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At least 19 records

Repeated exposure to eucalyptus wood smoke alters pulmonary gene and metabolic profiles in male Long-Evans rats

Abstract Exposure to wildfire smoke is associated with both acute and chronic cardiopulmonary illnesses, which are of special concern for wildland firefighters who experience repeated exposure to wood smoke. It is necessary to better understand the underlying pathophysiology by which wood smoke exposure increases pulmonary disease burdens in this population. We hypothesize that wood smoke exposure produces pulmonary dysfunction, lung inflammation, and gene expression profiles associated with future pulmonary complications. Male Long-Evans rats were intermittently exposed to smoldering eucalyptus wood smoke at 2 concentrations, low (11.0 ± 1.89 mg/m3) and high (23.7 ± 0.077 mg/m3), over a 2-week period. Whole-body plethysmography was measured intermittently throughout. Lung tissue and lavage fluid were collected 24 h after the final exposure for transcriptomics and metabolomics. Increasing smoke exposure upregulated neutrophils and select cytokines in the bronchoalveolar lavage fluid. In total, 3446 genes were differentially expressed in the lungs of rats in the high smoke exposure and only 1 gene in the low smoke exposure (Cd151). Genes altered in the high smoke group reflected changes to the Eukaryotic Initiation Factor 2 stress and oxidative stress responses, which mirrored metabolomics analyses. xMWAS-integrated analysis revealed that smoke exposure significantly altered pathways associated with oxidative stress, lung morphogenesis, and tumor proliferation pathways. These results indicate that intermittent, 2-week exposure to eucalyptus wood smoke leads to transcriptomic and metabolic changes in the lung that may predict future lung disease development. Collectively, these findings provide insight into cellular signaling pathways that may contribute to the chronic pulmonary conditions observed in wildland firefighters.

Toxicology↗

Policy-relevant differences between secondhand and thirdhand smoke: strengthening protections from involuntary exposure to tobacco smoke pollutants

Starting in the 1970s, individuals, businesses and the public have increasingly benefited from policies prohibiting smoking indoors, saving thousands of lives and billions of dollars in healthcare expenditures. Smokefree policies to protect against secondhand smoke exposure, however, do not fully protect the public from the persistent and toxic chemical residues from tobacco smoke (also known as thirdhand smoke) that linger in indoor environments for years after smoking stops. Nor do these policies address the economic costs that individuals, businesses and the public bear in their attempts to remediate this toxic residue. We discuss policy-relevant differences between secondhand smoke and thirdhand smoke exposure: persistent pollutant reservoirs, pollutant transport, routes of exposure, the time gap between initial cause and effect, and remediation and disposal. We examine four policy considerations to better protect the public from involuntary exposure to tobacco smoke pollutants from all sources. We call for (a) redefining smokefree as free of tobacco smoke pollutants from secondhandandthirdhand smoke; (b) eliminating exemptions to comprehensive smoking bans; (c) identifying indoor environments with significant thirdhand smoke reservoirs; and (d) remediating thirdhand smoke. We use the case of California as an example of how secondhand smoke-protective laws may be strengthened to encompass thirdhand smoke protections. The health risks and economic costs of thirdhand smoke require that smokefree policies, environmental protections, real estate and rental disclosure policies, tenant protections, and consumer protection laws be strengthened to ensure that the public is fully protected from and informed about the risks of thirdhand smoke exposure.

Public, Environmental & Occupational Health↗

Spacecraft Smoke Detector Characterization with Reference and Smoke Aerosols

Performance testing of consumer smoke detectors requires specific facilities and experiments with smoldering and flaming emissions from different fuels. Smoke detectors for use in spacecraft are tested using similar setups with representative fuel materials. To simplify smoke detector testing, this study explored the use of laboratory-generated reference aerosols as transfer standards to evaluate smoke detector performance. Among the three tested reference aerosols, mineral oil particles were reproducibly generated with a Gemini smoke detector tester, dioctyl sebacate (DOS) particles were generated with a wide concentration range and flexible size distributions using an atomizer, while polystyrene latex(PSL) particles were difficult to produce with the high concentrations needed for smoke detector testing. Reference aerosols generated from 1.5%–100% DOS solutions and mineral oil covered the response range of six types of smoke aerosols generated by oxidative pyrolysis of spacecraft-relevant materials. Although no single reference aerosol can be used to simulate the response of different smoke detection technologies to different smoke aerosols within ±10% error, the relationship between reference and smoke aerosols derived from this study can be used to predict smoke detector responses to combustion aerosols.

