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DOE OSTI2025

Patchy burn severity explains heterogeneous soil viral and prokaryotic responses to fire in a mixed conifer forest

ABSTRACT Effects of fire on soil viruses and virus–host dynamics are largely unexplored, despite known microbial contributions to biogeochemical processes and ecosystem recovery. Here, we assessed how viral and prokaryotic communities responded to a prescribed burn in a mixed conifer forest. We sequenced 91 viral-size fraction metagenomes (viromes) and 115 16S rRNA gene amplicon libraries from 120 samples: four samples at five timepoints (two before fire and three after fire) at six sites (four treatment, two control). We hypothesized that compositional differences would be most significant between burned and unburned soils, but instead, plot location best distinguished viral communities, more than treatment (burned or not), depth (0–3 or 3–6 cm), or timepoint. For both viruses and prokaryotes, some burned communities resembled unburned controls, while others were significantly different, revealing heterogeneous responses to fire. These patterns were explained by burn severity, here defined by soil chemistry. Viral but not prokaryotic richness decreased significantly with burn severity, and low viromic DNA yields indicated substantial loss of viral biomass at higher severity. The relative abundances of Firmicutes, Actinobacteriota, and the viruses predicted to infect them increased significantly with burn severity, suggesting survival and viral infection of these fire-responsive and potentially spore-forming taxa. The degree of burn severity experienced by each patch of soil, rather than burn status alone, differed over mere meters in the same fire. Therefore, our analyses highlight the importance of high-resolution, paired biogeochemical data to explain soil community responses to fire. IMPORTANCE The impact of fire on the soil microbiome, particularly on understudied soil viral communities, warrants investigation, given known microbial contributions to biogeochemical processes and ecosystem recovery. Here, we collected 120 soil samples before and after a prescribed burn in a mixed conifer forest to assess the impacts of this disturbance on soil viral and prokaryotic communities. We show that simple categorical comparisons of burned and unburned areas were insufficient to reveal the underlying community response patterns. The patchy nature of the fire (indicated by soil chemistry data) led to significant changes in viral and prokaryotic community composition in areas of high burn severity, while communities that experienced lower burn severity were indistinguishable from those in unburned controls. Our results highlight the importance of considering highly resolved burn severity and biogeochemical measurements, even in nearby soils after the same fire, in order to understand soil microbial responses to prescribed burns.

Microbiology↗

DOE OSTI2024

Molecular shifts in dissolved organic matter along a burn severity continuum for common land cover types in the Pacific Northwest, USA

Increasing wildfire severity is of growing concern in the western United States, with consequences for the production, composition, and mobilization of dissolved organic matter (DOM) from terrestrial to aquatic systems. Our current understanding of wildfire impacted DOM (often termed pyrogenic DOM) composition is largely built from temperature-based studies that can be difficult to extrapolate to field conditions, which are often defined by ‘burn severity’, or the post-wildfire impact observed at a site. Thus, burn severity can encapsulate a broader range of fire and environmental conditions not exclusive to temperature. Biogeochemical studies that describe DOM along burn severity continuums remain limited but are needed to better link DOM composition with field conditions post-fire. Here, in this study, we addressed this need with an experimental open air burn simulation that generated chars from vegetation representative of major land cover types in the western United States. The chars were leached to simulate DOM mobilization potential. The DOM composition was characterized by ultra-high resolution mass spectrometry (HR-MS) and UV/VIS absorbance and fluorescence. Our results indicated that the shifts of DOM production and composition along a burn-severity gradient depends on the land cover type that was burned, with the degree of change dependent on the composition of the starting parent vegetation material. Fluorescence signatures indicated a strong convergence across land cover types to more aromatic DOM with increasing severity, while HR-MS indicated an increase in the production of aromatic nitrogen containing DOM with increasing severity. Results from this study enhance our ability to describe DOM composition in a framework that can be more directly related with field and remote-sensing based metrics.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2023

Dynamic subcanopy leaf traits drive resistance of net primary production across a disturbance severity gradient

