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At least 19 records

Prescribed fires, smoke exposure, and hospital utilization among heart failure patients

Abstract Background Prescribed fires often have ecological benefits, but their environmental health risks have been infrequently studied. We investigated associations between residing near a prescribed fire, wildfire smoke exposure, and heart failure (HF) patients’ hospital utilization. Methods We used electronic health records from January 2014 to December 2016 in a North Carolina hospital-based cohort to determine HF diagnoses, primary residence, and hospital utilization. Using a cross-sectional study design, we associated the prescribed fire occurrences within 1, 2, and 5 km of the patients’ primary residence with the number of hospital visits and 7- and 30-day readmissions. To compare prescribed fire associations with those observed for wildfire smoke, we also associated zip code-level smoke density data designed to capture wildfire smoke emissions with hospital utilization amongst HF patients. Quasi-Poisson regression models were used for the number of hospital visits, while zero-inflated Poisson regression models were used for readmissions. All models were adjusted for age, sex, race, and neighborhood socioeconomic status and included an offset for follow-up time. The results are the percent change and the 95% confidence interval (CI). Results Associations between prescribed fire occurrences and hospital visits were generally null, with the few associations observed being with prescribed fires within 5 and 2 km of the primary residence in the negative direction but not the more restrictive 1 km radius. However, exposure to medium or heavy smoke (primarily from wildfires) at the zip code level was associated with both 7-day (8.5% increase; 95% CI = 1.5%, 16.0%) and 30-day readmissions (5.4%; 95% CI = 2.3%, 8.5%), and to a lesser degree, hospital visits (1.5%; 95% CI: 0.0%, 3.0%) matching previous studies. Conclusions Area-level smoke exposure driven by wildfires is positively associated with hospital utilization but not proximity to prescribed fires.

Raab, Henry↗

Analyzing Wildland Fire Smoke Emissions Data Using Compositional Data Techniques

By conservation of mass, the mass of wildland fuel that is pyrolyzed and combusted must equal the mass of smoke emissions, residual char and ash. For a given set of conditions, these amounts are fixed. This places a constraint on smoke emissions data which violates statistical assumptions for many of the methods currently used to analyze these data such as linear regression, analysis of variance, and t-tests. These data are inherently multivariate and non-negative parts of a whole. This paper introduces the field of compositional data analysis to the emissions community and provides examples of appropriate statistical treatment of emissions data. It is shown that modified combustion efficiency should not be used as a predictor variable for other smoke emissions because it is not an independent variable. An alternative method based on compositional linear trends to estimate trace gas composition using CO and CO2 is presented. The data used in this paper resulted from projects the DOD/DOE/EPA Strategic 586 Environmental Research and Development Program projects RC-1648 and 1649. The senior 587 author appreciates the guidance and R scripts provided by Prof. Girty at San Diego State 588 University to estimate linear trends by perturbation. J. P.-A. was supported by the Spanish 589 Ministry of Science, Innovation and Universities under the project CODAMET (RTI2018-590 095518-B-C21, 2019-2021). The data used in this study have been previously published and are 591 available in the original publications. DRW conceived the initial manuscript (70 percent) and 592 performed the bulk of the data analysis. JPA provided statistical guidance and compositional data 593 expertise and contributed 20 percent of the manuscript. TJJ and HJ were extensively involved in 594 the study that provided the data. TJJ provide smoke emissions expertise and HJ provided 595 combustion expertise. The authors declare that they have no conflict of interest. The use of trade 596 or firm names in this publication is for reader information and does not imply endorsement by 597 the U.S. Department of Agriculture of any product or service.

simplex, compositional data analysis, balance, log↗

Fire and Smoke [Slides]

Prescribed (Rx) fire is a planned, usually low-intensity, fire conducted by professionals with ecosystem-dependent objectives. Prescribed fire is not just about reducing fire risk. Ecological benefit include: (1) Maintaining fire-adapted ecosystems; (2) Promote ecological diversity; (3) Controlling invasive species; (4) Habitat maintenance; (5) Hydrologic balances; and (6) Carbon Management.

54 ENVIRONMENTAL SCIENCES↗

Modelling Framework For Fire And Smoke Detection In Imagery

This framework was developed to ingest images/video images to train and test artificial neural network structures for image-based detection of fire and smoke. The code includes data preprocessing, model development, and testing. The framework is designed to work with RGB video imagery.

Griffel, LloydM.↗

Short-term impacts of 2017 western North American wildfires on meteorology, the atmosphere’s energy budget, and premature mortality

Abstract Western North American fires have been increasing in magnitude and severity over the last few decades. The complex coupling of fires with the atmospheric energy budget and meteorology creates short-term feedbacks on regional weather altering the amount of pollution to which Americans are exposed. Using a combination of model simulations and observations, this study shows that the severe fires in the summer of 2017 increased atmospheric aerosol concentrations leading to a cooling of the air at the surface, reductions in sensible heat fluxes, and a lowering of the planetary boundary layer height over land. This combination of lower-boundary layer height and increased aerosol pollution from the fires reduces air quality. We estimate that from start of August to end of October 2017, ∼400 premature deaths occurred within the western US as a result of short-term exposure to elevated PM 2.5 from fire smoke. As North America confronts a warming climate with more fires the short-term climate and pollution impacts of increased fire activity should be assessed within policy aimed to minimize impacts of climate change on society.

