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Diurnal variations of total FRP (left), mean FRP per GEO-pixel (right). SEVIRI, mean over 2010. Relative unit.  

Diurnal variations of total FRP (left), mean FRP per GEO-pixel (right). SEVIRI, mean over 2010. Relative unit.  

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The problem of characteristic vertical profile of smoke released from wildland fires is considered. A method-ology for bottom-up evaluation of this profile is suggested and a corresponding global dataset is calculated. The pro-file estimation is based on: (i) a semi-empirical formula for plume-top height recently suggested by the authors, (ii) sate...

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... The biomass burning inventory is provided by the Quick Fire Emissions Dataset (QFED) version 2.4 (Darmenov and da Silva, 2015; Pan et al., 2020) with emission factors from Andreae (2019) and are vertically distributed according to Sofiev et al. (2013). Natural emissions of isoprene, monoterpenes, and methylbutenol and natural sources of NOx are prescribed as detailed in Sect. ...
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Natural emissions (vegetation, soil, lightning) are the dominant sources of non-methane biogenic volatile organic compounds (BVOCs) and nitrogen oxides (NOx ≡ NO + NO2) released into the atmosphere over Africa. BVOCs and NOx interact with each other and strongly impact their own chemical lifetimes and degradation pathways, in particular through their influence on hydroxyl radical levels. To account for this intricate interplay between NOx and VOCs, we design and apply a novel inversion setup aiming at the simultaneous optimisation of monthly VOC and NOx emissions in 2019 in a regional chemistry-transport model, based on TROPOMI HCHO and NO2 satellite observations. The TROPOMI-based inversions suggest substantial underestimations of natural NOx and VOC emissions used as a priori in the model. The annual flux over Africa is increased from 125 to 165 Tg yr−1 for isoprene, and from 1.9 to 2.4 TgN yr−1 and from 0.5 to 2.0 TgN yr−1 for the soil and lightning NO emissions, respectively. Despite the NOx emission increase, evaluation against in situ NO2 measurements at seven rural sites in Western Africa displays significant model underestimations after optimisation. The large increases in lightning emissions are supported by comparisons with TROPOMI cloud-sliced upper-tropospheric NO2 volume mixing ratios, which even remain underestimated by the model after optimisation. Our study strongly supports the application of a bias correction to the TROPOMI HCHO data and the use of a double-species constraint (vs single-species inversion), based on comparisons with isoprene columns retrieved from the Cross-track Infrared Sensor (CrIS).
... After applying the emission factors, all fire types are lumped together into a single biomass burning fire type. Since both inventories only provide 2D surface level emissions, they are used in conjunction with injection heights from the IS4FIRES Integrated Monitoring and Modelling System for wildland fires developed at FMI (Sofiev et al., 2012(Sofiev et al., , 2013. ...
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Carbon monoxide in the atmosphere adversely affects air quality and climate, making knowledge about its sources crucial. However, current global bottom-up emission estimates retain significant uncertainties. In this study, we attempt to reduce these uncertainties by optimizing emission estimates for the second half of the year 2018 on a global scale with a focus on the northern hemisphere through the top-down approach of inverse modeling. Specifically, we introduce observations from the TROPOspheric Monitoring Instrument (TROPOMI) into the TM5-4DVAR model. The emissions are further constrained using NOAA surface flask measurements. We conducted six experiments to investigate the impact of data use in our inversions, varying the a priori emissions and observational datasets. Notably, the inversion driven by satellite observations alone captures flask measurements south of 55° N almost as good as the inversions that included those measurements. This indicates that our method could be suitable for near real-time inversions based purely on satellite observations. Compared to the bottom-up estimates, all experiments result in strong (by up to 75 %) broad-scale emission reductions in China and India. In part, the reduction over China can be attributed to policy changes. Additionally, the OH climatology used to simulate chemical loss appears to be underestimated in that region, which also skews the inversions towards lower emissions. Conversely, in most experiments, we find strong localized emission increments over Europe and the Sahara. These are likely artifacts caused by the model's limited capabilities to capture the surface flask measurements in those regions and are not reproduced by the satellite-only inversion.