Smoke↗

SMOKE: Characterization of Smoke Particulate for Spacecraft Fire Detection

'Smoke' is a flight definition investigation whose purpose is to characterize the smoke particulate from microgravity smoke sources to enable improved design of future space-craft smoke detectors. In the earliest missions (Mercury, Gemini and Apollo), the crew quarters were so cramped that it was considered reasonable that the astronauts would rapidly detect any fire. The Skylab module, however, included approximately 30 UV-sensing fire detectors. The Space Shuttle Orbiter has nine particle-ionization smoke detectors in the mid-deck and flight deck. The detectors for the US segments of the International Space Station (ISS) are laser-diode, forward-scattering, smoke detectors. Current plans for the ISS call for two detectors in the open area of the module, and detectors in racks that have cooling air-flow. Due to the complete absence of microgravity data, all three of these detector systems were designed based upon 1-g test data and experience. As planned mission durations and complexity increase and the volume of spacecraft increases, the need for and importance of effective, crew-independent, fire detection will grow significantly, necessitating more research into microgravity fire phenomena. In 1997 the Comparative Soot Diagnostics Experiment (CSD) flew in the Orbiter Middeck as a Glovebox payload. The CSD experiment was designed to produce small quantities of smoke from several sources to obtain particulate samples and to determine the response of the ISS and Orbiter smoke detectors to these sources. Marked differences in the performance of the detectors compared to their behavior in 1-g were observed. In extreme cases, the detector used in the orbiter was completely blind to easily visible smoke from sources that were readily detected in 1-g. It is hypothesized but as yet unverified that this performance difference was due to enhanced growth of liquid smoke droplets in low-g. These CSD results clearly demonstrate that spacecraft smoke detector design cannot be based on 1-g experience.

Urban, D. L.↗

Particle and Smoke Detection on ISS for Next Generation Smoke Detectors

Rapid fire detection requires the ability to differentiate fire signatures from background conditions and nuisance sources. Proper design of a fire detector requires detailed knowledge of all of these signal sources so that a discriminating detector can be designed. Owing to the absence of microgravity smoke data, all current spacecraft smoke detectors were designed based upon normal-g conditions. The removal of buoyancy reduces the velocities in the high temperature zones in flames, increasing the residence time of smoke particles and consequently allowing longer growth time for the particles. Recent space shuttle experiments confirmed that, in some cases, increased particles sizes are seen in low-gravity and that the relative performance of the ISS (International Space Station) and space-shuttle smoke-detectors changes in low-gravity; however, sufficient particle size information to design new detectors was not obtained. To address this issue, the SAME (Smoke Aerosol Measurement Experiment) experiment is manifested to fly on the ISS in 2007. The SAME experiment will make measurements of the particle size distribution of the smoke particulate from several typical spacecraft materials providing quantitative design data for spacecraft smoke detectors. A precursor experiment (DAFT: Dust Aerosol measurement Feasibility Test) flew recently on the ISS and provided the first measurement of the background smoke particulate levels on the ISS. These background levels are critical to the design of future smoke detectors. The ISS cabin was found to be a very clean environment with particulate levels substantially below the space shuttle and typical ground-based environments.