Across the globe, the forest carbon sink is increasingly vulnerable to an expanding array of low- to moderate-severity disturbances. However, some forest ecosystems exhibit functional resistance (i.e., the capacity of ecosystems to continue functioning as usual) following disturbances such as extreme weather events and insect or fungal pathogen outbreaks. Unlike severe disturbances (e.g., stand-replacing wildfires), moderate severity disturbances do not always result in near-term declines in forest production because of the potential for compensatory growth, including enhanced subcanopy production. Community-wide shifts in subcanopy plant functional traits, prompted by disturbance-driven environmental change, may play a key mechanistic role in resisting declines in net primary production (NPP) up to thresholds of canopy loss. However, the temporal dynamics of these shifts, as well as the upper limits of disturbance for which subcanopy production can compensate, remain poorly characterized. In this study, we leverage a 4-year dataset from an experimental forest disturbance in northern Michigan to assess subcanopy community trait shifts as well as their utility in predicting ecosystem NPP resistance across a wide range of implemented disturbance severities. Through mechanical girdling of stems, we achieved a gradient of severity from 0% (i.e., control) to 45, 65, and 85% targeted gross canopy defoliation, replicated across four landscape ecosystems broadly representative of the Upper Great Lakes ecoregion. We found that three of four examined subcanopy community weighted mean (CWM) traits including leaf photosynthetic rate (p = 0.04), stomatal conductance (p = 0.07), and the red edge normalized difference vegetation index (p < 0.0001) shifted rapidly following disturbance but before widespread changes in subcanopy light environment triggered by canopy tree mortality. Surprisingly, stimulated subcanopy production fully compensated for upper canopy losses across our gradient of experimental severities, achieving complete resistance (i.e., no significant interannual differences from control) of whole ecosystem NPP even in the 85% disturbance treatment. Additionally, we identified a probable mechanistic switch from nutrient-driven to light-driven trait shifts as disturbance progressed. Our findings suggest that remotely sensed traits such as the red edge normalized difference vegetation index (reNDVI) could be particularly sensitive and robust predictors of production response to disturbance, even across compositionally diverse forests. The potential of leaf spectral indices to predict post-disturbance functional resistance is promising given the capabilities of airborne to satellite remote sensing. We conclude that dynamic functional trait shifts following disturbance can be used to predict production response across a wide range of disturbance severities.

resistance↗

DOE OSTI2024

Severe and mild drought cause distinct phylogenetically linked shifts in the blue grama (Bouteloua gracilis) rhizobiome

Plants rely on a diverse rhizobiome to regulate nutrient acquisition and plant health. With increasing severity and frequency of droughts worldwide due to climate change, untangling the relationships between plants and their rhizobiomes is vital to maintaining agricultural productivity and protecting ecosystem diversity. While some plant physiological responses to drought are generally conserved, patterns of root exudation (release of small metabolites shown to influence microbes) and the consequential effects on the plant rhizobiome can differ widely across plant species under drought. To address this knowledge gap, we conducted a greenhouse study using blue grama ( Bouteloua gracilis ), a drought-tolerant C4 grass native to shortgrass prairie across North American plains, as a model organism to study the effect of increasing drought severity (ambient, mild drought, severe drought) on root exudation and the rhizobiome. Our previous results demonstrated physiological effects of increasing drought severity including an increase in belowground carbon allocation through root exudation and shifts in root exudate composition concurrent with the gradient of drought severity. This work is focused on the rhizobiome community structure using targeted sequencing and found that mild and severe drought resulted in unique shifts in the bacterial + archaeal and fungal communities relative to ambient, non-droughted controls. Specifically, using the change in relative abundance between ambient and drought conditions for each ZOTU as a surrogate for population-scale drought tolerance (e.g., as a response trait), we found that rhizobiome response to drought was non-randomly distributed across the phylogenies of both communities, suggesting that Planctomycetota , Thermoproteota (formerly Thaumarchaeota ), and the Glomeromycota were the primary clades driving these changes. Correlation analyses indicated weak correlations between droughted community composition and a select few root exudate compounds previously implicated in plant drought responses including pyruvic acid, D-glucose, and myoinositol. This study demonstrates the variable impacts of drought severity on the composition of the blue grama rhizobiome and provides a platform for hypothesis generation for targeted functional studies of specific taxa involved in plant-microbe drought responses.

