References

F. Lasserre, G. Cautenet, C. Bouet, X. Dong, Y. J. Kim, N. Sugimoto, I. Matsui, and A. Shimizu Laboratoire de Météorologie Physique, Université Blaise Pascal, Complexe scientifique des Cézeaux, BP 45, 63170, Aubière, France Sino-Japan Friendship Center for Environmental Protection, Beijing 100029, China Advanced Environment Monitoring Research Center, Department of Environmental Science and Engineering, Gwangju Institute of Science and Technology, 1 Oryong-dong, Gwangju 500-712, Korea 4 National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan


Introduction
Anthropogenic pollution is a permanent element of the climate over Asian megalopolis 20 and surrounding countries. Moreover, these areas are also subject to natural pollutions from mineral origin, when a dust desert storm occurs (Sun et al., 2001). Thus, mainly at spring, aerosols plumes from natural and anthropogenic origins can coexist over northern China, Korea and Japan. According to , mesoscale simulations of heterogeneous reactions in the boundary layer show an average decrease of al. (2005) provided microscopic analyses and chemical characterization of the mineral dust and particles containing sulphur elements. These analyses detailed the extreme difficulty of the "inversion" work which consists in seeking the weather conditions, as Relative Humidity (RH) and cloud cover, for conversion of SO 2 gas into sulphur products. It is also true for carbonaceous soot mixed with mineral dust: see, for example, and anthropogenic aerosol schemes (sources/sinks), as described in Sects. 2.2, 2.3 and 2.4.
The model grid is centered on (40 N, 108 E) and extends (with stereopolar projection) from (26 N, 79 E), to (45 N, 145 E). There are 235 gripoints in longitude and 95 in latitude, with a grid size of 25 km. In the vertical, we have 30 levels, from surface to about 15 22 km in expanding size (including 10 vertical steps from surface to about 1.2 km). The simulation begins on 25 April 2005 (00:00 UTC) in order to give 48 h for the fields' initialization. The time step used in calculation is 10 s. This low value is necessary for the numerical stability due to the presence of severe reliefs (Tibet and Pamir) in the South and West of the modelled zone. Simulation is carried out on 64 paralleled processors 20 and needs approximately 30 h in CPU.

Desert dust processing
As regards desert dust, the aerosol flux is provided by the Dust Production Model (hereafter referred to as DPM) developed by Marticorena and Bergametti (1995), Marticorena et al. (1997a, b) and by Alfaro et al. (1998), Alfaro and Gomes (2001). In this grid point, the DPM calculates the amount of mobilized dust, which is redistributed in the first model levels. We use a spectral representation, i.e. the dust mass flux is redistributed over 20 size classes (20 discrete bins) with radius values ranging from 0.1 µm to 13 µm. The spectrum has three lognormal mass components with radii: 0.75 µm, 3.35 µm and 7.1 µm, and logarithmic standard deviations 1.7, 1.6 and 1.5. 20 The respective weights of each mode in the initial spectrum, i.e. during the dust rise and before any deposition, are governed by the available kinetic energy of the saltating aggregates (Alfaro et al., 1998;Alfaro and Gomes, 2001). The mineral aerosol density is assumed to be 2650 kg m −3 (Marticorena and Bergametti, 1995). Each dust class is then diffused by turbulence, advected in the three dimensions and deposited by gravity 25 (dry removal) or by wet removal. For all these processes except removal, we have used the built-in "inert tracer" facility of RAMS: this scheme provides advection and diffusion of any passive scalar.
The coupling of the dust scheme with RAMS is described in Cautenet et al. (2000), Introduction

Anthropogenic particles inventories 2.3.1 Sulphur particles and black carbons in East Asia area
We voluntary limit the list of the anthropogenic pollutants to only two major chemical families: (i) the main sulphur compounds, that is sulphur dioxide SO 2 and its deriva-5 tive products as gaseous H 2 SO 4 and sulphate ions SO 2− 4 (e.g. ammonium sulphates), all species thereafter referred to as "sulphates"; (ii) carbonaceous soots of all forms, members of the BC family.
Nitrogen oxides are reputed as major anthropogenic urban pollutants. However, for our approach, we don't consider them because of their short life time inside the 10 free troposphere before being caught by atmospheric moisture (Kunhikrishnan et al., 2004). Moreover, their contribution to the total AOT is weak compared to those of the absorbing BC and the scattering sulphates (Trijonis et al., 1990;Watson et al., 2001;Reddy et al., 2005).
70% of the Chinese power needs are provided by combustion of poor quality coal 15 (inclosing up to 5% sulphur) which generates considerable amounts of atmospheric SO 2 . For the year 2000, Chinese government statistics evaluate at 20 Mt the country SO 2 emissions, with 85% directly linked with coal combustion (Yang et al., 2002). Such sulphur pollution severely impacts on the public health and contributes to the acid rain process, the consequences of which concern more than 30% of China. Introduction