Bernstein, Diana N. (ORCID:0000000308279336)↗

Modeling the impact of smoke from prescribed fire on road visibility

Prescribed fires are planned to achieve conservation and fuel reduction objectives while minimizing smoke ground concentration to limit health impacts and road visibility impairment. Prescribed burns cannot indeed be conducted if those hazards are not within predefined limits. This paper proposes a new framework to evaluate road visibility that overcomes the limitation of the state of the art model, VSMOKE. The framework leverages the fast-running framework QUIC-Fire/QUIC-SMOKE to capture fire and smoke dynamics, and the timing and duration of hazardous conditions on the road network close to the burn unit (within 50–100 km). The paper presents parametric study using a real burn plot at Fort Stewart (GA, USA), under hypothetical wind conditions to understand the interplay between buoyancy and smoke dilution. Here, results showed that faster winds caused fire escape while slower winds did not achieve a complete burn. Furthermore, faster winds featured brief road visibility reduction below braking distance.

54 ENVIRONMENTAL SCIENCES↗

Attributing human mortality from fire PM 2.5 to climate change

Climate change intensifies fire smoke, emitting hazardous air pollutants that impact human health. However, the global influence of climate change on fire-induced health impacts remains unquantified. Here, in this study, we used three well-tested fire-vegetation models in combination with a chemical transport model and health risk assessment framework to attribute global human mortality from fire fine particulate matter (PM 2.5 ) emissions to climate change. Of the 46401 (1960s) –to 98748 (2010s) annual fire PM 2.5 mortalities, 669 (1.2%, 1960s) –to 12566 (12.8%, 2010s) were attributed to climate change. The most substantial influence of climate change on fire mortality occurred in South America, Australia, and Europe, coinciding with decreased relative humidity, and in boreal forests with increased air temperature. Increasing relative humidity lowered fire mortality in other regions, like South Asia. Our study highlights the role of climate change in fire mortality, aiding public health authorities in spatial targeting adaptation measures for sensitive fire-prone areas.

54 ENVIRONMENTAL SCIENCES↗

Wildfire Smoke Adjustment Factors for Low-Cost and Professional PM 2.5 Monitors with Optical Sensors

Air quality monitors using low-cost optical PM 2.5 sensors can track the dispersion of wildfire smoke; but quantitative hazard assessment requires a smoke-specific adjustment factor (AF). This study determined AFs for three professional-grade devices and four monitors with low-cost sensors based on measurements inside a well-ventilated lab impacted by the 2018 Camp Fire in California (USA). Using the Thermo TEOM-FDMS as reference, AFs of professional monitors were 0.85 for Grimm mini wide-range aerosol spectrometer, 0.25 for TSI DustTrak, and 0.53 for Thermo pDR1500; AFs for low-cost monitors were 0.59 for AirVisual Pro, 0.48 for PurpleAir Indoor, 0.46 for Air Quality Egg, and 0.60 for eLichens Indoor Air Quality Pro Station. We also compared public data from 53 PurpleAir PA-II monitors to 12 nearby regulatory monitoring stations impacted by Camp Fire smoke and devices near stations impacted by the Carr and Mendocino Complex Fires in California and the Pole Creek Fire in Utah. Camp Fire AFs varied by day and location, with median (interquartile) of 0.48 (0.44–0.53). Adjusted PA-II 4-h average data were generally within ±20% of PM 2.5 reported by the monitoring stations. Adjustment improved the accuracy of Air Quality Index (AQI) hazard level reporting, e.g., from 14% to 84% correct in Sacramento during the Camp Fire.

47 OTHER INSTRUMENTATION↗

Intense formation of secondary ultrafine particles from Amazonian vegetation fires and their invigoration of deep clouds and precipitation

New particle formation (NPF) in fire smoke is thought to be unlikely due to large condensation and coagulation sinks that scavenge molecular clusters. We analyze aircraft measurements over the Amazon and find that fires significantly enhance NPF and ultrafine particle (UFP < 50 nm diameter) numbers compared to background conditions, contrary to previous understanding. We identify that the nucleation of dimethylamine with sulfuric acid, which is aided by the formation of extremely low volatility organics in biomass-burning smoke, can overcome the large condensation and coagulation sinks and explain aircraft observations. We show that freshly formed clusters rapidly grow to UFP sizes through biomass-burning secondary organic aerosol formation, leading to a 10-fold increase in UFP number concentrations. Here, we find a contrasting effect of UFPs on deep convective clouds compared to the larger particles from primary emissions for the case investigated here. UFPs intensify the deep convective clouds and precipitation due to increased condensational heating, while larger particles delay and reduce precipitation.

