Laurent Menut

Bertrand Bessagnet

Augustin Colette

Dmitry Khvorostiyanov

On the impact of the vertical resolution on chemistry transport modelling

This paper presents a sensitivity analysis of the modelling of air pollutant concentrations in the surface layer with the WRF/CHIMERE models. The influence of the vertical resolution near the surface is studied. The simulations are carried out over two periods (winter and summer 2009) over the Paris area. Three model configurations are used: (i) the CHIMERE mesh used for the PREVAIR forecast (8 levels from 995 to 500 hPa), (ii) a mesh refined along the whole vertical axis (20 levels from 995 to 500 hPa) and (iii) a mesh with a refinement near the surface (9 levels from 999 to 500 hPa). The results are discussed in terms of differences on surface concentrations between the reference case and an improved resolution. Adding a point close to the surface appears to be important mainly for high nocturnal concentrations in very stable boundary layers. Refining the vertical mesh, with 20 levels instead of 8, enables to model new structures in the well mixed boundary layer, but with a moderate impact at the surface. It is shown that the different model configurations lead to changes of a few µg/m 3 at most, showing that the vertical mesh is not the most sensitive factor in chemistry-transport modelling when results are compared to surface measurements. This finding validates the fact that a simplified vertical mesh is suitable for air quality forecasting even if an improved vertical resolution close to the ground is important to take into account the urban increment.

Introduction

Albeit the knowledge of pollution sources and meteorology are constantly improved, representing these processes in chemistry transport models (CTM) remains challenging. In particular, the representation of turbulence in the surface layer is difficult and has an important impact on the vertical mixing of meteorological parameters [START_REF] Cionco | High resolution urban morphology data for urban wind flow modeling[END_REF], [START_REF] Kim | Improving ozone modeling in complex terrain at a fine grid resolution: Part I -examination of analysis nudging and all PBL schemes associated with LSMs in meteorological model[END_REF]) and surface emissions [START_REF] Pierce | Dynamic evaluation of a regional air quality model: Assessing the emissions-induced weekly ozone cycle[END_REF]). It influences the whole atmospheric chemical cycle and, in turn, the impact of pollution on human health [START_REF] Imhof | Vertical distribution of aerosol particles and nox close to a motorway[END_REF], [START_REF] Andersson | Population exposure and mortality due to regional background pm in europelong-term simulations of source region and shipping contributions[END_REF], [START_REF] Valari | Using a chemistry transport model to account for the spatial variability of exposureconcentrations in epidemiologic air pollution studies[END_REF]). In order to improve our knowledge of human exposure, it is necessary to improve the representation of pollutants in the boundary layer and more specifically within the first 100 meters above the ground [START_REF] Lin | Impacts of boundary layer mixing on pollutant vertical profiles in the lower troposphere: Implications to satellite remote sensing[END_REF]). This would give more realistic concentrations values where people live i.e. where the major part of primary pollutants are emitted and where air quality networks monitor pollutant concentrations, while models usually give a "mean vertical concentration value" around 20 to 50 m above ground level (agl).

The are various techniques used to retrieve more realistic values near the surface in the litterature.

First, a parameterization can be developped to extrapolate 50 m concentrations (calculated by the CTM) to the surface [START_REF] Byun | Design artifacts in eulerian air quality models: Evaluation of the effects of layer thickness and vertical profile concentration on surface ozone concentrations[END_REF]). In this case, the extrapolation has to take into account the difference between gaseous and particulate species, because of their chemical and physical characteristics and densities, leading to different settling velocities and deposition rates [START_REF] Xiao | On equilibrium profiles of suspended particles[END_REF], [START_REF] Chamecki | Concentration profiles of particles settling in the neutral and stratified atmospheric boundary layer[END_REF]). The challenge consists in building such a parameterization, knowing that pollutant concentrations are exposed to mixing and chemistry [START_REF] Cheinet | A simple formulation for the eddydiffusivity parameterization of cloudtopped boundary layers[END_REF]). There is thus no straightforward technique to extrapolate concentrations values down to the ground, because of the nonlinearities in the vertical profile of the concentration near the ground.

A second way would be to embed a Large Eddy Simulation (LES) or a local dispersion model in the CTM [START_REF] Aristodemou | A comparison of mesh-adaptive LES with wind tunnel data for flow past buildings: Mean flows and velocity fluctuations[END_REF], [START_REF] Garmory | Simulations of the dispersion of reactive pollutants in a street canyon, considering different chemical mechanisms and micromixing[END_REF], [START_REF] Hara | Validation studies of turbulence closure schemes for high resolutions in mesoscale meteorological models -a case of gas dispersion at the local scale[END_REF], [START_REF] Lee | The impact of topography and urban building parameterization on the photochemical ozone concentration of seoul, korea[END_REF], [START_REF] Murena | Modelling dispersion of traffic pollution in a deep street canyon: Application of cfd and operational models[END_REF], [START_REF] Santos | Numerical simulation of flow and dispersion around an isolated cubical building: The effect of the atmospheric stratification[END_REF]. For example, the ADMS-urban [START_REF] Righi | Statistical and diagnostic evaluation of the adms-urban model compared with an urban air quality monitoring network[END_REF]) model is sometimes used for urban pollution applications [START_REF] Davies | Urban air pollution modelling and measurements of boundary layer height[END_REF]). This is certainly the more realistic way in terms of fine turbulence modelling. This method is suitable for complex studies on restricted areas but the methodology is difficult to extend over large domains and not suitable for long term modelling or forecast purposes.

A third technique consists in adding discrete points in the vertical mesh at requested altitudes, or to refine this vertical mesh [START_REF] Byun | Design artifacts in eulerian air quality models: Evaluation of the effects of layer thickness and vertical profile concentration on surface ozone concentrations[END_REF]). The advantage is that the chemical and meteorological behavior of the surface layer are maintained. This is crucial since most sources are emitted near the surface, such as nitrogen oxides emissions due to traffic in urbanised areas. The main goal of this paper is to estimate the impact of (i) increas-ing the number of vertical model levels in the boundary layer, and (ii) changing the first model layer altitude, on pollutant concentrations.

In this study, three model configurations were defined and used to simulate two different periods over the Paris area (January and August 2009). The results are presented in terms of modelled concentrations differences between the configurations and discussed in terms of surface maps and vertical profiles for the usual regulated pollutants: ozone, nitrogen oxides and particulate matter (PM10).

Models configurations

The meteorological model WRF

The regional model used in this study is the Weather Research and Forcasting (WRF) model in its version 3.2.1. This configuration was already used with CHIMERE for many studies such as [START_REF] Colette | Assessing in near real time the impact of the April 2010 Eyjafjallajokull ash plume on air quality[END_REF] and [START_REF] Menut | Evaluation of regional climate simulations for air quality modelling purposes[END_REF], among others. The model is used in its nonhydrostatic configuration. The coarse and fine horizontal domains include 90x70 and 58x58 grid points, respectively with 45km and 15km resolutions. The vertical domain covers 38 levels from the surface to 50 hPa and the integration time step is 40s for the fine domain. For the microphysics, the WRF Single Moment-5 class scheme is used allowing for mixed phase processes and super cooled water, [START_REF] Hong | A revised approach to ice microphysical processes for the bulk parameterization of clouds and precipitation[END_REF]). The radiation scheme is RRTMG scheme with the MCICA method of random cloud overlap, [START_REF] Mlawer | Radiative transfer for inhomogeneous atmosphere: RRTM, a validated correlated k-model for the longwave[END_REF]). The surface layer scheme is based on Monin-Obukhov with Carslon-Boland viscous sub-layer. The surface physics is calculated using the Noah Land Surface Model scheme with four soil temperature and moisture layers, [START_REF] Chen | Coupling an advanced landsurface/hydrology model with the penn state NCARMM5 modeling system. part i: Model implementation and sensitivity[END_REF]). The planetary boundary layer physics is processed using the Yonsei University scheme, [START_REF] Hong | A new vertical diffusion package with an explicit treatment of entrainment processes[END_REF]) and the cumulus parameterization uses the Kain-Fritsch scheme for deep and shallow convection using a mass flux approach with downdrafts and CAPE removal time scale [START_REF] Kain | The Kain-Fritsch convective parameterization: an update[END_REF]).

The chemistry-transport model CHIMERE

CHIMERE is an Eulerian off-line chemistry-transport model (CTM), as such it uses prescribed meteorological fields and emissions. The results presented in this paper were obtained with the 2011a version. Using these meteorological input data and a set of NO x , SO x , NH 3 , PM, VOCs (Volatile Organic Compounds) and CO emissions, CHIMERE calculates the atmospheric concentrations of tens of gas-phase and aerosol species over local to continental domains (from 1 km to 1 degree resolution), and with a hourly output time step. All important chemical and physical processes are taken into account: emissions, transport (advection and mixing), chemistry and deposition. The concentrations fields are calculated for pollution event analysis, scenarios studies and forecasts [START_REF] Menut | Atmospheric composition forecasting in Europe[END_REF]).

The dynamics and gas-phase mechanisms of the model are described in [START_REF] Schmidt | A comparison of simulated and observed ozone mixing ratios for the summer of 1998 in western Europe[END_REF], and improvements have successively been carried over [START_REF] Vautard | On the contribution of natural Aeolian sources to particulate matter concentrations in Europe: testing hypotheses with a modelling approach[END_REF], [START_REF] Bessagnet | Modelling dust emissions and transport within Europe: the Ukraine March 2007 event[END_REF]).