Goemann, Hannah M.↗

DOE OSTI2020

Injury severity analysis of truck-involved crashes under different weather conditions

This paper investigates truck-involved crashes to determine the statistically significant factors that contribute to injury severity under different weather conditions. The analysis uses crash data from the state of Ohio between 2011 and 2015 available from the Highway Safety Information System. To determine if weather conditions should be considered separately for truck safety analyses, parameter transferability tests are conducted; the results suggest that weather conditions should be modeled separately with a high level of statistical confidence. To this end, three separate mixed logit models are estimated for three different weather conditions: normal, rain and snow. The estimated models identify a variety of statistically significant factors influencing the injury severity. Different weather conditions are found to have different contributing effects on injury severity in truck-involved crashes. Rural, rear-end and sideswipe crash parameters were found to have significantly different levels of impact on injury severity. Based on the findings of this study, several countermeasures are suggested: 1) safety and enforcement programs should focus on female truck drivers, 2) a variable speed limit sign should be used to lower speeds of trucks during rainy condition, and 3) trucks should be restricted or prohibited on non-interstates during rainy and snowy conditions. These countermeasures could reduce the number and severity of truck-involved crashes under different weather conditions.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2025

Evaluating post-fire watershed response to varying burn severity and precipitation regimes using fully-distributed and integrated hydrologic models

Wildfires can cause significant changes in vegetation and soil, which may lead to increased surface runoff and soil erosion, thereby affecting water cycling within ecosystems. This study uses the Advanced Terrestrial Simulator (ATS), an integrated and fully distributed hydrologic model at the watershed scale, to examine post-fire hydrologic responses in selected watersheds with varying burn severities in the Pacific Northwest region of the United States. The model integrates surface overland flow, subsurface flow, and canopy biophysical processes. We have developed a new fire module in ATS to account for changes in soil hydraulic properties caused by fire in the topsoil layer. Modeling results indicate that, in the year following a high-severity burn, watershed-averaged evapotranspiration decreases by 25%. Additionally, post-fire peak flows increase by 18-29% in watersheds burned with medium to high severity due to changes in soil properties. Conversely, a low-severity burn results in less than a 1% increase in post-fire peak flow. Furthermore, a high-severity fire causes a 38% reduction in the infiltration rate within the affected watershed during the first post-fire wet season. Hypothetical numerical experiments with varying precipitation regimes after a high-severity fire show that post-fire peak flows can increase by 1-29% due to fire-induced changes in soil hydraulic properties. This study highlights the importance of using fully distributed hydrologic models to quantify disturbance-feedback loops, which are essential for understanding the complexities brought about by spatial heterogeneity in post-fire landscapes.

ATS↗

DOE OSTI2022

Root exudate composition reflects drought severity gradient in blue grama (Bouteloua gracilis)

Abstract Plant survival during environmental stress greatly affects ecosystem carbon (C) cycling, and plant–microbe interactions are central to plant stress survival. The release of C-rich root exudates is a key mechanism plants use to manage their microbiome, attracting beneficial microbes and/or suppressing harmful microbes to help plants withstand environmental stress. However, a critical knowledge gap is how plants alter root exudate concentration and composition under varying stress levels. In a greenhouse study, we imposed three drought treatments (control, mild, severe) on blue grama ( Bouteloua gracilis Kunth Lag. Ex Griffiths), and measured plant physiology and root exudate concentration and composition using GC–MS, NMR, and FTICR. With increasing drought severity, root exudate total C and organic C increased concurrently with declining predawn leaf water potential and photosynthesis. Root exudate composition mirrored the physiological gradient of drought severity treatments. Specific compounds that are known to alter plant drought responses and the rhizosphere microbiome mirrored the drought severity-induced root exudate compositional gradient. Despite reducing C uptake, these plants actively invested C to root exudates with increasing drought severity. Patterns of plant physiology and root exudate concentration and composition co-varied along a gradient of drought severity.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Analyzing Relationships Between Economic and Neighborhood-Related Social Determinants of Health and Intensive Care Unit Length of Stay for Critically Ill Children With Medical Complexity Presenting With Severe Sepsis

