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This study aims at investigating the biomass burning aerosols (BBA) from 2019 to 2020 extreme wildfires in California, Australia and Siberia, in terms of aerosol characteristics and direct radiative effect. This study is based on the comparison between global climate simulations (ARPEGE‐Climat) and reference aerosol data sets (reanalyzes, ground‐based observations and satellite data). First, our results demonstrate the need to constrain the injection heights in the model in order to realistically represent extinction vertical profiles observed during fire events, both in the troposphere and in the lower stratosphere due to the contribution of pyro‐convection. Without specific vertical emission profiles for fires, the ARPEGE‐Climat simulations fail in representing aerosol extinction vertical profiles. For each region studied, the modeled aerosol optical depth (AOD) is extremely high (above 3 at 550 nm). An important long‐range transport of BBA emitted in Australia and California is shown, with high AOD further from sources. These extremely dense plumes significantly perturb the surface incident solar radiation and exert a large direct (surface) shortwave radiative effect up to −13, −29 and −17 W m−2 ${\mathrm{m}}^{-2}$ on monthly average over Australia (January 2020), California (September 2020) and Siberia (August 2019), respectively. A noteworthy positive BBA direct radiative effect (warming) is found at the top of the atmosphere, when dense and strongly absorbing smoke plumes are advected over cloudy oceanic regions, characterized by high surface albedo. This absorption leads to an increase of the solar heating rate up to 0.3 K day−1 ${\text{day}}^{-1}$ with possible implications on the atmospheric temperature and dynamics. Plain Language Summary: Australian, Californian and Siberian regions were affected by extreme wildfires in the 2019–2020 period, which have emitted huge amounts of particles in the atmosphere. This study aims at investigating the characteristics and radiative effects of these particles, based on numerical climate simulations and various observations. Our results first demonstrate the need to constrain the smoke injection heights in the model in order to realistically represent the particle vertical distribution characterized by the influence of pyro‐convection. These smoke plumes are transported over long distance, perturbating Earth's radiative budget. Indeed, at the top of the atmosphere, the smoke radiative effect is found to be positive, thus warming the atmosphere, when dense and strongly absorbing smoke plumes are advected over cloudy oceanic regions, characterized by high surface albedo. Key Points: Aerosols from 2019 to 2020 extreme fires in Australia, California and Siberia are assessed using a global reanalysis‐driven climate simulationThe aerosol injection height must be constrained to simulate the observed aerosol vertical distribution influenced by the pyro‐convectionThese fires feature high aerosol loads, long‐range transport and positive radiative effect at the top of the atmosphere over cloudy regions [ABSTRACT FROM AUTHOR]

The occurrence of forest ground smoldering combustion has been increasingly frequent in recent years, resulting in significant emissions that have a detrimental impact on the ecological environment. Current research on smoldering emissions, however, is relatively scarce and fragmented across the fields of ecology, environmental protection, medicine, and forestry. The present paper offers a comprehensive review of the research methodologies employed in emissions, emission quantification results, the correlation between emissions and fire behaviors, and the potential for identifying smoldering combustion through emissions. Due to various factors such as the research region, characteristics of the samples, and experimental methods, it becomes challenging to arrive at comprehensive and accurate conclusions regarding the carbon cycle, dynamics of smoke plumes, and toxicological hazards. The limited research on the correlation between emissions and fire behaviors hampers the development and application of smoldering combustion identification technology based on emissions. It is suggested that standardized and universal methods for studying emissions should be popularized among researchers. In addition, the research on the correlation between emission characteristics and combustion temperature, spread direction, and spread velocity needs to be further strengthened. [ABSTRACT FROM AUTHOR]

During summer 2023 Canada experienced its most intense wildfire season on record. Smoke plumes from these fires advected across the United States (U.S.) Upper Midwest, producing regional scale surface enhancements of PM2.5 and ozone, as recorded by the U.S. surface monitoring network. These events are notable because they occurred early in the fire season (May 15‐June 30), and they produced the highest regional‐scale surface ozone levels ever recorded across the northern tier of the U.S. during early (May–June) or late (July‐August) summer. Specifically, the Upper Midwest 50th ozone percentile was greater than in any other year since 1995, when the ozone monitoring network had sufficient coverage to assess regional‐scale ozone levels; the 90th percentile was the highest since 2002. Satellite and aircraft measurements demonstrate the availability of ozone precursors and ozone production within the smoke plumes. Plain Language Summary: Ozone is a trace gas in the atmosphere that acts as an important greenhouse gas, and high concentrations near Earth's surface are a form of air pollution, detrimental to human health and vegetation productivity. Ozone is formed by sunlight reacting with precursor gases, such as those emitted by fossil fuel combustion. Wildfires are also an important source of ozone precursor gases. During summer 2023 Canada experienced its most intense wildfire season on record. Smoke from these fires impacted the U.S. Upper Midwest during May–June 2023, leading to regional scale surface enhancements of fine particulate matter and ozone. These unusual early season fires produced the highest regional‐scale surface ozone levels ever recorded across the northern U.S. Mid‐latitude wildfires have increased as the planet warms, and their frequency is expected to increase further with continued climate change. This analysis suggests that extreme ozone pollution episodes associated with wildfires could also increase in the future. Key Points: During summer 2023 Canada experienced its most intense wildfire season on recordSmoke from these fires impacted the United States (U.S.) Upper Midwest during May–June, leading to regional scale surface enhancements of PM2.5 and ozoneThese unusual early season fires produced the highest regional‐scale surface ozone levels ever recorded across the northern United States [ABSTRACT FROM AUTHOR]