... These inventories include the Global Fire Assimilation System (GFAS; Rémy et al., 2017) and the Integrated Monitoring and Modelling System for Wildland Fires (IS4FIRES; Sofiev et al., 2009;Soares et al., 2015). Both GFAS and IS4FIRES rely on a plume rise model (Freitas et al., 2007(Freitas et al., , 2010 and semiempirical parameterization (Sofiev et al., 2012(Sofiev et al., , 2013 to determine injection heights. Besides these two methods for estimating injection heights, Yao et al. (2018) used a machine learning model (random forest) and CALIOP data to predict the minimum heights of forest fire smoke in Canada. ...
... We use the daily injection heights compiled by the GFAS emission inventory (Rémy et al., 2017), which provides four parameters representing the vertical extent of each smoke plume at 0.1°× 0.1°resolution: the top and bottom heights of plumes, the MHMI, and injection height. These parameters are calculated with two distinct algorithms: the 1-D plume rise model (Freitas et al., 2007(Freitas et al., , 2010Rémy et al., 2017) and the IS4FIRES parameterization (Sofiev et al., 2012(Sofiev et al., , 2013. The plume rise model predicts the daily vertical velocity, horizontal plume velocity, temperature, and plume radius. ...
... IS4FIRES also offers global maps of monthly mean injection profiles of fire emissions at a spatial resolution of 1°× 1°× 500 m from the surface to 10 km altitude (20 layers), averaged over the years 2000-2012 (http://is4fires.fmi.fi; last access: 21 October 2022). The IS4FIRES parameterization assumes that each fire lasts for 24 h and that the plume heights of this fire depend on fire intensity, which is based on the mean diurnal variation of the FRP derived from the geostationary orbiting instrument Spinning Enhanced Visible and Infrared Imager (Roberts et al., 2009;Sofiev et al., 2013). The resulting hourly injection profiles are averaged over the whole day and aggregated to the monthly level. ...
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... Quantifying those impacts is made difficult by the large number and diversity of non-methane volatile organic compounds (NMVOCs), with chemical lifetimes ranging from a few minutes to several months (Shu and Atkinson, 1994;Atkinson, 2000), and by important gaps in our understanding of their emissions and chemical degradation mechanisms. Even biogenic isoprene, the most abundantly emitted NMVOC at the global scale, has very uncertain emissions due (among others) to the strong variability of emission rates among different plant species and to the large uncertainties in the climate and vegetation maps used to calculate the fluxes in state-of-the-art emission models Sindelarova et al., 2014). In addition, field campaigns in various environments such as cities (e.g., Karl et al., 2018) and remote areas (e.g., Read et al., 2012;Wang et al., 2012;Lawson et al., 2015;Travis et al., 2020) suggest that current inventories of anthropogenic and natural emissions of many NMVOCs and particularly oxygenated volatile organic compounds (OVOCs) are incomplete. ...
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... Moreover, variations in the temporal and spatial resolution of emissions data can have a significant effect on chemical transport and reaction rates and can potentially impact the climate response in models (Sofiev et al., 2013). One deficiency in the emissions data used in current models, for example, is the inconsistent representation of sub-annual emission rates. ...
... We note that diurnal and weekly patterns can also influence results; however, these are not evaluated in this work. Aerosol formation and transport (Stohl et al., 2013), as well as chemical reaction rate (Sofiev et al., 2013;Pregger and Friedrich, 2009), are dependent on the season. Therefore, aerosol and precursor species can have a longer or shorter lifetime depending on the emission seasonality in the model. ...
