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This paper describes the GENerator of reduced Organic Aerosol mechanism (GENOA) that produces semi-explicit mechanisms for simulating the formation and evolution of secondary organic aerosol (SOA) in air quality models. Using a series of predefined reduction strategies and evaluation criteria, GENOA trains and reduces SOA mechanisms from near-explicit chemical mechanisms (e.g., the Master Chemical Mechanism – MCM) under representative atmospheric conditions. As a consequence, these trained SOA mechanisms can preserve the accuracy of detailed gas-phase chemical mechanisms on SOA formation (e.g., molecular structures of crucial organic compounds, the effect of “non-ideality”, and the hydrophilic/hydrophobic partitioning of aerosols), with a size (in terms of reaction and species numbers) that is manageable for three-dimensional (3-D) aerosol modeling (e.g., regional chemical transport models). Applied to the degradation of sesquiterpenes (as β-caryophyllene) from MCM, GENOA builds a concise SOA mechanism (2 % of the MCM size) that consists of 23 reactions and 15 species, with 6 of them being condensable. The generated SOA mechanism has been evaluated regarding its ability to reproduce SOA concentrations under the varying atmospheric conditions encountered over Europe, with an average error lower than 3 %.

A large fraction of the European population is exposed to atmospheric pollutant concentration levels above health-related thresholds, leading to excess mortality and morbidity. Densely populated urban areas are generally more concerned than rural regions due to higher emission of atmospheric pollutants especially from the road network. Atmospheric modelling is a necessary tool to assess urban scale air-quality for both research and operational purposes. It provides a spatially and temporally resolved information for several gaseous and particulate species. It is also used for forecast and scenario evaluation for policy making. Modelling atmospheric composition at street level is challenging because pollutant concentration within street-canyons depends largely on local emissions but also on the transport of polluted air masses from remote areas. Therefore, regional scale modelling and local applications must be combined to provide accurate simulations of the atmospheric composition at urban scale. In our study we compare two such strategies. In both cases the regional scale chemistry-transport model CHIMERE, fed by WRF meteorological fields, provides urban background concentrations. To simulate the local component of pollutant concentrations over roads we use i) the statistical sub grid-scale approach embedded in the chemistry-transport model and ii) the street-network model MUNICH. Simulation results over the city of Paris from both modelling approaches are compared to in-situ measurements of the local air-quality network for all available traffic monitors.The major challenge of this inter comparison exercise is to find a consistent configuration setup for both models allowing a one-to-one comparison of the simulations. To do so we had to implement the same chemical and dynamical mechanisms for gases and suspended particles in both models. We also tested several vertical discretizations to obtain a consistent first-layer depth. Different turbulence parametrizations, including or not the urban canopy model (UCM) within WRF, were compared to obtain stable results for concentrations. We show these latter are particularly sensitive to the parametrization of the anthropogenic heat flux. To obtain realistic heat fluxes and satisfactory results for both modelling strategies we have to include in the simulations all three of the following aspects i) a highly resolved land-cover database (CORINE) ; ii) a three urban class distinction in the UCM and iii) the sub-grid scale urban fraction.Results of two-month wintertime simulations for NOx, NO2, PM2.5 are discussed. The street-network approach provides better results for both gases and particles especially at high-traffic highways. The conclusion is less straightforward at low-traffic roads. Our results highlight the need to develop a consistent coupling of the street-network model MUNICH with the regional scale chemistry transport model CHIMERE to accurately simulate gases and particulate matter concentrations over the street network.

With the growing evidence that high particle number concentrations may impact health, modelling their emissions and understanding formation processes is necessary, especially in cities where many people are exposed. As emission inventories of particle numbers and size distribution over cities are usually not available, a methodology is defined to estimate them from PM2.5 emissions and ratios of PM1 / PM2.5 and PM0.1 / PM2.5 by activity sector. In this methodology, a fitting parameter αem is used to redistribute the number concentrations in the lowest emission diameter range. This parameter is chosen by comparing measured and simulated number concentrations during non-nucleation days. The emission size distribution is then finely discretised by conserving both mass and number in each of the size ranges where emissions are specified. The methodology is applied over Greater Paris during the MEGAPOLI campaign (July 2009). Three-dimensional simulations are performed using the chemistry transport model Polair3D/Polyphemus coupled to the aerosol module SSH-aerosol to represent the evolution of particles by condensation, evaporation, coagulation, and nucleation, with a sectional approach for the size distribution. The model is first compared to measurements during non-nucleation days, and the influence over the month of July 2009 of three different nucleation parameterisations is assessed, i.e. binary (sulfuric acid, water), ternary (sulfuric acid, ammonia, water), and heteromolecular (extremely low-volatility organic compounds (ELVOCs) from monoterpenes and sulfuric acid). The modelled number concentrations compare very well to measurements, with an average normalised mean error of 42 % for the daily number concentrations of particles larger than 10 nm and 37 % for the number concentrations of particles larger than 100 nm. The influence of the binary nucleation is low, and the ternary nucleation scheme leads to better simulated number concentrations (in terms of bias and error) at only one site out of three, but it systematically reduces the model to measurement correlation, suggesting that ternary nucleation may not be the dominant process in new particle formation. However, the relative bias and error, as well as the correlation at suburban sites, are systematically improved using the heteromolecular nucleation scheme involving sulfuric acid and ELVOCs from monoterpenes. This suggests that heteromolecular nucleation may be important in cities, especially at suburban sites in summer, and that a better characterisation of the emissions of ELVOC precursors from traffic is needed.

Populations in urban areas are exposed to high local concentrations of pollutants, such as nitrogen dioxide and particulate matter, because of unfavorable dispersion conditions and the proximity to traffic. To simulate these concentrations over cities, models like the street-network model MUNICH (Model of Urban Network of Intersecting Canyons and Highways) rely on parameterizations to represent the air flow and the concentrations of pollutants in streets. In the current version MUNICH v2.0, concentrations are assumed to be homogeneous in each street segment. A new version of MUNICH where the street volume is discretized is developed to represent the street gradients and better estimate people exposure. Three vertical levels are defined in each street segment. A horizontal discretization is also introduced under specific conditions by considering two zones with a parameterization taken from the Operational Street Pollution Model (OSPM). Simulations are performed over two districts of Copenhagen, Denmark, and one district of Greater Paris, France. Results show an improvement of the comparison to observations with higher concentrations at the bottom of the street, closer to traffic, of pollutants emitted by traffic (NOx, black carbon, organic matter). Finally, a sensitivity analysis to the influence of the street network highlights the importance to use the model MUNICH with a network rather than with a single street.