In September 2020, the Western United States experienced anomalously severe wildfires that resulted in carbon monoxide (CO) emissions almost three times the 2001–2019 average. In this study, we investigate the influence of wildfires on atmospheric carbon monoxide (CO) variability through a comparative analysis of observations from the Measurements of Pollution in the Troposphere (MOPITT), the Infrared Atmospheric Sounding Interferometer (IASI), and the Tropospheric Monitoring Instrument (TROPOMI). Our focus is on the North American domain, aiming to understand the differences among these products. In general, all instruments show excellent agreement under typical atmospheric CO conditions. However, notable discrepancies were observed in the CO data from the three sensors, particularly in regions with elevated CO total column (TC) values. IASI and TROPOMI consistently showed higher CO values over the western U.S. compared to MOPITT. During the fire episodes, we found that the IASI retrievals suggested higher CO abundances near the surface than the MOPITT thermal infrared retrievals that are probably the result of the differences in the covariance matrices used in IASI and MOPITT retrievals. We also found that the high IASI and TROPOMI CO observations over the western U.S. coincided with high values of the TROPOMI aerosol index (AI), suggesting the presence of absorbing aerosols. The analysis exhibited better agreement between TROPOMI and MOPITT CO TC when the AI values were low. Our results suggest that appropriate quality filtering should be employed when analyzing pollution events with these data. In particular, utilizing the AI for quality filtering may be useful when analyzing extreme pollution events with these satellite products. Plain Language Summary: In September 2020, wildfires in the Western U.S. caused large smoke plumes that spread across the continent, significantly increasing atmospheric carbon monoxide (CO) levels. Using data from the MOPITT, IASI, and TROPOMI satellite sensors, this study found strong CO enhancements from the fires. The sensors showed good agreement under moderate CO conditions but diverged in areas of high CO and heavy aerosol loads, suggesting aerosol interference in CO retrievals. TROPOMI's UV Aerosol Index (AI) and CALIPSO data were used to evaluate aerosol impacts, emphasizing the need for quality filtering when analyzing CO during intense pollution events. Key Points: All the three CO satellite instruments (Measurements of Pollution in the Troposphere, Infrared Atmospheric Sounding Interferometer (IASI), and Tropospheric Monitoring Instrument (TROPOMI)) show excellent agreement under typical atmospheric CO conditionsThe CO data from the three sensors indicated large discrepancies in regionsThe very high IASI and TROPOMI CO observations over the PNW coincide with the high TROPOMI aerosol index values [ABSTRACT FROM AUTHOR]

Aerosol absorption of visible light has an important impact on global radiative forcing. Wildfires are one of the major sources of light-absorbing aerosol, but there remains significant uncertainty about the magnitude, wavelength dependence, and bleaching of absorption from biomass burning aerosol. We collected and analyzed data from 21 western US wildfire smoke plumes during the 2018 Western Wildfire Experiment for Cloud Chemistry, Aerosol Absorption and Nitrogen (WE-CAN) airborne measurement campaign to determine the contribution of black carbon (BC), brown carbon (BrC), and lensing to the aerosol mass absorption cross section (MAC). Comparison to commonly used parameterizations and modeling studies suggests that model overestimation of absorption is likely due to incorrect BrC refractive indices. Modelers (Wang et al., 2018; Carter et al., 2021) invoke a bleaching process that decreases the MAC of organic aerosol (OA) to offset the overestimation of absorption in models. However, no evidence of a decreasing MAC is observed in individual WE-CAN fire plumes or in aged plumes from multiple fires. A decrease in OA mass and water-soluble organic carbon (WSOC), both normalized by carbon monoxide (CO) to correct for dilution, is observed with an increasing oxygen-to-carbon (O : C) ratio and a decreasing gas-phase toluene : benzene ratio, when data from all fires are combined in half of the individual fire plumes. This results in a strong decrease in total absorption at 405 nm and a slight decrease at 660 nm with these chemical markers. These results demonstrate that changes in absorption with chemical markers of plume age are the result of decreasing OA rather than changes in the MAC of the organic material itself. While decreasing MAC or OA mass with aging could both be called bleaching and can both correct overestimation of absorption in models, it is important to distinguish between these two effects because decreasing OA mass will also decrease scattering, which will cause a significantly different net radiative effect. We also find that an average of 54 % of non-BC absorption (23 % total absorption) at 660 nm is from water-soluble BrC, confirming that BrC absorption is important across the visible spectrum. Quantification of significant BrC at red wavelengths and observation of bleaching being caused by changes in OA with O : C and toluene : benzene markers of plume age provide important improvements to our understanding of BrC and critical constraints on aerosol absorption in regional and global climate models. [ABSTRACT FROM AUTHOR]

