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The problem of characteristic vertical profile of smoke released from wildland fires is considered. A methodology for bottom-up evaluation of this profile is suggested and a corresponding global dataset is calculated. The profile estimation is based on: (i) a semi-empirical formula for plume-top height recently suggested by the authors, (ii) satellite observations of active wildland fires, and (iii) meteorological conditions evaluated for each fire using output of the numerical weather prediction model. Injection profiles of the plumes from all fires recorded globally from March 2000 till November 2012 are estimated with a time step of 1 h. The resulting 4-dimensional dataset is split into daytime and nighttime subsets. The subsets are projected onto a global grid with a resolution of 1° × 1° × 500 m, aggregated to a monthly level, and normalised by total emissions in each vertical column. Evaluation of the obtained dataset was performed in several ways. Firstly, the quality of the semi-empirical formula for plume-top computations was evaluated using updated MISR fire Plume Height Project data. Secondly, the upper percentiles of the profiles are compared with an independent dataset of space lidar CALIOP. Thirdly, the results are compared with the distribution suggested for AEROCOM modelling community. Finally, the inter-annual variations of the calculated profiles are estimated.
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In this study, 121 daily PM<sub>2.5</sub> (aerosol particle with aerodynamic diameter less than 2.5 μm) samples were collected from an urban site in Beijing in four months between April 2009 and January 2010 representing the four seasons. The samples were determined for various compositions, including elements, ions, and organic/elemental carbon. Various approaches, such as chemical mass balance, positive matrix factorization (PMF), trajectory clustering, and potential source contribution function (PSCF), were employed for characterizing aerosol speciation, identifying likely sources, and apportioning contributions from each likely source. Our results have shown distinctive seasonality for various aerosol speciations associated with PM<sub>2.5</sub> in Beijing. Soil dust waxes in the spring and wanes in the summer. Regarding the secondary aerosol components, inorganic and organic species may behave in different manners. The former preferentially forms in the hot and humid summer via photochemical reactions, although their precursor gases, such as SO<sub>2</sub> and NO<sub>x</sub>, are emitted much more in winter. The latter seems to favorably form in the cold and dry winter. Synoptic meteorological and climate conditions can overwhelm the emission pattern in the formation of secondary aerosols. The PMF model identified six main sources: soil dust, coal combustion, biomass burning, traffic and waste incineration emission, industrial pollution, and secondary inorganic aerosol. Each of these sources has an annual mean contribution of 16, 14, 13, 3, 28, and 26%, respectively, to PM<sub>2.5</sub>. However, the relative contributions of these identified sources significantly vary with changing seasons. The results of trajectory clustering and the PSCF method demonstrated that regional sources could be crucial contributors to PM pollution in Beijing. In conclusion, we have unraveled some complex aspects of the pollution sources and formation processes of PM<sub>2.5</sub> in Beijing. To our knowledge, this is the first systematic study that comprehensively explores the chemical characterizations and source apportionments of PM<sub>2.5</sub> aerosol speciation in Beijing by applying multiple approaches based on a completely seasonal perspective.
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The coupled model LMDZORINCA has been used to simulate the transport, wet and dry deposition of the radioactive tracer <sup>137</sup>Cs after accidental releases. For that reason, two horizontal resolutions were deployed and used in the model, a regular grid of 2.5° × 1.27°, and the same grid stretched over Europe to reach a resolution of 0.66° × 0.51°. The vertical dimension is represented with two different resolutions, 19 and 39 levels respectively, extending up to the mesopause. Four different simulations are presented in this work; the first uses the regular grid over 19 vertical levels assuming that the emissions took place at the surface (RG19L(S)), the second also uses the regular grid over 19 vertical levels but realistic source injection heights (RG19L); in the third resolution the grid is regular and the vertical resolution 39 levels (RG39L) and finally, it is extended to the stretched grid with 19 vertical levels (Z19L). The model is validated with the Chernobyl accident which occurred in Ukraine (ex-USSR) on 26 May 1986 using the emission inventory from Brandt et al. (2002). This accident has been widely studied since 1986, and a large database has been created containing measurements of atmospheric activity concentration and total cumulative deposition for <sup>137</sup>Cs from most of the European countries. <br><br> According to the results, the performance of the model to predict the transport and deposition of the radioactive tracer was efficient and accurate presenting low biases in activity concentrations and deposition inventories, despite the large uncertainties on the intensity of the source released. The best agreement with observations was obtained using the highest horizontal resolution of the model (Z19L run). The model managed to predict the radioactive contamination in most of the European regions (similar to De Cort et al., 1998), and also the arrival times of the radioactive fallout. As regards to the vertical resolution, the largest biases were obtained for the 39 layers run due to the increase of the levels in conjunction with the uncertainty of the source term. Moreover, the ecological half-life of <sup>137</sup>Cs in the atmosphere after the accident ranged between 6 and 9 days, which is in good accordance to what previously reported and in the same range with the recent accident in Japan. The high response of LMDZORINCA model for <sup>137</sup>Cs reinforces the importance of atmospheric modelling in emergency cases to gather information for protecting the population from the adverse effects of radiation.
