The Lagrangian particle dispersion model FLEXPART was originally designed for calculating long-range and mesoscale dispersion of air pollutants from point sources, such that occurring after an accident in a nuclear power plant. In the meantime, FLEXPART has evolved into a comprehensive tool for atmospheric transport modeling and analysis at different scales. A need for further multiscale modeling and analysis has encouraged new developments in FLEXPART. In this paper, we present a FLEXPART version that works with the Weather Research and Forecasting (WRF) mesoscale meteorological model. We explain how to run this new model and present special options and features that differ from those of the preceding versions. For instance, a novel turbulence scheme for the convective boundary layer has been included that considers both the skewness of turbulence in the vertical velocity as well as the vertical gradient in the air density. To our knowledge, FLEXPART is the first model for which such a scheme has been developed. On a more technical level, FLEXPART-WRF now offers effective parallelization, and details on computational performance are presented here. FLEXPART-WRF output can either be in binary or Network Common Data Form (NetCDF) format, both of which have efficient data compression. In addition, test case data and the source code are provided to the reader as a Supplement. This material and future developments will be accessible at http://www.flexpart.eu.Peer ReviewedPostprint (published version

Abstract. We use a Lagrangian dispersion model driven by a mesoscale model with four-dimensional data assimilation to simulate the dispersion of elemental carbon (EC) over a region encompassing Mexico City and its surroundings. The region was the study domain for the 2006 MAX-MEX experiment, which was a component of the MILAGRO campaign. The results are used to identify periods when biomass burning was likely to have had a significant impact on the concentrations of elemental carbon at two sites, T1 and T2, downwind of the city, and when emissions from the Mexico City Metropolitan Area (MCMA) were likely to have been more important. They are also used to estimate the median ages of EC affecting the specific absorption of light, α ABS , at 870 nm as well as to identify periods when the urban plume from the MCMA was likely to have been advected over T1 and T2. Median EC ages at T1 and T2 are substantially larger during the day than at night. Values of α ABS at T1, the nearer of the two sites to Mexico City, were smaller at night and increased rapidly after mid-morning, peaking in the mid-afternoon. The behavior is attributed to the coating of aerosols with substances such as sulfate or organic carbon during daylight hours, but such coating appears to be limited or absent at night. Evidence for this is provided by scanning electron microscopy images of aerosols collected at the sampling sites. During daylight hours the values of α ABS did not increase with aerosol age for median ages in the range of 1-4 h. There is some evidence for absorption increasing as aerosols were advected from T1 to T2 but the statistical significance of that result is not strong.

In the recent chemistry version (v3.3) of the Weather Research and Forecasting (WRF-Chem) model, we have coupled the Morrison double-moment microphysics scheme with interactive aerosols so that two-way aerosol-cloud interactions are included in the simulations. We have used this new WRF-Chem functionality in a study focused on assessing predictions of aerosols, marine stratocumulus clouds, and their interactions over the Southeast Pacific using measurements from the VAMOS Ocean-Cloud-Atmosphere-Land Study Regional Experiment (VOCALS-REx) and satellite retrievals. This study also serves as a detailed analysis of our WRF-Chem simulations contributed to the VOCALS model Assessment (VOCA) project. The WRF-Chem 31-day (15 October–16 November 2008) simulation with aerosol-cloud interactions (AERO hereafter) is also compared to a simulation (MET hereafter) with fixed cloud droplet number concentrations assumed by the default in Morrison microphysics scheme with no interactive aerosols. The well-predicted aerosol properties such as number, mass composition, and optical depth lead to significant improvements in many features of the simulated stratocumulus clouds: cloud optical properties and microphysical properties such as cloud top effective radius, cloud water path, and cloud optical thickness, and cloud macrostructure such as cloud depth and cloud base height. In addition to accounting for the aerosol direct and semi-direct effects, these improvements feed back to the prediction of boundary-layer characteristics and energy budgets. Particularly, inclusion of interactive aerosols in AERO strengthens the temperature and humidity gradients within the capping inversion layer and lowers the marine boundary layer depth by 150 m from that of the MET simulation. Mean top-of-the-atmosphere outgoing shortwave fluxes, surface latent heat, and surface downwelling longwave fluxes are in better agreement with observations in AERO, compared to the MET simulation. Nevertheless, biases in some of the simulated meteorological quantities (e.g., MBL temperature and humidity over the remote ocean) and aerosol quantities (e.g., overestimations of supermicron sea salt mass) might affect simulated stratocumulus and energy fluxes over the southeastern Pacific Ocean, and require further investigations. Although not perfect, the overall performance of the regional model in simulating mesoscale aerosol-cloud interactions is encouraging and suggests that the inclusion of spatially varying aerosol characteristics is important when simulating marine stratocumulus over the southeastern Pacific