A real-time air quality forecasting system was developed using the Weather Research and Forecasting model coupled with Chemistry (WRF-Chem) to provide support for flight planning activities during the NOAA Atmospheric Emissions and Reactions Observed from Megacities to Marine Areas (AEROMMA) and NASA Synergistic TEMPO Air Quality Science (STAQS) 2023 field campaigns. The forecasting system operated on two separate domains centered on Chicago, IL, and New York City, NY, and provided 72-hour predictions of atmospheric composition, aerosols, and clouds. This study evaluates the Chicago-centered forecasting system's 1-, 2-, and 3-day ozone (O3) forecast skill for Chiwaukee Prairie, WI, a rural area downwind of Chicago that often experiences high levels of O3 pollution. Comparisons to vertical O3 profiles collected by a Tropospheric Ozone Lidar Network (TOLNet) instrument revealed that forecast skill decreases as forecast lead time increases. When compared to surface measurements, the forecasting system tended to underestimate O3 concentrations on high O3 days and overestimate on low O3 days at Chiwaukee Prairie regardless of forecast lead time. Using July 25, 2023, as a case study, analyses show that the forecasts underestimated peak O3 levels at Chiwaukee Prairie during this regionwide bad air quality day. Wind speed and direction data indicates that this underestimation can partially be attributed to lake breeze simulation errors. Surface fine particulate matter (PM2.5) measurements, Geostationary Operational Environmental Satellite-16 (GOES-16) aerosol optical depth (AOD) data, and back trajectories from the NOAA Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model show that transported Canadian wildfire smoke impacted the Lake Michigan region on this day. Errors in the forecasted chemical composition and transport of the smoke plumes also contributed to underpredictions of O3 levels at Chiwaukee Prairie on July 25, 2023. The results of this work help identify improvements that can be made for future iterations of the WRF-Chem forecasting system. Implications: Air quality forecasting is an important tool that can be used to inform the public about upcoming high pollution days so that individuals may plan accordingly to limit their exposure to health-damaging air pollutants. Forecasting also helps scientists make decisions about where to make observations during air quality field campaigns. A variety of observational datasets were used to evaluate the accuracy of an air quality forecasting system that was developed for NOAA and NASA field campaigns that occurred in the summer of 2023. These evaluations inform areas of improvement for future development of this air quality forecasting system. [ABSTRACT FROM AUTHOR]

Agriculture crop residue burning has become a major environmental problem facing the Indo-Gangetic plain, as well as contributing to global warming. This paper reports the results of a comprehensive study, examining the variations in aerosol optical, microphysical, and radiative properties that occur during biomass-burning events at Amity University Haryana (AUH), at a rural station in Gurugram (Latitude: 28.31° N, Longitude: 76.90° E, 285 m AMSL), employing ground-based observations of AERONET and Aethalometer, as well as satellite and model simulations during 7–16 November 2021. The smoke emissions during the burning events enhanced the aerosol optical depth (AOD) and increased the Angstrom exponent (AE), suggesting the dominance of fine-mode aerosols. A smoke event that affected the study region on 11 November 2021 is simulated using the regional NAAPS model to assess the role of smoke in regional aerosol loading that caused an atmospheric forcing of 230.4 W/m2. The higher values of BC (black carbon) and BB (biomass burning), and lower values of AAE (absorption Angstrom exponent) are also observed during the peak intensity of the smoke-event period. A notable layer of smoke has been observed, extending from the surface up to an altitude of approximately 3 km. In addition, the observations gathered from CALIPSO regarding the vertical profiles of aerosols show a qualitative agreement with the values obtained from AERONET observations. Further, the smoke plumes that arose due to transport of a wide-spread agricultural crop residue burning are observed nationwide, as shown by MODIS imagery, and HYSPLIT back trajectories. Thus, the present study highlights that the smoke aerosol emissions during crop residue burning occasions play a critical role in the local/regional aerosol microphysical and radiation properties, and hence in the climate variability. [ABSTRACT FROM AUTHOR]

We study how air pollution impacts the U.S. labor market by analyzing the effects of drifting wildfire smoke. We link satellite-based smoke plume data with labor market outcomes to estimate that an additional day of smoke exposure reduces quarterly earnings by about 0.1%. Extensive margin responses, including employment reductions and labor force exits, explain 13% of the overall earnings losses. The implied welfare costs from lost earnings due to air pollution exposure is on par with standard valuations of the mortality burden. The findings highlight the importance of labor market channels in air pollution policy responses. [ABSTRACT FROM AUTHOR]

