clustering on higher order summary statistics of weak gravitational lensing data. By comparing simulated data with galaxies that either trace or do not trace the underlying density field, we show that this effect can exceed measurement uncertainties for common higher order statistics for certain analysis choices. We evaluate the impact on different weak lensing observables, finding that third moments and wavelet phase harmonics are more affected than peak count statistics. Using Dark Energy Survey (DES) Year 3 (Y3) data, we construct null tests for the source-clustering-free case, finding a p-value of p = 4 × 10 −3 (2.6σ) using third-order map moments and p = 3 × 10 −11 (6.5σ) using wavelet phase harmonics. The impact of source clustering on cosmological inference can be either included in the model or minimized through ad hoc procedures (e.g. scale cuts). We verify that the procedures adopted in existing DES Y3 cosmological analyses were sufficient to render this effect negligible. Failing to account for source clustering can significantly impact cosmological inference from higher order gravitational lensing statistics, e.g. higher order N-point functions, wavelet-moment observables, and deep learning or field-level summary statistics of weak lensing maps.

79 ASTRONOMY AND ASTROPHYSICS↗
DOE OSTI2024

Major impacts of widespread structural variation on sorghum

Genetic diversity is critical to crop breeding and improvement, and dissection of the genomic variation underlying agronomic traits can both assist breeding and give insight into basic biological mechanisms. Although recent genome analyses in plants reveal many structural variants (SVs), most current studies of crop genetic variation are dominated by single-nucleotide polymorphisms (SNPs). The extent of the impact of SVs on global trait variation, as well as their utility in genome-wide selection, is not yet understood. In this study, we built an SV data set based on whole-genome resequencing of diverse sorghum lines (n = 363), validated the correlation of photoperiod sensitivity and variety type, and identified SV hotspots underlying the divergent evolution of cellulosic and sweet sorghum. In addition, we showed the complementary contribution of SVs for heritability of traits related to sorghum adaptation. Importantly, inclusion of SV polymorphisms in association studies revealed genotype–phenotype associations not observed with SNPs alone. Three-way genome-wide association studies (GWAS) based on whole-genome SNP, SV, and integrated SNP + SV data sets showed substantial associations between SVs and sorghum traits. The addition of SVs to GWAS substantially increased heritability estimates for some traits, indicating their important contribution to functional allelic variation at the genome level. Our discovery of the widespread impacts of SVs on heritable gene expression variation could render a plausible mechanism for their disproportionate impact on phenotypic variation. This study expands our knowledge of SVs and emphasizes the extensive impacts of SVs on sorghum.

59 BASIC BIOLOGICAL SCIENCES↗
DOE OSTI2021

Application of machine learning in the determination of impact parameter in the 132 Sn+ 124 Sn system

Here, 132 Sn + 124 Sn collisions at a beam energy of 270 MeV/nucleon were performed at the Radioactive Isotope Beam Factory (RIBF) in RIKEN to investigate the nuclear equation of state. Reconstructing the impact parameter is one of the important tasks in the experiment as it relates to many observable. In this work, we employ three commonly used algorithms in machine learning, the artificial neural network (ANN), the convolutional neural network (CNN), and the light gradient boosting machine (LightGBM), to determine the impact parameter by analyzing either the charged particle spectra or several features simulated with events from the ultrarelativistic quantum molecular dynamics (UrQMD) model. To closely imitate experimental data and investigate the generalizability of the trained machine learning algorithms, incompressibility of nuclear equation of state and the in-medium nucleon-nucleon cross sections are varied in the UrQMD model to generate the training data. The mean absolute error Δb between the true and the predicted impact parameter is smaller than 0.45 fm if training and testing sets are sampled from the UrQMD model with the same parameter set. However, if training and testing sets are sampled with different parameter sets, Δb would increase to 0.8 fm. The generalizability of the trained machine learning algorithms suggests that these machine learning algorithms can be used reliably to reconstruct the impact parameter in experiment.

