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Laser desorption ionisation, coupled with ultrahigh-resolution mass spectrometry, provides an apt reflection of the physical properties of tar balls in wildfire smoke.
The 2018 Camp Fire was a large late-year (November) wildfire that produced an urban firestorm in the Town of Paradise, California, USA, and destroyed more than 18 000 structures. Runoff from burned wildland areas is known to contain ash, which can transport contaminants including metals into nearby watersheds. However, due to historically infrequent occurrences, the effect of wildland-urban interface (WUI) fires, such as the Camp Fire, on surface water quality has not been well-characterized. Therefore, this study investigated the effects of widespread urban burning on surface water quality in major watersheds of the Camp Fire area. Between November 2018 and May 2019, 140 surface water samples were collected, including baseflow and stormflow, from burned and unburned watersheds with varying extent of urban development. Samples were analyzed for total and filter-passing metals, dissolved organic carbon, major anions, and total suspended solids. Ash and debris from the Camp Fire contributed metals to downstream watersheds via runoff throughout the storm season. Increases in concentration up to 200-fold were found for metals Cr, Cu, Ni, Pb, and Zn in burned watersheds compared to pre-fire values. Total concentrations of Al, Cd, Cu, Pb, and Zn exceeded EPA aquatic habitat acute criteria by up to 16-fold for up to five months after the fire. To assess possible transport mechanisms and bioavailability, a subset of 18 samples was analyzed using four filters with nominal pore sizes ranging from 0.22 to 1.2 μm to determine the particulate size distribution of metals. Trace and major metals (Al, Ba, Co, Cr, Cu, Fe, Hg, Mn, Ni, Pb, and Zn) were found mostly associated with larger grain sizes (>0.45 μm), and some metals (Al, Cr, Fe, and Pb) also included a substantial colloidal phase (0.22 to 0.45 μm). This study suggests that fires in the wildland–urban interface increase metal concentrations, mainly through particulate driven transport. The metals with the largest increases are likely from anthropogenic disaster materials, though biomass ash also is a major contributor to water quality. In conclusion, the increase in metals following WUI burning may have adverse ecological impacts.
As the permafrost region warms, its large organic carbon pool will be increasingly vulnerable to decomposition, combustion, and hydrologic export. Models predict that some portion of this release will be offset by increased production of Arctic and boreal biomass; however, the lack of robust estimates of net carbon balance increases the risk of further overshooting international emissions targets. Precise empirical or model-based assessments of the critical factors driving carbon balance are unlikely in the near future, so to address this gap, we present estimates from 98 permafrost-region experts of the response of biomass, wildfire, and hydrologic carbon flux to climate change. Results suggest that contrary to model projections, total permafrost-region biomass could decrease due to water stress and disturbance, factors that are not adequately incorporated in current models. Assessments indicate that end-of-the-century organic carbon release from Arctic rivers and collapsing coastlines could increase by 75% while carbon loss via burning could increase four-fold. Experts identified water balance, shifts in vegetation community, and permafrost degradation as the key sources of uncertainty in predicting future system response. In combination with previous findings, results suggest the permafrost region will become a carbon source to the atmosphere by 2100 regardless of warming scenario but that 65%–85% of permafrost carbon release can still be avoided if human emissions are actively reduced.
Post-wildfire extreme rainfall events can have destructive impacts in the western United States. Using two climate model large ensembles, we assess the future risk of extreme fire weather events being followed by extreme rainfall in this region. By mid-21st century, in a high warming scenario (RCP8.5), we report large increases in the number of extreme fire weather events followed within 1 year by at least one extreme rainfall event. By 2100, the frequency of these compound events increases by 100% in California and 700% in the Pacific Northwest in the Community Earth System Model v1 Large Ensemble. We further project that more than 90% of extreme fire weather events in California, Colorado, and the Pacific Northwest will be followed by at least three spatially colocated extreme rainfall events within five years. Our results point to a future with substantially increased post-fire hydrologic risks across much of the western United States.