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Anthropogenic emissions of aerosols and precursor compounds are known to significantly affect the energy balance of the Earth–atmosphere system, alter the formation of clouds and precipitation, and have a substantial impact on human health and the environment. Global models are an essential tool for examining the impacts of these emissions. In this study, we examine the sensitivity of model results to the assumed height of SO2 injection, seasonality of SO2 and black carbon (BC) particulate emissions, and the assumed fraction of SO2 emissions that is injected into the atmosphere as particulate phase sulfate (SO4) in 11 climate and chemistry models, including both chemical transport models and the atmospheric component of Earth system models. We find large variation in atmospheric lifetime across models for SO2, SO4, and BC, with a particularly large relative variation for SO2, which indicates that fundamental aspects of atmospheric sulfur chemistry remain uncertain. Of the perturbations examined in this study, the assumed height of SO2 injection had the largest overall impacts, particularly on global mean net radiative flux (maximum difference of -0.35 W m-2), SO2 lifetime over Northern Hemisphere land (maximum difference of 0.8 d), surface SO2 concentration (up to 59 % decrease), and surface sulfate concentration (up to 23 % increase). Emitting SO2 at height consistently increased SO2 and SO4 column burdens and shortwave cooling, with varying magnitudes, but had inconsistent effects across models on the sign of the change in implied cloud forcing. The assumed SO4 emission fraction also had a significant impact on net radiative flux and surface sulfate concentration. Because these properties are not standardized across models this is a source of inter-model diversity typically neglected in model intercomparisons. These results imply a need to ensure that anthropogenic emission injection height and SO4 emission fraction are accurately and consistently represented in global models.
... The evaluation of wildfire emissions often solely relied on fuel consumption data because of the lack of measurements of wildfire emission factors (van der Werf et al 2017) or adopted emission factors estimated from temperate prescribed burning beyond the wildfire season or laboratory combustion (Yokelson et al 2007, Akagi et al 2011, Alves et al 2011, Mebust et al 2011, Urbanski et al 2011, Urbanski 2013, Liu et al 2017. The injection height of wildfire emissions is also crucial to air quality modeling, which has been thoroughly studied using semi-empirical formulas and satellite observations to constrain the vertical profile of wildfire emissions (Rio et al 2010, Sofiev et al 2013, Paugam et al 2016. And it has been revealed that wildfire plume top height showed enhanced trend throughout the Western US (Wilmot et al 2022). ...
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The impacts of climate change on wildfires have been studied extensively. Along with declining emissions from fossil fuel combustion due to anthropogenic emission control, black carbon (BC) released from wildfires is expected to contribute a more significant portion to its atmospheric burden. However, from a global perspective, little is known about the BC burden and radiative forcing caused by wildfires. Here, we report the results from the long-term wildfire-induced BC concentration and direct radiative forcing (DRF) from 1981 to 2010 globally simulated by an Earth System Model using an updated wildfire BC emission inventory. We show that wildfire-induced BC concentration and DRF varied significantly spatially and temporarily, with the highest in sub-Saharan Africa, attributable to its highest level of wildfire BC emission worldwide. The temporal trends of near-surface air temperature, precipitation, and evapotranspiration and their association with wildfire-induced BC concentration are explored using the multidimensional ensemble empirical mode decomposition. A statistically significant relation between changes in climate parameters and wildfire-induced BC concentration was found for 53% of the land grid cells, explaining on average 33% of the concentration variations. The result suggests that the wildfire-induced BC DRF, with an increasing trend, would be an important contributor to climate change, especially in sub-Saharan Africa. Occurrences of wildfires in the Amazon Basin respond most strongly to climate change and play an increasingly important role in changing the global climate.
... IS4FIRES also offers global maps of monthly mean injection profiles of fire emissions at a spatial resolution of 1° × 1° × 500 m from the surface to 10 km altitude (20 layers), averaged over the years 2000 to 2012 (http://is4fires.fmi.fi, last accessed: October 21, 2022). The IS4FIRES parameterization assumes that each fire lasts for 24 hours and that the plume heights of this fire depend on fire intensity, which is based on the mean diurnal variation of the FRP derived from the geostationary orbiting instrument Spinning Enhanced Visible and Infrared Imager (Roberts et al., 2009, Sofiev et al., 2013. The resulting hourly injection profiles are averaged over the whole day and aggregated to the monthly level. ...
... The profiles are then normalized by monthly mean emissions in that vertical column. More details are described in Sofiev et al. (2013). ...