71 CLASSICAL AND QUANTUM MECHANICS, GENERAL PHYSIC↗
DOE OSTI2021

The Impact of the Lightning Surge on SiC-based Medium-voltage Three-phase Four-wire Grid-connected Converters

The surge voltage induced by lightning will generate an inrush current in a grid-connected converter. It may not be large in Si-based converters because of the large grid side inductive filter. However, for SiC-based multi-level converters, the inrush current could be very large due to the small filter inductance, which is selected based on the current harmonic consideration. Most previous work focuses on system-level lightning protection while the converter-level impact, especially the internal components of the converter, is rarely discussed. This paper presents the analysis of the impact of the lightning surge on a 10 kV SiC MOSFET-based 13.8 kV three-phase four-wire grid-connected converter. The IEEE arrester model and the combined wave generator model in IEC 61000-4-5 standard are used to evaluate the inrush current, DC-link overvoltage, and component-to-ground potential of the converter. Analysis and simulation results have been provided to demonstrate the impact of lightning on the grid-connected converter. It is found that large inrush current occurs due to the small filter inductance, and the neutral-to-ground impedance impacts both the inrush current and the neutral point-to-ground potential.

Li, Haiguo↗
DOE OSTI2024

Impact Study of Thunderstorms on the US Power Grid Using Publicly Available Datasets

This work analyzes the impact of thunderstorms on the US power grid based on publicly available data. Since thunderstorms can bring lightning, heavy precipitation, and wind storms, analyzing their impact on the power system provides a combined correlation of lightning strikes, floods, and wind storms on power outages. This paper leverages publicly available thunderstorm datasets from the National Weather Service (NWS) and power outage datasets from Oak Ridge National Laboratory’s Environment for Analysis of Geo-Located Energy Information (EAGLE-I) to study the correlation between thunderstorms and power outages. This work is analyzing the patterns of thunderstorms from 2013-2022, which shows that the thunderstorms are not slowing down and will seem to continue their impact on human life in the future. This work also analyzes the monthly and yearly pattern of the impact of thunderstorms on power systems at the national, state, and county level.

Bhusal, Narayan↗
DOE OSTI2023

Lipid–enhanced Oilcane does not impact soil carbon dynamics compared with wild–type Sugarcane

The carbon neutral potential of bioenergy relies in part on the ability of feedstocks to sequester carbon (C) in the soil. Sugarcane is one of the most widely used bioenergy crops, yet there remain unknowns about how it impacts soil C dynamics. In addition, Oilcane, a genetically modified version of Sugarcane has been produced to accumulate more energy-dense oils and less soluble lignin, which enhances conversion efficiency but may also impact soil C cycling. Thus, our objectives were to examine the impact of Sugarcane litter decomposition on soil C formation and losses and determine if the genetic modifications to produce Oilcane alter these dynamics. To do this, we incubated bagasse (processed stem litter) and leaf litter from Sugarcane and Oilcane in microcosms with forest soil for 11 weeks. We used differences in natural abundance δ 13 C between C 3 forest soil and C 4 litter to trace the fate of the litter into respiratory losses as well as stable and unstable soil C pools. Our results show that genetic modifications to Oilcane did not substantially alter soil C dynamics. Sugarcane and Oilcane litter both led to net soil C gains dominated by an accumulation of the added litter as unstable, particulate organic C (POC). Oilcane litter led to small but significantly greater net soil C gains than Sugarcane litter due to greater POC formation, but the formation of stable, mineral associated organic matter (MAOC) did not differ between crop types. Sugarcane and Oilcane had opposing effects on tissue type where Sugarcane bagasse formed more MAOC, while Oilcane leaves preferentially remained as POC which may have important management implications. These results suggest that genetic modifications to Sugarcane will not significantly impact soil C dynamics; however, this may not be universal to other crops particularly if modifications lead to greater differences in litter chemistry.