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International audienceDuring the POLARCAT-France airborne campaign in April 2008, pollution originating from anthropogenic and biomass burning emissions was measured in the European Arctic. We compare these aircraft measurements with simulations using the WRF-Chem model to investigate model representation of aerosols transported from Europe to the Arctic. Modeled PM2.5 is evaluated using EMEP measurements in source regions and POLARCAT aircraft measurements in the Scandinavian Arctic, showing a good agreement, although the model overestimates nitrate and underestimates organic carbon in source regions. Using WRF-Chem in combination with the Lagrangian model FLEXPART-WRF, we find that during the campaign the research aircraft sampled two different types of European plumes: mixed anthropogenic and fire plumes from eastern Europe and Russia transported below 2 km, and anthropogenic plumes from central Europe uplifted by warm conveyor belt circulations to 5–6 km. Both modeled plume types had significant wet scavenging (> 50% PM10) during transport. Modeled aerosol vertical distributions and optical properties below the aircraft are evaluated in the Arctic using airborne LIDAR measurements. Evaluating the regional impacts in the Arctic of this event in terms of aerosol vertical structure, we find that during the 4 day presence of these aerosols in the lower European Arctic (< 75° N), biomass burning emissions have the strongest influence on concentrations between 2.5 and 3 km altitudes, while European anthropogenic emissions influence aerosols at both lower (~1.5 km) and higher altitudes (~4.5 km). As a proportion of PM2.5, modeled black carbon and SO4= concentrations are more enhanced near the surface. The European plumes sampled during POLARCAT-France were transported over the region of springtime snow cover in Northern Scandinavia, where they had a significant local atmospheric warming effect. We find that, during this transport event, the average modeled top of atmosphere (TOA) shortwave direct and semi-direct radiative effect (DSRE) north of 60° N over snow and ice-covered surfaces reaches +0.58 W m−2, peaking at +3.3 W m−2 at noon over Scandinavia and Finland

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MACMILLANEnglish edition © N. V. Philips ' Gloeilampenfabrieken, Eindhoven, 1971 Softcover reprint of the hardcover 1st edition 1971 978-0-333-07564-7 PREFACELike the first volume of 'Interaction of Metals and Gases' this second volume with the sub-title 'Kinetics and Mechanisms' handles the theoretical background as simply as possible. It has been written for metallurgical students, industrial metallurgists and chemists. Three subjects have been omitted from the book, those of adsorption, catalysis and oxidation, not because they are unimportant but rather because they are so all-important that a large number of excellent books are already devoted to them. Consequently this volume, with the exception of Section 4.12, deals exclusively with the behaviour of gases in the interior of metals, leaving interactions with metal surfaces out of consideration. Eindhoven, October 1971J.D. Fast CONTENTS

Abstract. It has been established that observed local and regional levels of secondary organic aerosols (SOA) in polluted areas cannot be explained by the oxidation and partitioning of anthropogenic and biogenic VOC precursors, at least using current mechanisms and parameterizations. In this study, the 3-D regional air quality model CHIMERE is applied to quantify the contribution to SOA formation of recently identified semi-volatile and intermediate volatility organic vapors (S/IVOC) in and around Mexico City for the MILAGRO field experiment during March 2006. The model has been updated to include explicitly the volatility distribution of primary organic aerosols (POA), their gas-particle partitioning and the gas-phase oxidation of the vapors. Two recently proposed parameterizations, those of Robinson et al. (2007) ("ROB") and Grieshop et al. (2009) ("GRI") are compared and evaluated against surface and aircraft measurements. The 3-D model results are assessed by comparing with the concentrations of OA components from Positive Matrix Factorization of Aerosol Mass Spectrometer (AMS) data, and for the first time also with oxygen-to-carbon ratios derived from high-resolution AMS measurements. The results show a substantial enhancement in predicted SOA concentrations (3–6 times) with respect to the previously published base case without S/IVOCs (Hodzic et al., 2009), both within and downwind of the city leading to much reduced discrepancies with the total OA measurements. The predicted anthropogenic POA levels are found to agree within 20% with the observed HOA concentrations for both the ROB and GRI simulations, consistent with the interpretation of the emissions inventory by previous studies. The impact of biomass burning POA within the city is underestimated in comparison to the AMS BBOA, presumably due to insufficient nighttime smoldering emissions. Model improvements in OA predictions are associated with the better-captured SOA magnitude and diurnal variability. The predicted production from anthropogenic and biomass burning S/IVOC represents 40–60% of the total SOA at the surface during the day and is somewhat larger than that from aromatics, especially at the T1 site at the edge of the city. The SOA production from the continued multi-generation S/IVOC oxidation products continues actively downwind. Similar to aircraft observations, the predicted OA/ΔCO ratio for the ROB case increases from 20–30 μg sm−3 ppm−1 up to 60–70 μg sm−3 ppm−1 between a fresh and 1-day aged air mass, while the GRI case produces a 30–40% higher OA growth than observed. The predicted average O/C ratio of total OA for the ROB case is 0.16 at T0, substantially below observed value of 0.5. A much better agreement for O/C ratios and temporal variability (R2=0.63) is achieved with the updated GRI treatment. Both treatments show a deficiency in regard to POA evolution with a tendency to over-evaporate POA upon dilution of the urban plume suggesting that atmospheric HOA may be less volatile than assumed in these parameterizations. This study highlights the important potential role of S/IVOC chemistry in the SOA budget in this region, and highlights the need for improvements in current parameterizations. We note that our simulations did not include other proposed pathways of SOA formation such as formation from very volatile species like glyoxal, which can also contribute SOA mass and especially increase the O/C ratio.