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Smoke plume dynamics involve various smoke processes and mechanics in the atmosphere and provide the scientific foundation for the development of tools to simulate and predict smoke and its environmental and human impacts. The increasing occurrence of wildfires and the demands for more extensive application of prescribed fires in the U.S. have posed great challenges and immediate actions for advancing smoke plume dynamics and improving smoke predictions and impact assessments to mitigate smoke impacts. Numerous efforts have been made recently to address these needs and challenges. This paper synthesizes advances in smoke plume dynamics research mainly conducted in the U.S. in the recent decade, identifies gaps, and suggests future research needs. The main advances include smoke data collections from comprehensive field campaigns, new satellite products, improved understanding of smoke plume properties and chemistry, structure and evolution, evaluation and improvement of smoke modeling and prediction systems, the development of coupled smoke models, and applications of machine-learning techniques. The major remaining gaps are the lack of comprehensive simultaneous measurements of smoke, fuels, fire, and atmospheric interactions during wildfires, high-resolution coupled modeling systems of these components, and real-time smoke prediction capacity. The findings from this synthesis study are expected to support smoke research and management to meet various challenges under increasing wildland fires and impacts.

The plume rising height of a ship will directly affect the maximum ground concentration and distance from the source caused by flue gas emission. Ship movement has an important effect on plume rising, but it is often ignored in previous studies. We simulated the weakening effect caused by ship movement by considering the influence of four main parameters (wind speed, ship speed, flue gas exit velocity, and flue gas exit temperature) on the smoke plume rising height, using the computational fluid dynamics (CFD) model (PHOENICS version 6.0 CHAM, London, UK). The main parameters affecting the difference in plume rising height between stationary and moving sources for the same parameter settings are the wind speed and the ship speed. Therefore, we established two simplified calculation methods that corrected the flue gas exit velocity (Vexit′) and the flue gas exit temperature (T′) for approximately simulating the smoke plume rising height of the moving ship using the formula of a stationary ship. Verification cases indicated that the corrected Vexit′ (the average of relative error is 5.48%) and the corrected T′(the average of relative error is 60.07%) not only saved calculation time but also improved the simulation accuracy compared with the uncorrected stationary source scheme (the average of relative error is 135.38%). Of these correction methods, the scheme with corrected Vexit′ is more effective. The intention is to provide some references for the field experimentation of moving ship plume rising in different ports in the future and to further study the mechanism of moving ship plume rising.

Prescribed burns produce smoke pollution, but little is known about the spatial and temporal pattern because smoke plumes are usually small and poorly captured by State air-quality networks. Here, we sampled smoke around 18 forested prescribed burns in the Sydney region of eastern Australia using up to 11 Nova SDS011 particulate sensors and developed a Generalised Linear Mixed Model to predict hourly PM2.5 concentrations as a function of distance, fire size and weather conditions. During the day of the burn, PM2.5 tended to show hourly exceedances (indicating poor air quality) up to ~2 km from the fire but only in the downwind direction. In the evening, this zone expanded to up to 5 km and included upwind areas. PM2.5 concentrations were higher in still, cool weather and with an unstable atmosphere. PM2.5 concentrations were also higher in larger fires. The statistical model confirmed these results, identifying the effects of distance, period of the day, wind angle, fire size, temperature and C-Haines (atmospheric instability). The model correctly identified 78% of hourly exceedance and 72% of non-exceedance values in retained test data. Applying the statistical model predicts that prescribed burns of 1000 ha can be expected to cause air quality exceedances over an area of ~3500 ha. Cool weather that reduces the risk of fire escape, has the highest potential for polluting nearby communities, and fires that burn into the night are particularly bad.