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In this study we present a novel approach for improving the air quality predictions using an ensemble of air quality models generated in the context of AQMEII (Air Quality Model Evaluation International Initiative). The development of the forecasting method makes use of modelled and observed time series (either spatially aggregated or relative to single monitoring stations) of ozone concentrations over different areas of Europe and North America. The technique considers the underlying forcing mechanisms on ozone by means of spectrally decomposed previsions. With the use of diverse applications, we demonstrate how the approach screens the ensemble members, extracts the best components and generates bias-free forecasts with improved accuracy over the candidate models. Compared to more traditional forecasting methods such as the ensemble median, the approach reduces the forecast error and at the same time it clearly improves the modelled variance. Furthermore, the result is not a mere statistical outcome depended on the quality of the selected members. The few individual cases with degraded performance are also identified and analysed. Finally, we show the extensions of the approach to other pollutants, specifically particulate matter and nitrogen dioxide, and provide a framework for its operational implementation. <br><br> <br><br> *One out of many
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Atmospheric mineral dust particles exert significant direct radiative forcings and are important drivers of climate and climate change. We used the GEOS-Chem global three-dimensional chemical transport model (CTM) coupled with the Fu-Liou-Gu (FLG) radiative transfer model (RTM) to investigate the dust radiative forcing and heating rate based on different vertical profiles for April 2006. We attempt to actually quantify the sensitivities of radiative forcing to dust vertical profiles, especially the discrepancies between using realistic and climatological vertical profiles. In these calculations, dust emissions were constrained by observations of aerosol optical depth (AOD). The coupled calculations utilizing a more realistic dust vertical profile simulated by GEOS-Chem minimize the physical inconsistencies between 3-D CTM aerosol fields and the RTM. The use of GEOS-Chem simulated vertical profile of dust extinction, as opposed to the FLG prescribed vertical profile, leads to greater and more spatially heterogeneous changes in the estimated radiative forcing and heating rate produced by dust. Both changes can be attributed to a different vertical structure between dust and non-dust source regions. Values of the dust vertically resolved AOD per grid level (VRAOD) are much larger in the middle troposphere, though smaller at the surface when the GEOS-Chem simulated vertical profile is used, which leads to a much stronger heating rate in the middle troposphere. Compared to the FLG vertical profile, the use of GEOS-Chem vertical profile reduces the solar radiative forcing at the top of atmosphere (TOA) by approximately 0.2–0.25 W m<sup>−2</sup> over the African and Asian dust source regions. While the Infrared (IR) radiative forcing decreases 0.2 W m<sup>−2</sup> over African dust belt, it increases 0.06 W m<sup>−2</sup> over the Asian dust belt when the GEOS-Chem vertical profile is used. Differences in the solar radiative forcing at the surface between the use of the GEOS-Chem and FLG vertical profiles are most significant over the Gobi desert with a value of about 1.1 W m<sup>−2</sup>. The radiative forcing effect of dust particles is more pronounced at the surface over the Sahara and Gobi deserts by using FLG vertical profile, while it is less significant over the downwind area of Eastern Asia.