The impact of wildfire smoke is largely determined by the height where they are injected into the atmosphere. Current plume rise models tend to underestimate the high smoke injection heights because the previous models and configurations were mainly constrained and validated by the plume height observation from Multi‐angle Imaging SpectroRadiometer (MISR), of which most cases inject low within the planetary boundary layer (PBL). Here we retrieve smoke injection heights from intense pyro‐convections based on pyrocumulonimbus satellite images in PYROCAST data set alongside meteorological reanalysis. It largely augments the MISR data set with smoke injection heights up to the upper troposphere and lower stratosphere (UTLS). Constrained by both MISR and PYROCAST, we show that a scaling down of factor 0.2 to the entrainment efficiency parameterized in the one‐dimensional plume‐rise model (1‐D PRM, Freitas et al. (2010, https://doi.org/10.5194/acp‐10‐585‐2010)) significantly improves the model performance for high injection cases without compromising the accuracy of low injection cases. We also found that the fire intensity input can be obtained through a simplified dependence on the biome and biomass burning emission flux. While being unable to represent high cases before, the improved 1‐D PRM model predicts similarly well in injection heights both low near the PBL height and high into the UTLS. The improved 1‐D PRM is then coupled into Community Atmosphere Model with Chemistry (CAM‐chem). The coupled CAM‐chem‐PRM, when predicting injection heights in tests imitating real BB emission, exhibited consistent predictive capabilities with the standalone 1‐D PRM while saw a mere 15% increase of computation time. Plain Language Summary: When wildfires happen, smoke goes into the sky at different heights and usually the higher smoke rises, the longer distance it could influence. Scientists rely on computer models to predict the smoke rise height but previous models often have trouble replicating those smoke plumes injected very high. In this work, we obtained new smoke height data from satellite images. Based on that, we improve the model's ability to predict both low smoke (near the ground) and high smoke (way up high). The improved model was then added to a bigger model that predicts the whole Earth's atmosphere. The coupled model would grant us the ability to better understand the role of wildfire smoke, especially the smoke rising very high, in global air quality, atmospheric chemistry and climate. Key Points: This work retrieved smoke injection heights of high plume rise events related to intense pyro‐convectionsBased on this data, a one‐dimensional plume rise model was improved to accurately represent both high and low injection casesThe improved plume rise model was coupled into an earth system model, Community Atmosphere Model with Chemistry (CAM‐chem) [ABSTRACT FROM AUTHOR]

Humans are frequently exposed to various chemical hazards, with smoking being a significant source of indoor air pollution. This pollution is particularly pronounced in environments such as smoking rooms, conference halls, cafes, and coffee houses. This study focuses on analyzing the concentration, distribution, and behavior of emitted particles from both mainstream and sidestream smoke in a controlled smoking room environment. A critical aspect of the research is the consideration of the thermal plume generated by the smoker's body, particularly around the breathing zone, which plays a crucial role in the dispersion and inhalation of pollutants. To conduct this analysis, a computational fluid dynamics approach was employed, incorporating a displacement ventilation (DV) system integrated with a detailed surface mesh model of a standing manikin. A Lagrangian approach was utilized to track the particle paths, considering factors such as particle size, density, and initial velocity. This approach was complemented by an Eulerian method to simulate the complex airflow patterns within the smoking room, accounting for turbulent flow and temperature variations. The integration of these methods provides a comprehensive understanding of both the macroscopic and microscopic behaviors of smoke particles. The motion equations governing the particles incorporated several forces, including inertial drag force, viscous drag force, buoyancy force, and gravitational force. Additionally, the study examined the interaction between thermal plumes and smoke particles, particularly how temperature gradients around the body affect particle dispersion and concentration. The study meticulously evaluated the distribution and volume average of respirable suspended particles (RSPs) and nicotine by analyzing a plane opposite to the breathing zone of both heated and unheated manikins. It was observed that the thermal plume generated by the temperature gradient around the body could significantly alter the flow field of both sidestream and mainstream smoke between puff periods. The simulation results demonstrated that the thermal plume increased the concentration of RSPs in the breathing zone, highlighting a critical exposure pathway for smokers and nonsmokers alike. A significant increase of approximately 70% in the nicotine concentration is due to the thermal plume. The concentration of nicotine peaks at approximately 0.003 mg/m3 by the third second in smoker#1's (6 smokers' position) breathing zone. Specific configurations of the DV system showed varying efficiencies in reducing pollutant concentrations, emphasizing the need for targeted ventilation strategies. In a chamber with six smokers, researchers found that the time required for suspended particles to reach a cleaning ratio, considering the dynamics of particle movement due to smoking activity, was approximately 184 s per puff. [ABSTRACT FROM AUTHOR]

Background: NOAA's Hazard Mapping System (HMS) smoke product comprises smoke plumes digitised from satellite imagery. Recent studies have used HMS as a proxy for surface smoke presence. Aims: We compare HMS with airport observations, air quality station measurements and model estimates of near-surface smoke. Methods: We quantify the agreement in numbers of smoke days and trends, regional discrepancies in levels of near-surface smoke fine particulate matter (PM2.5) within HMS polygons, and separation of total PM2.5 on smoke and non-smoke days across the contiguous US and Alaska from 2010 to 2021. Key results: We find large overestimates in HMS-derived smoke days and trends if we include light smoke plumes in the HMS smoke day definition. Outside the western US and Alaska, near-surface smoke PM2.5 within areas of HMS smoke plumes is low and almost indistinguishable across density categories, likely indicating frequent smoke aloft. Conclusions: Compared with airport, Environmental Protection Agency (EPA) and model-derived estimates, HMS most closely reflects surface smoke in the Pacific and Mountain regions and Alaska when smoke days are defined using only heavy plumes or both medium and heavy plumes. Implications: We recommend careful consideration of biases in the HMS smoke product for air quality and public health assessments of fires. NOAA's Hazard Mapping System (HMS) smoke product, which comprises smoke plumes digitised from satellite imagery, was used as a proxy for surface smoke in recent air quality and public health assessments of fires. We find biases in HMS relative to airport observations, ground measurements and model estimates of surface smoke. [ABSTRACT FROM AUTHOR]