09 BIOMASS FUELS↗
DOE OSTI2025

Combining Eddy Covariance Towers, Field Measurements, and the MEMS 2 Ecosystem Model Improves Confidence in the Climate Impacts of Bioenergy With Carbon Capture and Storage

ABSTRACT Carbon dioxide removal technologies such as bioenergy with carbon capture and storage (BECCS) are required if the effects of climate change are to be reversed over the next century. However, BECCS demands extensive land use change that may create positive or negative radiative forcing impacts upstream of the BECCS facility through changes to in situ greenhouse gas fluxes and land surface albedo. When quantifying these upstream climate impacts, even at a single site, different methods can give different estimates. Here we show how three common methods for estimating the net ecosystem carbon balance of bioenergy crops established on former grassland or former cropland can differ in their central estimates and uncertainty. We place these net ecosystem carbon balance forcings in the context of associated radiative forcings from changes to soil N 2 O and CH 4 fluxes, land surface albedo, embedded fossil fuel use, and geologically stored carbon. Results from long term eddy covariance measurements, a soil and plant carbon inventory, and the MEMS 2 process‐based ecosystem model all agree that establishing perennials such as switchgrass or mixed prairie on former cropland resulted in net negative radiative forcing (i.e., global cooling) of −26.5 to −39.6 fW m −2 over 100 years. Establishing these perennials on former grassland sites had similar climate mitigation impacts of −19.3 to −42.5 fW m −2 . However, the largest climate mitigation came from establishing corn for BECCS on former cropland or grassland, with radiative forcings from −38.4 to −50.5 fW m −2 , due to its higher plant productivity and therefore more geologically stored carbon. Our results highlight the strengths and limitations of each method for quantifying the field scale climate impacts of BECCS and show that utilizing multiple methods can increase confidence in the final radiative forcing estimates.

Falvo, Grant [Department of Plant, Soil and Microb↗
DOE OSTI2024

The impacts of rising vapour pressure deficit in natural and managed ecosystems

Abstract An exponential rise in the atmospheric vapour pressure deficit (VPD) is among the most consequential impacts of climate change in terrestrial ecosystems. Rising VPD has negative and cascading effects on nearly all aspects of plant function including photosynthesis, water status, growth and survival. These responses are exacerbated by land–atmosphere interactions that couple VPD to soil water and govern the evolution of drought, affecting a range of ecosystem services including carbon uptake, biodiversity, the provisioning of water resources and crop yields. However, despite the global nature of this phenomenon, research on how to incorporate these impacts into resilient management regimes is largely in its infancy, due in part to the entanglement of VPD trends with those of other co‐evolving climate drivers. Here, we review the mechanistic bases of VPD impacts at a range of spatial scales, paying particular attention to the independent and interactive influence of VPD in the context of other environmental changes. We then evaluate the consequences of these impacts within key management contexts, including water resources, croplands, wildfire risk mitigation and management of natural grasslands and forests. We conclude with recommendations describing how management regimes could be altered to mitigate the otherwise highly deleterious consequences of rising VPD.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Analyzing the Multiscale Impacts of Implementing Energy-Efficient HVAC Improvements Through Energy Audits and Economic Input–Output Analysis

Abstract Heating, ventilation, and air-conditioning (HVAC) systems are usually an industry’s highest consumer of energy, most of which goes toward space cooling in buildings. Industrial energy-efficiency audits not only benefit manufacturers but also generate significant economic and environmental benefits to localities, states, and the nation. This article analyzes the micro- and macro scale impacts of implementing energy-efficient HVAC systems by integrating the industrial building energy data with the macroeconomic regional economic flow model. Micro-scale data include 10 years of historical energy, cost, and carbon dioxide savings achieved from energy-efficient HVAC implementation offered to manufacturers through industrial energy audits. The data were integrated into the macroeconomic modeling framework to illuminate the cascading regional economic impacts of implementing energy-efficient HVAC recommendations in manufacturing facilities. Results show that if recommendations had been implemented throughout all manufacturers in the region, $656 M energy costs would have been directly saved, 7.8 million metric tons of carbon dioxide emissions would have been avoided, and 4387 jobs could have been created, resulting in a total annual economic impact of $899 M stemming from direct, indirect, and induced impacts. The results offer insight into how industrial energy systems can be designed and provide models for how communities can accomplish a net-zero society.