Clouds have a strong influence on the amount of solar irradiance reaching the ground. However, they have large spatio-temporal variations and are difficult to model. The 1D irradiance model of code_saturne is used to estimate the global and direct solar irradiances at the ground, taking into account the impact of atmospheric gas, clouds and aerosols. Simulations are conducted and compared to measurements at the French SIRTA observatory (instrumental site for atmospheric remote sensing research), located in Palaiseau, Ile-de-France in August 2009 and in the year 2014. Although irradiance is very well modelled during clear-sky days, it is over-estimated during cloud-sky days. The estimation of irradiance during cloudy-sky days is improved by coupling the model to on-site measurements of cloud parameters from the SIRTA. RMSEs around 59 W m−2 and 50 W m−2 and MBEs around +17 W m−2 and -18 W m−2 are obtained, respectively, for global and direct irradiances during cloudy-sky days using pyranometer measurements for cloud fraction and microwave radiometric measurements for liquid water path. A sensitivity analysis on the cloud parameters that may lead to the best improvement of simulated irradiance is performed. The cloud optical depth is the most important one, followed by the cloud fraction. The different instruments used for the determination of these parameters are examined. Moreover, hourly values of solar fluxes are analysed to determine and physically understand persistent errors between model and measurements when measured cloud parameters are used.

In the urban environment, gas and particles impose adverse impacts on the health of pedestrians. The conventional computational fluid dynamics (CFD) methods that regard pollutants as passive scalars cannot reproduce the formation of secondary pollutants and lead to uncertain prediction. In this study, SSH-aerosol, a modular box model that simulates the evolution of gas, primary and secondary aerosols, is coupled with the CFD software, OpenFOAM and Code_Saturne. The transient dispersion of pollutants emitted from traffic in a street canyon is simulated using the unsteady Reynolds-averaged Navier–Stokes equations (RANS) model. The simulated concentrations of NO2, PM10, and black carbon (BC) are compared with field measurements on a street of Greater Paris. The simulated NO2 and PM10 concentrations based on the coupled model achieved better agreement with measurement data than the conventional CFD simulation. Meanwhile, the black carbon concentration is underestimated, probably partly because of the underestimation of non-exhaust emissions (tire and road wear). Aerosol dynamics lead to a large increase of ammonium nitrate and anthropogenic organic compounds from precursor gas emitted in the street canyon.

A new version of a street-network model, the Model of Urban Network of Intersecting Canyons and Highways version 2.0 (MUNICH v2.0), is presented. The comprehensive aerosol model SSH-aerosol is implemented in MUNICH v2.0 to simulate the street concentrations of multiple pollutants, including secondary aerosols. The implementation uses the application programming interface (API) technology so that the SSH-aerosol version may be easily updated. New parameterisations are also introduced in MUNICH v2.0, including a non-stationary approach to model reactive pollutants, particle deposition and resuspension, and a parameterisation of the wind at roof level. A test case over a Paris suburb is presented for model evaluation and to illustrate the impact of the new functionalities. The implementation of SSH-aerosol leads to an increase of 11 % in PM10 concentration because of secondary aerosol formation. Using the non-stationary approach rather than the stationary one leads to a decrease in NO2 concentration of 16 %. The impact of particle deposition on built surfaces and road resuspension on pollutant concentrations in the street canyons is low.

Trees provide many ecosystem services in cities such as urban heat island reduction, water runoff limitation, and carbon storage. However, the presence of trees in street canyons reduces the wind velocity in the street and limits pollutant dispersion. Thus, to obtain accurate simulations of pollutant concentrations, the aerodynamic effect of trees should be taken into account in air quality models at the street level. The Model of Urban Network of Intersecting Canyons and Highways (MUNICH) simulates the pollutant concentrations in a street network, considering dispersion and physico-chemical processes. It can be coupled to a regional-scale chemical transport model to simulate air quality over districts or cities. The aerodynamic effect of the tree crown is parameterized here through its impact on the average wind velocity in the street direction and the vertical transfer coefficient associated with the dispersion of a tracer. The parameterization is built using local-scale simulations performed with the computational fluid dynamics (CFDs) code Code_Saturne. The two-dimensional CFD simulations in an infinite street canyon are used to quantify the effect of trees, depending on the tree characteristics (leaf area index, crown volume fraction, and tree height to street height ratio) using a drag porosity approach. The tree crown slows down the flow and produces turbulent kinetic energy in the street, thus impacting the tracer dispersion. This effect increases with the leaf area index and the crown volume fraction of the trees, and the average horizontal velocity in the street is reduced by up to 68 %, while the vertical transfer coefficient by up to 23 % in the simulations performed here. A parameterization of these effects on horizontal and vertical transfers for the street model MUNICH is proposed. Existing parameterizations in MUNICH are modified based on Code_Saturne simulations to account for both building and tree effects on vertical and horizontal transfers. The parameterization is built to obtain similar tree effects (quantified by a relative deviation between the cases without and with trees) between Code_Saturne and MUNICH. The vertical wind profile and mixing length depend on leaf area index, crown radius, and tree height to street height ratio. The interaction between the trees and the street aspect ratio is also considered.

In the urban environment, gas such as nitrogen dioxide NO2, and particles impose adverse impacts on pedestrians’ health. The conventional computational fluid dynamics (CFD) methods that regard pollutant as passive scalar cannot reproduce the formation of secondary pollutants, such as NO2 and secondary inorganic and organic aerosols, leading to uncertain prediction. In this study, SSH-Aerosol, a modular box model that simulates the evolution of gas, primary and secondary aerosols, is coupled with the CFD software OpenFOAM and Code_Saturne. The transient dispersion of pollutants emitted from traffic in a street canyon is simulated using unsteady Reynolds-averaged Navier–Stokes equations (RANS) model. The simulated concentrations of NO2, PM10 and black carbon are compared with field measurements on a street of Greater Paris. The simulated NO2 and PM10 concentrations based on the coupled model achieved better agreement with measurement data than the conventional CFD simulation. Meanwhile, the black carbon concentration is underestimated, probably partly because of the underestimation of non-exhaust emissions (tyre and road wear). Vehicles are considered the main source of ammonia (NH3) in urban environments, which may condense with nitric acid (HNO3) to form ammonium nitrate. In the reference simulation with NH3 traffic emissions accounting for 1–2 % of NOx emissions, aerosol dynamics leads to an ammonium nitrate increase of 46 % on average over a 12-hour simulation period (5 a.m. to 5 p.m.) compared to the conventional CFD simulation. Furthermore, an increase in NH3 traffic emissions (to 10 % and 20 % of NOx emissions) may leads to a large increase in ammonium nitrate (35 % and 55 %) compared to the reference simulation. In addition, aerosol dynamics leads to a 52 % increase in 12-hour time-averaged organic matter concentrations compared to the conventional CFD simulation, because of the condensation of anthropogenic compounds from precursor-gas emissions and of background biogenic precursor-gases on the enhance inorganic concentrations.