Objectives: Of the Social Determinants of Health (SDoH), we evaluated socioeconomic and neighborhood-related factors which may affect children with medical complexity (CMC) admitted to a Pediatric Intensive Care Unit (PICU) in Shelby County, Tennessee with severe sepsis and their association with PICU length of stay (LOS). We hypothesized that census tract-level socioeconomic and neighborhood factors were associated with prolonged PICU LOS in CMC admitted with severe sepsis in the underserved community. Methods: This single-center retrospective observational study included CMC living in Shelby County, Tennessee admitted to the ICU with severe sepsis over an 18-month period. Severe sepsis CMC patients were identified using an existing algorithm incorporated into the electronic medical record at a freestanding children's hospital. SDoH information was collected and analyzed using patient records and publicly available census-tract level data, with ICU length of stay as the primary outcome. Results: 83 encounters representing 73 patients were included in the analysis. The median PICU LOS was 9.04 days (IQR 3.99–20.35). The population was 53% male with a median age of 4.1 years (IQR 1.96–12.02). There were 57 Black/African American patients (68.7%) and 85.5% had public insurance. Based on census tract-level data, about half (49.4%) of the CMC severe sepsis population lived in census tracts classified as suffering from high social vulnerability. There were no statistically significant relationships between any socioeconomic and neighborhood level factors and PICU LOS. Conclusion: Pediatric CMC severe sepsis patients admitted to the PICU do not have prolonged lengths of ICU stay related to socioeconomic and neighborhood-level SDoH at our center. A larger sample with the use of individual-level screening would need to be evaluated for associations between social determinants of health and PICU outcomes of these patients.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2022

A Phenome-Wide Association Study of genes associated with COVID-19 severity reveals shared genetics with complex diseases in the Million Veteran Program

The study aims to determine the shared genetic architecture between COVID-19 severity with existing medical conditions using electronic health record (EHR) data. We conducted a Phenome-Wide Association Study (PheWAS) of genetic variants associated with critical illness (n = 35) or hospitalization (n = 42) due to severe COVID-19 using genome-wide association summary data from the Host Genetics Initiative. PheWAS analysis was performed using genotype-phenotype data from the Veterans Affairs Million Veteran Program (MVP). Phenotypes were defined by International Classification of Diseases (ICD) codes mapped to clinically relevant groups using published PheWAS methods. Among 658,582 Veterans, variants associated with severe COVID-19 were tested for association across 1,559 phenotypes. Variants at the ABO locus (rs495828, rs505922) associated with the largest number of phenotypes (n rs495828 = 53 and n rs505922 = 59); strongest association with venous embolism, odds ratio (OR rs495828 1.33 (p = 1.32 x 10 –199 ), and thrombosis OR rs505922 1.33, p = 2.2 x10 -265 . Among 67 respiratory conditions tested, 11 had significant associations including MUC5B locus (rs35705950) with increased risk of idiopathic fibrosing alveolitis OR 2.83, p = 4.12 × 10 –191 ; CRHR1 (rs61667602) associated with reduced risk of pulmonary fibrosis, OR 0.84, p = 2.26× 10 –12 . The TYK2 locus (rs11085727) associated with reduced risk for autoimmune conditions, e.g., psoriasis OR 0.88, p = 6.48 x10 -23 , lupus OR 0.84, p = 3.97 x 10 –06 . PheWAS stratified by ancestry demonstrated differences in genotype-phenotype associations. LMNA (rs581342) associated with neutropenia OR 1.29 p = 4.1 x 10 –13 among Veterans of African and Hispanic ancestry but not European. Overall, we observed a shared genetic architecture between COVID-19 severity and conditions related to underlying risk factors for severe and poor COVID-19 outcomes. Differing associations between genotype-phenotype across ancestries may inform heterogenous outcomes observed with COVID-19. Divergent associations between risk for severe COVID-19 with autoimmune inflammatory conditions both respiratory and non-respiratory highlights the shared pathways and fine balance of immune host response and autoimmunity and caution required when considering treatment targets.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2022