Energy & Fuels↗
DOE OSTI2024

Genetic modification of the shikimate pathway to reduce lignin content in switchgrass ( Panicum virgatum L.) significantly impacts plant microbiomes

Switchgrass (Panicum virgatum L.) is considered a sustainable biofuel feedstock, given its fast-impact growth, low input requirements, and high biomass yields. Improvements in bioenergy conversion efficiency of switchgrass could be made by reducing its lignin content. Engineered switchgrass that expresses a bacterial 3-dehydroshikimate dehydratase (QsuB) has reduced lignin content and improved biomass saccharification due to the rerouting of the shikimate pathway towards the simple aromatic protocatechuate at the expense of lignin biosynthesis. However, the impacts of this QsuB trait on switchgrass microbiome structure and function remain unclear. To address this, wild-type and QsuB-engineered switchgrass were grown in switchgrass field soils, and samples were collected from inflorescences, leaves, roots, rhizospheres, and bulk soils for microbiome analysis. We investigated how QsuB expression influenced switchgrass-associated fungal and bacterial communities using high-throughput Illumina MiSeq amplicon sequencing of ITS and 16S rDNA. Compared to wild-type, QsuB-engineered switchgrass hosted different microbial communities in roots, rhizosphere, and leaves. Specifically, QsuB-engineered plants had a lower relative abundance of arbuscular mycorrhizal fungi (AMF). Additionally, QsuB-engineered plants had fewer Actinobacteriota in root and rhizosphere samples. These findings may indicate that changes in the plant metabolism impact both AMF and Actinobacteriota similarly or potential interactions between AMF and the bacterial community. This study enhances understanding of plant-microbiome interactions by providing baseline microbial data for developing beneficial bioengineering strategies and by assessing nontarget impacts of engineered plant traits on the plant microbiome.

09 BIOMASS FUELS↗
DOE OSTI2020

Impact Modeling and Testing of Pouch and Prismatic Cells

Understanding battery response under impact is critical to improve the safety of electrified vehicles. Nevertheless, predicting the impact behaviors of batteries is not straightforward since a battery cell usually contains hundreds of thin layers with dramatically different material properties and multiple physical processes occur simultaneously during cell deformation. Here we utilized both empirical tests and numerical models to capture the failure process of pouch and prismatic cells in various impact scenarios. In each test, a cell was hit once by an indenter dropped from a certain height. During which the cell penetration, loading force, voltage and temperature were monitored to characterize the cell’s response. Meanwhile, numerical models were developed to capture the coupled mechanical, electrical, electrochemical and thermal responses of batteries. In these models, the cell bulk was treated as a homogeneous part to achieve computational efficiency required by large-scale simulations, and it was represented by the geologic cap model that allows both shear and compaction deformation. Simulation results showed agreement with experimental data in essential features of cell behaviors during impact. Details of the test setup, model development and cell failure behaviors are presented in this paper. Additionally, capabilities, limitations and future improvement of the battery safety modeling are discussed.

25 ENERGY STORAGE↗
DOE OSTI2020

Impacts of Stochastic Mixing in Idealized Convection-Permitting Simulations of Squall Lines

This study investigates impacts of altering subgrid-scale mixing in “convection-permitting” kilometer-scale horizontal-grid-spacing (Δ h ) simulations by applying either constant or stochastic multiplicative factors to the horizontal mixing coefficients within the Weather Research and Forecasting Model. In quasi-idealized 1-km Δ h simulations of two observationally based squall-line cases, constant enhanced mixing produces larger updraft cores that are more dilute at upper levels, weakens the cold pool, rear-inflow jet, and front-to-rear flow of the squall line, and degrades the model’s effective resolution. Reducing mixing by a constant multiplicative factor has the opposite effect on all metrics. Completely turning off parameterized horizontal mixing produces bulk updraft statistics and squall-line mesoscale structure closest to an LES “benchmark” among all 1-km simulations, although the updraft cores are too undilute. The stochastic mixing scheme, which applies a multiplicative factor to the mixing coefficients that varies stochastically in time and space, is employed at 0.5-, 1-, and 2-km Δ h . It generally reduces midlevel vertical velocities and enhances upper-level vertical velocities compared to simulations using the standard mixing scheme, with more substantial impacts at 1- and 2-km Δ h compared to 0.5-km Δ h . Further, the stochastic scheme also increases updraft dilution to better agree with the LES for one case, but has less impact on the other case. Stochastic mixing acts to weaken the cold pool but without a significant impact on squall-line propagation. It also does not affect the model’s overall effective resolution unlike applying constant multiplicative factors to the mixing coefficients.