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The BC mass production is by far less than the acidic pollutant mass emission. Thus, with Wang (2004), we agree with a minor role of the BC on the global temperature trend. On a regional scale however, as suggested by this author and the scientific community, BC becomes a major actor of the local radiative budget and the local meteorological dynamics. BC aerosol strongly absorbs the solar wavelengths. 5 Consequently, BC increases the temperature of its atmospheric layer and decreases, on the same time, the surface solar radiation. The heated air makes the air surrounding more unstable, creating a favourable ascending convection, in particular in China, with the formation of clouds which, in turn, are likely to produce precipitations on the strongly polluted areas. This situation is observed in China but the opposite situation (desaturation of the layer and subsequent inhibition of the formation of the clouds) can be observed on the Indian sub-continent (Minvielle, 2003). To sum up, the BC has complex radiative effects (direct and semi-direct). Besides, these effects are associated with the indirect effects of other pollutants like sulphates causing, for example, an average reduction of 5% of the droplets radii and an increase in same percentage 15 of the cloud water (Kristjánsson, 2002). The ascending polluted and wet air above coastal China tends to be balanced by subsidences of dry air in the North, what contributes to desertification of this part of China. These last years, the North of China suffered from frequent sandstorms, whereas southcoastal China underwent precipitations in increased quantities. Menon et al. (2002) see in the anthropogenic emissions 20 of absorbing pollutants the principal cause of these regional climatic tendencies. Wu et al. (2004) quantified this double climatic impact in China, detailing how the Southern areas are more and more subject to rains reinforced by the BC and coupling this phenomenon with the drying of the Northern air masses. In term of direct effect, they calculated a maximum cooling of 1.5 K (Minvielle et al., 2004a, b). We again use these databases. For SO 2, we use the EDGAR database (Emission Database for Global Atmospheric Research) available on http://www.mnp.nl/edgar/model/edgarv32/ 5 acidifying/ (Olivier et al., 1996). For BC emissions, we use the GEIA database Global Emissions Inventory Activity) on http://www.geiacenter.org/ (with all references). EDGAR database shows strong emissions of SO 2 around central China (South of the studied zone) as, for example, around Shangaï. A set of urban centres, roughly included inside a (32 N-37 N; 110 E-118 E) zone, give a annual average of SO 2 emis-10 sion higher than 0.75×10 −9 kg m −2 s −1 . The area between Dalian and Shenyang, in the North of the Bohai Sea, a zone of intense activity with industries and power plants, is estimated to be strongly emissive. In South Korea, Seoul is characterized by EDGAR as a very emissing place, just like the industrial port of Pusan in the South of the country. 15 Main BC emission areas are found at the same locations than SO 2 emitting zones: the principal urban centres and places of industrial activities, mining productions and power plants.
2.4 A simple physico-chemical approach 2.4.1 Sulphur to sulphate conversion 20 We suppose that sulphur emissions are SO 2 gas emissions. After being injected within the RAMS first level, sulphur mass will be ruled according to the processes illustrated in Fig. 3. Even if the major part of SO 2 remains "free", we model the part which is coated (adsorbed) onto the mineral aerosol . The one chemical conversion explicitly considered in our model is SO 2 into H 2 SO 4 (gas conversion ] is the SO 2 mass converted into sulphates every time step. The 1.5 coefficient accounts for the molar mass ratio. Note that the rates of dry transformation of SO 2 into SO 2− 4 derived from the literature range over more than one order of magnitude. For example, Cox (1974) estimates this rate at 1∼10% per hour in an urban plume. Eliassen and Salt-10 bones (1975) estimate a rate of transformation of approximately 0.7% per hour. The evaluation by Alkezweeny and Powell (1977) from airborne measurements is about 10 to 12% per hour, in an atmosphere which can contain more water than the preceding studies. The MICS-ASIA working group (Carmichael et al., 2001)  conversion is close to 1.10 −5 s −1 , which corresponds to a transformation of 60% per day. Obviously, the implied processes are not only gas phase processes. Especialy, Carmichael et al. (2001), note that the predictions show disparities in the results of concentrations of both SO 2 and sulphates. For China, concentrations estimates easily 20 vary with a factor of 10 from one model to another.