Droughts Reduce Growth Rates and Increase Vulnerability to Increasingly Frequent and Severe Drying Events in an Aquatic Ectotherm

Many aquatic organisms are experiencing increasingly severe and frequent droughts and drying events. Simultaneously, drought effects are carrying over to nondrought years as ecosystems remain in incomplete states of recovery. Aquatic organisms are thus faced with fewer sequential years under degraded environmental conditions to prepare for increasingly severe droughts and potential drying events. We assessed the effect of droughts and sex on the growth, mass, and mass-dependent estivation potential of long-lived aquatic salamanders (Greater Sirens, Siren lacertina) that estivate during drying events brought on by severe droughts. We calculated growth rates of S. lacertina based on mark–recapture data spanning 11 yr of a severe drought local minimum (of past 50 yr) in the southeastern United States. Sirens showed a distinct seasonal gain in body length and mass from March through September and little growth for the rest of the year. Gains during the growth season were strongly reduced by drought conditions. Although male and female sirens were predicted to reach a similar maximum body size, females grew much slower. Recruitment into drying event ‘‘size refugia’’ is constrained by drying event severity (determines minimum size required), frequency (determines available time between events to grow), and environmental conditions between drying events (determines the rate of growth). Thus, increases in drying event severity and frequency will require faster growth to a larger body size for successful recruitment into a size class that is resistant to drying events. The slower growth of females and reduction of growth during suboptimal years (mild to moderate droughts) suggest that the life history strategy of Greater Sirens for persisting through drying events potentially increases their demographic susceptibility to the predicted effects of climate change.

59 BASIC BIOLOGICAL SCIENCES↗

DOE OSTI2020

A Bayesian modeling framework for crash severity effects of active traffic management systems

Transportation agencies utilize Active traffic management (ATM) systems to dynamically manage recurrent and non-recurrent congestion based on real-time conditions. While these systems have been shown to have some safety benefits, their impact on injury severity outcomes is currently uncertain. In this paper, we used full Bayesian mixed logit models to quantify the impact that ATM deployment had on crash severities. The estimation results revealed lower severities with ATM deployment. Marginal effects for ATM deployments that featured hard shoulder running (HSR) revealed lower likelihoods for severe and moderate injury crashes of 15.9 % and for minor injury crashes of 10.1 %. The likelihood of severe and moderate injury crashes and minor injury crashes reduced by 12.4 % and 8.33 % with ATM without HSR. The models were observed to be temporally transferable and had forecast error of 0.301 and 0.304 for the two models, revealing better performance with validation data. These results have implications for improving freeway crash risk at critical locations.