The model documentation can be found on the web server, (www.lmd.polytechnique.fr/chimere).

For both ozone and PM 10 , the model has undergone extensive modelled aerosols intercomparisons at European and city scales [START_REF] Vautard | Boundary layer photochemistry simulated with a two-stream convection scheme[END_REF]; van Loon et al. (2007); [START_REF] Schaap | Evaluation of longterm aerosol simulations from seven air quality models and their ensemble in the eurodelta study[END_REF]). The aerosols model species are sulphates, nitrates, ammonium, secondary organic aerosols, primary particles and sea-salt (see [START_REF] Bessagnet | Impact of dry deposition of semi-volatile organic compounds on secondary organic aerosols[END_REF] for details). The particle size distribution ranges from about 40 nm to 10 µm distributed in 8 bins. The gas-particle partitioning of the ensemble Sulfate/Nitrate/Ammonium is managed by the ISORROPIA scheme [START_REF] Nenes | ISORROPIA: A new thermodynamic model for inorganic multicomponent atmospheric aerosols[END_REF]) implemented in CHIMERE.

The surface emissions account for both anthropogenic and biogenic emissions. The biogenic emissions are diagnosed using the MEGAN model [START_REF] Guenther | Estimates of global terrestrial isoprene emissions using MEGAN (Model of Emissions of Gases and Aerosols from Nature)[END_REF]). The anthropogenic emissions are based on the EMEP inventory and regridded over the specific CHIMERE domain, by reaggregating the chemical species following the gas-phase and particles chemical mechanism used (Menut et al. (2012a)). The simulation domains are centered on the Paris area, as shown in Figure 1 . In order to calculate realistic pollutants concentrations, three different domains are nested and are described in Table 1. The largest domain, IDF45, has an horizontal resolution of 0.5 o × 0.5 o and covers the whole western Europe. It is designed to describe long-range transport of pollutants and provides accurate boundary conditions to the two other domains. The IDF15 domain has a 15km×15km horizontal resolution, it is centered over Paris and covers the northern part of France.

Modelling domains

The domain IDF5, has a 5km×5km horizontal resolution and is located at the center of IDF15. Figure 2 presents the land cover as used by CHIMERE. The city of Paris is considered as 100% urban. This percentage decreases sharply around the city and the suburb represents a circle around Paris with a radius of ≈20km. For the rest of the domain, the region is mainly composed of agricultural lands, and, to a lesser extent, of grassland and forests.

In this paper, the results of the IDF5 domain are analysed, the IDF45 and IDF15 simulations provide exclusively meteorological and chemical boundary conditions to the IDF5 domain.

Landuse

There are currently 9 land use categories in CHIMERE. Those categories are calculated from available global land use databases, which can contain different number of classes. In this version, we used the GlobCover Land Cover database, a global land cover map at 10 arc second (300 meter) resolution [START_REF] Bicheron | Geolocation assessment of 300m resolution MERIS GLOBCOVER ortho-rectified products[END_REF]). It contains 22 global land cover classes defined within the UN Land Cover Classification System (LCCS). The GlobCover database is based on the ENVISAT satellite mission's MERIS sensor (Medium Resolution Image Spectrometer) Level 1B data retrieved in Full Resolution (FR) mode with a spatial resolution of 300 meters. GlobCover LC was derived from an automatic and regionally-tuned classification of a time series of MERIS FR composites covering the period December 2004-June 2006.

Figure 2 [top] presents the domain landuse in each cell and over the Paris area. Over the whole domain, the 'Agricultural land / crops' is the main landuse type, when the center of the domain is fully urbanised with the Paris city.

Vertical meshes

Three vertical meshes are defined for the sensitivity studies performed with the CHIMERE model. The altitudes of the vertical levels are displayed in Table 2. The three model configurations are described hereafter: • C8: Eight vertical levels are defined from 995 to 500 hPa, representing the lower troposphere, and starting with the first vertical point at about 40m above ground level. This corresponds to the operational forecast configuration designed for the PREVAIR system [START_REF] Rouïl | PREV'AIR : an operational forecasting and mapping system for air quality in Europe[END_REF]). This configuration is considered in this study as the reference case. • C20: Twenty vertical levels are defined, also from 995 to 500 hPa. This version is designed to examine the impact of a higher resolution mesh compared to C8. • C9: Nine vertical levels are defined. This is strictly the same as C8 but adding one point near the surface located at 999 hPa. This configuration aims at quantifying the variability in the surface concentrations results by adding a point near the surface which would be more representative of measurements.

Label

Altitude of levels tops (m) WRF30 27; 93; 153; 298; 443; 627; 852; 1157; 1531; 1918; 2320; 2910; 3690; 4485; 5273; 6050; 6850; 7640; 8420; 9200; 10010; 11700; 12600; 13480; 14420; 15370; 16400; 17400; 18500; 19700 C8 40; 108; 226; 431; 790; 1438; 2654; 5191 C9 8; 40; 108; 226; 431; 790; 1438; 2654; 5191 C20 40; 86; 139; 200; 271; 353; 448; 559; 687; 836; 1012; 1216; 1457; 1741; 2075; 2479; 2967; 3558; 4278; 5191 Table 2: Top layers altitudes in meters for the WRF meteorological model (30 levels) and for the three CHIMERE configurations: C8 (8 levels), C9 (9 levels) and C20 (20 levels).

The results will be presented in terms of differences in modelled concentrations fields compared to surface measurements. The following behaviours are expected for the three configurations:

• The C8 and C20 vertical meshes have the same first level point. The only difference is that C20 has more discrete values in the boundary layer (the number of points in the boundary layer is not constant since it depends on the boundary layer height). By difference between C8 and C20 concentrations fields, the results will quantify the impact of a vertical refinement and thus the impact of the accuracy of meteorological vertical gradients within the boundary layer. • The C8 and C9 vertical meshes have the same vertical mesh, but C9 has an additional point near the surface.

In this case, the mixing and transport within the surface layer would have the same behaviour, but with C9 the model will calculate explicitly a more realistic value at the ground level.

In the next sections, results will be presented either as absolute values for each of the three configurations, or as differences: in that case the C8 configuration is considered as the reference because it is used in operational forecast mode in the PREVAIR system, [START_REF] Rouïl | PREV'AIR : an operational forecasting and mapping system for air quality in Europe[END_REF], [START_REF] Honoré | Predictability of European air quality: The assessment of three years of operational forecasts and analyses by the PREV'AIR system[END_REF], [START_REF] Menut | Atmospheric composition forecasting in Europe[END_REF].

Estimation of turbulent parameters

CHIMERE offers the possibility to use either diagnostic available variables from meteorological drivers or diagnose some meteorological variables in the pre-processing step. In this study, the latter option is selected in order to use the same turbulent parameterizations and also to be consistent with the CHIMERE model configuration used in the PREVAIR system [START_REF] Rouïl | PREV'AIR : an operational forecasting and mapping system for air quality in Europe[END_REF]). The full WRF vertical resolution is used to diagnose the vertical turbulent diffusivity K z and the boundary layer height h. After this evaluation, the diagnosed profiles of K z are averaged over the CHIMERE vertical grid in the same way as all others meteorological parameters. It is during this final vertical averaging that the number of vertical levels used by the CHIMERE model are changed.

The following variables are calculated: the friction velocity u * , the surface sensible heat flux Q 0 , the vertical convective velocity w * , the boundary layer height h, the Monin-Obukhov length L and the vertical diffusivity profile K z .

The friction velocity u * is used for deposition and the calculation of diffusivities. It is a particularly sensitive parameter for ozone in summer through the calculation of aerodynamic resistance r a . It depends strongly on land use types which are critical to deposition. In large scale meteorological models, roughness lengths are sometimes too coarse and cannot be applied for high-resolution deposition. Recomputing u * as proposed by [START_REF] Louis | A short history of the PBL parametrization at ECMWF[END_REF] gives satisfactory results. In addition it yields a deposition that is consistent with the high-resolution land use.

u * = C 2 DN F m |u(z)| 2 (1)
where F m is the [START_REF] Louis | A short history of the PBL parametrization at ECMWF[END_REF] stability function, z the height above ground level where the meteorological data are available (in our case z=10m). C DN the neutral drag coefficient as:

C DN = k ln z + z 0m z 0m (2)
with k=0.41, the Karman constant. z 0m is the dynamical roughness length (in meters) and values are tabulated for each landuse type. F m is the momentum stability function and is estimated depending on the bulk Richardson number value. Under stable cases (if R ib < 0):

F m = 1 - 2bR ib 1 + 3bcC 2 DN . z + z 0m z 0m |R ib | (3)
and under unstable cases (if R ib > 0):

F m = 1 1 + 2bR ib √ 1 + dR ib (4) with the constant b = c = d = 5. Under neutral case, i.e R ib = 0, F m =1.
The bulk Richardson number is estimated as:

R ib (z) = g z θ v (z) ∆θ v ∆|U | 2 (5) with ∆θ v = θ v (z) -θ v (z 0 ), ∆|U | = |U |(z).
Heat fluxes are used for the calculation of w * (and therefore the vertical mixing), and the height of the boundary layer. Only the virtual heat flux is required, which can be recalculated from an empirical formula [START_REF] Priestley | Heat transport and zonal stress between latitudes[END_REF] using temperatures in the first meteorological model layers. Because of uncertainties in the later formula, it is strongly advised to use the heat fluxes of the meteorological model if available. If the surface sensible heat fluxes Q 0 are provided by the meteorological model, they are directly used for the calculation of the convective velocity w * :

w * = gQ 0 h ρC p θ v 1/3 (6)
where g=9.81 m 2 .s -2 , Q 0 is the surface sensible heat flux, h is the convective boundary layer height, C p is the specific heat of air at constant pressure, θ v is the mean virtual potential temperature representative of the surface layer.