Anthropogenic aerosols deposits
The dry deposit of the sulphur compounds (except for those captured by dust, Sect. 2.4.3) is treated in a way similar to that recommended by Carmichael et al. (2001) in their modellings within MICS-ASIA. Models are particularly sensitive to the direct ra- 25 tio between the wet deposit of sulphates and precipitations on the one hand, and the estimate of the dry deposit of SO 2 on the other hand. About the turbulent deposit rates, Introduction  Xu and Carmichael (1998) studied in detail the dry deposit rates of SO 2 and sulphates in Asia. Their model highlights a strong seasonal dependence as well as a daily variability, both linked, amongst others, with the nature of the subjacent surface of deposit. The dry diurnal deposition speed of SO 2 in summer would be 4-5 mm s −1 above the top of forests and meadows, 2 mm s −1 above the top of cultures and 8 mm s −1 above 5 oceans, with values 2 to 3 times lower by night. Sulphates would have dry deposition speed which may fluctuate but lower than 1 mm s −1 . In this work, we choose a turbulent deposition velocity of 2 mm s −1 for SO 2 . The interaction of the aerosols with condensated water limits, in our case, to the washout processes because we estimate that rainout, if it could happen, influence only 10 in a marginal way the mass assessment of free aerosols: we suppose that most of the aerosols captured by cloudy water will be released during the cloud evaporation. Thus, we only consider capture by rainwater. Observed rainfalls were weak during the modelled period. Nevertheless, we have taken the aerosol wet scavenging into account. In this work, we do not consider the conversion SO 2 →SO 2− 4 by aqueous 15 way. In their study of transport of primary and secondary pollutants above the China and Japan Seas, McNaughton et al. (2004) concluded that after 2 days of transport from their emission area, only 10% to 30% of the aerosol consisted of secondary and transformed aerosols. In spite of a high production during process of nucleation, the secondary aerosols advected above the Pacific Ocean will have, according to these 20 authors, a weak impact in term of indirect radiative effect and a negligible direct effect in comparison to those of primary aerosols and species which condense onto them. In the report on the intercomparison exercise of simulation of the sulphur cycles entitled COSAM and implying 11 global models, Roelofs et al. (2001) estimate that, in winter, SO 2 oxidation in gas phase by radical OH would represent a chemical sink of about 25 10%, a rate which may increase up to 20% over the summer period (with a 35-45% relative uncertainty between models). Oxidation in aqueous phase would remove 42% of SO 2 over one year for the whole concerned areas, with an uncertainty between the models varying from 25 to 65%. These figures raise interrogations on the accuracy of Introduction EGU the assessments of quantities of sulphur compounds deposit (Roelofs et al., 2001). In our simulations, we will take into account the BC like a single scalar, without spectral distribution in size or mass, precribed according to a constant flow in the first level of the model, i.e. diluted on the first hundred meters above surface. Once these carbonaceous soots in suspension, unlike SO 2 , we do not consider a capture by mineral 5 dust. The BC particles will thus play the role of a chemically inert tracer compared to the other pollutants. Its sinks will be managed like in the case of sulphur compounds (Fig. 3). Uno et al. (2003) modelled the BC distribution during spring 2001 over a geographical area including China, Korea and Japan, in order to retrieve the transport of these pollutants such as they were observed during the ACE-ASIA experiment. These authors coupled their chemical model CFORS with the RAMS model. They supposed that the BC particles existed in a single mode (fine mode) and chose to be unaware of any process of gravitational or wet deposit like any process of chemical conversions. They simply took account of a turbulent deposit on the surface. We followed the same assumptions in this work. Uno et al. (2003) gave a turbulent velocity for BC deposit 15 of 1 mm s −1 to the ground surface and 0.1 mm s −1 on the surface of the oceans. According to previous sensitivity tests, we choose a single turbulent deposit velocity of 2 mm s −1 .