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We adapt general statistical methods to estimate the optimal error covariance matrices in a regional inversion system inferring methane surface emissions from atmospheric concentrations. Using a minimal set of physical hypotheses on the patterns of errors, we compute a guess of the error statistics that is optimal in regard to objective statistical criteria for the specific inversion system. With this very general approach applied to a real-data case, we recover sources of errors in the observations and in the prior state of the system that are consistent with expert knowledge while inferred from objective criteria and with affordable computation costs. By not assuming any specific error patterns, our results depict the variability and the inter-dependency of errors induced by complex factors such as the misrepresentation of the observations in the transport model or the inability of the model to reproduce well the situations of steep gradients of concentrations. Situations with probable significant biases (e.g., during the night when vertical mixing is ill-represented by the transport model) can also be diagnosed by our methods in order to point at necessary improvement in a model. By additionally analysing the sensitivity of the inversion to each observation, guidelines to enhance data selection in regional inversions are also proposed. We applied our method to a recent significant accidental methane release from an offshore platform in the North Sea and found methane fluxes of the same magnitude than what was officially declared.
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During the VOCALS campaign spaceborne satellite observations showed that travelling gravity wave packets, generated by geostrophic adjustment, resulted in perturbations to marine boundary layer (MBL) clouds over the south-east Pacific Ocean (SEP). Often, these perturbations were reversible in that passage of the wave resulted in the clouds becoming brighter (in the wave crest), then darker (in the wave trough) and subsequently recovering their properties after the passage of the wave. However, occasionally the wave packets triggered irreversible changes to the clouds, which transformed from closed mesoscale cellular convection to open form. In this paper we use large eddy simulation (LES) to examine the physical mechanisms that cause this transition. Specifically, we examine whether the clearing of the cloud is due to (i) the wave causing additional cloud-top entrainment of warm, dry air or (ii) whether the additional condensation of liquid water onto the existing drops and the subsequent formation of drizzle are the important mechanisms. We find that, although the wave does cause additional drizzle formation, this is not the reason for the persistent clearing of the cloud; rather it is the additional entrainment of warm, dry air into the cloud followed by a reduction in longwave cooling, although this only has a significant effect when the cloud is starting to decouple from the boundary layer. The result in this case is a change from a stratocumulus to a more patchy cloud regime. For the simulations presented here, cloud condensation nuclei (CCN) scavenging did not play an important role in the clearing of the cloud. The results have implications for understanding transitions between the different cellular regimes in marine boundary layer (MBL) clouds.
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Accurate measurements of natural aerosol emissions over the ocean are needed to estimate the anthropogenic impact on the environment. In this study, we measured sea spray aerosol (SSA) concentrations with diameters larger than 0.040 <abbr>μm</abbr> produced by open-ocean breaking waves over the SEP (southeastern Pacific). Robust statistics were established through repeated airborne flights over 1000 km along 20° S from the coastline of Chile to 85° W during VOCALS-REx (VAMOS Ocean-Cloud-Atmosphere-Land-Study Regional Experiment). Non-volatile SSA number concentrations were inferred using a thermally resolved technique constrained for clean conditions with an Ångström exponent below 0.5, black carbon mass concentration at values lower than 15 ng m<sup>−3</sup> and organic aerosol concentration less than 0.02 μg m<sup>−3</sup>. We found that number concentrations of SSAs active as cloud condensation nuclei (CCN) for a supersaturation of 0.25% varied between 17 and 36 cm<sup>−3</sup>, but these did not increase with the increasing mean wind speed typically observed further offshore along 20° S. Concurrent increases in mean offshore precipitation rate in excess of about 1 mm d<sup>−1</sup> indicate that scavenging of SSAs by precipitation exceeds increases in production at wind speeds above about 8 m s<sup>−1</sup>. This demonstrates the critical role of precipitation as a major sink of SSA over the remote ocean. Finally, we found that under clean conditions and for estimated stratus supersaturations between 0.20 and 0.43%, SSA represented about 20% of the total potential CCN along 20° S.