The Monin-Obhukov length is estimated as:

L = -θ v u 3 * kgQ 0 (7)
The boundary layer height (h) differs for stable and unstable conditions. Under stable conditions, i.e when L > 0, h is estimated as the altitude where the Richardson number reaches a critial number here chosen as R ic = 0.5, following [START_REF] Troen | A simple model of the atmospheric boundary layer: Sensitivity to surface evaporation[END_REF].

Under unstable (i.e convective) conditions, h is also chosen as the altitude where R i = R ic , including the influence of boundary layer convective clouds. The latter is based on a simplified and diagnostic version of the approach of [START_REF] Cheinet | A simple formulation for the eddydiffusivity parameterization of cloudtopped boundary layers[END_REF]. It consists in the resolution of the (dry) thermal plume equation with diffusion. The in-plume vertical velocity and buoyancy equations are solved and the boundary layer is taken as the height where the vertical velocity stops. Thermals are initiated with a non-vanishing vertical velocity and potential temperature departure, depending on the turbulence similarity parameters in the surface layer.

A usual approximation for CTMs, considered as numerically diffusive, is to neglect the horizontal turbulent fluxes. Vertical turbulent mixing takes place only in the boundary-layer. The formulation uses K-diffusion following the parameterization of [START_REF] Troen | A simple model of the atmospheric boundary layer: Sensitivity to surface evaporation[END_REF], with no counter-gradient term. In each model column, the diffusivity K z (m 2 /s) is calculated as:

K z = kw s z h 1 - z h 2 (8)
In this equation, w s is a vertical scale given by similar formulas:

• In the stable case (when the surface sensible heat flux is negative):

w s = u * (1 + 4.7z/L) (9)
• In the unstable case:

w s = (u 3 * + 2.8 e w 3 * ) 1/3 (10)
where e = max(0.1, z/h). A minimal K(z) is assumed, with a value of 0.01 m 2 /s in the dry boundary layer and of 1 m 2 /s in the cloudy boundary layer. In the boundary layer, a maximal value of K z =500 m 2 /s is used to avoid unrealistic mixing. Above the boundary layer, a fixed value of K z =0.1 m 2 /s is prescribed. The results in this study are presented for the 1-31 January and 1-31 August 2009 periods. These periods consist of one winter and one summer month over the Paris area, in order to cover several meteorological situations leading to pollution events in this region. These periods were selected for the following reasons: (i) they correspond to "classical" meteorological situations leading to normal pollution episodes; (ii) no precipitations were recorded, leading to a more robust analysis of the modelled vertical mixing of pollutants, (iii) in the two cases, pollution events were reported by the local air quality networks. Time series of meteorological parameters such as 2m temperature, boundary layer height and 10m wind speed are presented in Figure 3 . These parameters correspond to the meteorological parameters used by the CHIMERE model. They are fully independent from the vertical resolution chosen for the chemistry-transport modelling. The boundary layer heights are very different between January and August: the diurnal cycle is rather low during January when values quickly evolve during the daytime in August. In January, the mean values are ≈ 400m, and maximal values of ≈ 1500m are observed between the 15 and 22 January. In August, the boundary layer top is always between 1500 and 2500m. The 2m temperature also exhibits low diurnal cycles during January and a high daily amplitude in August. The mean values are ≈ 0 and 23 o C for January and August, respectively. In summer, the nocturnal values are relatively low (from 10 to 15 o C). The 10m wind speed is low in August, with a mean value of ≈ 3m/s favourable to stagnation and, thus, photochemical pollution episodes. During winter, the 10m wind speed may rapidly change, from very low wind periods (e.g. 8 January) to high surface wind speed days (e.g. 16, 18, 22 January). These high wind speed values of mid-January explain the high boundary layer height diagnosed for that period.

Pollutant concentrations

The first model level concentrations maps are displayed in Figure 4 for NO 2 , PM 10 and O 3 (in µg/m 3 ). The model configuration considered as the reference case is the C8 simulation [START_REF] Honoré | Predictability of European air quality: The assessment of three years of operational forecasts and analyses by the PREV'AIR system[END_REF]). The maps represent monthly average concentrations over January and August 2009. Even if absolute values are different between summer and winter, the regional patterns are similar for the three pollutants O 3 , NO 2 and PM 10 . The Paris area is at the center of the domain and exhibits the major source of primay pollutants such as PM 10 and NO 2 . The limited spread around the city correspond to the mean concentrations transported a few kilometers out of the city center, and each pattern represents the mean wind direction during each month.

For both periods, the maximum values of NO 2 and PM 10 are observed over Paris, characterised by the most important anthropogenic emissions fluxes. Due to fast chemical reactions (mainly titration), Paris is also the location of the lowest surface ozone values: ≈ 20 µg/m 3 in January and ≈ 70 µg/m 3 in August.

Around Paris, background values are homogeneous and lower, averaging the potential ozone plumes and the background concentrations (local biogenic production or longrange transport, [START_REF] Menut | Measurements and modelling of atmospheric pollution over the Paris area: an overview of the ESQUIF Project[END_REF], [START_REF] Derognat | Effect of biogenic voc emissions on the tropospheric chemistry during elevated ozone periods in ile de france[END_REF]). The main differences are observed for ozone, the background averaged values are ≈ 40-50 µg/m 3 in winter and ≈ 70-80 µg/m 3 in summer.

Impact of a higher vertical resolution

Monthly averaged surface concentrations

The comparisons are presented for the differences (C20-C8) and (C9-C8), for the three studied pollutants, O 3 , NO 2 and PM 10 , and for January and August 2009. Results are displayed in Figure 5 and for the first vertical level only: it represents the "surface" concentrations i.e the mean value between the ground and the top layer altitude. Such concentrations are the values usually compared to the air quality measurements stations. For (C20-C8), the model configurations have the same first vertical level but not the same vertical resolution. A direct comparison between the first model level horizontal fields gives the direct impact of an increased vertical resolution. For (C9-C8), the first vertical levels are not at the same altitude above ground level: 8 and 40m respectively. It shows the potential improvement of adding a lower first level close to the observations (i.e usually ≈3m).

Globally, the maps represent surface concentrations and not surface emissions. The most important emissions are located in the Paris city center (the center of the modelled domain). Due to horizontal transport and chemistry, the main differences are observed (i) in the south-west of Paris during January and August 2009 , due the meteorology during this period. Thus, the most important impact appears to be in the suburb but has to be directly rely to the changes in the Paris city center.

For NO 2 surface concentrations ( Figure 5 , left), the differences are very low and never exceed ±3 µg/m 3 . In January, the main negative differences (i.e. C8 > C20) are observed in the center of the Paris area, while the main differences of positive sign are observed at the border of the domain. For the same period, the contrary is observed for (C9-C8), more logically directly linked to the fact that the compared vertical levels are different and that the NO 2 concentrations are always more important near the surface due to traffic emissions. In August, the (C20-C8) values are close to zero due to the photochemistry for the same vertical level and close to the ground. But some non negligible values may be observed with (C9-C8), with higher values for C9, for the same reason than during January.

For PM 10 surface concentrations, the differences are larger and C20 shows concentrations higher by +0.5 to +2 µg/m 3 all over the domain in August and January, respectively. The differences are spatially more homogeneous over the domain for PM 10 than for NO 2 . The main components of PM 10 are a primary anthropogenic fraction and a secondary biogenic origin.

For O 3 concentrations, the differences are always negative, so that C8 > C20 over the whole domain. For January and August, the differences range is -3 to -1 µg/m 3 . The differences are not spatially homogeneous and have to be directly related to the spatial patterns observed for NO 2 over the main source of the Paris city. The O 3 deposition in the C9 simulations is enhanced over forested areas, lower concentrations are simulated compare to the reference simulation C8.

For the three pollutants, the differences reach on average ±3 µg/m 3 . For PM 10 and O 3 , Figure 5 clearly shows that refining the whole vertical mesh has a large scale impact, while adding one level near the surface has a more variable impact at the local scale depending on emissions and landuses.

Vertical cross sections

In this section, the analysis focussed on the vertical structure. Vertical time series are displayed to estimate the impact of the different vertical meshes on the whole troposphere concentrations. Two examples are chosen: the vertical profiles of PM 10 during winter (January 2009, Figure 6 , left panel) and ozone during summer (August 2009, Figure 6 , right panel). As for all following results, the modelled concentrations are extracted from the model cell the most affected by the anthropogenic emissions, the Paris city center (longitude 2.35 o W and latitude 48.86 o N).

The comparison is purposely limited to a qualitative discussion. Since the vertical resolution is different, a quantification would require to interpolate the pollutant concentrations at identical altitudes. This interpolation process at such low native resolution would generate more differences than the differences observed between the three models configurations. Therefore, the results are thus just qualitatively discussed in this section.