Annual wildfire area in California has rapidly grown in recent decades, with increasingly negative impacts on people. The fire season is also lengthening, with an earlier onset. This trend has been hypothesized to be driven by anthropogenic warming, but it has yet to be quantitatively attributed to climate drivers. Using a comprehensive fire occurrence dataset, we analyze fire season onset and climate controls on its variability and change during 1992–2020 in 13 California ecoregions. Northern California ecoregions show stronger trends toward earlier onset compared to more arid southern California ecoregions. Onset has trended earlier for all but one ecoregion. Interannual variability of onset is dominated by climate variability and its influence on fuel moisture. Trend attribution inferred from onset-climate relationships suggests that anthropogenic warming advanced fire season onset by 6 to 46 days during 1992–2020 in 11 of 13 ecoregions. Continued warming is expected to further promote earlier fire season onsets.
Aerosols emitted from wildfires could significantly affect global climate through perturbing global radiation balance. In this study, the Community Earth System Model with prescribed daily fire aerosol emissions is used to investigate fire aerosols’ impacts on global climate with emphasis on the role of climate feedbacks. The total global fire aerosol radiative effect (RE) is estimated to be -0.78 ± 0.29 W m -2 , which is mostly from shortwave RE due to aerosol–cloud interactions (REaci; -0.70 ± 0.20 W m -2 ). The associated global annual-mean surface air temperature (SAT) change ΔT is -0.64 ± 0.16 K with the largest reduction in the Arctic regions where the shortwave REaci is strong. Associated with the cooling, the Arctic sea ice is increased, which acts to reamplify the Arctic cooling through a positive ice-albedo feedback. The fast response (irrelevant to ΔT) tends to decrease surface latent heat flux into atmosphere in the tropics to balance strong atmospheric fire black carbon absorption, which reduces the precipitation in the tropical land regions (southern Africa and South America). The climate feedback processes (associated with ΔT) lead to a significant surface latent heat flux reduction over global ocean areas, which could explain most (~80%) of the global precipitation reduction. The precipitation significantly decreases in deep tropical regions (5°N) but increases in the Southern Hemisphere tropical ocean, which is associated with the southward shift of the intertropical convergence zone and the weakening of Southern Hemisphere Hadley cell. Such changes could partly compensate the interhemispheric temperature asymmetry induced by boreal forest fire aerosol indirect effects, through intensifying the cross-equator atmospheric heat transport.
The effectiveness of land-based climate mitigation strategies is generally estimated on a case-by-case basis without considering interactions with other strategies or influencing factors. Here we evaluate a new, comprehensive approach that incorporates interactions among multiple management strategies, land use/cover change, wildfire, and climate, although the potential effects of climate change are not evaluated in this study. The California natural and working lands carbon and greenhouse gas model (CALAND) indicates that summing individual practice estimates of greenhouse gas impacts may underestimate emission reduction benefits in comparison with an integrated estimate. Annual per-area estimates of the potential impact of specific management practices on landscape emissions can vary based on the estimation period, which can be problematic for extrapolating such estimates over space and time. Furthermore, the actual area of implementation is a primary factor in determining potential impacts of management on landscape emissions. Nonetheless, less intensive forest management, avoided conversion to urban land, and urban forest expansion generally create the largest annual per-area reductions, while meadow restoration and forest fuel reduction and harvest practices generally create the largest increases with respect to no management. CALAND also shows that data uncertainty is too high to determine whether California land is a source or a sink of carbon emissions, but that estimating effects of management with respect to a baseline provides valid results. Important sources of this uncertainty are initial carbon density, net ecosystem carbon accumulation rates, and land use/cover change data. The appropriate choice of baseline is critical for generating valid results.
This data package is associated with the publication “Ecosystem leaf area, gross primary production, and evapotranspiration responses to wildfire in the Columbia River Basin” submitted to Biogeosciences (Shi et al., 2024; doi: 10.22541/au.171053013.30286044/v1). In this research, data products, leaf area index (LAI), gross primary production (GPP), and evapotranspiration (ET), from the Moderate Resolution Imaging Spectroradiometer (MODIS) are used to quantify the resistance and resilience of different ecosystem types in the Columbia River Basin (CRB). A machine learning algorithm, random forest (RF), was used to examine the impacts of precipitation, vapor pressure deficit (VPD), and burn severity from Monitoring Trends in Burn Severity (MTBS) on ecosystem resilience. The data package includes the processed MODIS data products, precipitation, VPD, and burn severity in 138 fire regions in CRB and the input files for RF model training. This data package includes six folders. The MODIS products are included in three MODIS_* folders with shell scripts for data clipping and *ncl files for data processing: (1) “/MODIS_LAI_CRB”; (2) “/MODIS_GPP_CRB”; and (3) “/MODIS_ET_CRB”. All the processed data for each fire event are NetCDF formatted. The MTBS burn severity data and the shell and *ncl scripts used for data processing are in the folder named (4) “MTBS_fire”. The ERA meteorological fields and the data processing scritps are in (5) “ERA_Var_CR”. All the scripts for figure development are in the format of *ncl and in the folder (6) “paper_scripts”. See the file ending in “flmd.csv” for a list of all files contained in this data package and descriptions for each. Tabular column headers and units are described in the data dictionary file ending in “dd.csv”.