Sulphur mixing with dust
Both chemistry sulphur products and mineral dust are modified by their mixing. For 20 example, Ma et al. (2004) established -from measurements made on the Island of Cheju, South Korea -that approximately 21% of CaCO 3 present in the desert mineral particles were converted into CaSO 4 by chemical reaction with sulphuric acid H 2 SO 4 during the transport of the two mixed species. In the same way, the physico-chemical analysis of collected samples at Qingdao in October 1996 indicated that 3.3-12.2%

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of dust particles contained sulphates ions (and 6.5-10% of nitrates) on their surface (Zhang, 2003). We seek here to account for the SO 2 gas capture by the mineral particles over geo- EGU graphical areas polluted by the anthropogenic emissions. The term of "capture" will be understood as an internal mixing between the two species, whatever the mechanism we did not consider BC capture or secondary sulphates capture by dust. Moreover, as explained above, SO 2 →SO 2− 4 conversion at dust surface is not modelled, but this phenomenon can be reasonably supposed to occur quickly. The dry and wet eliminations 5 of sulphate captured on dust particles are driven in the same manner as dust particles, i.e. gravitational dry deposition and wet removal (Sect. 2.2).

SO 2 concentrations
Validation of simulations of the sulphur compounds in China can be made problematic 10 by lack of experimental data: which orders of magnitude may be realistic with regard to the SO 2 concentrations in East Asia? In their medical study of the mortal effects of pollution by SO 2 with Beijing, Xu et al. (1994)

Sulphate concentrations
We also recall some orders of magnitude of sulphate concentrations, SO 2− 4 . In their study devoted to the ionic composition of the PM 2.5 in Beijing, Yao et al. (2002) propose two principal production modes of sulphates: (i) gaseous phase oxidation of SO 2 in winter, (ii) an internal cloud process in summer, fast because of the aqueous phase 5 which supports and accelerates this oxidation. Yao et al. (2002Yao et al. ( , 2003  3.3 BC concentrations BC particles originate from combustions of various types. They are seldom insulated in 15 troposphere, because we also find Organic Carbons (OC) particles and WSOC (Water Soluble Organic Carbon). Here, we focus on BC as an anthropogenic pollution marker.
By lack of measurements of BC, the TC (Total Carbon, i.e. the sum of the various compounds) data, when available, may be considered as an upper limit for BC. The airborne measurements carried out by Huebert et al. (2004) give an idea of the TC 20 concentrations on the Chinese coasts of the Yellow Sea and on the Sea of Japan. These measurements indicate TC concentrations higher in the atmospheric boundary layer (7.6 µg m −3 on average) than those obtained in the free troposphere (3.1 µg m −3 on average). In continental rural zone, in Lin'an, located approximately 200 km Southwestern of Shangaï, measured TC are 24 µg m −3 on average since mid-February to 25 the end of April 2001  EGU (South Korea) and Sado Island (Japan), for 18 months. The daily median values of PM 10 masses were respectively 33, 14 and 11 µg m −3 and those of PM 2.5 were worth 29, 16 and 9 µg m −3 . The mean composition, in mass, on the whole PM 2.5 for the three sites contained approximately (8.4±4) % of BC, (7.7±7) % of minerals and (43±14) % of ammonium sulphates (Cohen et al., 2004). Again during ACE-Asia, Clarke et 5 al. (2004) investigated the mixture and optical properties of the BC possibly present in mineral dust plumes. They noted that 85% of the internaly mixed BC was in the accumulation mode and that BC accounted for approximately 5 to 15% of the mass of the mixture. For the BC particles in Beijing, Wang et al. (2005) recall that these last few years, 10 the total yearly consumption (industrial and domestic) of coal in Beijing was close to 1500 Mt and increases at a rate of 3.8% per annum. To estimate the BC average concentrations in Beijing, at the beginning of the winter period, we can use the diurnal variations suggested by Wang et al. (2005). Pollution by BC would decrease on average during the last few years, in spite of the increasing coal consumption, which is difficult to interpret in a simple manner. Anyhow, concentrations of several tens of micrograms per cubic meter were often measured in October and November 2000. The article by Yu et al. (2005) shows that the daily variability in BC concentrations is more important in winter than in summer but the daily averages for both seasons are of the same order of magnitude.