The vertical PM 10 profiles showed that the largest concentrations are simulated close to the surface, due to anthropogenic emissions. During the month of January 2009, the most important concentrations are observed during the first two and the last weeks. The lowest concentrations are observed during the period of 14 to 22 January 2009, being those when the highest boundary layer height and 10m wind speed values are modelled ( Figure 3 ): surface concentrations are vertically mixed and/or advected out of the modelled domain. The impact of C20 appears clearly around the 20th of January, when a concentration of ≈ 20 µg/m 3 is modelled between 800 and 1000m, but not with C8 and C9. The same type of structure, only modelled by C20, is also observed on January, 27 between 900 and 1000m.

The vertical profiles of ozone are different, ozone has always larger concentrations in the upper boundary layer than near the surface, when fast titration by NO x occurs. The C20 configuration shows that the vertical gradients are more pronounced than for C8 and C9, mainly around 3000m, at the top of the boundary layer. But, on average, the most important vertical structures are modelled and the number of vertical levels does not seem to impact much the behaviour of ozone in the boundary layer. The most important differences are observed up to 4000m, showing that a finer resolution has an impact on the representation of long-range transport.

The comparison of vertical profiles for the three configurations showed that C20 is able to model ozone and PM 10 in the boundary layer with differences up to 10 to 20 µg/m 3 . These differences are often above the boundary layer and are related to long-range transport rather than local production. This feature shows that the vertical refinement has a moderate impact on surface concentrations.

Analysis of monthly mean vertical profiles

In order to better evaluate the impact of the vertical resolution on concentrations profiles, the concentrations displayed in Figure 6 are averaged on a monthly basis and presented for each model configuration in Figure 7 . The upper panel presents K z vertical profiles for two hours, 06:00 UTC and 15:00 UTC. For 06:00 UTC, for example, this means that all profiles of January and August at 06:00 UTC are averaged to obtain one profile for each month, representative of this specific hour. For O 3 and NO 2 pollutants, all hourly profiles of the month are averaged.

The K z profiles show different shapes and magnitudes between 06:00 and 15:00 UTC. At 06:00 UTC, before the convective period, the values of diffusivity are low and do not exceed 30 and 70 m 2 /s, at ≈ 300m and 1000m, in January and August, respectively. The shape of the profile is noisy because of the day to day variability. Note that the standard deviation was not found as a relevant information here, its values being of the same order of magnitude as the mean profiles. The K z values are more important during summer than the winter, and may reach up to 160 m 2 /s in August at 15:00 UTC, for a mean altitude of 1000m. For all times and periods, the most important differences are in the lowest layer in the C9 simulation, showing that the extra point close to the surface generates a very low mixing (K z < 2 m 2 /s), whilst the two other simulations always display minimum values between 5 and 10 m 2 /s.

The NO 2 profiles show maximum values close to the surface, where emissions take place. The differences between C8 and C20 are rather low, as previously showed with the horizontal maps in Figure 5 . The differences between C9 and the two other configurations are important, the concentrations gradually increase close to the ground. This leads to an increase of NO 2 concentrations of ≈ 1 µg/m 3 in January and ≈ 3 µg/m 3 August 2009.

For ozone, concentrations usually increase with altitude. This leads to lower values near the surface with C9. The differences are very low and never exceed a few µg/m 3 compared to C8 and C20. Up to 40m, the C8 and C9 profiles are similar and show large differences comparted to the C20 profile. The C20 concentrations are lower between 40m and 1500m, but higher up to 1500m. The same impact is observed on the January profile, but with an inversion of differences around 700m. This feature reflects the impact of a refined vertical transport, between the boundary layer and the free troposphere.

The monthly mean concentrations profiles showed that the C8 and C9 configurations have the same values down to 40m. The additional point with C9, around 8m above groud level, appears as an extrapolation of the upper profile. This leads to higher primary pollutants (here NO 2 ) and lower ozone concentrations at the first model vertical level. However, differences remain low and an additional extrapolation to 1 or 2m above ground level would not give large variations in surface time series of pollutants. In order to quantify the impact of K z on surface concentrations, the simulations are compared by ranking the concentrations differences, (C20-C8) and (C9-C8), as a function of the corresponding value of surface K z (during August 2009). The surface K z values are discretised into regular bins of 1 m 2 /s step. For each K z bin, the corresponding (C20-C8) and (C9-C8) hourly concentrations are averaged. The result gives an indication about the surface K z value for which the most important concentrations differences are obtained. The results are displayed in Figure 8 , for O 3 , NO 2 and PM 10 .

Sensitivity to the vertical mixing

For ozone concentrations, the (C20-C8) and (C9-C8) differences for the two months are always negative in low K z conditions. The differences do not exceed -5 µg/m 3 . This means that in case of low mixing, adding a point near the surface or increasing the vertical resolution tends to have lower surface ozone concentrations. For higher K z values, between 10 and 16 m 2 /s, the differences turn positive and larger (up to 25 µg/m 3 for the (C20-C8) and during January 2009. In the case of ozone, when the vertical diffusivity is high, during convective conditions, there is a competition between an enhanced titration close to the surface and an import of ozone coming from the upper layers. The large variability observed for ozone is not diagnosed for NO 2 and PM 10 . The distributions are relatively flat and tend to show that the differences between the model configurations are not really sensitive to the mixing values near the surface.

For NO 2 , the values of differences are mainly positive, on average between 0 and +2 µg/m 3 , showing that C9 and C20 tends to increase NO 2 concentrations compared to the reference run C8. Negative values are only observed for very low mixing (K z < 1 m 2 /s) and for the C20 configuration. In this case, the refined vertical meshes gives lower NO 2 , but with moderate differences (with a maximum of -1.5 µg/m 3 ).

For PM 10 , the differences are always close to zero between C8 and C9. For this primary/secondary pollutant, whatever the K z value, i.e the stability conditions, there is a competition effect between chemistry and dynamics, that explains this feature. The chemistry leads to negative differences (as for ozone) and the dynamics to negative differences (as for NO 2 ). The differences are higher between C8 and C20, with values up to +3µg/m 3 , showing that an increase of the vertical resolution will increase surface PM 10 concentrations.

Model to data comparison

In the previous sections, the impact of a change in the vertical resolution was discussed by comparing various model configurations. Here we evaluate whether these changes give better modelled results when compared to measurements. These comparisons are performed thanks to the measurements issued from the local air quality network operating over the Paris area (AIRPARIF). Hourly measurements are used to evaluate the day to day variability and the change of diurnal cycles in the various model configurations.

Surface time series

Many previous studies have been carried out regarding the comparison of modelled surface concentrations with CHIMERE in the Paris area: the ESQUIF experiment [START_REF] Menut | Measurements and modelling of atmospheric pollution over the Paris area: an overview of the ESQUIF Project[END_REF], through the routine validation of the PREVAIR forecast system [START_REF] Rouïl | PREV'AIR : an operational forecasting and mapping system for air quality in Europe[END_REF] or the sensitivity study of the horizontal resolution [START_REF] Valari | Does increase in air quality models resolution bring surface ozone concentrations closer to reality[END_REF]. It was shown that CHIMERE can accurately simulate and forecast ozone and NO 2 concentrations. Since the goal of this paper is not to discuss again the model validation but to evaluate its sensitivity to the vertical resolution, this section does not contain a full quantitative performance analysis but more a qualitative discussion of a change in the horizontal resolution and K z values on modelled pollutant concentrations.

Figure 9 displays time series at the first vertical model level of the turbulent diffusivity coefficient, K z , ozone and nitrogen dioxides concentrations. In order to focus on diurnal cycle changes, time series are restricted to the time period between the 13 and 21 August 2009, representative of a large day to day variability. The comparisons are done between the Paris grid cell for the model and the AIRPARIF network measurements, for the NO 2 et O 3 measurements data.

Figure 9 (top) shows the time series of K z for the three configurations, C8, C20 and C9 and with a log scale along the y axe in order to have a focus on low values. Having the same first vertical level, the values for C8 and C20 are exactly the same: the diurnal variability ranges from 0.1 to 2 m 2 /s during the night (stable conditions) to 15-20 m 2 /s during the afternoon (fully convective conditions). For C9, the same kind of diurnal variability is observed but with lower values, between 0.1 and 4 m 2 /s. For all configurations, very low K z values are diagnosed for the nights of 14-15, 15-16 and 19-20 August 2009. The minimum K z of 0.1 m 2 /s is reached for C8 and C20, but not for C9 (with higher values, 0.2 m 2 /s for the same time).

The comparison between modelled and measured NO 2 concentrations ( Figure 9 (middle)) shows that the period is well modelled except (i) for the night of 15-16 August when the model overestimates the concentrations and, the period from 19 to 20 August, when the model underestimates the concentrations. In general, the most important NO 2 surface concentrations are modelled during the night and the morning when the K z are the lowest. But, the fact that some K z were very low in the model has no a systematic impact on surface concentrations: for the night of 15-16 August, the NO 2 overestimation can be attributed to the very low corresponding K z values. This is not the case for the night of 19-20 August when the model underestimates the NO 2 while K z values are also very low.

For ozone ( Figure 9 (bottom)), the day to day variability is well captured by the model, and the major daily peaks are well captured. The main differences between the three configurations occur during the night, when the K z differ. This is the case of the 15-16 August night, when the modelled ozone concentrations tends to zero while the observations are about 50µg/m 3 . This is a direct impact of the low K z values, producing a low mixing and thus overestimating NO 2 concentrations and O 3 titration. For night of 19-20 August, the underestimation of NO 2 concentration leads to non-zero ozone concentrations while the observations are close to zero.