75 CONDENSED MATTER PHYSICS, SUPERCONDUCTIVITY AND↗
DOE OSTI2023

Agriculture, bioenergy, and water implications of constrained cereal trade and climate change impacts

International trade increases connections and dependencies between countries, weaving a network of global supply chains. Agricultural commodity trade has implications for crop producers, consumers, crop prices, water and land uses, and other human systems. Interconnections among these systems are not always easy to observe when external impacts penetrate across multiple sectors. To better understand the interactions of non-linear and globally coupled agricultural-bioenergy-water systems under the broader economy, we introduce systematic perturbations in two dimensions, one human (restrictions on agricultural trade) and the other physical (climate impacts on crop yields). We explore these independently and in combination to distinguish the consequences of individual perturbation and interactive effects in long-term projections. We show that most regions experience larger changes in cereal consumption due to cereal import dependency constraints than due to the impacts of climate change on agricultural yields. In the scenario where all regions ensure an import dependency ratio of zero, the global trade of cereals decreases ~50% in 2050 compared to the baseline, with smaller decreases in cereal production and consumption (4%). The changes in trade also impact water and bioenergy: global irrigation water consumption increases 3% and corn ethanol production decreases 7% in 2050. Climate change results in rising domestic prices and declining consumption of cereal crops in general, while the import dependency constraint exacerbates the situation in regions which import more cereals in the baseline. The individual and interactive effects of trade perturbations and climate change vary greatly across regions, which are also affected by the regional ability to increase agricultural production through intensification or extensification.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2020

Selection of Vadose Zone Flow and Transport Properties with Gravel Fraction Corrections for the Hanford Site Composite Analysis and Cumulative Impact Evaluation

This environmental calculation file (ECF) is a compilation of hydrologic and radiological/chemical properties to be used for the updated Hanford Site Composite Analysis (CA) and Cumulative Impact Evaluation (CIE) vadose zone (VZ) modeling. The CA will provide an all-pathways dose projection to a hypothetical future member of the public from all planned low-level radioactive waste disposal facilities and potential contributions from all other projected end-state sources of radioactive material left at the Hanford Site following site closure. Its primary purpose is to support the decision-making process of the U.S. Department of Energy (DOE) under DOE O 435.1 Chg 1, Radioactive Waste Management, related to managing low-level waste disposal facilities at the Hanford Site. The CIE evaluates the effects of cleanup decisions regarding groundwater quality in the Hanford Site Central Plateau (DOE/RL-2018-69, Cumulative Impact Evaluation Technical Approach Document). Due to the complexity and large number of waste sites in source operable units (OUs), the computational tools used for the CIE must be capable of representing a range of site conditions and source terms in the VZ while also efficiently computing the impact that cleanup decisions have on the underlying aquifer. Waste-site proximity between and within source OUs has resulted in contaminants commingling in the vadose and saturated zones in complex ways. Plume commingling requires cleanup decisions to be evaluated considering the surrounding waste sites and existing groundwater contamination, therefore demonstrating the need to evaluate cumulative impacts from the VZ to groundwater.