Regional-scale chemistry-transport models have coarse spatial resolution (coarser than 1 km ×1 km) and can thus only simulate background concentrations. They fail to simulate the high concentrations observed close to roads and in streets, where a large part of the urban population lives. Local-scale models may be used to simulate concentrations in streets. They often assume that background concentrations are constant and/or use simplified chemistry. Recently developed, the multi-scale model Street-in-Grid (SinG) estimates gaseous pollutant concentrations simultaneously at local and regional scales by coupling them dynamically. This coupling combines the regional-scale chemistry-transport model Polair3D and a street-network model, the Model of Urban Network of Intersecting Canyons and Highway (MUNICH), with a two-way feedback. MUNICH explicitly models street canyons and intersections, and it is coupled to the first vertical level of the chemical-transport model, enabling the transfer of pollutant mass between the street-canyon roof and the atmosphere. The original versions of SinG and MUNICH adopt a stationary hypothesis to estimate pollutant concentrations in streets. Although the computation of the NOx concentration is numerically stable with the stationary approach, the partitioning between NO and NO2 is highly dependent on the time step of coupling between transport and chemistry processes. In this study, a new nonstationary approach is presented with a fine coupling between transport and chemistry, leading to numerically stable partitioning between NO and NO2. Simulations of NO, NO2 and NOx concentrations over Paris with SinG, MUNICH and Polair3D are compared to observations at traffic and urban stations to estimate the added value of multi-scale modeling with a two-way dynamical coupling between the regional and local scales. As expected, the regional chemical-transport model underestimates NO and NO2 concentrations in the streets. However, there is good agreement between the measurements and the concentrations simulated with MUNICH and SinG. The two-way dynamic coupling between the local and regional scales tends to be important for streets with an intermediate aspect ratio and with high traffic emissions.

International audience; Indoor measurements of OH and sum of peroxy radicals XO2=HO2+RO2 were conducted in a room using window glasses of different transparencies and applying different coatings to the walls. Average OH and XO2 concentrations were found to vary in the range (0.6-4) × 105 molecule cm-3 and (1-7) × 107 molecule cm-3 respectively with anti-UV windows, and (6-10) × 105 molecule cm-3 and (4-16) × 107 molecule cm-3 respectively with borosilicate glasses. The OH and XO2 concentrations were compared with simulation results obtained using the H2I model, which accounts for the mixing between the sunlit and shaded volumes of the room. Taking into account the measurement uncertainty, the simulated OH concentrations agree with the observations on average while the simulated XO2 concentrations tend to be overestimated. Based on the model results, ozonolysis of unsaturated VOCs and photolysis of HONO and of organic compounds are found to represent the main primary sources of OH and XO2 radicals, the latter being more important in the sunlit volume. Despite the lower rate of the radical initiation in the shaded volume, the difference of radical concentrations in the shaded and sunlit volumes is mitigated by an interplay between the mixing time and the lifetime of XO2 radicals, allowing efficient transport of XO2 radicals into the shaded volume and acting there as a source of OH via radical propagation processes.

Cloud condensation nuclei (CCN) are the subset of aerosol particles able to form cloud droplets. CNN activation is influenced by the size distribution, chemical composition and number of particles. They consequently impact the cloud microstructure, which affects the radiative properties of clouds, atmospheric circulation and thermodynamics, as well as radiative budgets. By influencing the single scattering albedos of clouds, some particles lead to an increase of the solar irradiation absorption and solar heating in the cloud layers. A good example of these absorbing particles is those made of black carbon (BC), which is emitted during the combustion of various types of fuel and non-exhaust traffic-related processes. The present study deals with the role of BC in a solar radiative scheme and its interaction with clouds during a well-documented case of a fog that evolves into a low stratus cloud. To do so, the solar scheme of the computational fluid dynamic model Code Saturne is used for the estimation of fluxes and heating rates in the atmosphere. It is based on the two-stream parameterization with calculations done in the ultraviolet-visible (UV-Vis) and solar infrared (SIR) bands. A special attention is given on the impact of BC on the dissipation of the fog. As expected, the introduction of BC in cloud droplets accentuates the heating in the layers at the top of the cloud where water liquid content is maximum. In the SIR band, there is an increase of approximatively 80 %. In the UV-Vis band, where absorption of solar irradiance by ozone is minor, the heating rate is now 10 times higher. The contribution of the UV-Vis band becomes more important. The augmentation of solar heating leads to a reduction of the liquid water content and, consecutively, to a faster dissipation of the fog and the stratus. Therefore, direct surface fluxes are also increased.When increasing the volume fraction of black carbon in cloud droplets, the water liquid content is furthermore reduced leading to a faster dissipation of the fog. However, this impact is small, because the fog is formed in the morning. At this time, the cooling rate due to thermal radiation is higher than the solar heating at the top of the cloud. We expect the impact of black carbon in cloud droplets to be higher for more persistent clouds or for a fog in the boundary layer of the urban atmosphere, where the fraction of BC in particles is higher.

Solar radiation modelling is important for the evaluation and deployment of solar renewable energy systems. The amount of solar radiation reaching the ground is influenced by geographical parameters (seasons, latitude and local characteristics of the site) and meteorological and atmospheric parameters (like humidity, clouds or particles). Those parameters have important spatio-temporal variations that make solar radiation hard to model. Various radiation models exist in literature. Among them, the 1D radiation model part of the computational fluid dynamics software “Code_Saturne” estimates the global and direct solar irradiances at the ground. It takes into account the impact of meteorology, atmospheric gas, particles and clouds whose influence is represented using the two-stream approximation. The model showed satisfactory results during clear-sky days but not during cloudy-sky days. It is a common problem in solar radiation modelling, because of the complexity to accurately represent clouds, which are extremely variable in space and time and have a strong influence on the depletion of solar irradiance. In the current study, the estimation of radiation during cloudy-sky days is improved by coupling the 1D radiation model of Code_Saturne with on-site and satellite measurements of the cloud optical properties. Meteorological data are obtained from the Weather Research and Forecasting (WRF) model, aerosol’s concentrations from the air-quality modelling platform Polyphemus, and on-site measurements from the SIRTA observational site (close to Paris). Two periods are simulated: 'august 2009' and 'year 2014'. It is shown that the introduction of the measured cloud properties in the computation of the surface radiation fluxes leads to a strong reduction of the simulated errors, compared to the case where these properties are derived from the WRF model. A sensitivity analysis on the parameters representing clouds in the model is conducted. It enabled us to identify the most influencing parameters - cloud optical thickness (COD) and cloud fraction - and instruments that are sufficient and mandatory for a good description of solar radiation during cloudy-sky days. A fitted model is developed to deduce the COD from liquid water path measurements. Satellite and radiometric measurements could both be used, although satellite measurements are not always available. For the estimation of cloud fraction, the best results are obtained from shortwave radiometric measurements or from a sky imager. Moreover, large error cases in hourly values of solar fluxes are examined to understand their origin. For a large part of these error cases, there is a high variation within the hour of satellite or in situ measurements, or the presence of low clouds (in more than 50% of these cases in august 2009).