Urban, David L.↗

"Smoke": Characterization Of Smoke Particulate For Spacecraft Fire Detection

The "Smoke" experiment is a flight definition investigation that seeks to increase our understanding of spacecraft fire detection through measurements of particulate size distributions of preignition smokes from typical spacecraft materials. Owing to the catastrophic risk posed by even a very small fire in a spacecraft, the design goal for spacecraft fire detection is to detect the fire as quickly as possible, preferably in the preignition phase before a real flaming fire has developed. Consequently the target smoke for detection is typically not soot (typical of established hydrocarbon fires) but instead, pyrolysis products, and recondensed polymer particles. At the same time, false alarms are extremely costly as the crew and the ground team must respond quickly to every alarm. The U.S. Space Shuttle (STS: Space Transportation System) and the International Space Station (ISS) both use smoke detection as the primary means of fire detection. These two systems were designed in the absence of any data concerning low-gravity smoke particle (and background dust) size distributions. The STS system uses an ionization detector coupled with a sampling pump and the ISS system is a forward light scattering detector operating in the near IR. These two systems have significantly different sensitivities with the ionization detector being most sensitive (on a mass concentration basis) to smaller particulate and the light scattering detector being most sensitive to particulate that is larger than 1 micron. Since any smoke detection system has inherent size sensitivity characteristics, proper design of future smoke detection systems will require an understanding of the background and alarm particle size distributions that can be expected in a space environment.

Urban, David L.↗

The Influence of Smoke Particle Properties and Cabin Characteristics on Smoke Detection in Lunar Gravity

Spacecraft fires pose a threat to the success of future Lunar, Martian, and deep space exploration missions. As NASA plans to return humans to the Moon in the next decade, novel mission requirements will present new fire safety challenges. For example, materials that are fire resistant on Earth are expected to burn under planned habitat conditions (elevated oxygen concentrations and reduced cabin pressure) and partial gravity (0.16g). Optimal smoke detector placement will depend on a combination of buoyant plume velocities, induced by partial gravity, and Environmental Control and Life Support Systems (ECLSS) parameters, including particle filtration rates, supply and return placement within the cabin, and forced air velocities. These ECLSS parameters must also address the need for rapid Lunar dust removal, as Lunar dust exposure poses a risk to crew health and hardware functionality. Here, we present progress toward a computational fluid dynamics model to evaluate smoke transport in a Lunar habitat. Recent work has demonstrated that if air supplies are placed on ceilings and returns on the floor, a buoyant smoke layer at the ceiling may disperse over the order of minutes even under low forced flow conditions. We expand upon these results to examine the influence of different supply and return configurations on smoke plume development. Additionally, we also address differences in the transport of smoke particles and Lunar dust by varying particle parameters like size, density, and shape factor. Finally, we discuss ongoing and future experimental efforts to measure smoke particle properties and transport under partial gravity, elevated oxygen, and reduced pressure conditions.

Claire Fortenberry↗

Evaluation of Novel NASA MODIS and VIIRS Aerosol Products and Assessment of Smoke Height Boundary Layer Ratio During Extreme Smoke Events in the Western U.S.

We analyze new aerosol products from NASA satellite retrievals over the western U.S. during August 2013, with special attention to locally generated wildfire smoke and downwind plume structures. Aerosol optical depth (AOD) at 550 nm from MODIS (Terra and Aqua Collections 6 and 6.1) and VIIRS Deep Blue (DB) and MODIS (Terra and Aqua) Multi‐Angle Implementation of Atmospheric Correction (MAIAC) retrievals are evaluated against ground‐based AErosol RObotic NETwork (AERONET) observations. We find a significant improvement in correlation with AERONET and other metrics in the latest DB AOD (MODIS C6.1 r^2=0.75, VIIRS r^2=0.79) compared to MODIS C6 (r2=0.62). In general, MAIAC (r^2=0.84) and DB (MODIS C6.1 and VIIRS) present similar statistical evaluation metrics for the western U.S. and are useful tools to characterize aerosol loading associated with wildfire smoke. We also evaluate three novel NASA MODIS plume injection height (PIH) products, one from MAIAC and two from the Aerosol Single scattering albedo and layer Height Estimation (ASHE) (MODIS and VIIRS) algorithm. Both Terra and Aqua MAIAC PIHs statistically agree with ground‐based and satellite lidar observations near the fire source, as do ASHE, although the latter is sensitive to assumptions about aerosol absorption properties. We introduce a first‐order approximation Smoke Height Boundary Layer Ratio (SHBLR) to qualitatively distinguish between aerosol pollution within the planetary boundary layer and the free troposphere. We summarize the scope, limitations, and suggestions for scientific applications of surface level aerosol concentrations specific to wildfire emissions and smoke plumes using these novel NASA MODIS and VIIRS aerosol products.