... One possible reason for this overestimate can be traced to the inaccuracies in the input data and the semi-460 empirical parameterization(Rémy et al., 2017). Based onSofiev et al. (2013), plume injection height is proportional to the PBL height, which is usually large in northern Australia compared to other regions, leading to a higher injection fraction of fire emissions above the PBL. In the INJ-RF experiment, the mean simulated total PM2.5 concentrations are in best agreement with the surface measurements with a NMB of -2.5% averaged from 2011 to 2020. ...
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Wildfires can have a significant impact on air quality in Australia during severe burning seasons, but incomplete knowledge of the injection heights of smoke plumes poses a challenge for quantifying smoke exposure. In this study, we use two approaches to quantify the fractions of fire emissions injected above the planetary boundary layer (PBL), and we further investigate the impact of plume injection fractions on daily mean surface concentrations of fine particulate matter (PM2.5) from wildfire smoke in key cities over northern and southeastern Australia from 2009 to 2020. For the first method, we rely on climatological, monthly mean vertical profiles of smoke emissions from the Integrated Monitoring and Modelling System for wildland fires (IS4FIRES), together with assimilated PBL heights from NASA Modern-Era Retrospective analysis for Research and Application (MERRA) version 2. For the second method, we develop a novel approach based on the Multi-angle Imaging Spectro-Radiometer (MISR) observations and a random forest, machine-learning model that allows us to directly predict the daily plume injection fractions above the PBL in each grid cell. We apply the resulting plume injection fractions quantified by the two methods to smoke PM2.5 concentrations simulated by the Stochastic Time-Inverted Lagrangian Transport (STILT) model in target cities. We find that characterization of the plume injection heights greatly affects estimates of surface daily smoke PM2.5, especially during severe wildfire seasons, when intense heat from fires can loft smoke high in the troposphere. However, using climatological injection profiles cannot capture well the spatiotemporal variability of plume injection fractions, resulting in a 63 % underestimate of daily fire emission fluxes injected above the PBL. Our random forest model successfully reproduces the daily injected fire emission fluxes against MISR observations (R2 = 0.88, normalized mean bias = 10 %), which predicts that 27 % and 45 % of total fire emissions rise above the PBL in northern and southeastern Australia, respectively, from 2009 to 2020. Using the plume behavior predicted by the random forest method also leads to the best model agreement with observed surface PM2.5 in several key cities, with smoke PM2.5 accounting for 5 % to 52 % of total PM2.5 during fire seasons from 2009 to 2020.
... An accurate emissions inventory is an indispensable factor in obtaining accurate PM2.5 simulations. Meteorological conditions, particularly turbulent diffusion, play a critical role in the evolution of pollutants in the boundary layer (BL) when emissions are constant on a monthly scale (Kurata et al., 2004;Sofiev et al., 2013;Jia et al., 2021b;Liu et al., 2022). ...
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Weak turbulence often occurs during heavy pollution events in eastern China. However, existing mesoscale models cannot accurately simulate turbulent diffusion under weakened turbulence, particularly under the nocturnal stable boundary layer (SBL), often leading to significant turbulent diffusivity underestimation and surface aerosol simulation overestimation. In this study, based on the Weather Research and Forecasting model coupled with the Chemistry model (WRF-Chem 3.9.1), a new parameterization of minimum turbulent diffusivity (Kzmin) is tested and applied in PM2.5 simulations in eastern China under SBL conditions. Sensitivity experiments show that there are different value ranges of available Kzmin over the northern (0.8 to 1.3 m2·s-1) and southern (1.0 to 1.5 m2·s-1) regions of East China. The geographically related Kzmin could be parameterized by means of two factors: sensible heat flux (H) and latent heat flux (LE), which also exhibited a regional difference related to the climate and underlying surface. The revised Kzmin scheme obviously enhanced the turbulent diffusion (north: 0.88 m2·s-1, south: 1.17 m2·s-1 on average) under the SBL, simultaneously improving the PM2.5 simulations, with the PM2.5 relative bias decreasing from 43.0 % to 15.6 % on the surface. The improvement in the mean bias of the surface simulation was more noticeable in the north (54.01 to 3.79 ug·m-3) than in the south (37.05 to 17.99 ug·m-3). It also increased the PM2.5 concentration in the upper SBL. Furthermore, we discussed the physical relationship between Kzmin and two factors. Kzmin was inversely correlated with sensible heat flux (negative) and latent heat flux (positive) in the SBL. Process analysis showed that vertical mixing is the key process to improve PM2.5 simulations on the surface in the revised scheme. The increase in the PM2.5 concentration in the upper SBL was attributed to vertical mixing, advection, and aerosol chemistry. This study highlights the importance of improving turbulent diffusion in current mesoscale models under the SBL and has great significance for aerosol simulation research under heavy air pollution events.