This study analyzes the vertical distribution, optical properties, radiative forcing, and several perturbation events of stratospheric aerosols using observations from a ground-based polarization lidar in Wuhan (30.5° N, 114.4° E) from 2010 to 2021. The background stratospheric aerosol optical depth (sAOD) was 0.0044 ± 0.0019 at 532 nm , as calculated during a stratosphere-quiescent period from January 2013 to August 2017. In addition, several cases of volcanic aerosol and wildfire-induced smoke were observed. Volcanic aerosols from the Nabro (2011) and Raikoke (2019) eruptions (both in boreal summer) increased the sAOD to 2.9 times the background level. Tracers of smoke from the Canadian wildfire in the summer of 2017 were observed twice, at 19–21 km on 14–17 September and at 20–23 km on 28–31 October, with a plume-isolated aerosol optical depth (AOD) of 0.002–0.010 and a particle linear depolarization ratio δp of 0.14–0.18, indicating the dominance of non-aged smoke particles. During these summertime events, the injected stratospheric aerosols were captured by the large-scale Asian monsoon anticyclone (AMA), confining the transport pathway to mid-latitude Asia. On 8–9 November 2020, smoke plumes originating from the California wildfire in October 2020 appeared at 16–17 km , with a mean δp of 0.13. Regarding seasonal variation, the sAOD in the cold half-year (0.0054) is 69 % larger than in the warm half-year (0.0032) due to stronger meridional transport of stratospheric aerosols from the tropics to middle latitudes. The stratospheric radiative forcing was - 0.11 Wm-2 during the stratosphere-quiescent period and increased to - 0.31 Wm-2 when volcanic aerosols were largely injected. These findings contribute to our understanding of the sources and transport patterns of stratospheric aerosols over mid-latitude Asia and serve as an important database for the validation of model outputs. [ABSTRACT FROM AUTHOR]

The western North Atlantic Ocean is strongly influenced by continental outflow, making it an ideal region to study the atmospheric transition from a polluted coastline to the marine environment. Utilizing eight transit flights between the NASA Langley Research Center (LaRC) in Hampton, Virginia, and the remote island of Bermuda from NASA's Aerosol Cloud meTeorology Interactions oVer the western ATlantic Experiment (ACTIVATE), we examine the evolution of trace gas and aerosol properties off the US East Coast. The first pair of flights flew along the wind trajectory of continental outflow, while the other flights captured a mix of marine and continental air mass sources. For measurements within the boundary layer (BL), there was an offshore decline in particle N<100nm , N>100nm , CH 4 , CO, and CO 2 concentrations, all leveling off around ∼900 km offshore from the LaRC. These trends are strongest for the first pair of flights. In the BL, offshore declines in organic mass fraction and increases in sulfate mass fraction coincide with increasing hygroscopicity based on f (RH) measurements. Free troposphere measurements show a decline in N<100nm , but other measured parameters are more variable when compared to the prominent offshore gradients seen in the BL. Pollution layers exist in the free troposphere, such as smoke plumes, that can potentially entrain into the BL. This work provides detailed case studies with a broad set of high-resolution measurements to further our understanding of the transition between continental and marine environments. [ABSTRACT FROM AUTHOR]

High-volume space structures are characterized by high combustible loads, rapid fire development, difficulty in firefighting, and potential building collapse risks, making early fire detection particularly crucial. The effectiveness of early fire detection technologies relies on their ability to adapt to the characteristics of smoke-dominant combustion products in the protected space. However, there is a lack of targeted research on the characteristics of the smoke generated during the early low-power stages of fires in high-volume spaces, which has not supported the development of early fire detection technologies for such environments. To address this, this paper presents an experimental study that, for the first time, collects data on fire smoke parameters such as temperature, velocity, concentration, and particle size at heights ranging from 6.5 m to 18.5 m using lightweight sensors. The study analyzes the characteristic and correlations of these parameters and their impact on early fire detection in high-volume spaces for the first time, presenting variation patterns in the plume velocity and particle size distribution of early fire smoke with height. It identifies three patterns of particle size distribution, contrasting with previous studies, and offers a qualitative explanation for these findings. This research enhances the understanding of early fire smoke signals in large spaces and offers valuable insights for developing more accurate and efficient fire detection strategies and technologies. [ABSTRACT FROM AUTHOR]