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the Gobi Desert at the end of April 2005. As shown by the MODIS Terra image for the morning of April 28 (Fig. 4), the effects of this rising appear like a transport of yellow dust and will be observed over Japan in early May.

Ground based data (AERONET, LIDAR)
In order to constrain our work, we use the AOT and the Angström Exponent (AE) 5 provided by the spectrophotometers of the AERONET network. EGU are not reported there or are too much spaced in time, and the other stations proposed not exploitable temperatures (to derive RH), or gave wind speeds higher than 60 m s −1 , suspect values that imply mistrust of the other values measured in these same places.
We trace some of the horizontal wind speed vectors measured at the stations. They indicate the ground level air mass movements, and allow us to remark the geographi-5 cally heterogeneous distribution of the measurement sites.
The maps produced by this method show the isocontours connecting between them the weather stations where the local visibility falls of an equal percentage compared to the standard local maximum value of visibility set to 100%, and this for a visibility reduction of at least 50%. Isocontours are thus right centered on the zone of less 10 visibility, i.e. the zone where dust should be dense. At the same stations, we compute the air humidity, with special emphasis for cases where it is greater than 80%: under these conditions, fog, mist or low stratus could explain the low visibility. On the other hand, a low visibility with dry air may be attributed to dust. On the Southern China-Mongolia border, the area of interest, we find no important air humidity between April 15 27 and 30 ( Fig. 6a and Fig. 6b). The drastic zones of visibility reduction during this period are sharply confined, which can be interpreted as mineral dust events.
On 27 April, an episode is located towards (45 N, 115 E). In the beginning of 28 April, the episode is located near the Southern point of the China-Mongolia border, an area inside 40-45 N, 100-109 E (area thereafter named "zone 1", Fig. 2). On 29 April, over 20 Korqin and Otindaq deserts, inside the (42-47 N, 110-119 E) area, noted thereafter "zone 2", we note a fall of visibility due to dust transportation. In the morning of 1 May (local time), the decreases in visibility are important between South Korea and the South of Japan, but the weather conditions show condensed water (in all shapes of hydrometeors), thus do not have there a merely interpretation in term of desert dust 25 transport.
To conclude on the use of the visibility data, we note that they consolidate the first approaches by the 24 h time-step satellite images. This method has the advantage to give an idea of the geographical extension concerned by the sandstorm with a 6 h Introduction