Plume injection height↗

The use of the high flux heater in the smoke chamber to measure ignitability and smoke evolution of composite panels

Ten samples of composite panels were evaluated in the smoke chamber using a high flux heater to produce heat flux levels up to 9.5 watts per square cm. This study demonstrated the potential of the apparatus as a means of evaluating ignitability as well as smoke evolution. Depending on the material and the heat flux level, ignitability results ranged from ignition within 2 seconds to no ignition during the test period. Smoke density generally increased with increasing heat flux. A composite panel consisting of bismaleimide-fiberglass/bismaleimide honeycomb with carbon microballoons exhibited the lowest smoke density at high heat flux levels and the greatest resistance to autoignition.

Hilado, C. J.↗

Quantitative determination of smoke and toxic product potential of materials with the AMINCO (registered) NBS smoke density chamber

Quantitative measurements of smoke obscuration produced by standard area samples under high energy pyrolysis both with and without an ignition source, using a collimated vertical light beam in conjunction with an ultra-linear photomultiplier microphotometer are obtainable with the smoke density chamber. Results are expressed in dimensionless specific optical density permitting usage calculations in accordance with a geometric relationship.

Greenberg, S.↗

The Effect of Habitual Smoking on VO2max

VO2max is associated with many factors, including age, gender, physical activity, and body composition. It is popularly believed that habitual smoking lowers aerobic fitness. PURPOSE: to determine the effect of habitual smoking on VO2max after controlling for age, gender, activity and BMI. METHODS: 2374 men and 375 women employed at the NASA/Johnson Space Center were measured for VO2max by indirect calorimetry (RER>=1.1), activity by the 11 point (0-10) NASA Physical Activity Status Scale (PASS), BMI and smoking pack-yrs (packs day*y of smoking). Age was recorded in years and gender was coded as M=1, W=0. Pack.y was made a categorical variable consisting of four levels as follows: Never Smoked (0), Light (1-10), Regular (11-20), Heavy (>20). Group differences were verified by ANOVA. A General Linear Models (GLM) was used to develop two models to examine the relationship of smoking behavior on VO2max. GLM #1(without smoking) determined the combined effects of age, gender, PASS and BMI on VO2max. GLM #2 (with smoking) determined the added effects of smoking (pack.y groupings) on VO2max after controlling for age, gender, PASS and BMI. Constant errors (CE) were calculated to compare the accuracy of the two models for estimating the VO2max of the smoking subgroups. RESULTS: ANOVA affirmed the mean VO2max of each pack.y grouping decreased significantly (p<0.01) as the level of smoking exposure increased. GLM #1 showed that age, gender, PASS and BMI were independently related with VO2max (R2 = 0.642, SEE = 4.90, p<0.001). The added pack.y variables in GLM #2 were statistically significant (R2 change = 0.7%, p<0.01). Post hoc analysis showed that compared to Never Smoked, the effects on VO2max from Light and Regular smoking habits were -0.83 and -0.85 ml.kg- 1.min-1 respectively (p<0.05). The effect of Heavy smoking on VO2max was -2.56 ml.kg- 1.min-1 (p<0.001). The CE s of each smoking group in GLM #2 was smaller than the CE s of the smoking group counterparts in GLM #1. CONCLUSIONS: After accounting for the effects of gender, age, PASS and BMI the effect of habitual smoking on reducing VO2max is minimal, about 0.85 ml/kg/min, until the habit exceeds 20 pack.y at which point an additional decrease of 1.71 ml/kg/min is noted. Adding pack.y data improves the accuracy of predicting the VO2max of smokers.