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In the US, wildfires and prescribed burning present significant challenges to air regulatory agencies attempting to achieve and maintain compliance with air quality regulations. Fire emission factors (EF) are essential input for the emission models used to develop wildland fire emission inventories. Most previous studies quantifying wildland fire EF of temperate ecosystems have focused on emissions from prescribed burning conducted outside of the wildfire season. Little information is available on EF for wildfires in temperate forests of the conterminous US. The goal of this work is to provide information on emissions from wildfire-season forest fires in the northern Rocky Mountains, US. In August 2011, we deployed airborne chemistry instruments and sampled emissions over eight days from three wildfires and a prescribed fire that occurred in mixed conifer forests of the northern Rocky Mountains. We measured the combustion efficiency, quantified as the modified combustion efficiency (MCE), and EF for CO<sub>2</sub>, CO, and CH<sub>4</sub>. Our study average values for MCE, EFCO<sub>2</sub>, EFCO, and EFCH<sub>4</sub> were 0.883, 1596 g kg<sup>−1</sup>, 135 g kg<sup>−1</sup>, 7.30 g kg<sup>−1</sup>, respectively. Compared with previous field studies of prescribed fires in temperate forests, the fires sampled in our study had significantly lower MCE and EFCO<sub>2</sub> and significantly higher EFCO and EFCH<sub>4</sub>. The fires sampled in this study burned in areas reported to have moderate to heavy components of standing dead trees and down dead wood due to insect activity and previous fire, but fuel consumption data was not available. However, an analysis of MCE and fuel consumption data from 18 prescribed fires reported in the literature indicates that the availability of coarse fuels and conditions favorable for the combustion of these fuels favors low MCE fires. This analysis suggests that fuel composition was an important factor contributing to the low MCE of the fires measured in this study. This study only measured EF for CO<sub>2</sub>, CO, and CH<sub>4</sub>; however, we used our study average MCE to provide rough estimates of wildfire-season EF for PM<sub>2.5</sub> and four non-methane organic compounds (NMOC) using MCE and EF data reported in the literature. This analysis suggests the EFPM<sub>2.5</sub> for wildfires that occur in forests of the northern Rocky Mountains may be significantly larger than those reported for temperate forests in the literature and that used in a recent national emission inventory. If the MCE of the fires sampled in this work are representative of the combustion characteristics of wildfire-season fires in similar forest types across the western US then the use of EF based on prescribed fires may result in an underestimate of wildfire PM<sub>2.5</sub> and NMOC emissions. Given the magnitude of biomass consumed by western US wildfires, this may have important implications for the forecasting and management of regional air quality.
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The behavior of the extratropical transition layer (ExTL) is investigated using a chemistry transport model (CTM) and analyses derived from assimilation of MLS (Microwave Limb Sounder) O<sub>3</sub> and MOPITT (Measurements Of Pollution In The Troposphere) CO data. We firstly focus on a stratosphere–troposphere exchange (STE) case study that occurred on 15 August 2007 over the British Isles (50° N, 10° W). We evaluate the effect of data assimilation on the O<sub>3</sub>–CO correlations. It is shown that data assimilation disrupts the relationship in the transition region. When MLS O<sub>3</sub> is assimilated, CO and O<sub>3</sub> values are not consistent between each other, leading to unphysical correlations at the STE location. When MLS O<sub>3</sub> and MOPITT CO assimilated fields are taken into account in the diagnostics the relationship happens to be more physical. We then use O<sub>3</sub>–CO correlations to quantify the effect of data assimilation on the height and depth of the ExTL. When the free-model run O<sub>3</sub> and CO fields are used in the diagnostics, the ExTL distribution is found 1.1 km above the thermal tropopause and is 2.6 km wide (2σ). MOPITT CO analyses only slightly sharpen (by −0.02 km) and lower (by −0.2 km) the ExTL distribution. MLS O<sub>3</sub> analyses provide an expansion (by +0.9 km) of the ExTL distribution, suggesting a more intense O<sub>3</sub> mixing. However, the MLS O<sub>3</sub> analyses ExTL distribution shows a maximum close to the thermal tropopause and a mean location closer to the thermal tropopause (+0.45 km). When MLS O<sub>3</sub> and MOPITT CO analyses are used together, the ExTL shows a mean location that is the closest to the thermal tropopause (+0.16 km). We also extend the study at the global scale on 15 August 2007 and for the month of August 2007. MOPITT CO analyses still show a narrower chemical transition between stratosphere and troposphere than the free-model run. MLS O<sub>3</sub> analyses move the ExTL toward the troposphere and broaden it. When MLS O<sub>3</sub> analyses and MOPITT CO analyses are used together, the ExTL matches the thermal tropopause poleward of 50°.