This is the AmeriFlux version of the carbon flux data for the site US-Fwf Flagstaff - Wildfire. Site Description - Ponderosa pine forest subject to high severity stand replacing wild fire in 1996. Project webpage http://nau.edu/CEFNS/Forestry/Research/Carbon-Flux/Sites/.
Repeated perturbations, both biotic and abiotic, can lead to fundamental changes in the nature of ecosystems including changes in state. Sagebrush-steppe communities provide important habitat for wildlife and grazing for livestock. Fire is an integral part of these systems, but there is concern that increased ignition frequencies and invasive species are fundamentally altering these systems. Despite these issues, the majority of studies of fire effects in Artemisia tridentata wyomingensis-dominated systems have focused on the effects of single burns. The Arid Lands Ecology Reserve (ALE), in south-central Washington (U.S.A.), was one of the largest areas of continuous shrub-steppe habitat in the state until large wildfires burnt the majority of it in 2000 and 2007. We analysed data from permanent vegetation transects established in 1996 and resampled in 2002 and 2009. Our objective was to describe how the fires, and subsequent post-fire restoration efforts, affected communities successional pathways. Plant communities differed in response to repeated fire and restoration; these differences could largely be ascribed to the functional traits of the dominant species. Low elevation communities, previously dominated by obligate seeders, moved farthest from their initial composition and were dominated by weedy, early successional species in 2009. Higher elevation sites with resprouting shrubs, native bunchgrasses and few invasive species were generally more resilient to the effects of repeated disturbances. Shrub cover has been almost entirely removed from ALE, though there is evidence of recovery where communities were dominated by re-sprouters. Cheatgrass (Bromus tectorum) dominance was reduced by herbicide application in areas where it was previously abundant but increased significantly in untreated areas. Several re-sprouting species, notably Phlox longifolia and Poa secunda, expanded remarkably following competitive release from shrub canopies and/or abundant cheatgrass. Our results suggest that community dynamics can be understood through a state-and-transition model with two axes (shrub/grass and native/invasive abundance), though such models also need to account for differences in plant functional traits and disturbance regimes. We use our results to develop an illustrative model that will be expanded with further research.
This paper deals with wildfire identification in the Alaska regions as a semantic segmentation task using support vector machine classifiers. Instead of colour information represented by means of BGR channels, we proceed with a normalized reflectance over 152 days so that such time series is assigned to each pixel. We compare models associated with $\mathcal{l}1$-loss and $\mathcal{l}2$-loss functions and stopping criteria based on a projected gradient and duality gap in the presented benchmarks.
The presentation focus is on looking at various sub-grid topography elements' impact on being able to simulate wildfire progressions.
Multispectral satellite imagery has been demonstrated to accurately detect wildfires over a variety of land cover types at coarse- and medium-resolution (i.e., 1km to 30m), typically by detecting burned area after the fire has caused substantial damage. We developed an algorithm to map active fire (i.e., flame) in 2-meter resolution WorldView time-series imagery and monitor fire trajectory over time. Our results depict robust mapping across scenes collected from different fires over grassy and forested land cover, identifying fires as small as 4m 2 throughout the image. Operational deployment at scale may provide valuable near-real time maps of active fire for responders to leverage for timely, targeted mitigation efforts. This white paper describes the current capability specifications and indicates requirements for scaling.