97 MATHEMATICS AND COMPUTING↗

DOE OSTI2020

Understanding the Effects of Vehicle Platoons on Crash Type and Severity

Crash type is an informative indicator to infer driving behaviors and conditions that cause a crash. For example, rear-end and side-swipe crashes are typically caused by improper vehicle interaction such as sudden lane-changing or speed control while hit-object crashes are likely the result of a single driver’s mistake. This study investigated the impact of vehicles travelling as a group (platoon) and its configuration (i.e., types of vehicles consisting of the platoon) on crash type and severity since the vehicles could affect each other when travelling in close proximity. This study applied Generalized Structure Equation Modeling (GSEM) to capture the complex relationships among the various crash factors such as traffic condition, driver characteristics, environmental conditions, and vehicle interaction to the crash attributes including type and severity. This study collected over 3 million individual vehicle data from 39 traffic count sites in California to estimate the vehicle interactions and driving behaviors. The microscopic traffic data are matched to 1417 crash reports. Results showed that vehicles traveling in platoons are associated with more rear-end and side-swipe crashes. Speed difference in the platoon had a positive effect on hit-object crashes if the platoon comprises vehicles of homogeneous type – either trucks or non-trucks. In addition, human factors such as age and gender were identified as significant influential factors in all type of crashes, however truck involvement particularly played an important role amongst side-swipe crashes. Crash severity was negatively affected by total flow, and rear-end crashes were more likely to be severe compared with hit-object crashes. Based on findings, this study suggests practical operational strategies to reduce traffic instability associated with platooned vehicle patterns. Understanding the high-risk factors for different crash types and severities would provide valuable insights for decision-makers and transportation engineers to develop targeted intervention strategies in consideration of road users and traffic conditions such as fleet mix and speed.

ADVANCED PROPULSION SYSTEMS↗

DOE OSTI2020

Severe Accident Phenomena: A Comparison Among the NuScale SMR, Other Advanced LWR Designs, and Operating LWRs

During a severe accident in a nuclear reactor, there are a number of phenomenological events which can present a challenge to containment integrity. These include the generation and combustion of hydrogen, energetic fuel-coolant interactions, thermal attack of fission product barriers, core-concrete interactions, direct containment heating, and gradual overpressurization. The advanced design of the NuScale small modular reactor has resulted in the reduced likelihood and severity of severe accident challenges to containment. This paper discusses the features of the NuScale design that reduce the likelihood of occurrence of these severe accident phenomena, and discusses the ability of containment to survive in the unlikely event that they do occur. Here, the impact of severe accident phenomena for the NuScale design is compared and contrasted against other advanced light water reactors, such as AP1000 and ESBWR, as well as the existing fleet, using information from publicly available documents.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

DOE OSTI2023

Host genetics and gut microbiota composition: Baseline gut microbiota composition as a possible prognostic factor for the severity of COVID-19 in patients with familial Mediterranean fever disease

It is known that the gut microbiome of a healthy person affects the process of COVID-19 after getting infected with SARS-CoV-2 virus. It is also believed that colchicine can alleviate the severity of COVID-19. Current investigations aimed to evaluate the associations between the baseline gut microbiota composition of healthy and Familial Mediterranean fever (FMF) - carrier Armenian men populations, and the severity of the COVID-19 disease after their infection with the SARS-CoV-2. The study has a purpose of answering three core questions: i. Do the characteristics of gut microbiome of Armenians affect the course of COVID-19 severity? ii. How does the COVID-19 disease course on go for FMF patients who have been taking colchicine as a medication over the years after getting infected with SARS-CoV-2? iii. Is there an initial gut micribiota structure pattern for non-FMF and FMF patients in the cases when COVID-19 appears in mild form? The gut microbiota composition in non-FMF and FMF patients before the first infection (mild and moderate course of COVID-19) was considered. COVID-19 was diagnosed by SARS-CoV-2 nucleic acid RT-PCR in nasopharyngeal swab and/or sputum. The number of patients with male FMF with mild COVID-19 was approximately two times higher than that of non-FMF male subjects with COVID-19. In addition, an association of COVID-19 disease severity with the baseline gut Prevotella, Clostridium hiranonis, Eubacterium biforme, Veillonellaceae, Coprococcus, and Blautia diversities in the non-FMF and FMF populations were revealed by us, which can be used as risk/prognostic factor for the severity of COVID-19.