Wier, Larry T.↗

Wildfire smoke impacts lake ecosystems

Abstract Wildfire activity is increasing globally. The resulting smoke plumes can travel hundreds to thousands of kilometers, reflecting or scattering sunlight and depositing particles within ecosystems. Several key physical, chemical, and biological processes in lakes are controlled by factors affected by smoke. The spatial and temporal scales of lake exposure to smoke are extensive and under‐recognized. We introduce the concept of the lake smoke‐day, or the number of days any given lake is exposed to smoke in any given fire season, and quantify the total lake smoke‐day exposure in North America from 2019 to 2021. Because smoke can be transported at continental to intercontinental scales, even regions that may not typically experience direct burning of landscapes by wildfire are at risk of smoke exposure. We found that 99.3% of North America was covered by smoke, affecting a total of 1,333,687 lakes ≥10 ha. An incredible 98.9% of lakes experienced at least 10 smoke‐days a year, with 89.6% of lakes receiving over 30 lake smoke‐days, and lakes in some regions experiencing up to 4 months of cumulative smoke‐days. Herein we review the mechanisms through which smoke and ash can affect lakes by altering the amount and spectral composition of incoming solar radiation and depositing carbon, nutrients, or toxic compounds that could alter chemical conditions and impact biota. We develop a conceptual framework that synthesizes known and theoretical impacts of smoke on lakes to guide future research. Finally, we identify emerging research priorities that can help us better understand how lakes will be affected by smoke as wildfire activity increases due to climate change and other anthropogenic activities.

54 ENVIRONMENTAL SCIENCES↗

Satellite-based aerosol optical depth estimates over the continental U.S. during the 2020 wildfire season: Roles of smoke and land cover

Wildfires produce smoke that can affect an area >1000 times the burn extent, with far-reaching human health, ecologic, and economic impacts. Accurately estimating aerosol load within smoke plumes is therefore crucial for understanding and mitigating these impacts. We evaluated the effectiveness of the latest Collection 6.1 MODIS Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm in estimating aerosol optical depth (AOD) across the U.S. during the historic 2020 wildfire season. We compared satellite-based MAIAC AOD to ground-based AERONET AOD measurements during no-, light-, medium-, and heavy-smoke conditions identified using the Hazard Mapping System Fire and Smoke Product. This smoke product consists of maximum extent smoke polygons digitized by analysts using visible band imagery and classified according to smoke density. We also examined the strength of the correlations between satellite- and ground-based AOD for major land cover types under various smoke density levels. MAIAC performed well in estimating AOD during smoke-affected conditions. Correlations between MAIAC and AERONET AOD were strong for medium- (r = 0.91) and heavy-smoke (r = 0.90) density, and MAIAC estimates of AOD showed little bias relative to ground-based AERONET measurements (normalized mean bias = 3 % for medium, 5 % for heavy smoke). During two high AOD, heavy smoke episodes, MAIAC underestimated ground-based AERONET AOD under mixed aerosol (i.e., smoke and dust; median bias = −0.08) and overestimated AOD under smoke-dominated (median bias = 0.02) aerosol. MAIAC most overestimated ground-based AERONET AOD over barren land (mean NMB = 48 %). Our findings indicate that MODIS MAIAC can provide robust estimates of AOD as smoke density increases in coming years. Increased frequency of mixed aerosol and expansion of developed land could affect the performance of the MAIAC algorithm in the future, however, with implications for evaluating wildfire-associated health and welfare effects and air quality standards.