The High-Resolution Rapid Refresh (HRRR) is a convection-allowing implementation of the Advanced Research version of the Weather Research and Forecasting (WRF-ARW) Model with hourly data assimilation that covers the conterminous United States and Alaska and runs in real time at the NOAA/National Centers for Environmental Prediction (NCEP). Implemented operationally at NOAA/NCEP in 2014, the HRRR features 3-km horizontal grid spacing and frequent forecasts (hourly for CONUS and 3-hourly for Alaska). HRRR initialization is designed for optimal short-range forecast skill with a particular focus on the evolution of precipitating systems. Key components of the initialization are radar-reflectivity data assimilation, hybrid ensemble-variational assimilation of conventional weather observations, and a cloud analysis to initialize stratiform cloud layers. From this initial state, HRRR forecasts are produced out to 18 h every hour, and out to 48 h every 6 h, with boundary conditions provided by the Rapid Refresh system. Between 2014 and 2020, HRRR development was focused on reducing model bias errors and improving forecast realism and accuracy. Improved representation of the planetary boundary layer, subgrid-scale clouds, and land surface contributed extensively to overall HRRR improvements. The final version of the HRRR (HRRRv4), implemented in late 2020, also features hybrid data assimilation using flow-dependent covariances from a 3-km, 36-member ensemble (“HRRRDAS”) with explicit convective storms. HRRRv4 also includes prediction of wildfire smoke plumes. The HRRR provides a baseline capability for evaluating NOAA’s next-generation Rapid Refresh Forecast System, now under development.

Weather is an important factor that determines smoke development, which is essential information for planning smoke field measurements. This study identifies the synoptic systems that would favor to produce the desired smoke plumes for the Fire and Smoke Model Evaluation Experiment (FASMEE). Daysmoke and PB-Piedmont (PB-P) models are used to simulate smoke plume evolution during the day time and smoke drainage and fog formation during the nighttime for hypothetical prescribed burns on 5–8 February 2011 at the Stewart Army Base in the southeastern United States. Daysmoke simulation is evaluated using the measured smoke plume heights of two historical prescribed burns at the Eglin Air Force Base. The simulation results of the hypothetical prescribed burns show that the smoke plume is not fully developed with low plume height during the daytime on 5 February when the burn site is under the warm, moist, and windy conditions connected to a shallow cyclonic system and a cold front. However, smoke drainage and fog are formed during the nighttime. Well-developed smoke plumes, which rise mainly vertically, extend to a majority portion of the planetary boundary layer, and have steady clear boundaries, appear on both 6 and 7 February when the air is cool but dry and calm during a transition between two low-pressure systems. The plume rises higher on the second day, mainly due to lighter winds. The smoke on 8 February shows a loose structure of large horizontal dispersion and low height after passage of a deep low-pressure system with strong cool and dry winds. Smoke drainage and fog formation are rare for the nights during 5–8 February. It is concluded that prescribed burns conducted during a period between two low-pressure systems would likely generate the desired plumes for FASMEE measurement during daytime. Meanwhile, as the fire smolders into the night, the burns would likely lead to fog formation when the burn site is located in the warm and moist section of a low-pressure system or a cold front.

Wildfires emit large amounts of black carbon and light-absorbing organic carbon, known as brown carbon, into the atmosphere. These particles perturb Earth’s radiation budget through absorption of incoming shortwave radiation. It is generally thought that brown carbon loses its absorptivity after emission in the atmosphere due to sunlight-driven photochemical bleaching. Consequently, the atmospheric warming effect exerted by brown carbon remains highly variable and poorly represented in climate models compared with that of the relatively nonreactive black carbon. Given that wildfires are predicted to increase globally in the coming decades, it is increasingly important to quantify these radiative impacts. Here we present measurements of ensemble-scale and particle-scale shortwave absorption in smoke plumes from wildfires in the western United States. We find that a type of dark brown carbon contributes three-quarters of the short visible light absorption and half of the long visible light absorption. This strongly absorbing organic aerosol species is water insoluble, resists daytime photobleaching and increases in absorptivity with night-time atmospheric processing. Our findings suggest that parameterizations of brown carbon in climate models need to be revised to improve the estimation of smoke aerosol radiative forcing and associated warming.Atmospheric short-wave absorption due to wildfire smoke is caused predominantly by dark brown carbon particles, according to observations from smoke plumes in the United States.