Due to their major role in atmospheric chemistry and secondary pollutant formation such as ozone or secondary organic aerosols, an accurate representation of OH and HO2 (HOX) radicals in air quality models is essential. Air quality models use simplified mechanisms to represent atmospheric chemistry and interactions between HOX and organic compounds. In this work, HOX concentrations during the oxidation of toluene and xylene within the Regional Atmospheric Chemistry Mechanism (RACM2) are improved using a deterministic–near-explicit mechanism based on the Master Chemical Mechanism (MCM) and the generator of explicit chemistry and kinetics of organics in the atmosphere (GECKO-A). Flow tube toluene oxidation experiments are first simulated with RACM2 and MCM/GECKO-A. RACM2, which is a simplified mechanism, is then modified to better reproduce the HOX concentration evolution simulated by MCM/GECKO-A. In total, 12 reactions of the oxidation mechanism of toluene and xylene are updated, making OH simulated by RACM2 up to 70% more comparable to the comprehensive MCM/GECKO-A model for chamber oxidation simulations.

Black carbon (BC) is a primary and inert pollutant often used as a traffic tracer. Even though its concentrations are generally low at regional scale, BC presents very high concentrations in streets (local scale), potentially causing important effects on human health and environment. modelling studies of BC concentrations usually underestimate BC concentrations, because of uncertainties in both emissions and modelling. Both exhaust and non-exhaust traffic emissions present uncertainties, but those on non-exhaust emissions, such as tyre, brake and road wear and particle resuspension, are particularly high. In terms of modelling, the street models do not always consider the two-way interactions between the local and regional scales, i.e. the influence of the high BC concentrations observed in streets on the urban background concentrations, which can enhance the BC concentrations in streets. This study uses the multi-scale Street-in-Grid model (SinG) to simulate BC concentrations in a Paris suburb street-network, taking into account the two-way coupling between local and regional scales. The BC concentrations in streets proved to have an important influence on urban background concentrations. The two-way dynamic coupling leads to an increase in BC concentrations in large streets with high traffic emissions (with a maximal increase of about 48 %), and a decrease in narrow streets with low traffic emissions and low BC concentrations (with a maximal decrease of about 50 %). A new approach to estimate particle resuspension in streets is implemented, strictly respecting the mass balance on the street surface. The resuspension rate is calculated from the available deposited mass on the street surface, which is estimated based on a particle deposition and wash-off parametrizations adapted to street-canyon geometries. The simulations show that particle resuspension presents a low contribution to black carbon concentrations, as the deposited mass is not significant enough to justify high resuspension rates. Non-exhaust emission, such as brake and tyre and road wear, largely contribute to BC emissions, with a contribution equivalent to exhaust emissions. Here, emission factors of tyre, brake and road wear are calculated based on the literature, and a sensitivity analysis of these emission factors on BC concentrations in streets is performed. The model to measurement comparison shows that tyre-emission factors usually used in Europe are probably under-estimated, and tyre-emission factors coherent with some studies of the literature and the comparison performed here are proposed.

High particle concentrations are observed in the streets. Regional-scale chemistry-transport models are not able to reproduce these high concentrations, because their spatial resolution is not fine enough. Local-scale models are usually employed to simulate the high concentrations in street networks, but they often adopt substantial simplifications to determine background concentrations and use simplified chemistry. This study presents the new version of the local-scale Model of Urban Network of Intersecting Canyons and Highways (MUNICH) that integrates background concentrations simulated by the regional-scale chemistry-transport model Polair3D, and uses the same complex chemistry module as Polair3D, SSH-aerosol, to represent secondary aerosol formation. Gas and aerosol concentrations in Paris streets are simulated with MUNICH, considering a street-network with more than 3800 street segments, between 3 May and 30 June. Comparisons with PM10 and PM2.5 measurements at several locations of Paris show that the high PM10 and PM2.5 concentrations are well represented. Furthermore, the simulated chemical composition of fine particles corresponds well to a yearly measured composition. To understand the influence of the secondary pollutant formation, several sensitivity simulations are conducted. Simulations with and without gas-phase chemistry show that the influence of gas-phase chemistry on the formation of NO2 is large (37% on average over May and across all modelled streets), but the influence on condensables is lower (less than 2% to 3% on average at noon for inorganics and organics), but may reach more than 20% depending on the street. The assumption used to compute gas/particle mass transfer by condensation/evaporation is important for inorganic and organic compounds of particles, as using the thermodynamic equilibrium assumption leads to an overestimation of the organic concentrations by 4.7% on average (up to 31% at noon depending on the streets). Ammonia emissions from traffic lead to an increase in inorganic concentrations by 3% on average, reaching 26% depending on the street segments. Not taking into account gas-phase chemistry and aerosol dynamics in the modelling leads to an underestimation of organic concentrations by about 11% on average over the streets and time, but this underestimation may reach 51% depending on the streets and the time of the day.

This study was part of the work done by the ANSES working group on ambient particulate matter (chemical composition and road traffic emissions); International audience; Air pollution from road traffic and its mitigation is a major concern in most cities. A platform for simulating pollutant emissions and concentrations was developed and applied to the Île-de-France Region (Greater Paris) of France, taking account of anthropogenic and natural sources and ‘imported’ pollution from elsewhere in France and Europe. Four technological scenarios for 2025 were studied and compared to the 2014 reference situation (1-REF). These scenarios included the current evolution of the park with widespread adoption of diesel particulate filters (DPFs) (2-BAU), decline in the sale of diesel vehicles and a corresponding increase in petrol vehicle sales (3-PET), promotion of electric vehicles in urban areas (4-ELEC), and a combinaison with a decrease in traffic of about 15% in the densely populated area inside the A86 outer ring road (5-AIR). The corresponding vehicle fleets were determined using a fleet simulation model.Traffic pollutant emissions were computed with the COPERT4 European methodology and hourly traffic data over the Île-de-France road network. Particulate matter (PM10, PM2,5 and PM1,0), particles number (PN), black carbon (BC), organic matter (OM), nitrogen oxides (NOx) and nitrogen dioxide (NO2), non-methane volatile organic compounds (VOC), ammonia (NH3), carbon monoxide (CO) and carbon dioxide (CO2) were considered. Emissions for other sectors were taken from a regional inventory. Emissions outside the Île-de-France region (Europe and France) were derived from the European and French emission inventories. Pollutant concentrations (PM2,5, PM10, organic and inorganic PM10, PN, BC, NO2 and O3) were simulated over nested domains (Europe, France and Île-de-France) using the Polyphemus platform for two scenarios (2-BAU and 3-PET). Methodological aspects and results for Île-de-France are discussed here.All scenarios led to a sharp decrease in traffic emissions in Île-de-France (−30% to −60%) by 2025. The decline in diesel induced a stronger renewal of the fleet. PM and NOx emissions were more strongly reduced than VOC or NH3. Traffic reduction reduced all emissions in the densely populated area within the A86 outer ring road (−20% to −45% for exhaust particles and gaseous pollutants).The 2-BAU and 3-PET scenarios lowered annual average concentrations, especially for NO2 and BC, and more strongly influenced daily-peak than daily-average concentrations. In Île-de-France, PM of diameter