60 APPLIED LIFE SCIENCES↗

DOE OSTI2024

An editorial to the Special Issue on “Severe climate Risks”

The history of this Special Issue (https://www.sciencedirect.com/special-issue/10JD7LNJNQ0) indirectly dates back to the early 1990s, when the signature of the United Nations Framework Convention on Climate Change kicked-off an international political process based on one overarching and foundational principle: to avoid “dangerous anthropogenic interference with the climate system” at the global level. More than three decades later, such a principle remains central, though complementary aims made their way through the climate negotiation process, such as the importance of ensuring equity and justice, to give just one example here. Scientific knowledge also considerably progressed and we know more about the range of risks that climate change imposes and will continue to impose to the biosphere and humankind, worldwide and at all territorial levels. It is also clear that societal responses to these risks —“climate adaptation” as we know it— are increasingly happening, but definitely not at the pace of climate risk trends (Berrang-Ford et al., 2021, Erisken et al., 2021, Olazabal and Ruiz De Gopegui, 2021, Magnan et al., 2023a, Reckien et al., 2023, UNEP, 2023). As a result, concerns have emerged over the recent years in both the scientific and policy arenas around the idea that societies may not be able to address all climate risks, and that limits to adaptation and induced residual risks need to be considered more seriously. Such concerns further highlight the continuing importance of the imperative to minimise dangerous anthropogenic interference with the climate system, at any scale. But what does “dangerous interference” mean? How can we decide that we are entering the “dangerous” space, compared to a broader range of climate risks that would qualify as problematic but not necessarily “dangerous”? Who should make such a decision? Which conditions drive risk severity over time, including in the future? And what would be the environmental, economic, social and cultural implications of prioritising some climate risks over others? The Intergovernmental Panel on Climate Change (IPCC) was a pioneer in addressing such questions through the development of the “Key Risks” framing that describes those climate risks having the potential to become dangerous or “severe” over the course of this century (Schellnhuber et al., 2006, Schneider et al., 2007, Oppenheimer et al., 2014, O’Neill et al., 2022). The Fifth and Sixth assessment cycles (AR5 and AR6) went a step further by identifying about 120 Key Risks across regions and sectors, and clustering them into 8 “Representative Key Risks” covering a range of geographical systems (low-lying coasts, and to terrestrial and ocean ecosystems), sectors (critical infrastructure, living standards, human health, food security, and water security) and human dimensions (peace and mobility) (Oppenheimer et al., 2014, O’Neill et al., 2022). This Special Issue was born of the efforts of a range of authors, during the development of the IPCC AR6 main Assessment Report between 2019 and 2022, to characterise Key Risks and Representative Key Risks, and advance knowledge on what shapes “severe climate risks” conceptually as well as in the real-world. The series of papers forming this Special Issue is not intended to cover the topic exhaustively, but rather to give readers an overview through the following narrative: defining “severe climate risks” is highly challenging (Magnan et al., 2023b), but knowledge is expanding on the driving climate hazards (Tebaldi et al., 2023) and their implications on geographical systems, sectors and human dimensions, using here food security (Mirzabaev et al., 2023), human mobility (Gilmore et al., 2024) and peace (Buhaug et al., 2023) as illustrative examples. The overall intention is to support especially decision-makers, whatever the scale or sector considered, in asking severity-driven questions to identify sector- and context-specific “priority” risks from climate change.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2025

Mechanically induced thermal runaway severity analysis of Li-ion batteries and continuous energy release monitoring

The large-scale deployment of Li-ion batteries in stationary energy storage and electrical vehicle applications demands a strong focus on safety, particularly on the thermal runaway risk and severity evaluation. A standardized single-side mechanical indentation test protocol was developed to induce an internal short-circuit (ISC) and evaluate cells' thermal runaway severity at different state of charge (SOC). The observed hazard severity (OHS in five categories) and evaluated scores in this work have a comprehensive consideration of each cell's capacity, initial voltage, SOC, temperature and voltage change, allowing a better evaluation of the cells' thermal runaway potential. This method was applied to about 200 Li-ion batteries in order to build an extensive thermal runaway database covering various SOCs, capacities and chemistries. In this study, we monitored the transitions of stored electrochemical energy and applied mechanical energy into both thermal energy and acoustic emissions (AE). The surface temperature and mechanical failures were monitored by infrared imaging and AE to capture critical events within battery cells throughout the mechanical indentation tests. Furthermore, the initial temperature maps can predict two types of follow-up events: thermal runaway or gradual heat release via conduction. Analyzing each cell's severity, AEs, and leveraging the evolving database offer insights into predicting occurrences of thermal runaway. The test method, thermal runaway severity evaluation and prediction, and the corresponding database provide battery designers, manufacturers, and end-users a clear overview of Li-ion batteries' thermal runaway potential under mechanical abuse, advancing the safety design of Li-ion batteries.