The analysis of surface concentrations time series shows that the main impact of the vertical resolution occurs at night, when K z is very low and similar to the minimum value imposed in the model. These low values may induce very large overestimation of primary species such as NO 2 , and in turn an underestimation of nocturnal ozone.

Even if the change of the vertical resolution involves differences in modelled surface concentrations, these differences remain low compared to the differences between model and measurements. It appears obvious that the change in vertical resolution or the height of the first vertical level is not the most sensitive parameter in the modelling system even if refining the vertical mesh has a significan beneficial impact.

Diurnal cycles and comparisons to observations

In order to have an overview of the main differences, diurnal cycles are calculated for the whole months of January and August 2009. Cycles are calculated for ozone, NO 2 and PM 10 for the three model configurations and for the corresponding surface measurements in the center of Paris. The same cycles were also calculated for other locations in the Paris area and similar behaviors were observed: the discussion is thus focusing on the Paris station.

The model tends to overestimate ozone concentrations, and underestimate NO 2 and PM 10 concentrations. The correlation is good, and the main differences are related to a near-constant bias during the whole day. The most important differences occur during winter, when the boundary layer is less convective and with a lower boundary layer height. The C9 model configuration gives modelled concentrations closer to the measurements than C8 and C20. But the differences between the different model configurations are not so large compared to the differences with the measurements. The most important impact of C9 is for ozone and during summer, reducing the overestimation of the peaks during the afternoon.

Discussion and conclusion

This study is dedicated to an evaluation of the impact of different vertical resolutions in modelling near surface concentrations. The 'reference' vertical mesh was defined as the mesh used for the PREVAIR forecast platform using CHIMERE: 8 vertical levels, called C8, ranging from 995 hPa (≈40m above ground level) to 500 hPa (≈ 5000m agl). Two other meshes were defined: one with the same pressure boundaries (995 to 500 hPa), but with 20 vertical levels (called C20); and one with exactly the same 8 levels, but with an additional level close to the surface, at 999 hPa (≈8m above ground level), called C9.

The quantification of the impact of these different meshes was done by comparing directly the simulations amongst themselves as well as against surface measurements. The domain is the Paris area and the periods studied were chosen to be different in terms of pollution events: the whole month of January 2009 for NO 2 and PM 10 pollution, and the whole month of August 2009 for photochemical pollution with ozone, O 3 .

Based on monthly averaged maps, it was shown that the differences between C8 and C20 never exceed 3 µg/m 3 during winter and summer and over the whole area. The patterns of differences are mostly related to the main surface emissions sources, here the Paris city, and are slightly spatially shifted of a few kilometers, showing the main wind regimes over the region and the transport of pollutants. In average, a refined mesh (C20) tends to give more NO 2 and PM 10 and less ozone than C8. Vertically, C20 is able to capture finer structures, both for gases (O 3 ) and particles (PM 10 ). These vertical structures have no significant impact on the surface concentrations. The comparison of averaged vertical profiles of vertical diffusivity K z and pollutants showed that the differences between C8, C20 and C9 are low.

Adding a new point near the surface (C9 simulation) leads to concentrations that are more representative of the height of surface stations measurements. But the differences between C8 and C9 are moderate and cannot fully explain the differences between the model and measurements.

Distributions are calculated to discriminate the concentrations differences as a function of K z values. Globally, there is no clear signal and the differences seems to be relatively independent of the diffusivity values, except for NO 2 and the lowest K z values (between 0.1 and 1 m 2 /s) and for ozone in case of strong surface diffusivity (i.e K z ≈ 15 m 2 /s).

Comparisons with surface measurements were performed as time series and diurnal cycles. The main differences between the model and measurements were observed at night, when the vertical diffusivity shows very low values. But this feature is not systematic and, for some cases, low K z are not the reason for large model to observations differences. The diurnal cycles show an overestimation of surface ozone concentrations and an underestimation of NO 2 and PM 10 . But for the three vertical meshes, none is able to sufficiently unbias the model.

Finally, it was shown that different vertical meshes may change of a few µg/m 3 the modelled surface concentrations over a large urbanised area such as Paris. This variability is much smaller than the differences between measurements and predicted values. Changing the vertical mesh may be more realistic in specific cases: high concentrated ozone layers in the boundary layer, nocturnal concentrations of gas and particles in case of very stable nocturnal boundary layers.

The C8 configuration correspond to the one used in the PREVAIR operational system. We thus showed that the differences when using a refined mesh (C20) or a mesh with a point closest to the surface (C9) are low. This means that results of the C8 operational forecast are not due primarily to the vertical mesh definition.

However, the interest to add a point closest to the surface (C9) has been shown and this correspond to modify the 'urban increment' roughly defined as the difference between the city and background concentrations. This expected change is due to the conbined effects of (i) higher deposition rates in remote areas (over vegetative covers) and (ii) higher (or lower for ozone) concentrations over emission areas. The background values seems to be more affected by a change of the whole vertical resolution (simulation C20). This study was conducted over an highly urbanised area, known to be poorly represented in terms of sub-grid scale dynamical processes. While the first layer of C8 and C20 (40m) is more related to the buildings top heights, C9 (8m) is representative of the urban canopy layer and this should be expressed in the vertical mixing representation. Actually, this is not the case in the current CHIMERE version and has certainly to be improved in future model developments.

Figure 1 :

 1 Figure 1: Model simulations domains used for WRF meteorological model and CHIMERE chemistry-transport model.

Figure 2 :

 2 Figure 2: [top] Landuse map for the Paris region: for each cell the dominant landuse is drawed. The color code corresponds to: 1 Agricultural land / crops, 2. grassland, 3. barren land, 4. inland water, 5. urban, 6 shrubs, 7 needleaf forest, 8 broadleaf forest, 9 ocean. [bottom] the relative percentage [0:1] of the first sector, Agricultural land and crops.

  3. Overview of the two periods 3.1. Meteorological conditions Boundary layer height (m) 2m temperature (C) 10m wind speed (m/s)

Figure 3 :

 3 Figure 3: Times series of the mean meteorological parameters for the period of January and August 2009 at the center of the domain: Paris.

  C8 monthly averaged surface concentrations NO 2 (µg/m 3 ) -January 2009 PM 10 (µg/m 3 ) -January 2009 O 3 (µg/m 3 ) -January 2009 NO 2 (µg/m 3 ) -August 2009 PM 10 (µg/m 3 ) -August 2009 O 3 (µg/m 3 ) -August 2009

Figure 4 :

 4 Figure 4: Maps of monthly mean averaged surface concentrations for NO 2 , PM 10 and O 3 , and for the months of January and August 2009.

Figure 8 :

 8 Figure 8: Distributions of concentrations differences as a function of the Kz first model level values. The Kz profiles being different between the model configurations, the C20 configuration was used here for the distributions calculations.

Figure 9 :

 9 Figure 9: Example of times series of vertical turbulent diffusivity, ozone, O 3 , and nitrogen dioxide, NO 2 , at the first vertical level and during August 2009. Measurements and modelled concentrations represent the Paris center.

Figure 10 :

 10 Figure 10: Diurnal cycles for surface concentrations of ozone, NO 2 and PM 10 , January and August 2009 for Paris.

Figure 6 :

 6 Figure 6: Vertical cross section of [left] PM 10 concentrations (µg/m 3 ) for January 2009 and [right] O 3 concentrations (µg/m 3 ) for August 2009.

Figure 7 :

 7 Figure 7: Vertical profiles of Kz, NO 2 and O 3 , for January and August 2009 over Paris. The profiles are averaged for each month of January and August 2009 using only 06:00 and 15:00 UTC for Kz, and all day hours for NO 2 and O 3 .

Table 1 :

 1 Model domains set-up as displayed in Figure 1 . The WRF model uses a Lambert projection and CHIMERE a Lambert conformal projection

	Domain IDF45	Nx × Ny ∆x × ∆y
	WRF CHIMERE 68 × 50 72 × 54 IDF15	45km ×45km 0.5 o × 0.5 o
	WRF CHIMERE 45 × 48 49 × 52 IDF5	15km ×15km 0.2 o × 0.133 o
	WRF CHIMERE 38 × 35 46 × 49	5km × 5km 0.07 o × 0.05 o

Acknowledgments

This study was partly funded by the french Ministry in charge of Environment. This work was done under the auspices of the European project EC4MACS (EU LIFE, www.ec4macs.eu).


B R Mili

Olivier L C Le Bihan
email: olivier.le-bihan@ineris.fr

C Dutouquet

O Aguerre-Charriol

E Frejafon

Verneuil En

Particle Sampling by TEM Grid Filtration

Transmission electron microscopy (TEM) coupled with energy dispersive X-ray (EDX) offers a very comprehensive tool for individual particle analysis allowing the determination of size, morphology, specific surface, and elemental composition. This information is needed in aerosol studies, especially in the field of nanomaterials. However, observations with TEM require a controlled sampling on an adapted analysis support, namely TEM grid. Techniques allowing sampling on TEM grids are of great interest to aerosol analysis. Indeed, sample preparation is not required, thereby gaining time and avoiding a risk for the sample to be altered.

Free mean flow of gas molecules kinematic fluid viscosity (cm 2 /s)

The present study evaluates the efficiency of a new particle collection technique based on filtration through one class of TEM dedicated supports, namely TEM porous grids.

Two types of porous grids, considered as the best on the market for this application, have been put to the test: the "Quantifoil" type porous grid which has a regular structure, and the "Holey" type (Agar Scientific). A filter holder has been developed specifically for this application, the MPS ® ("Mini-Particle Sampler" ® ).