Homogeneous reactivity has been extensively studied over the past years through outdoor air-quality simulations. However, indoor atmospheres are known to be largely influenced by another type of chemistry, that is reactivity with surfaces. Despite progress in the understanding of heterogeneous reactions, these remain barely integrated in numerical models. In this paper, a room-scale indoor air-quality (IAQ) model is developed to represent both heterogeneous and homogeneous chemistry. Thanks to the introduction of sorbed species, deposition and surface reactivity are treated as two separate processes, and desorption reactions are incorporated. The simulated concentrations of inorganic species are compared to experimental measurements acquired in a real room, thus allowing to calibrate the model’s undetermined parameters. For the considered experiments durations, the influence of the simulations initial conditions is strong. The model succeeds in simulating correctly the four inorganic species concentrations that were measured, namely NO, NO2, HONO and O3, together with the HOx (HO + HO2) radicals. Each parameter is then varied to estimate its sensitivity and identify the most prevailing processes. The speed of air and building filtration factor are uncertain parameters which appear to have a strong influence, the first one on deposition, and the second one on the control of transport from outdoor. As expected, the NO2 surface hydrolysis plays a key role in the production of secondary species. The secondary production of NO by the reaction of sorbed HONO with sorbed HNO3 stands as an essential component to integrate in IAQ models.

International audience; Road transport is a major source of anthropogenic emissions especially in the Middle East where the regulations enforcement is generally poor. This study aims to quantify the Emission Factors (EF) of traffic-related gaseous and particulate pollutants inside the Salim Slam urban tunnel in Beirut, Lebanon. The fuel-based emission factors of measured pollutants were from the carbon mass balance model. The EF determined showed general higher values than those reported in recent studies from European and American countries, even for speciated NMVOC. The average CO and NOx emission factors for the mixed fleet (HDV + LDV) were determined to be 10.52 ± 3.00 g km−1 and 2.20 ± 0.57 g km−1 respectively, while the EF for PM2.5 55 ± 27 mg km−1. Moreover, IVOC species from gaseous phase were reported for the first time in the region. A reduction trend was observed in comparison with the previous tunnel study from Lebanon, however there is still a need to have tougher regulations to control the local practices such as removal of catalytic converter, adjustment of engine parameters for inspection, etc. The comparison of the EF to those calculated through EMEP or IPCC methodologies shows the need to take local practices while establishing national emission inventories.

Aerosols and in particular their black carbon (BC) content influence the atmospheric heating rate and fog dissipation. Substantial improvements have been introduced to the solar scheme of the computational fluid dynamic model code_saturne to estimate fluxes and heating rates in the atmosphere. This solar scheme is applied to a well-documented case of a fog that evolves into a low stratus cloud. Different sensitivity tests are conducted. They show that aerosols have a major effect with an overestimation of the direct solar fluxes by 150 W m−2 when aerosols are not considered and a reduction of the heating of the layers. Aerosols lead to an increase of the heating rate by as much as 55% in the solar infrared (SIR) band and 100% in the Ultra-Violet visible (UV-vis) band. Taking into account the fraction of BC in cloud droplets also accentuates the heating in the layers at the top of the fog layer where water liquid content is maximum. When the BC fraction in cloud droplets is equal to 8.6 × 10−6, there is an increase of approximately 7.3 °C/day in the layers. Increasing the BC fraction leads to an increase of this heating in the layer, especially in the UV-vis band.

Atmospheric particles may attenuate solar irradiance effectively during clear-sky days, but attenuation by particles is sometimes not taken into account in numerical models, or it is often parameterised using constant or climatological values for example. This paper compares different representations of the effects of particles on direct and global solar irradiance, using the software Code_Saturne. Particle concentrations, as well as aerosol optical properties AOPs (optical thickness, asymmetry factor and single scattering albedo), are estimated using the air-quality modelling platform Polyphemus. Modelled solar irradiance is compared to measurements in greater Paris and the south of France. Accurate modelling of AOPs leads to an improvement of statistical error indicators, especially in clear-sky conditions. A simplified scheme represents AOPs integrated over the full spectral range using only 6 wavelengths, and a sensitivity study on the influence of assumptions in AOPs on solar irradiance is performed.

Air quality is modelled at high resolution over Lebanon (5 × 5 km) and Beirut (1 × 1 km) using the WRF/Polyphemus modeling system for the year 2014. The observation data collected from the recently deployed national air quality monitoring network as well as ground measurement from a long-term campaign are used to evaluate both models performance. Statistical indicators are calculated and compared to a selection of performance criteria from the literature. Accordingly, the modelled results are satisfactory and within the range of the literature for both the meteorological parameters as well as air quality pollutants. For the meteorological model, some biases are observed for the wind components especially during winter, as better statistics are obtained during summer. As for the air quality, the model satisfied commonly used performance criteria for O3 and PM2.5. However, the model underestimates the carbon monoxide values in urban regions and overestimates sulfur dioxide and it appears that these biases results mainly from the emission inventory and the meteorology. Also, EC and OC components of PM2.5 are evaluated. The results highlight an underestimation of OC, which could relate to the sensitivity of the chemical mechanism to the temperature, the boundary conditions, or the emission inventory.

The impact of mixing state of particles from biomass burning on aerosol optical properties (aerosol optical depth (AOD) and single-scattering albedo (SSA)) is studied over the Euro- Mediterranean region during the severe fire event in the Balkans between 20 and 31 July 2007, also characterized by high dust concentrations. When the mixing state is resolved in chemistry-transport models, chemical compounds are grouped for computational reasons, and internal mixing is assumed within each group. Up to six groups are defined here (dust, black carbon, two inorganic groups and two organic groups). The influence of different grouping assumptions is studied here and compared to the influence of the distribution of black carbon (BC) in particles (“pure homogeneous” representation and “core-shell” one), and the influence of modeling the water absorbed by both inorganic and organic compounds. The comparisons of simulated AODs to observations from the surface network AERONET show that AOD is slightly underestimated when aerosol compounds are assumed to be externally mixed and slightly overestimated when they are assumed to be internally mixed. The mixing state of dust with other compounds, as well as the distribution of BC in particles, strongly influence the optical properties. The impact of the mixing state on AOD is higher than the impact of the distribution of BC in particles, reaching 8–12% on average over the fire regions and 16% in the fire plume. Analysis related to the impact of particle mixing state and BC distribution on SSA shows results similar to AOD. The impact of the mixing state on SSA can reach −8.5% over the fire regions and it is higher than the impact of the BC representation, which is lower than 2%. At the location of fires, water absorbed by inorganics and organics is shown to influence the AOD by about 2%, which is in the lower range of the influence of water on AOD over the region (between 0 and 40%). This low influence of water on AOD during fire is due to assumptions made in the modelling, where most of secondary organic aerosols formed during fires are assumed to be hydrophobic.