Acoustic emission↗

DOE OSTI2020

Distinctive Signals in 1-min Observations of Overshooting Tops and Lightning Activity in a Severe Supercell Thunderstorm

This work examines a severe weather event that took place over central Argentina on December 11, 2018. The evolution of the storm from its initiation, rapid organization into a supercell, and eventual decay was analyzed with high-temporal resolution observations. This work provides insight into the spatio-temporal co-evolution of storm kinematics (updraft area and lifespan), cloud-top cooling rates, and lightning production that led to severe weather. The analyzed storm presented two convective periods with associated severe weather. An overall decrease in cloud-top local minima IR brightness temperature (MinIR10.3), increase in overshooting top area, and lightning jump (LJ) preceded both periods. LJs provided the highest lead time to the occurrence of severe weather, with the ground-based lightning networks providing the maximum warning time of around 30 min. Lightning flash counts from the Geostationary Lightning Mapper (GLM) were underestimated when compared to detections from ground-based lightning networks. Among the possible reasons for GLM’s lower detection efficiency were an optically dense medium located above lightning sources and the occurrence of flashes smaller than GLM’s footprint. The minimum MinIR provided the shorter warning time to severe weather occurrence. However, secondary minima in MinIR10.3 that preceded the absolute minima improved this warning time by more than 10 min. Furthermore, trends in MinIR10.3 for time scales shorter than 6 min revealed shorter cycles of fast cooling and warming, which provided information about the lifecycle of updrafts within the storm. The advantages of using observations with high-temporal resolution to analyze the evolution and intensity of convective storms are discussed.

54 ENVIRONMENTAL SCIENCES↗

DOE OSTI2022

Identification of therapeutic targets in a murine model of severe exertional heat stroke

Exertional heat stroke (EHS) is a potentially lethal condition resulting from high core body temperatures (T C ) in combination with a systemic inflammatory response syndrome (SIRS) with varying degrees of severity across victims, and limited understanding of the underlying mechanism(s). We established a mouse model of severe EHS to identify mechanisms of hyperthermia/inflammation that may be responsible for organ damage. Mice were forced to run on a motorized wheel in a 37.5°C chamber until loss of consciousness and were either removed immediately (exertional heat injury or EHI; T CMax = 42.4 ± 0.2°C) or remained in the chamber an additional 20 min (EHS; T CMax = 42.5 ± 0.4°C). Exercise control mice (ExC) experienced identical procedures to EHS at 25°C. At 3 h post-EHS, there was evidence for an immune/inflammatory response as elevated blood chemokine [interferon γ-induced protein 10 (IP-10), keratinocytes-derived chemokine (KC), macrophage inflammatory proteins (MIP-1α), MIP-1β, MIP-2] and cytokine [granulocyte colony-stimulating factor (G-CSF), interleukins (IL-10), IL-6] levels peaked and were highest in EHS mice compared with EHI and ExC mice. Immunoblotting of organs susceptible to EHS damage indicated that several kinases were sensitive to stress associated with heat/inflammation and exercise; specifically, phosphorylation of liver c-Jun NH 2 -terminal kinase (JNK) at threonine 183/tyrosine 185 immediately (0 h) postheating related to heat illness severity. We have established a mouse EHS model, and JNK [or its downstream target(s)] could underlie EHS symptomatology, allowing the identification of molecular pathways or countermeasure targets to mitigate heat illness severity, enable complete recovery, and decrease overall EHS-related fatalities.

Physiology↗