Experimental tests have been carried out with a flow rate of 0.3 l.min -1 . They show that the collection is operational in the 5 nm -150 nm size range with a minimum efficiency of 15-18% around 30 nm. Simulation confirms these results and shows an increased efficiency even below 5 nm and beyond 150 nm.

The filter holder MPS ® designed in this study is a low cost, portable versatile and easy to use tool.

APPENDIX

Introduction

The characterization of the physical and chemical properties of aerosols is a recurrent need in numerous studies and research projects conducted in occupational health, atmospheric chemistry and physics, stack emissions, etc.

This need is particularly felt in studies on the risk associated with nanomaterials (NM), as it is necessary to be able to distinguish particles related to NM from those of the background (urban background, other nearby sources, etc.).

Transmission electronic microscopy (TEM) coupled with the analysis by Energy Dispersive X-ray (EDX) is part of the techniques responding to this need for characterisation as it allows the physical, chemical, morphological and individual analysis of the particles deposited on a support adapted to it, to be specific, a TEM grid. This is the reason that many studies have been conducted for many years to enable the effective deposit of particles directly on this specific support so as to eliminate an additional sample preparation procedure. It is important to emphasise the fact that, at this stage, it is a qualitative, not a quantitative approach.

The TEM grids available on the market are round metallic grids (copper, nickel, gold or molybdenum), approx. 3 mm in diameter, divided into several hundred squares (Figure 1).

They are generally provided with a fine, translucent electron beam membrane a few nanometres thick (often a carbon membrane) which allows the contrast of particles deposited on their surface to be viewed. These grids exist on the market under many categories and net size, according to their applications (Agar scientific ® ).

The sampling techniques utilizing TEM grids available today are various. Some are based on the phenomenon of diffusion [START_REF] Tsai | Airborne nanoparticle exposures associated with the manual handling of nanoalumina and nanosilver in fume hoods[END_REF], [START_REF] Cena | A Personal Nanoparticle Respiratory Deposition (NRD) Sampler[END_REF]), thermophoresis [START_REF] Lyyränen | A size selective nanoparticle collection device based on diffusion and thermophoresis[END_REF]), electrostatic precipitation (Dikens & Fissan (1999), [START_REF] Fierz | Theoretical and experimental evaluation of a portable electrostatic TEM sampler[END_REF], [START_REF] Li | Determining ultrafine particle collection efficiency in a nanometer aerosol sampler[END_REF][START_REF] Miller | A handheld electrostatic precipitator for sampling airborne particles and nanoparticles[END_REF]), etc.

The sampling technique with TEM grids proposed by [START_REF] Lyyränen | A size selective nanoparticle collection device based on diffusion and thermophoresis[END_REF] called APS-EM (ASPiration EM grid sampler), consisting of using a porous membrane TEM grid (see Figure 1) to sample particles by filtration is also noted.

Following feasibility studies conducted in a laboratory, this last technique has been applied by R'mili et al. (2011) during a characterisation study of particles emitted during manipulation of carbon nano-tubes (CNT) powders. It was also applied by [START_REF] Fleury | Identification of the main exposure scenarios in the production of CNT-polymer nanocomposites by melt-moulding process[END_REF] during a characterisation study of a work environment around an extruder manufacturing composite granules (polymer-CNT), and by Bouillard et al. (2010) to characterize exhaust from a combustion system. These studies have shown that the filtration technique with porous TEM grids allows the sampling of various types of particles (varied in size, shape, etc.), both in the laboratory and in the field. From a practical perspective, the technique has turned out to be easy to use, economical and portable; samples validated for microscopy analysis may be produced with collection times ranging from a few minutes to 30 minutes, depending on application. It is important to note that this technique has turned out to be easier to use than a sampling system by electrostatic precipitation which is more cumbersome and requires prior electrical charge of particles.

As these tests in realistic conditions are convincing it has seemed necessary to accurately evaluate the collection efficiency of this technique is --especially as regards the diameter of the particles--, and to identify the mechanisms of filtration. Moreover, it has seemed important to develop a TEM grid holder that is as versatile as possible and particularly one that connects easily to sampling lines and size selection systems (e.g. pre-impactors, differential mobility analysers (DMA)).

The study presented here covers the evaluation of the collection efficiency of the two main grids available on the market, adapted to the filtration sampling technique through porous TEM grids. It implements a versatile TEM grid holder developed specifically for this application, the MPS ® ("Mini-Particle Sampler" ® ).

Materials and method

TEM porous grids

Three types of porous membrane TEM grids are available on the market: "Lacey", "Holey", and "Quantifoil", each with a different carbon structure. The Lacey type has very large holes (a few micrometres in diameter), the "Holey" type has smaller holes, and the "Quantifoil" type has holes generally calibrated in diameter, evenly spaced and uniformly distributed.

For this study, we have selected a "Holey" type grid (Figure 1-b) and a "Quantifoil" type grid (Figure 1-c), both fitted with a 400 "mesh" grid (Figure 1 In this reference, 1.2 represents the hole diameter in micrometres, and 1.3 the distance between holes.

These two TEM grids have been selected for two main reasons. On the one side, their hole diameter, the smallest of all porous carbon membrane TEM grids which can be found on the market, promotes effective sampling. On the other, their grid (400 mesh) which is the most important. Indeed, on a weaker grid, the carbon membrane will present a more important surface to the air flow and thus risk to yield under the pressure induced by this flow during sampling.

MPS ® sampling system

Called MPS ® (Mini-Particle Sampler ® ), the sampling system developed in this study appears as a TEM grid holder measuring 12 cm x 1.5 cm. It is comprised of two connectors, a male and a female (Figure 2). A TEM grid and a copper joint (the copper joint ensures good air tightness -ref.

: Hole Grid Cu 2000µm, Agar Scientific, external diameter = 3.05 mm, internal diameter = 2 mm) are respectively placed on the male connector on a support adapted to their size. The female connector is designed to be attached to the male connector and also to keep the TEM grid and joint on their support. By aspiration, the air flow goes through the female connector and the porous TEM grid used via the holes of its membrane and leaves the system via the male connector.

Unlike the device used by [START_REF] Lyyränen | A size selective nanoparticle collection device based on diffusion and thermophoresis[END_REF], the MPS ® is fitted with a tube upstream of the TEM grid, which allows the connection with an equipment (instrument, reactor, etc.).

This particular feature, on the other hand, has made it easier to evaluate the collection efficiency of the porous TEM grid used in his study, as the device could be connected directly to a mono-dispersed aerosol source (see section 2.4).

Method

The capacity of a filter or membrane to collect particles is characterized by the collection efficiency E, determined by [START_REF] Hinds | Aerosol Technology -Properties, Behaviour and measurement of Airborne Particles[END_REF]):

(1) with, P t the penetration (also called penetrating fraction) represents the fraction of particles that goes through the filter medium and is given by:

(2)

where, N Up and N Dw represent respectively the concentration in number of particles upstream and downstream of the filtering medium.

The determination of the working method was based on the works of [START_REF] Heim | Filtration efficiency of aerosol particles below 20 nanometers[END_REF].

These works take into account several methods of assessing the efficacy of a filtering medium, available in the literature.

In certain approaches, the upstream and downstream filter concentration is measured by two different particle counters, which requires the use of a correction factor to take into account the counters' own intrinsic differences. Certain approaches avoid this constraint by using a single counter.

It is also interesting to set aside the losses by deposition due to the filter holder, in order to focus on the losses due to the filtering medium only. This may be done for example by setting up two devices in parallel: one fitted with filtering medium, the other one not.

From these observations, the method carried out for this study has been based on a single counter and has been focused on the TEM grid efficiency

The selected method is based on the use of a monodisperse aerosol, neutralised, stable over time for the duration of approximately 15 minutes. To ensure counting, a single counter is placed downstream of the filter holder, namely the MPS ® . The test comprises of three stages:

the second stage fitted with a filtering medium whereas the first and the third ones are not.

Each step lasts approximately 2.5 minutes and produces a result in the form of a total number concentration. These steps are separated by a pause of approximately 2 minutes, required for the removal and installation of the TEM grid.

The validation of the data is based on an aerosol stability criterion which rests on a maximum concentration difference of 5% between the results of the first and last step.

The tests have been conducted for a 0.3 l.min -1 flow rate within the MPS ® . This value is recommended by [START_REF] Lyyränen | A size selective nanoparticle collection device based on diffusion and thermophoresis[END_REF] in order to avoid the deterioration of the cabon membrane of the TEM grid studied. This value was also selected based upon previous experiments (e.g. R"mili (2011), Bouillard (2010), [START_REF] Fleury | Identification of the main exposure scenarios in the production of CNT-polymer nanocomposites by melt-moulding process[END_REF]); this flow rate requires collection times of a few minutes and is compatible with different applications (measurement in the workplace, in room air, etc.) and microscopy needs (non agglomeration of particles on the sampling surface).

Collection efficiency is calculated on the basis of the ratio of the concentration with (N stage2 )

and without (N stage1 ) the TEM grid. Thus Eq. (2) becomes:

(3)

This process has been repeated three times for each diameter and composition of particles in order to have an average efficiency and a standard deviation (cf. Table 2).

Experimental set-up

The experimental set-up is shown in Figure 3.