Regional-scale chemistry-transport models have coarse spatial resolution, and thus can only simulate background concentrations. They fail to simulate the high concentrations observed close to roads and in streets, i.e. where a large part of the urban population lives. Local-scale models may be used to simulate concentrations in streets. They often assume that background concentrations are constant and/or use simplified chemistry. Recently developed, the multi-scale model Street-in-Grid (SinG) estimates gaseous pollutant concentrations simultaneously at local and regional scales, coupling them dynamically. This coupling combines the regional-scale chemistry-transport model Polair3D and the street network model MUNICH (Model of Urban Network of Intersecting Canyons and Highway). MUNICH models explicitly street canyons and intersections, and it is coupled to the first vertical level of the chemical-transport model, enabling the transfer of pollutant mass between the street canyon roof and the atmosphere. The original versions of SinG and MUNICH adopt a stationary hypothesis to estimate pollutant concentrations in streets. Although the computation of NOx concentration is numerically stable with the stationary approach, the partitioning between NO and NO2 is highly dependent on the time step of coupling between transport and chemistry processes. In this study, a new non-stationary approach is presented with a fine coupling between transport and chemistry, leading to numerically stable partitioning between NO and NO2. Simulations of NO, NO2 and NOx concentrations over Paris city with SinG, MUNICH and Polair3D are compared to observations at traffic and urban stations to estimate the added value of multi-scale modeling with a dynamical coupling between the regional and local scales. As expected, the regional chemical-transport model underestimates NO and NO2 concentrations in the streets. However, there is a good agreement between the measurements and the concentrations simulated with MUNICH and SinG. The dynamic coupling between the local and regional scales tends to be important for streets with an intermediate aspect ratio and with high traffic emissions.

In order to estimate the atmospheric impact of the release of sodium oxide aerosols from an indoor sodium fire, two chemical models describing the evolution of sodium oxide aerosols have been implemented in the atmospheric version of the computational fluid dynamic model Code_Saturne. The first chemical model is a shrinking core model. It describes the hydration and transformation of sodium oxide particles to carbonate by assuming that particles are made of layers of different compositions (sodium oxide, sodium hydroxide and carbonate). In the second model, a reactive absorption model describes more accurately the carbonate formation from sodium hydroxide. Both model implementations favorably compare to the published results produced by the model authors, as well as to experimental data resulting from experiments in laboratory. They differ in the speed of carbonate formation, and notably in the atmospheric humidity dependence of this formation. The second model may be more adapted to relative humidity larger than 50% where the core of particles is liquid. The atmospheric dispersion of sodium aerosols is modelled with Code_Saturne by assuming a release particle size distribution and by taking into account the sedimentation and deposition processes. The differences between the shrinking core model and the reactive absorption model largely influence the composition of sodium particles during their dispersion in the atmosphere. Further comparisons to experimental measurements of sodium oxide in the real atmosphere are required to evaluate the accuracy of these models at determining atmospheric sodium carbonate concentrations occurring from the transformation of sodium oxides.

Particles are emitted by different sources and are also formed in the atmosphere. Despite the large impact of atmospheric particles on health and climate, large uncertainties remain concerning their representation in models. To reduce these uncertainties as much as possible, a representation of the main processes involved in aerosol dynamics and chemistry is necessary. For that purpose, SSH-aerosol was developed to represent the evolution of the mass and number concentrations of primary and secondary particles, across different scales, using state-of-the-art modules, taking into account processes that are usually not considered in air-quality or climate modelling. For example, the particle mixing state and the growth of ultra-fine particles are taken into account in the aerosol dynamics, the affinity of semi-volatile organic compounds with water and viscosity are taken into account in the partitioning between the gas and particle phases of organics and the formation of extremely low-volatility organic compounds from biogenic precursors is represented. SSH-aerosol is modular and can be used with different levels of complexity. It may be used as standalone to analyse chamber measurements. It is also designed to be easily coupled to 3D models, adapting the level of complexity to the spatial scale studied.

In this study, assumptions (ideality and thermodynamic equilibrium) commonly made in three-dimensional (3-D) air quality models were reconsidered to evaluate their impacts on secondary organic aerosol (SOA) formation over Europe. To investigate the effects of non-ideality, dynamic mass transfer and aerosol viscosity on the SOA formation, the Secondary Organic Aerosol Processor (SOAP) model was implemented in the 3-D air quality model Polyphemus. This study presents the first 3-D modeling simulation which describes the impact of aerosol viscosity on the SOA formation. The model uses either the equilibrium approach or the dynamic approach with a method specially designed for 3-D air quality models to efficiently solve particle-phase diffusion when particles are viscous. Sensitivity simulations using two organic aerosol models implemented in Polyphemus to represent mass transfer between gas and particle phases show that the computation of the absorbing aerosol mass strongly influences the SOA formation. In particular, taking into account the concentrations of inorganic aerosols and hydrophilic organic aerosols in the absorbing mass of the aqueous phase increases the average SOA concentration by 5 % and 6 %, respectively. However, inorganic aerosols influence the SOA formation not only because they constitute an absorbing mass for hydrophilic SOA, but also because they interact with organic compounds. Non-ideality (short-, medium- and long-range interactions) was found to influence SOA concentrations by about 30 %. Concerning the dynamic mass transfer for the SOA formation, if the viscosity of SOA is not taken into account and if ideality of aerosols is assumed, the dynamic approach is found to give generally similar results to the equilibrium approach (indicating that equilibrium is an efficient hypothesis for inviscid and ideal aerosols). However, when a non-ideal aerosol is assumed, taking into account the dynamic mass transfer leads to a decrease of concentrations of the hydrophilic compounds (compared to equilibrium). This decrease is due to differences in the values of activity coefficients, which are different between values computed for bulk aerosols and those for each size section. This result indicates the importance of non-ideality on the dynamic evolution of SOA. For viscous aerosols, assuming a highly viscous organic phase leads to an increase in SOA concentrations during daytime (by preventing the evaporation of the most volatile organic compounds). The partitioning of nonvolatile compounds is not affected by viscosity, but the aging of more volatile compounds (that leads to the formation of the less volatile compounds) slows down as the evaporation of those compounds is stopped due to the viscosity of the particle. These results imply that aerosol concentrations may deviate significantly from equilibrium as the gas–particle partitioning could be higher than predicted by equilibrium. Furthermore, although a compound evaporates in the simulation using the equilibrium approach, the same compound can condense in the simulation using the dynamic approach if the particles are viscous. The results of this study emphasize the need for 3-D air quality models to take into account the effect of non-ideality on SOA formation and the effect of aerosol viscosity for the more volatile fraction of semi-volatile organic compounds.