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 record Smoke from these fires impacted the United States (U.S.) Upper Midwest during May–June, leading to regional scale surface enhancements of PM2.5 and ozone These unusual early season fires produced the highest regional‐scale surface ozone levels ever recorded across the northern United States

Long-range-transported Canadian smoke layers in the stratosphere over northern France were detected by three lidar systems in August 2017. The peaked optical depth of the stratospheric smoke layer exceeds 0.20 at 532 nm, which is comparable with the simultaneous tropospheric aerosol optical depth. The measurements of satellite sensors revealed that the observed stratospheric smoke plumes were transported from Canadian wildfires after being lofted by strong pyro-cumulonimbus. Case studies at two observation sites, Lille (lat 50.612, long 3.142, 60 m a.s.l.) and Palaiseau (lat 48.712, long 2.215, 156 m a.s.l.), are presented in detail. Smoke particle depolarization ratios are measured at three wavelengths: over 0.20 at 355 nm, 0.18–0.19 at 532 nm, and 0.04–0.05 at 1064 nm. The high depolarization ratios and their spectral dependence are possibly caused by the irregular-shaped aged smoke particles and/or the mixing with dust particles. Similar results are found by several European lidar stations and an explanation that can fully resolve this question has not yet been found. Aerosol inversion based on lidar 2α+3β data derived a smoke effective radius of about 0.33 µm for both cases. The retrieved single-scattering albedo is in the range of 0.8 to 0.9, indicating that the smoke plumes are absorbing. The absorption can cause perturbations to the temperature vertical profile, as observed by ground-based radiosonde, and it is also related to the ascent of the smoke plumes when exposed in sunlight. A direct radiative forcing (DRF) calculation is performed using the obtained optical and microphysical properties. The calculation revealed that the smoke plumes in the stratosphere can significantly reduce the radiation arriving at the surface, and the heating rate of the plumes is about 3.5 K day−1. The study provides a valuable characterization for aged smoke in the stratosphere, but efforts are still needed in reducing and quantifying the errors in the retrieved microphysical properties as well as radiative forcing estimates.

Fires emit sufficient sulfur to affect local and regional air quality and climate. This study analyzes SO2 emission factors and variability in smoke plumes from US wildfires and agricultural fires, as well as their relationship to sulfate and hydroxymethanesulfonate (HMS) formation. Observed SO2 emission factors for various fuel types show good agreement with the latest reviews of biomass burning emission factors, producing an emission factor range of 0.47–1.2 g SO2 kg^(−1) C. These emission factors vary with geographic location in a way that suggests that deposition of coal burning emissions and application of sulfur-containing fertilizers likely play a role in the larger observed values, which are primarily associated with agricultural burning. A 0-D box model generally reproduces the observed trends of SO2 and total sulfate (inorganic + organic) in aging wildfire plumes. In many cases, modeled HMS is consistent with the observed organosulfur concentrations. However, a comparison of observed organosulfur and modeled HMS suggests that multiple organosulfur compounds are likely responsible for the observations but that the chemistry of these compounds yields similar production and loss rates as that of HMS, resulting in good agreement with the modeled results. We provide suggestions for constraining the organosulfur compounds observed during these flights, and we show that the chemistry of HMS can allow organosulfur to act as an S(IV) reservoir under conditions of pH > 6 and liquid water content >10^(−7) g sm^(−3). This can facilitate long-range transport of sulfur emissions, resulting in increased SO2 and eventually sulfate in transported smoke.

Just before midnight on August 12, 2015, violent explosions and massive fires occurred in the Tianjin Harbor, China, releasing extensive amounts of toxic gas and smoke, debris, and mineral dust into the atmosphere. Atmospheric damage resulted from the long-range transport of air pollutants (LRTAP) in neighboring areas and countries. It has been found that the smoke plumes circled around the Huabei Plain in the lee of the Taihang Mountains, the Shandong Peninsula, and the Bohai Sea before reaching the Yellow Sea and the Korean Peninsula. The transport of widespread smoke plumes in the Yellow Sea region was evidenced from detailed analyses of images from various satellites including NOAA, MODIS, Himawari, and MTSAT. Satellite images clearly showed the generation of smoke emissions from Tianjin, the entire covering of smoke plumes over the Yellow Sea and nearby shore areas, and the LRTAP to the Korean Peninsula. The deposit of soil dust after the trace of rainfall confirmed LRTAP from the explosions and large fires in Tianjin. Also, air quality measurements of particulate matter (PM) 10, PM2.5, O 3 , CO, and visibility showed the atmospheric impact of widespread smoke plumes from Tianjin.