A poster summarizing parts of Sandia National Labs Wildfire Electric Grid Resilience program
The respiratory and cardiovascular effects of smoke exposure are well documented from cigarette smoking and particulate matter (PM) associated with air-pollution studies, but epidemiological data also suggests exposure to high levels of woodsmoke correlate with central-nervous-system (CNS) dysfunction, including elevated rates of Alzheimer’s disease (AD) and dementia. Neuro-inflammation is believed to initiate the majority of Alzheimer’s and other neurodegenerative diseases attributed to environmental factors. We investigated whether inhaled PM and specific classes of compounds in wildfire smoke condensate extract (WSE) reach the brain and cause neuro-inflammation that can lead to progressive neurological degeneration, using isotope tracing of labeled particulate matter and major compound classes, biomarkers of blood-brain barrier (BBB) integrity, and biomarkers of neuro-inflammation. This project showed that inhalation exposure to PM and major compound classes present in WSE reached the brain through absorption in the nasal cavity and systemic circulation across the BBB. Twenty-four exposures of WSE to brain endothelial cells that form the main physical barrier of the BBB produced dose-dependent increases in biomarkers of inflammation and decreases in tight junction markers between cells. Intranasal exposure to WSE caused inflammatory disfunction in lung and brain. Biomarkers of inflammation increased and an enzyme inhibiting inflammation decreased. Similar patterns of chemical-induced changes in the lung and brain suggest either: (1) chemicals may act through shared molecular pathways upon entering lung and brain, or (2) that mediators originating in the lung circulate systemically to the brain and drive neuroinflammation. These findings warrant further mechanistic studies to delineate the temporal sequence of events to establish the lung-brain axis.
This document summarizes the key themes from our interviews with 10 remediation companies regarding common approaches used to remove odor and contaminants from homes impacted by fire and smoke damage Remediation companies are in agreement that thorough cleaning is the first step. Cleaning and removing contaminants from homes impacted by wildfires may be sufficient to eliminate smoke odor, which is the most important step when it comes to reducing exposure to any residues that may pose health risks to residents. Remediation companies differ in their approaches to addressing odors, such as using ozone generators, hydroxyl generators, chlorine dioxide treatment, thermal fogging and applying sealants. Their opinions of what works and why differs. There is little consensus on efficacy, safety, or application protocols. For example, some view ozone very favorably, while others would prefer using other methods. The influence of insurance companies in their coverage for some methods but not others also impact the decision about the approaches used. Remediation companies differ in their view on laboratory testing for contaminants, which may be partly influenced by insurance companies as well.
The primary objective of this project is to assess the techno-economic viability of hydropower resources with supplementary investments, including microgrid controllers, storage solutions, load banks, additional generation like diesel generators, communication links, and transmission infrastructure. The aim is to enable these systems to operate autonomously (in islanded mode) and ensure grid resiliency during and after wildfire events. The project seeks to establish a comprehensive framework for setting up hydropower-based microgrids, from risk estimation to final investment decisions. These microgrids can provide critical support during emergencies and offer additional grid stability and revenue opportunities during regular operations and other system contingencies.
Thermokarst is the process of ground subsidence caused by either the thawing of ice-rich permafrost or the melting of massive ground ice. The consequences of permafrost degradation associated with thermokarst for surface ecology, landscape evolution, and hydrological processes have been of great scientific interest and social concern. Part of a tundra patch affected by wildfire in northern Alaska (27.5 km 2 ) was investigated here, using remote sensing and in situ surveys to quantify and understand permafrost thaw dynamics after surface disturbances. A two-pass differential InSAR technique using L-band ALOS-PALSAR has been shown capable of capturing thermokarst subsidence triggered by a tundra fire at a spatial resolution of tens of meters, with supporting evidence from field data and optical satellite images. We have introduced a calibration procedure, comparing burned and unburned areas for InSAR subsidence signals, to remove the noise due to seasonal surface movement. In the first year after the fire, an average subsidence rate of 6.2 cm/year (vertical) was measured. Subsidence in the burned area continued over the following two years, with decreased rates. The mean rate of subsidence observed in our interferograms (from 24 July 2008 to 14 September 2010) was 3.3 cm/year, a value comparable to that estimated from field surveys at two plots on average (2.2 cm/year) for the six years after the fire. These results suggest that this InSAR-measured ground subsidence is caused by the development of thermokarst, a thawing process supported by surface change observations from high-resolution optical images and in situ ground level surveys.