54 ENVIRONMENTAL SCIENCES↗

Advanced optical smoke meters for jet engine exhaust measurement

Smoke meters with increased sensitivity, improved accuracy, and rapid response are needed to measure the smoke levels emitted by modern jet engines. The standard soiled tape meter in current use is based on filtering, which yields long term averages and is insensitive to low smoke levels. Two new optical smoke meter techniques that promise to overcome these difficulties have been experimentally evaluated: modulated transmission (MODTRAN) and photothermal deflection spectroscopy (PDS). Both techniques are based on light absorption by smoke, which is closely related to smoke density. They are variations on direct transmission measurements which produce a modulated signal that can be easily measured with phase sensitive detection. The MODTRAN and PDS techniques were tested on low levels of smoke and diluted samples of NO2 in nitrogen, simulating light adsorption due to smoke. The results are evaluated against a set of ideal smoke meter criteria that include a desired smoke measurement range of 0.1 to 12 mg cu.m. (smoke numbers of 1 to 50) and a frequency response of 1 per second. The MODTRAN instrument is found to be inaccurate for smoke levels below 3 mg/cu.m. and is able to make a only about once every 20 seconds because of its large sample cell. The PDS instrument meets nearly all the characteristics of an ideal smoke meter: it has excellent sensitivity over a range of smoke levels from 0.1 to 20 mg/cu.m. (smoke numbers of 1 to 60) and good frequency response (1 per second).

Pitz, R. W.↗

Evaluation and Intercomparison of Wildfire Smoke Forecasts from Multiple Modeling Systems for the 2019 Williams Flats Fire

Wildfire smoke is one of the most significant concerns of human and environmental health, associated with its substantial impacts on air quality, weather, and climate. However, biomass burning emissions and smoke remain among the largest sources of uncertainties in air quality forecasts. In this study, we evaluate the smoke emissions and plume forecasts from 12 state-of-the-art air quality forecasting systems during the Williams Flats fire in Washington State, US, August 2019, which was intensively observed during the Fire Influence on Regional to Global Environments and Air Quality (FIREX-AQ) field campaign. Model forecasts with lead times within 1 d are intercompared under the same framework based on observations from multiple platforms to reveal their performance regarding fire emissions, aerosol optical depth (AOD), surface PM2.5, plume injection, and surface PM2.5 to AOD ratio. The comparison of smoke organic carbon (OC) emissions suggests a large range of daily totals among the models, with a factor of 20 to 50. Limited representations of the diurnal patterns and day-to-day variations of emissions highlight the need to incorporate new methodologies to predict the temporal evolution and reduce uncertainty of smoke emission estimates. The evaluation of smoke AOD (sAOD) forecasts suggests overall underpredictions in both the magnitude and smoke plume area for nearly all models, although the high-resolution models have a better representation of the fine-scale structures of smoke plumes. The models driven by fire radiative power (FRP)-based fire emissions or assimilating satellite AOD data generally outperform the others. Additionally, limitations of the persistence assumption used when predicting smoke emissions are revealed by substantial underpredictions of sAOD on 8 August 2019, mainly over the transported smoke plumes, owing to the underestimated emissions on 7 August. In contrast, the surface smoke PM2.5 (sPM2.5) forecasts show both positive and negative overall biases for these models, with most members presenting more considerable diurnal variations of sPM2.5. Overpredictions of sPM2.5 are found for the models driven by FRP-based emissions during nighttime, suggesting the necessity to improve vertical emission allocation within and above the planetary boundary layer (PBL). Smoke injection heights are further evaluated using the NASA Langley Research Center's Differential Absorption High Spectral Resolution Lidar (DIAL-HSRL) data collected during the flight observations. As the fire became stronger over 3–8 August, the plume height became deeper, with a day-to-day range of about 2–9 km a.g.l. However, narrower ranges are found for all models, with a tendency of overpredicting the plume heights for the shallower injection transects and underpredicting for the days showing deeper injections. The misrepresented plume injection heights lead to inaccurate vertical plume allocations along the transects corresponding to transported smoke that is 1 d old. Discrepancies in model performance for surface PM2.5 and AOD are further suggested by the evaluation of their ratio, which cannot be compensated for by solely adjusting the smoke emissions but are more attributable to model representations of plume injections, besides other possible factors including the evolution of PBL depths and aerosol optical property assumptions. By consolidating multiple forecast systems, these results provide strategic insight on pathways to improve smoke forecasts.

AOD↗