12 MANAGEMENT OF RADIOACTIVE AND NON-RADIOACTIVE W↗
DOE OSTI2020

EXPERIMENTAL INVESTIGATION OF IMPACT AND ABRASION EROSIONS AT LOW VELOCITIES AND COMPARISON TO CFD SIMULATIONS

Wear and erosion damage of materials due to interaction of the surface with solid particles is a major issue in various industries. This phenomenon is common in mining, and oil and gas production, causing damages worth millions of dollars annually. Erosion is becoming a critical issue in renewable technologies as well such as concentrated solar thermal power (CSP) systems. In some CSP systems, solid particles can be used to absorb solar energy and enhance the heat storage. However, these particles may cause significant amount of wear to system components while falling down the power tower at high temperatures. This damage can be costly, and therefore, investigating solid particle erosion in CSP systems is of utmost importance. In collaboration with Sandia National Laboratories, the erosion durability of particle-based Generation 3 (GEN3) CSP system are being investigated both experimentally and numerically. In order to develop models to predict the life time of such systems, erosion under low temperature and low particle impact velocity conditions are investigated. Impact erosion and abrasion erosion experiments are conducted for low velocity and low temperature conditions for various candidate particles and containment materials. The impact erosion testing is conducted for three different containment material including Stainless Steel 316, special refractory material, and Inconel 740H with CARBOBEAD HSP 40/70 ceramic particles and UNIWEST 430 silica quartz erodent particles. All this data will enable us to better model the erosion behavior of these materials and provides a data base to investigate erosion at high temperatures experienced in CSP systems. At low temperatures and low velocities the softer refractory material exhibited greater erosion by an order-of-magnitude when compared to the harder Inconel 740H and Stainless Steel 316 materials. The overall erosion ratio for all the candidate materials was of the order of 10 -7 kg/kg. We also investigated wear in containment materials from sliding of particles over the surfaces at very low angles, also referred to as abrasion. For the velocities expected in a typical 1MW CSP plant, visible surface wear was noted, but the overall mass loss per unit surface area was found to be dependent on the hardness of the containment material tested. In this manuscript, we also present Computational Fluid Dynamics (CFD) simulations and erosion prediction of low velocity impact erosion. These results are compared with the experimental data to evaluate the ability of available erosion models for predicting erosion under these conditions.

14 SOLAR ENERGY↗
DOE OSTI2020

Impacts of Price Formation Efforts Considering High Renewable Penetration Levels and System Resource Adequacy Targets

Future markets with very high penetrations of renewable energy could have many low- to zero-cost periods, which would reduce energy revenues for the generation fleet. This can impact the ability of resources that are needed for long-term reliability to recover operating and capital costs. This paper explores the impact of an alternative pricing mechanism, relaxed minimum pricing, on revenue sufficiency on existing and future resource mixes, including those with high penetrations of wind and solar. This study evaluates eight scenarios encompassing three different sensitivity categories: (1) one alternative pricing mechanism versus traditional LMP pricing, (2) high versus low renewable penetration levels, and (3) using a resource mix that has been adjusted to a preset resource adequacy target versus one that contains a full set of resources. Results show renewable penetration has a greater impact on pricing and resulting profits than does the adjusted resource mix, the two pricing methods have modest variations in profits, and prices under the higher renewable penetration case were higher than under low renewable penetration. These conclusions are not intended to be direct predictions for future outcomes but rather to lead to additional research on the impacts of pricing on investment incentives and future resource adequacy targets.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗
DOE OSTI2020

COVID-19 and the Power Sector in Southeast Asia: Impacts and Opportunities

The COVID-19 pandemic is unique among the range of threats encountered over the last century, and its specific impacts do not necessarily resemble those of other disasters. In the near term, the pandemic is causing demand shocks, workforce impacts, supply chain complications, and a global, economic contraction with long-term consequences as yet unknown. In contrast, with natural disasters the principal impacts are more acute. These include infrastructure destruction, displaced populations, and often localized economic impact; however, the long-term response to both of these threats–pandemics and destructive forces of nature–requires similar approaches to building short-term and long-term resilience that prepare power sectors for safe and reliable operation during times of disruption.

29 ENERGY PLANNING, POLICY, AND ECONOMY↗