An atomiser (TSI, model 3076) followed by a dryer has been used to generate polydisperse sodium chloride (NaCl) aerosol from solutions of NaCl concentration of approximately 0.01 g/l. This configuration has allowed the creation in a stable manner over time of a NaCl aerosol in a range of sizes between approximately 15 and 200 nm.

The range of sizes between approximately 5 nm and 15 nm has been considered thanks to a copper aerosol produced by a spark type generator [START_REF] Schwyn | Aerosol generation by spark discharge[END_REF] -GFG-1000 palas ® ), technique which has been demonstrated [START_REF] Roth | Generation of ultrafine particles by spark discharging[END_REF], [START_REF] Evans | The generation and characterization of metallic and mixed element aerosols for human challenge studies[END_REF]) that it can generate metallic aerosols in a stable manner with an average diameter of approximately 10 to 30 nm.

For both sources, a platform (TSI, model 3080), fitted with a Nano-DMA column (TSI, model 3085) was used for size selection. By using this platform, NaCl aerosol particles were monodispersed between 15 and 150 nm and copper aerosol particles between 5 and 20 nm.

The monodisperse aerosol thus produced has been neutralised by a radioactive source (Krypton 85).

Measurement of the number concentration at the outlet of the MPS ® collector was determined using a CNC (TSI, model 3775).

Theory

The TEM grids selected in this study are comparable to a microporous membrane. Given their geometric characteristics, the "capillary tube model" was chosen [START_REF] Rubow | Characteristics of membrane filters for particle collection in fluid filtration[END_REF], an approach started by J. Pich (1964). This model consists in assimilating the structure of a microporous membrane to a group of capillary holes, with the same section, uniformly distributed, equally distant, and perpendicular to its surface in a way as to consider the system (flow of carrier fluid and behaviour of particles) starting from a unitary hole.

The collection efficiency by filtration of a membrane depends on many physical mechanisms.

In the absence of any external field of energy other than gravity, the most important ones are inertial impaction, interception and Brownian diffusion ((K. L. [START_REF] Rubow | Characteristics of membrane filters for particle collection in fluid filtration[END_REF]). The existing theoretical models are generally formulated starting from the expressions of efficiency of each of these mechanisms supposed to act independently from each other.

It is essential to take into account the potential role of the thickness of the filtering media:

Cyrs et al. ( 2010) have noted the predominant character of this parameter for membranes which are only 10 µm thick. In the case of the selected TEM grids, the carbon membrane is of a particularly low thickness (L< 20 nm). This allows the hypothesis that the deposit of particles in the internal walls of the holes is negligible, indeed, non-existent. In this case, it's solely a surface deposit. As a result, our theoretical approach consists in considering only expressions of the fraction of surface deposit, that is, by impaction, by interception and by surface diffusion.

As for the capillary tube model, the microporous carbon membrane of a TEM grid may be characterised by a characteristic hole diameter D 0 a surface hole density (number of holes per surface unit) and a porosity P. The latter parameter represents the fraction of the total membrane surface occupied by the opening of the holes. It may be given by the following equation (adapted from [START_REF] Manton | The impaction of aerosols on a nucleopore filter[END_REF][START_REF] Manton | Brownian diffusion of aerosols to the face of a nuclepore filter[END_REF]:

(4)
where, is the area occupied by the opening of a beam hole .

The unitary hole (Figure 4) may be considered as a ring of the internal beam R 0 and of the external beam R e . The latter is given by the following equation (adapted from [START_REF] Manton | The impaction of aerosols on a nucleopore filter[END_REF][START_REF] Manton | Brownian diffusion of aerosols to the face of a nuclepore filter[END_REF]):

(5)

The flow of carrier fluid may be characterised by the noted frontal velocity U 0 . It is the speed at which the carrying fluid approaches the membrane. It depends on the geometry of the filter holder of the flowrate of the sampling Q. As the MPS ® is a cylinder tube with a section S, the frontal velocity may be obtained by the following equation:

(6)
Moreover, the existing theoretical expressions are developed based on an approach according to which the flow of the carrying fluid as it approaches a hole is considered like the flow into the cylinder tube of a beam R e (Figure 4). As the latter is generally of the order of micrometers, the flow is supposed to be laminar in the Stokes' regime, i.e., with a low Reynolds number (Re < 1). In fact, this allows a simplification of the system studied.

Reynolds number is given in this case by the following equation:

(7)
where, is the kinematic fluid viscosity ( ≈ 0.15 cm 2 /s for air).

Thus, the collection efficiency (E Im ) due to inertial impaction takes on the following expression (Pich (1964)):

(8) with,

-E Im the collection efficiency due to the impaction mechanism, -: a parameter that takes into account membrane porosity and is expressed as:

an impaction parameter given by: (10)

-Stokes Stk number is expressed:

(11)

The Cunningham correction factor takes into account the discontinuity of the medium and is expressed: , Knudsen's number, is a dimensionless number defined as the relationship between the free mean flow of gas molecules carrying and the physical diameter of the particle , and is expressed:

(13)

In the case of the collection efficiency by filtration due to interception (E In ), many expressions have been proposed [START_REF] Spurny | Aerosol filtration by means of Nuclepore filters: structural and filtration properties[END_REF], T. N. [START_REF] Smith | Diffusive collection of aerosol particles on Nuclepore membrane filter[END_REF], [START_REF] Smith | Inertial collection of aerosol particles at circular aperture[END_REF], Happel and Berner (1973), W. John and G. [START_REF] Reischl | Anomalous filtration of solid particles by Nuclepore filters[END_REF], [START_REF] Marre | Theoretical study of aerosol filtration by nucleopore filters: the intermediate crossover regime of brownian diffusion and direct interception[END_REF])

out of which the one proposed by John and G. [START_REF] Reischl | Anomalous filtration of solid particles by Nuclepore filters[END_REF] has been considered the most appropriate in case of a porous TEM grid:

(14) with a dimensionless interception parameter given by For collection efficiency due to Brownian diffusion, most of these existing models only take into account transfers by particle diffusion toward the internal walls of the holes [START_REF] Twomey | Equations for the decay of diffusion of particles in an aerosol flowing through circular and rectangular channels[END_REF], [START_REF] Gormley | Diffusion from a stream flowing through a cylindrical tube[END_REF], [START_REF] Marre | Theoretical study of aerosol filtration by nucleopore filters: the intermediate crossover regime of brownian diffusion and direct interception[END_REF][START_REF] Marre | Modeling of submicrometer aerosol penetration through sintered granular membrane filters[END_REF]). This assumes that the transfers by particle diffusion toward the membrane surface are negligible. However, [START_REF] Smith | Diffusive collection of aerosol particles on Nuclepore membrane filter[END_REF] and recently [START_REF] Cyrs | Nanoparticle collection efficiency of capillary pore membrane filters[END_REF] have shown that these transfers may also be very important. [START_REF] Manton | Brownian diffusion of aerosols to the face of a nuclepore filter[END_REF] had already studied the issue and proposed an expression to this effect; yet he did not consider it to be satisfying, putting forth a likely problem at the level of definition of the diffusion parameter. It actually happens that this expression does not agree with the experimental results of this study, as it does not agree with the results obtained by [START_REF] Kirsch | Gas flow in Nuclepore filters[END_REF], [START_REF] Liu | Efficiency of membrane and nuclepore filters for submicrometer aerosols[END_REF] and [START_REF] Smith | Diffusive collection of aerosol particles on Nuclepore membrane filter[END_REF],

As a result, it has been necessary to search for different approach. Specifically, this work

proposes an adaptation of the model developed by [START_REF] Stechkina | Studies on fibrous aerosol filters -I. Calculation of diffusional deposition of aerosols in fibrous filters[END_REF], Kirsch and Fuchs (1969) starting from Kuwabara's cell flow model Kuwabara ( 1959):

(15) where ( , represents the solid fraction of the membrane,

In fact, in our case represents Péclet's number related to the characteristic hole diameter D 0 of the membrane.

In the absence of interactions of streamline flows in the inter-pore space, the total fraction of the penetrating particles is equal to the product of penetration efficiency attributed to each mechanism. Therefore, the total collection efficiency can be expressed as [START_REF] Hinds | Aerosol Technology -Properties, Behaviour and measurement of Airborne Particles[END_REF]):

(16)

Characteristics of grids and flow

To use the above models, the following is required:

1. To characterise the structure of the TEM grids examined by determining the following parameters: the characteristic hole diameter of membrane D 0, the surface density of holes N 0 (number of holes per surface unit) and membrane porosity P. These parameters are required for the calculations.

2. Verify that the flow of carrying fluid when it approaches a hole is laminar, in the Stokes' regime, in which case the above expressions are valid.

Characteristics of TEM grids examined

The characteristics of the TEM grids selected have been determined experimentally by processing images taken by TEM with the help of a library of algorithms integrated to an image processing software (Visilog ® ).

Table 1 collects the characteristics recorded on a dozen grids, for each of the two types of TEM grids studied.

One may notice that the characteristic parameters of "Quantifoil 1.2/1.3" TEM grids do not change between grids. The same does not apply to "Holey" TEM grids, whose characteristic parameters may differ between grids and sometimes significantly.

Nature of carrier fluid flow

On the one side, the TEM grid is placed within a cylinder measuring 2 mm in diameter (Figure 2). On the other, the flowrate selected for this study is 0.3 l/min (see 2.3). This parametering makes the mean fluid velocity in this conduit rise to 1.6 m/s (Equation 6). This velocity is considered in our case as the frontal velocity of the carrying fluid U 0 (see. Section 3).