The fast prediction of the extent and impact of accidental air pollution releases is important to enable a quick and informed response, especially in cities. Despite this importance, only a small number of case studies are available studying the dispersion of air pollutants from fires in a short distance (O(1 km)) in urban areas. While monitoring pollution levels in Southampton, UK, using low-cost sensors, a fire broke out from an outbuilding containing roughly 3000 reels of highly flammable cine nitrate film and movie equipment, which resulted in high values of PM2.5 being measured by the sensors approximately 1500 m downstream of the fire site. This provided a unique opportunity to evaluate urban air pollution dispersion models using observed data for PM2.5 and the meteorological conditions. Two numerical approaches were used to simulate the plume from the transient fire: a high-fidelity computational fluid dynamics model with large-eddy simulation (LES) embedded in the open-source package OpenFOAM, and a lower-fidelity Gaussian plume model implemented in a commercial software package: the Atmospheric Dispersion Modeling System (ADMS). Both numerical models were able to quantitatively reproduce consistent spatial and temporal profiles of the PM2.5 concentration at approximately 1500 m downstream of the fire site. Considering the unavoidable large uncertainties, a comparison between the sensor measurements and the numerical predictions was carried out, leading to an approximate estimation of the emission rate, temperature, and the start and duration of the fire. The estimation of the fire start time was consistent with the local authority report. The LES data showed that the fire lasted for at least 80 min at an emission rate of 50 g/s of PM2.5. The emission was significantly greater than a 'normal' house fire reported in the literature, suggesting the crucial importance of the emission estimation and monitoring of PM2.5 concentration in such incidents. Finally, we discuss the advantages and limitations of the two numerical approaches, aiming to suggest the selection of fast-response numerical models at various compromised levels of accuracy, efficiency and cost. [ABSTRACT FROM AUTHOR]

Quantifying the variable impacts of wildfire smoke on ozone air quality is challenging. Here we use airborne measurements from the 2018 Western Wildfire Experiment for Cloud Chemistry, Aerosol Absorption, and Nitrogen (WE‐CAN) to parameterize emissions of reactive nitrogen (NOy) from wildfires into peroxyacetyl nitrate (PAN; 37%), NO3− (27%), and NO (36%) in a global chemistry‐climate model with 13 km spatial resolution over the contiguous US. The NOy partitioning, compared with emitting all NOy as NO, reduces model ozone bias in near‐fire smoke plumes sampled by the aircraft and enhances ozone downwind by 5–10 ppbv when Canadian smoke plumes travel to Washington, Utah, Colorado, and Texas. Using multi‐platform observations, we identify the smoke‐influenced days with daily maximum 8‐hr average (MDA8) ozone of 70–88 ppbv in Kennewick, Salt Lake City, Denver and Dallas. On these days, wildfire smoke enhanced MDA8 ozone by 5–25 ppbv, through ozone produced remotely during plume transport and locally via interactions of smoke plume with urban emissions. Plain Language Summary: Wildfires have torn across western North America over the last decade. Smoke from wildland fires in Canada can travel thousands of kilometers to US cities and reacts with urban pollution to create harmful ozone, a criteria pollutant regulated by the US Environmental Protection Agency. Accurately quantifying this impact is needed to inform US air quality policy, but is challenging due to complex physical and chemical processes. In this study, we analyze surface and airborne measurements, alongside a new variable‐resolution global chemistry‐climate model, to better understand these processes. We show that the near‐field conversion of nitrogen oxide (NOx) emissions from wildfires to peroxyacetyl nitrate (PAN) and other more oxidized forms reduces their localized impacts on ozone. PAN is the principal tropospheric reservoir for NOx radicals. When aged smoke plumes descend southward from Canada toward US cities, higher temperatures cause PAN to decompose and thus help production of ozone during smoke transport. On days when the observed ozone levels exceed the air quality limit (70 ppbv for 8‐hr average), wildfire smoke can contribute 5–25 ppbv. Key Points: Sequestration of wildfire NOx emissions in Canada as peroxyacetyl nitrate (PAN) enhances the downwind impacts on US O3 air qualityPyrogenic volatile organic compounds and PAN decomposition increase the contribution of aged Canadian smoke plumes to O3 in US citiesAccounting for these effects in a high‐resolution chemistry‐climate model improves simulation of smoke‐impacted high‐O3 events in US cities [ABSTRACT FROM AUTHOR]

In August 2017, a smoke plume from wildfires in British Columbia and the Northwest Territories recirculated and persisted over northern Canada for over two weeks. We compared a full‐factorial set of NASA Goddard Institute for Space Studies ModelE simulations of the plume to satellite retrievals of aerosol optical depth and carbon monoxide, finding that ModelE performance was dependent on the model configuration, and more so on the choice of injection height approach, aerosol scheme and biomass burning emissions estimates than to the choice of horizontal winds for nudging. In particular, ModelE simulations with free‐tropospheric smoke injection, a mass‐based aerosol scheme and comparatively high fire NOx emissions led to unrealistically high aerosol optical depth. Using paired simulations with and without fire emissions, we estimated that for 16 days over an 850,000 km2 region, the smoke decreased planetary boundary layer heights by between 253 and 547 m, decreased downward shortwave radiation by between 52 and 172 Wm−2, and decreased surface temperature by between 1.5°C and 4.9°C, the latter spanning an independent estimate from operational weather forecasts of a 3.7°C cooling. The strongest surface climate effects were for ModelE configurations with more detailed aerosol microphysics that led to a stronger first indirect effect. Plain Language Summary: Smoke from biomass burning is known to have effects on surface weather. We used the NASA GISS ModelE to estimate these effects for a large 2017 smoke plume over northern Canada that persisted for two weeks. We first found that the height of the smoke release at the source was the most important factor influencing agreement between ModelE and satellite retrievals of aerosols and carbon monoxide, and that specific, plausible configurations of the model led to unrealistically high aerosol amounts. By comparing simulations with and without fire, we estimated a 16‐day cooling over a 850,000 km2 region of between 1.5°C and 4.9°C, depending on the model configuration. Key Points: We captured the overall pattern and magnitude of a large 2017 smoke plume over Canada with the NASA GISS ModelEOf the sixteen plausible model configurations tested under a full‐factorial design, two with higher NOx emissions, free‐tropospheric smoke release and mass‐based aerosols led to unrealistically high aerosol optical depthOver an 850,000 km2 region, we estimated a 16‐day surface cooling of between 1.5°C and 4.9°C [ABSTRACT FROM AUTHOR]