This work aims at quantifying the relative contribution of secondary organic aerosol (SOA) precursors emitted by wildfires to organic aerosol (OA) formation during summer of 2007 over the Euro-Mediterranean region, where intense wildfires occurred. A new SOA formation mechanism, H2Oaro, including recently identified aromatic volatile organic compounds (VOCs) emitted from wildfires, is developed based on smog chamber experiment measurements under low- and high-NOx regimes. The aromatic VOCs included in the mechanism are toluene, xylene, benzene, phenol, cresol, catechol, furan, naphthalene, methylnaphthalene, syringol, guaiacol, and structurally assigned and unassigned compounds with at least six carbon atoms per molecule (USC>6). This mechanism H2Oaro is an extension of the H2O (hydrophilic–hydrophobic organic) aerosol mechanism: the oxidation of the precursor forms surrogate species with specific thermodynamic properties (volatility, oxidation degree and affinity to water). The SOA concentrations over the Euro-Mediterranean region in summer of 2007 are simulated using the chemistry transport model (CTM) Polair3D of the air-quality platform Polyphemus, where the mechanism H2Oaro was implemented. To estimate the relative contribution of the aromatic VOCs, intermediate volatility, semi-volatile and low-volatility organic compounds (I/S/L-VOCs), to wildfires OA concentrations, different estimations of the gaseous I/S/L-VOC emissions (from primary organic aerosol – POA – using a factor of 1.5 or from non-methanic organic gas – NMOG – using a factor of 0.36) and their ageing (one-step oxidation vs. multi-generational oxidation) are also tested in the CTM. Most of the particle OA concentrations are formed from I/S/L-VOCs. On average during the summer of 2007 and over the Euro-Mediterranean domain, they are about 10 times higher than the OA concentrations formed from VOCs. However, locally, the OA concentrations formed from VOCs can represent up to 30 % of the OA concentrations from biomass burning. Amongst the VOCs, the main contributors to SOA formation are phenol, benzene and catechol (CAT; 47 %); USC>6 compounds (23 %); and toluene and xylene (12 %). Sensitivity studies of the influence of the VOCs and the I/S/L-VOC emissions and chemical ageing mechanisms on PM2.5 concentrations show that surface PM2.5 concentrations are more sensitive to the parameterization used for gaseous I/S/L-VOC emissions than for ageing. Estimating the gaseous I/S/L-VOC emissions from POA or from NMOG has a high impact on local surface PM2.5 concentrations (reaching −30 % in the Balkans, −8 % to −16 % in the fire plume and +8 % to +16 % in Greece). Considering the VOC as SOA precursors results in a moderate increase in PM2.5 concentrations mainly in the Balkans (up to 24 %) and in the fire plume (+10 %).

This study examines the uncertainties on air quality modeling associated with the integration of wildfire emissions in chemistry-transport models (CTMs). To do so, aerosol concentrations during the summer of 2007, which was marked by severe fire episodes in the Euro-Mediterranean region especially in the Balkans (20–31 July, 24–30 August 2007) and Greece (24–30 August 2007), are analyzed. Through comparisons to observations from surface networks and satellite remote sensing, we evaluate the abilities of two CTMs, Polyphemus/Polair3D and CHIMERE, to simulate the impact of fires on the regional particulate matter (PM) concentrations and optical properties. During the two main fire events, fire emissions may contribute up to 90 % of surface PM2.5 concentrations in the fire regions (Balkans and Greece), with a significant regional impact associated with long-range transport. Good general performances of the models and a clear improvement of PM2.5 and aerosol optical depth (AOD) are shown when fires are taken into account in the models with high correlation coefficients. Two sources of uncertainties are specifically analyzed in terms of surface PM2.5 concentrations and AOD using sensitivity simulations: secondary organic aerosol (SOA) formation from intermediate and semi-volatile organic compounds (I/S-VOCs) and emissions' injection heights. The analysis highlights that surface PM2.5 concentrations are highly sensitive to injection heights (with a sensitivity that can be as high as 50 % compared to the sensitivity to I/S-VOC emissions which is lower than 30 %). However, AOD which is vertically integrated is less sensitive to the injection heights (mostly below 20 %) but highly sensitive to I/S-VOC emissions (with sensitivity that can be as high as 40 %). The maximum statistical dispersion, which quantifies uncertainties related to fire emission modeling, is up to 75 % for PM2.5 in the Balkans and Greece, and varies between 36 % and 45 % for AOD above fire regions. The simulated number of daily exceedance of World Health Organization (WHO) recommendations for PM2.5 over the considered region reaches 30 days in regions affected by fires and ∼10 days in fire plumes, which is slightly underestimated compared to available observations. The maximum statistical dispersion (σ) on this indicator is also large (with σ reaching 15 days), showing the need for better understanding of the transport and evolution of fire plumes in addition to fire emissions.

International audience; In the framework of ChArMEx (the Chemistry-Aerosol Mediterranean Experiment), the air quality model Polyphemus is used to understand the sources of inorganic and organic particles in the western Mediterranean and evaluate the uncertainties linked to the model parameters (mete-orological fields, anthropogenic and sea-salt emissions and hypotheses related to the model representation of conden-sation/evaporation). The model is evaluated by comparisons to in situ aerosol measurements performed during three consecutive summers (2012, 2013 and 2014). The model-to-measurement comparisons concern the concentrations of PM 10 , PM 1 , organic matter in PM 1 (OM 1) and inorganic aerosol concentrations monitored at a remote site (Ersa) on Corsica Island, as well as airborne measurements performed above the western Mediterranean Sea. Organic particles are mostly from biogenic origin. The model parameterization of sea-salt emissions has been shown to strongly influence the concentrations of all particulate species (PM 10 , PM 1 , OM 1 and inorganic concentrations). Although the emission of organic matter by the sea has been shown to be low, organic concentrations are influenced by sea-salt emissions; this is owing to the fact that they provide a mass onto which gaseous hydrophilic organic compounds can condense. PM 10 , PM 1 , OM 1 are also very sensitive to meteorology, which affects not only the transport of pollutants but also natural emissions (biogenic and sea salt). To avoid large and unrealistic sea-salt concentrations, a parameterization with an adequate wind speed power law is chosen. Sulfate is shown to be strongly influenced by anthropogenic (ship) emissions. PM 10 , PM 1 , OM 1 and sulfate concentrations are better described using the emission inventory with the best spatial description of ship emissions (EDGAR-HTAP). However, this is not true for nitrate, ammonium and chloride concentrations, which are very dependent on the hypotheses used in the model regarding condensation/evaporation. Model simulations show that sea-salt aerosols above the sea are not mixed with background transported aerosols. Taking the mixing state of particles with a dynamic approach to condensation/evaporation into account may be necessary to accurately represent inorganic aerosol concentrations.