In the capillary tube model, the carrying fluid flow when it approaches a hole of the membrane is considered as being a flow into a cylinder beam tube R e (equation 5). Its nature is given by the Reynolds number (equation 7). In our case and according to the characteristics of the TEM grids studied, the values obtained are presented in Table 1.

As Re is <1, the flow is therefore laminar, in the Stokes" regime. The above models would therefore be valid in our conditions (sampling flowrate, geometry of sampling systems and characteristics of the two TEM grids studied).

Results

Figures 5 and 6 present the collection efficiency of TEM grids "Quantifoil 1.2/1.3" and "Holey", respectively, data also available in Table 2. In both cases, the values presented are an average of results of at least three tests.

A theoretical estimate is also presented for both cases of grids. In the case of "Holey" grids, three theoretical curves are proposed according to hole diameter: the high curve and the low curve corresponding to the extreme diameter values (high and low respectively) shown in

Table 1; the central simulation (solid line) corresponds to the average diameter.

For both types of grid, a very good theory-experiment convergence is observed, on the entire 5 nm -150 nm range. A minimum collection efficiency is obtained for particles with a diameter between 20 and 40 nm (diameter of electrical mobility).

This minimum efficiency is evaluated at approximately 15% for "Quantifoil 1.2/1.3" type grids and approximately 18% for "Holey" type grids. This diameter range corresponds, in our conditions (sampling speed equal to 1.6 m/s and characteristics of TEM grids studied), to the particles least sensitive to the different collection mechanisms.

The collection efficiency of both TEM grids is all the more important as the diameter of the particles reaches the area 20 -40 nm, simultaneously toward the higher or lower diameters.

In the case of "Quantifoil 1.2/1.3", the relative standard deviation of the experiment remains lower than or equal to 10%, which shows a very good reproducibility of the collection system (Table 2).

In the case of "Holey" grids (Table 2), the relative standard deviation of the experiment is less satisfying, between 5 and 15%. This would be due to the main difference existing between both types of grid, in particular the shape and diameter of the holes. Indeed, if the "Quantifoil" type has holes of constant shape and size (see. Figure 1-c), this is not the case for the "Holey" type, which shows a significant variation of the shape (see. Figure 1-b) and size of its holes (see. Table 1). Figure 6 shows the simulations obtained for the extreme values of the diameter: the difference between them in absolute values varies from 10% toward 30 nm, up to 30% at 150 nm.

Whatever the grid, the total collection efficiency turns out to be more important than by electrostatic precipitator, which, not mathematically corrected, is lower than 1% [START_REF] Li | Determining ultrafine particle collection efficiency in a nanometer aerosol sampler[END_REF], [START_REF] Bau | Experimental measurement of the collection efficiency of nanoparticle samplers based on electrostatic and thermophoretic precipitation[END_REF], Le [START_REF] Bihan | Assessment of the sampling efficiency of an electrostatic precipitator[END_REF]. Indeed, in this system, the surface of the TEM grid represents only a very minor part of the totality of particles collected on the surface deposition (electrode).

Behaviour of particles

This part lies only on the "Quantifoil 1.2/1.3" TEM grid, on account of its well defined structure (shape and size of holes) and reduced standard deviation (< 10%) obtained in the experimental section of the study.

Figure 7 shows experimental results as well as a theoretical estimate obtained for the collection efficiency with a "Quantifoil 1.2/1.3" TEM grid. The theoretical estimate distinguishes the impact of different collection mechanisms, i.e., inertial impaction, interception and diffusion.

The simulation shows that impaction and diffusion are the prevailing mechanisms, with impaction dominating the collection of particles above 30 nm, and diffusion dominating the collection of particles under 30 nm. The contribution of the interception mechanism to the collection only becomes significant for the particles whose diameter is above 200 nm.

This interpretation seems to be confirmed by observations of the grids studied by TEM (Figure 8) for which, it may be noted that most of the particles collected seems to be deposited on the surface of the membrane.

Moreover, it should be noted that the general appearance and dimensions of collection efficiency observed here show strong similarities with the experimental results obtained by [START_REF] Cyrs | Nanoparticle collection efficiency of capillary pore membrane filters[END_REF] for the surface collection efficiency, despite a relatively different membrane porosity and frontal velocity.

.

Conclusion and perspectives

Filtration on porous TEM grid is a new particle sampling technique in view of an analysis by transmission electron microscopy.

A TEM grid holder has been especially developed to allow the implementation of this technique in the simplest, fastest, and most versatile manner possible: it is the MPS ® (Mini-Particle Sampler ® ).

The study described here on the implementation of this filtration technique, with the help of MPS ® and both market products most often adapted today, in particular Quantifoil TEM

(1.2/1.3) and Holey TEM porous TEM grids.

The collection efficiency of these two grids has been tested experimentally on a generation bed of mono-dispersed copper and sodium chloride aerosol. Tests show that the collection is operational in the 5 nm -150 nm size range, with a minimum efficiency around 30 nm of 15-18%.

The collection efficiency has also been simulated, by relying on the studies done on porous membrane. The results obtained are consistent with the experimental results and show the prevailing character of the mechanisms of diffusional deposition by diffusion, under 30 nm and of impaction deposition, above 30 nm.

The simulation shows an increased efficiency around the small and large sizes.

This study shows therefore the validity of the filtration concept by porous TEM grid.

This technique is particularly simple when compared with other TEM grid collection techniques. Indeed, in addition to a filter holder and a pump, most of these techniques must implement supplementary and energy consuming tools with the aim of having an active element such as an electric field or a thermal gradient.

The modest size of the filter holder makes it a very good tool for individual collections (R"mili (2011), Fleury (2010)). It could also be easily integrated in experimental devices:

measurement downstream of a DMA, collection at reactor outlet (Bouillard ( 2010)), etc.

The filter holder designed in this study is now commercially available as a low cost, portable and easy to use tool.

8.

They also thank Laurence Le Coq, Aurélien Zantman, Emmanuel Peyret, Sophie Mary, Neeraj Shandilya, Aurélien Ustache and Christophe Bressot for their support.

  , c are experimentally determined coefficients. Numerous values are attributed to these coefficients. For this study, we have considered those proposed by Kim et al. (2005): a = 1.165, b = 0.483 and c = 0.997, determined with the help of a nano-DMA.

Figure 1 :

 1 Figure 1: examples of TEM porous grids -case of a "Holey" type and "Quantifoil" type

Figure 4 :

 4 Figure 4: characteristics of a unitary hole

Figure 6 :

 6 Figure6: Particle collection efficiency by size for the Holey TEM grid. The theoretical collection efficiency has been calculated using the parameters related to the operation conditions and characteristics of the TEM grid (cf. Table1).

Figure 7 :

 7 Figure 7: Comparison of experimental and theoretical approaches to assessing collection efficiency of the Quantifoil 1.2/1.3 TEM grid.

Figure 8 :

 8 Figure 8: Examples TEM images of NaCl and Cu collected particles from a polydisperse aerosol.

Table 1

 1 ).

			Experimental points (NaCl)	Experimental points (Cu)	Theory
	100%
	Collection efficiency (%)	30% 40% 50% 60% 70% 80% 90%
		20%
		10%
		0%
		1	10	100	1000
			Diameter(nm)

  Table 1).

		Experimental points (NaCl)	Experimental points (Cu)
		Theory		theoritical limit
		90%
		80%
	Collection efficiency (%)	20% 30% 40% 50% 60% 70%
		10%
		0%
		1	10	100	1000
			Diameter (nm)

Table 1 :

 1 Structural characteristics of the Quantifoil 1.2/1.3TEM grid 400 mesh carbon membrane and of the Holey membrane. The characteristic parameters of "Holey" TEM grids are given indicatively, as they concern only the grids used in this study. The Reynolds number is calculated according to the characteristics of the two TEM grids studied for a sampling speed U 0 = 1.6 m/s. domain of recorded average hole diameters. The actual recorded hole diameters are between approximately 0.15 and 5 µm **according to supplier D 0 = 1.2 µm and for measurements for TEM D 0 = 1.3 µm is found

	Characteristic parameters	Holey	Quantifoil 1.2/1.3
	Pore diameter D 0 (µm)	0.8 -1.6*	1.3**
	Density of pores	(# /cm 2 )	2,9.10 7 -1,1.10 8	1,3.10 7
	Porosity P (%)		40 -65	17
	Re (Equation 7)		0.05 -0.11	0.16

*

Table 2 :

 2 Measured overall collection efficiencies for each mean diameter of mono-disperse aerosol and each porous grid.

			Holey		Quantifoil
	Particle		Overall	Standard	Overall	Standard
	diameter		collection	deviation	collection	deviation
	(nm)		efficiency (%)	(%)	efficiency	(%)
					(%)
	5	Cu	74	12	70	10
	6	Cu	62	9	56	9
	7	Cu	54	8	42	8
	8	Cu	47	7	32	7
	10	Cu	36	6	23	6
	20	Cu	19	8	16	8
	15	NaCl	18	6	17	4
	20	NaCl	19	4	15	4
	30	NaCl	21	4	15	3
	40	NaCl	24	5	16	3
	50	NaCl	26	5	17	3
	60	NaCl	28	7	20	3
	80	NaCl	33	8	27	3
	100	NaCl	35	11	34	4
	150	NaCl	44	15	49	5

Acknowledgement

The authors thank the Picardy region and the Ministry for the Environment (programme 190) for their financial support.