In recent years, the role of the atmosphere in the formation of the chemical composition of water in Lake Baikal and its tributaries has been increasing. In this regard, the study of equivalent black carbon (eBC) in the air above the lake and its coast has an important practical application. This paper presents the results of the mass concentration of eBC and submicron aerosol in the air above the water area of Lake Baikal, which were obtained during expeditions onboard research vessels in the summer of 2019 and 2023. We analyzed the data from the coastal monitoring station Listvyanka. To measure eBC, an MDA-02 aethalometer was used in the water area of the lake, and a BAC-10 aethalometer at the Listvyanka station. The background level of the eBC concentration in the air at different areas of the lake ranged between 0.15 and 0.3 µg m−3. The results of the two expeditions revealed the influence of the coastal settlements and the air mass transport along the valleys of the lake's large tributaries on the five- to twentyfold growth of the eBC concentration in the near-water atmosphere. In the diurnal dynamics of eBC near settlements, we recorded high values in the evening and at night. In background areas, the diurnal dynamics were poorly manifested. In the summer of 2019, there were smoke plumes in the water area of Lake Baikal from distant wildfires and a local fire site on the east coast of the lake. The eBC concentration increased to 5–6 µg m−3, which was 10 to 40 times higher than the background. The long-range transport of plumes from coal-fired thermal power plants in large cities of the region made the major contribution to the eBC concentration at «Listvyanka» in winter, which data on aerosol, gas impurities, and meteorological parameters confirmed. [ABSTRACT FROM AUTHOR]

Previous works have shown the effectiveness of EfficientNet—a convolutional neural network built upon the concept of compound scaling—in automatically detecting smoke plumes at a distance of several kilometres in visible camera images. Building on these results, we have created enhanced EfficientNet models capable of precisely identifying the smoke location due to the introduction of a mosaic-like output and achieving extremely reduced false positive percentages due to using partial AUROC and applying class imbalance. Our EfficientNets beat InceptionV3 and MobileNetV2 in the same dataset and achieved a true detection percentage of 89.2% and a false positive percentage of only 0.306% across a test set with 17,023 images. The complete dataset used in this study contains 26,204 smoke and 51,075 non-smoke images. This makes it one of the largest, if not the most extensive, datasets reported in the scientific literature for smoke plume imagery. So, the achieved percentages are not only among the best reported for this application but are also among the most reliable due to the extent and representativeness of the dataset. [ABSTRACT FROM AUTHOR]

Convective dynamics in a supercell thunderstorm, a volcanic eruption, and two pyrocumulonimbus (pyroCb) events are compared by computing cloud‐top divergence (CTD) with an optical flow technique called Deepflow. Visible 0.64‐μm imagery sequences from Geostationary Operational Environmental Satellites (GOES)‐R series Advanced Baseline Imager (ABI) are used as input into the optical flow algorithm. CTD is computed after post‐processing of the retrieved motions. Analysis is performed on specific image times, as well as the full time series of each case. Multiple CTD‐based parameters, such as the maximum and the two‐dimensional area exceeding a specified CTD threshold, are examined along with the optical flow‐retrieved wind speed. CTD is shown to accurately and quantitatively represent the behavior and magnitude of different deep convective phenomena, including distinguishing between convective pulses within each individual event. CTD captures updraft intensification as well as differences in convective activity between two pyroCb events and individual updraft pulses occurring within a single pyroCb event. Finally, the characteristics of high‐altitude smoke plumes injected by two separate pyroCb pulses are linked to CTD using ultraviolet aerosol index and satellite imagery. Optical flow‐derived parameters can therefore be applied to individual pyroCbs in real‐time, with potential to characterize pyroCb smoke source inputs for downstream smoke modeling applications and to facilitate future tools supporting air quality modeling and firefighting efforts. Plain Language Summary: Under certain weather conditions, wildfires can generate pyrocumulonimbus, which are deep, convective storms that inject smoke particles high into the atmosphere, resulting in significant aviation and climate impacts. This research tracks cloud‐top motion using computer vision algorithms and satellite data to compare the dynamics of pyrocumulonimbus with a volcanic eruption and supercell thunderstorm, which represent similar deep convective phenomena. The primary goal is to quantify updraft magnitude, duration, and evolution from space. Results show that cloud‐top motion accurately captures variations in updraft magnitude over time and distinguishes between different types of updrafts. Cloud‐top motion is likely more effective than traditional techniques at distinguishing individual, high‐altitude smoke injections from pyrocumulonimbus activity over specific fires. This research lays a foundation for improved smoke source inputs for downstream smoke modeling applications. Key Points: General dynamical characteristics for pyrocumulonimbus (pyroCb), volcano, and supercell cases are compared using satellite‐retrieved cloud‐top divergenceCloud‐top divergence time series analysis distinguishes individual convective pulses of pyroCb and volcano casesCloud‐top divergence is potentially related to the magnitude of pyroCb smoke plume injection height and mass [ABSTRACT FROM AUTHOR]