This study examines the uncertainties on air quality modeling associated with the integration of wildfire emissions in chemistry-transport models (CTMs). To do so, aerosol concentrations during the summer 2007, which was marked by severe fire episodes in the Euro-Mediterranean region especially in Balkan (20–31 July 2007, 24–30 August 2007) and Greece (24–30 August 2007), are analysed. Through comparisons to observations from surface networks and satellite remote sensing, we evaluate the abilities of two CTMs, Polyphemus/Polair3D and CHIMERE, to simulate the impact of fires on the regional particulate matter (PM) concentrations and optical properties. During the two main fire events, fire emissions may contribute up to 90 % of surface PM2.5 concentrations, with a significant regional impact associated with long-range transport. Good general performances of the models and a clear improvement of PM2.5 and aerosol optical depth (AOD) are shown when fires are taken into account in the models with high correlation coefficients. Two sources of uncertainties are specifically analysed in terms of surface PM concentrations and AOD using sensitivity simulations: secondary organic aerosol (SOA) formation from intermediate and semi-volatile organic compounds (I/S-VOCs) and emissions' injection heights. The analysis highlights that surface PM2.5 concentrations are highly sensitive to injection heights (with a sensitivity that can be as high as 50 % compared to the sensitivity for I/S-VOCs emissions which is lower than 30 %). However, AOD which is vertically integrated is less sensitive to the injection heights (mostly below 20 %), but highly sensitive to I/S-VOCs emissions (with sensitivity that can be as high as 40 %). The maximum dispersion, which quantifies uncertainties related to fire emissions modeling, is up to 75 % for PM2.5 in Balkan and Greece, and varies between 36 and 45 % for AOD above fire regions. The simulated number of daily exceedance of World Health Organization (WHO) recommendations for PM2.5 over the considered region reaches 30 days in regions affected by fires and ∼ 10 days in fire plumes which is slightly underestimated compared to available observations. The maximum dispersion (σ) on this indicator is also large (with σ reaching 15 days), showing the need for better understanding of the transport and evolution of fire plumes in addition to fire emissions.

International audience; Exhaust particle emissions are mostly made of black carbon and/or organic compounds, with some of these organic compounds existing in both the gas and particle phases. Although emissions of volatile organic compounds (VOC) are usually measured at the exhaust, emissions in the gas phase of lower volatility compounds (POAvapor) are not. However, these gas-phase emissions may be oxidised after emission and enhance the formation of secondary organic aerosols (SOA). They are shown here to contribute to most of the SOA formation in Central Paris. POAvapor emissions are usually estimated from primary organic aerosol emissions in the particle phase (POA). However, they could also be estimated from VOC emissions for both gasoline and diesel vehicles using previously published measurements from chamber measurements. Estimating POAvapor from VOC emissions and ageing exhaust emissions with a simple model included in the Polyphemus air-quality platform compare well to measurements of SOA formation performed in chamber experiments. Over Greater Paris, POAvapor emissions estimated using POA and VOC emissions are compared using the HEAVEN bottom-up traffic emissions model. The impact on the simulated atmospheric concentrations is then assessed using the Polyphemus/Polair3D chemistry-transport model. Estimating POAvapor emissions from VOC emissions rather than POA emissions lead to lower emissions along motorway axes (between −50% and −70%) and larger emissions in urban areas (up to between +120% and +140% in Central Paris). The impact on total organic aerosol concentrations (gas plus particle) is lower than the impact on emissions: between −8% and 25% along motorway axes and in urban areas respectively. Particle-phase organic concentrations are lower when POAvapor emissions are estimated from VOC than POA emissions, even in Central Paris where the total organic aerosol concentration is higher, because of different assumptions on the emission volatility distribution, stressing the importance of characterizing not only the emission strength, but also the emission volatility distribution.

International audience; The Mediterranean basin is among one of the areas that can be most sensitive to climate change (Giorgi et al, 2006). This fact, along with the population density around this basin, the high burden in aerosol concentration that the basin experiences throughout the year and the increasing projections for shipping emissions in the future make it an important area to explore. While the organic aerosol can have an important impact on the local and also the regional air quality presently and in the future, the simulation of this aerosol in the western part of the Mediterranean basin is a subject that has not been studied thoroughly for present conditions and has been studied even less for the future. The present work consists of two phases. The first phase explores existing climatic runs performed with CHIMERE chemistry transport model with climate inputs corresponding to RCP2.6, RCP4.5 and RCP8.5 during the French PRIMEQUAL Salut’air project; with a focus on the Mediterranean basin and the changes that these scenarios induce in the concentration of particulate matter and especially organic aerosols. The effects of boundary conditions, and anthropogenic emission changes are assessed. Major driving climate variables affecting organic and fine aerosol levels over the basin are identified. During the second phase, sensitivity runs of the RCP4.5 scenario are performed, in which three different aerosol models are used, including a VBS scheme with and without biogenic aging (Robinson et al. 2007, Lane et al. 2008), and a modified VBS scheme containing fragmentation and formation of non-volatile organic aerosols (Shrivastava et al., 2013). These schemes have been previously compared to measurements obtained during the MISTRAL / CHARMEX summer 2013 campaign (Cholakian, 2017, in preparation). 10 years of historic and years 10 future runs have been performed, and a specific method allows chosing years maximizing the temperature and organic aerosol differences between past and future runs. This allows assessing the climate sensitivity of different organic aerosol schemes. This is a new and complex topic, as organic aerosol formation depends on several parameters (temperature playing on biogenic VOC emissions and phase partition of semi-volatile compounds, winds impacting advection, and precipitation impacting aerosol removal) and their representation in a model.

The Size-Composition Resolved Aerosol Model (SCRAM) for simulating the dynamics of externally mixed atmospheric particles is presented. This new model classifies aerosols by both composition and size, based on a comprehensive combination of all chemical species and their mass-fraction sections. All three main processes involved in aerosol dynamics (coagulation, condensation/evaporation and nucleation) are included. The model is first validated by comparison with a reference solution and with results of simulations using internally mixed particles. The degree of mixing of particles is investigated in a box model simulation using data representative of air pollution in Greater Paris. The relative influence on the mixing state of the different aerosol processes (condensation/evaporation, coagulation) and of the algorithm used to model condensation/evaporation (bulk equilibrium, dynamic) is studied.