... Although the last item is possible within HYSPLIT using linear mass conversion formulations, it is most useful for ozone studies [24], and therefore, not a component explored in this study. Throughout its development cycle, HYSPLIT has made significant improvements toward better representation of the plume-rise schemes [24][25][26]. ...
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Accurate representation of fire emissions and smoke transport is crucial for current and future wildfire-smoke projections. We present a flexible modeling framework for emissions sourced from the First Street Foundation Wildfire Model (FSF-WFM) to provide a national map for near-surface smoke conditions exceeding the threshold for unhealthy concentrations of particulate matter at or less than 2.5 µm, or PM2.5. Smoke yield from simulated fires is converted to emissions transported by the National Oceanic and Atmospheric Administration’s HYSPLIT model. We present a strategy for sampling from a simulation of ~65 million individual fires, to depict the occurrence of “unhealthy smoke days” defined as 24-h average PM2.5 concentration greater than 35.4 µg/m3 from HYSPLIT. The comparison with historical smoke simulations finds reasonable agreement using only a small subset of simulated fires. The total amount of PM2.5 mass-released threshold of 1015 µg was found to be effective for simulating the occurrence of unhealthy days without significant computational burden.
... Moreover, variations in the temporal and spatial resolution of emissions data can have a significant effect on chemical transport and reaction rates and can potentially impact the climate response in models (Sofiev et al., 2013). One deficiency in the emissions data used in current models, for example, is the inconsistent representation of sub-annual emission rates. ...
... We note that diurnal and weekly patterns can also influence results; however, these are not evaluated in this work. Aerosol formation and transport (Stohl et al., 2013), as well as chemical reaction rate (Sofiev et al., 2013;Pregger and Friedrich, 2009), are dependent on the season. Therefore, aerosol and precursor species can have a longer or shorter lifetime depending on the emission seasonality 175 in the model. ...
Preprint
Full-text available
Anthropogenic emissions of aerosols and precursor compounds are known to significantly affect the energy balance of the Earth-atmosphere system, alter the formation of clouds and precipitation, and have substantial impact on human health and the environment. Global models are an essential tool for examining the impacts of these emissions. In this study, we examine the sensitivity of model results to the assumed height of SO2 injection, seasonality of SO2 and BC emissions, and the assumed fraction of SO2 emissions that is injected into the atmosphere as SO4 in 11 climate and chemistry models, including both chemical transport models and the atmospheric component of Earth system models. We find a large variation in atmospheric lifetime across models for SO2, SO4, and BC, with a particularly large relative variation for SO2, which indicates that fundamental aspects of atmospheric sulfur chemistry remain uncertain. Of the perturbations examined in this study, the assumed height of SO2 injection had the largest overall impacts, particularly on global mean net radiative flux (maximum difference of -0.35 W m-2), SO2 lifetime over northern hemisphere land (maximum difference of 0.8 days), surface SO2 concentration (up to 59 % decrease), and surface sulfate concentration (up to 23 % increase). Emitting SO2 at height consistently increased SO2 and SO4 column burdens and shortwave cooling, with varying magnitudes, but had inconsistent effects across models on the sign of the change in implied cloud forcing. The assumed SO4 emission fraction also had a significant impact on net radiative flux and surface sulfate concentration. Because these properties are not standardized across models this is a source of inter-model diversity typically neglected in model intercomparisons. These results imply a need to assure that anthropogenic emission injection height and SO4 emission fraction are accurately and consistently represented in global models.