Forest fires require rapid and precise early smoke detection to minimize damage. This study focuses on employing smoke recognition methods for early warning systems in forest fire detection, identifying smoke as the primary indicator. A significant hurdle lies in the absence of a large-scale dataset for real-world early forest fire smoke detection. Early smoke videos present characteristics such as smoke plumes being small, slow-moving, and/or semi-transparent in color, and include images where there is background interference, posing critical challenges for practical recognition algorithms. To address these issues, this paper introduces a real-world early smoke monitoring video dataset as a foundational resource. The proposed 4D attention-based motion target enhancement network includes an important frame sorting module which adaptively selects essential frame sequences to improve the detection of slow-moving smoke targets. Additionally, a 4D attention-based motion target enhancement module is introduced to mitigate interference from smoke-like objects and enhance recognition of light smoke during the initial stages. Moreover, a high-resolution multi-scale fusion module is presented, incorporating a small target recognition layer to enhance the network's ability to detect small smoke targets. This research represents a significant advancement in early smoke detection for forest fire surveillance, with practical implications for enhancing fire management. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Interactions between urban and wildfire pollution emissions are active areas of research, with numerous aircraft field campaigns and satellite analyses of wildfire pollution being conducted in recent years. Several studies have found that elevated ozone and particulate pollution levels are both generally associated with wildfire smoke in urban areas. We measured pollutant concentrations at two Utah Division of Air Quality regulatory air quality observation sites and a local hot spot (a COVID-19 testing site) within a 48 h period of increasing wildfire smoke impacts that occurred in Salt Lake City, UT (USA) between 20 and 22 August 2020. The wildfire plume, which passed through the study area during an elevated ozone period during the summer, resulted in increased criteria pollutant and greenhouse gas concentrations. Methane (CH4) and fine particulate matter (PM2.5) increased at comparable rates, and increased NOx led to more ozone. The nitrogen oxide/ozone (NOx/O3) cycle was clearly demonstrated throughout the study period, with NOx titration reducing nighttime ozone. These findings help to illustrate how the compounding effects of urban emissions and exceptional pollution events, such as wildfires, may pose substantial health risks. This preliminary case study supports conducting an expanded, longer-term study on the interactions of variable intensity wildfire smoke plumes on urban air pollution exposure, in addition to the subsequent need to inform health and risk policy in these complex systems. [ABSTRACT FROM AUTHOR]

Worsening wildfire seasons in recent years are reversing decadal progress on the reduction of harmful air pollutants in the US, particularly in Western states. Measurements of the contributions of wildfire smoke to ambient air pollutants, such as fine particulate matter (PM2.5), at fine resolution scales would be valuable to public health research on climate vulnerable populations and compound climate risks. We estimate the influence of wildfire smoke emissions on daily PM2.5 at fine-resolution, 3 km, for California 2011–2020, using a geostatistical modeled ambient PM2.5 estimate and wildfire smoke plume data from NOAA Hazard Mapping System. Additionally, we compare this product with the US Environmental Protection Agency (EPA) daily and annual standards for PM2.5 exposure. Our results show wildfires significantly influence PM2.5 in California and nearly all exceedances of the daily US EPA PM2.5 standard were influenced by wildfire smoke, while annual exceedances were increasingly attributed to wildfire smoke influence in recent years. This wildfire-influenced PM2.5 product can be applied to public health research to better understand source-specific air pollution impacts and assess the combination of multiple climate hazard risks. [ABSTRACT FROM AUTHOR]

Smoke plumes emitted from wildland-urban interface (WUI) wildfires contain toxic chemical substances that are harmful to human health, mainly due to the burning of synthetic components. Accurate measurement of these air toxics is necessary for understanding their impacts on human health. However, air pollution is typically measured using ground-based sensors, manned airplanes, or satellites, which all provide low-resolution data. Unmanned Aerial Vehicles (UAVs) have the potential to provide high-resolution spatial and temporal data due to their ability to hover in specific locations and maneuver with precise trajectories in 3-D space. This study investigates the use of an octocopter UAV, equipped with a customized air quality sensor package and a volatile organic compound (VOC) air sampler, for the purposes of collecting and analyzing air toxics data from wildfire plumes. The UAV prototype developed has been successfully tested during several prescribed fires conducted by the California Department of Forestry and Fire Protection (CAL FIRE). Data from these experiments were analyzed with emphasis on the relationship between the air toxics measured and the different types of vegetation/fuel burnt. BTEX compounds were found to be more abundant for hardwood burning compared to grassland burning, as expected.