54 ENVIRONMENTAL SCIENCES↗

Multiscale Wildfire Simulation Framework and Remote Sensing

Wildfire as one type of climate extreme events causes huge socioeconomic losses and damages. Large wildfires (i.e., generated pyrocumulonimbus (PyroCb)) can inject tremendous amounts of smoke into the stratosphere, where black carbon and organic carbon aerosols can persist months to years and influence climate by imposing a significant reduction in the radiative forcing like that associated with large volcanic eruptions or proposed via climate interventions such as geoengineering. Both observations and numerical modeling results clearly indicate an increasing trend in wildfire frequency and intensity in many regions during the recent decades with climate change. However, current understanding of wildfire remains largely uncertain owing to limitations of modeling capabilities in representing the multiscale wildfire physics and dynamics and a scarcity of observations constraining important wildfire and environmental variables. This study primarily aims to improve the wildfire simulation capabilities in the state-of-the-art climate model by filling in two major gaps: (1) model resolution is typically too coarse to resolve fine scale processes associated with fires, and (2) chemistry and aerosol processes in fire smoke are poorly represented.

54 ENVIRONMENTAL SCIENCES↗

Upper Troposphere Smoke Injection From Large Areal Fires

Abstract Large areal fires, such as those ignited following a nuclear detonation, can inject smoke into the upper troposphere and lower stratosphere. Detailed fire simulations allow for assessment of how local weather interacts with these fires and affects smoke lofting. In this study, we employ the fire simulation package in the Weather Research and Forecasting (WRF‐Fire) model, Version 4.0.1, to explore how smoke lofting from a fire burning a homogeneous fuel bed changes with varying local winds, relative humidity, and atmospheric boundary‐layer stability for two different‐sized areal fires. The presence of moisture has the greatest influence on the results by raising the altitude of lofting, while faster wind speeds dampen lofting and lower the injection height. Stably stratified conditions inhibit plume propagation compared with neutrally stratified conditions, although the impact of stability is not as strong as that of moisture and winds. These findings highlight the importance of using an appropriate atmospheric profile when simulating large fires, as the local weather can have a meaningful influence on smoke lofting.

54 ENVIRONMENTAL SCIENCES↗

Burn parameters affect PAH emissions at conditions relevant for prescribed fires

Wildfire smoke is a health hazard as it contains carcinogenic volatile compounds and fine particulate matter. In particular, exposure to polycyclic aromatic hydrocarbons (PAHs) is a major concern, since these compounds have been recognized as important contributors to the overall carcinogenic risk. In this work, gas and particle-phase PAH emissions from combustion of Eastern White Pine (Pinus strobus) were quantified using time-of-flight mass spectrometry over a range of burn conditions representative of wildfires and prescribed fires, including fuel moisture, heat flux, and oxygen concentration. We found that changing the burn environment lead to a variability of up to 77% in phenanthrene/anthracene emissions. This could explain a large part of the variability in PAH emission factors from biomass combustion reported in the literature. Here, we found that optimal conditions for fuel moisture content of 20–30%, sample heat load of 60 - 70 kW m -2 , and oxygen concentrations of 5–15% can significantly reduce the emissions of heavy molar weight PAHs. Our analysis showed that the relative carcinogenic risk from PAH exposure can be reduced by more than 50% under optimal conditions. In light of the increasing use of prescribed fire for forest management, the relationship between emissions and burn conditions that we have established provides a guidance for assessing the expected health impact from prescription burns, and can inform strategies to reduce PAH emissions from prescribed fire activities.

63 RADIATION, THERMAL, AND OTHER ENVIRON. POLLUTAN↗

A Multi-Analysis Approach for Estimating Regional Health Impacts from the 2017 Northern California Wildfires

In the evening of October 8 and early hours of October 9, 2017, high winds in Northern California downed trees and power lines, igniting some of the most devastating wildfires the state had seen, and within hours unhealthy air quality impacted millions of people. We simulated these air quality conditions using fire detection information from the MODIS, VIIRS, and GOES-16 ABI satellite instruments, and applying a set of three WRF–CMAQ simulations, one data fusion, and three machine learning methods. We investigated using the 5-min available GOES-16 fire detection data to simulate timing of fire activity to allocate emissions hourly for the WRF-CMAQ air quality modeling system. Interestingly, this approach did not necessarily improve results compared to the baseline case, which used a default time profile. However, this approach was key to simulating the initial 12-hr explosive fire activity and smoke impacts. The WRF-CMAQ simulations compared well with observational data for the October 8-15 time period and tended to overestimate concentrations October 16-20. To improve these results, we applied three machine learning algorithms. We also had a unique opportunity to evaluate results with temporary monitors deployed specifically for wildfires, and performance was markedly different. For example, at the permanent monitoring locations, the WRF-CMAQ simulations had a Pearson correlation of 0.65, and the data fusion approach improved this (Pearson correlation = 0.95), while at the temporary monitor locations across the WRF-CMAQ, data fusion, and machine learning datasets, the best Pearson correlation was 0.5. The data fusion and machine learning results were biased low and WRF-CMAQ results were biased high. Finally, we applied the optimized PM2.5 exposure estimate in a short-term exposure-response function. Total estimated mortality attributable to PM2.5 exposure during the smoke episode was 83 (95% confidence interval: 0, 196) with 47% of these deaths attributable to wildland fire smoke.

O'Neill, Susan↗

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↗