In situ data and API data for Hohhot and Beijing cities
We take advantage of in situ data of surface PM 10 concentrations for the towns of Hohhot and Beijing. We focus on these places because they are representative of 2 distinct situations of aerosols mixtures. The real-time in situ concentrations were 5 recorded by a Chinese team collaborating with the NIES team. Hohhot (112 E, 41 N, 1100 m, 1.5 M inhabitants) is located in Inner Mongolia, North East of the loop of the Yellow River (or Huang He), approximately 450 km West of Beijing. This city is an interesting place for aerosol measurements, because it is under the influence of winds carrying dust from Gobi Deserts, from Alxa plateau (also spelled 10 Alashan) and Mongolia. Let's draw attention to the North and Western North mountains close to the city (whereas the 2 other cardinal directions are open on plains) where shielding effect on surface dust transport, due to this relief, cannot be neglected. Our analyses with Hohhot will be interpreted as revealing case studies of aerosol mixtures close to the mineral dust sources, but keeping in mind that Hohhot can be polluted 15 by anthropogenic emissions, partly because of heavy industries (e.g. steel-works and power station) being located in the Western side of the city.
Beijing (116 E, 39 N, 15 M inhabitants), capital city of the People's Republic of China, is located near mountains of an average altitude of 1000 to 1500 m in the West, North and North-East. At the East, the city opens on a large plain going gradually down to the 20 Bohai Sea, maritime outlet of the Pekinese agglomeration. The high hills account for 62% of the total surface of the city with 10 400 km 2 and the plain account for 38% with 6400 km 2 . We analyze the results relative to this city as being particularly representative of the conjunction of the aerosols that interest us here: mineral dust transported by the sandstorms generated in the continental deserts and the anthropogenic pollutants 25 emitted by the city itself and the surrounding towns.
As regards a last surface available database, we will have the opportunity -for these chinese cities -to use, as an indication and without claim of exactitude, the estimates 11912 Introduction as "PM 10 " by the SEPA, which means that pollution was controlled by particulate matter: it can include mineral dust. In case of prevailing gas pollution, the API would be either SO 2 or NO x , but that case never happened during this period.
With the help of the conversions tables of daily API into daily means PM 10 concentrations, valid for 6 successive linear intervals limited, by construction, between a 10 minimum of 50 µg m −3 and a maximum 600 µg m −3 for PM 10 , we find, by polynomial regression, a continuous easy-to-use conversion law: Some authors (Li et al., 2003;Guo J. et al., 2004;Han et al., 2004) regard -as ourselves -API as an interesting indicator of the episodes of mineral dust, like in 15 Beijing (Zhang et al., 2003b) and use API to extrapolate the concentrations of various specific species of aerosols. As it is difficult to know what is exactly chemically meant in the "PM 10 " mass load, and as API are only daily averages, we will not interpret them more accurately than an rough order of magnitude of the concentration in mixture of particles with diameters lower than 10 µm, as far as these particles do not exceed 20 actually 600 µg m −3 because the corresponding API are not defined beyond (this value of 600 µg m −3 is a "saturation" maximum value).
ACPD 7,2007 Modelling mineral and anthropogenic pollutants in East Asia Information on dust emissions is summarized in Table 1. Dust fluxes are presented over 3 source areas ( Fig. 2): zone 1 (south of Gobi desert, remote from shoreline), 5 zone 2 (SE Gobi desert) and zone 3 (overall Gobi, which roughly covers the whole emission areas). Note that the relative anticyclonic situation over Taklamakan prevents any intense dust uptake from this desert during the period under study. Zones 1 and 2 are approximately of same size (about 440 000 km 2 ). We present the local maximum uptake for every 3 h-interval modelled within each zone. The detailed results (not  15 We show the main features of dust and anthropogenic species, and we compare with observational (and literature) data, from 27 April to 2 May. Figs. 7a to f are an overview of the surface plumes at 00:00 UTC (∼08:00 LT). The anthropogenic pollutants plume is located along the shoreline from Shanghai to Koreas and Japan Sea via Beijing, which gradually extends towards Japan. During   (Sun et al., 2006). Farther from megalopolis, the model BC concentrations lie between 1 to 15-20 µg m −3 , also in agreement with the observations reported in literature.

Surface plumes of dust, SO 2 and BC particles
The modelled surface dust plumes (Fig. 7) patterns highlight the contrasting origins between desert particles and pollutant sources, along with the particular role of wind in aeolian emission. The intermittency is therefore a common rule for desert dust, not 10 for anthropogenic pollutants. From these figures, it appears that the mixing zones of anthropogenic and mineral pollutants are of limited extent because the anthropogenic pollutants are on the East and South-East of the modelled area when mineral dust plume lies from the centre to the East and South-East area. Until 1 May, the mineral dust plume seems to blow the anthropogenic pollutants already present in the atmo- 15 sphere in front of him. This partition between natural and anthropogenic aerosols inside the boundary layer is confirmed by observations. Recent studies of particles collected at Qingdao (south of Beijing) during 3 dust storms of spring 2001 revealed that mineral aerosol compositions showed rarely indications of mixing with anthropogenic pollution (Zhang et al., 2003c) before their arrival above the metropolis, even for a long-range 20 distance as, for instance, a transport from Northern deserts to Taiwan (Lin et al., 2007).
Behind the dust front, when the dusty air mass lies above the sources of pollution, it is permanently resupplied with the local anthropogenic pollutants which favour some vertical mixing (and SO 2 uptake onto dust particle as explained in next section). However, as a general rule, the different aerosol species are modelled in separate plumes.  EGU followed by polluted mineral particles. The authors measured the average concentration of anthropogenic sulphates on Rishiri Island, North of Japan, with approximately 2.5 µg m −3 in spring, and some higher values in the case of abrupt incoming of continental polluted air masses. This behaviour is also true over the continent itself were we find peaks of concentrations towards Shanghai and Seoul, certainly over-estimated We did not examine in detail the role of liquid water (wet scavenging). It is however certain that water was involved in the capture of the pollutants. This point will be addressed in later studies, with the help of chemical data concerning the wet deposits.
In conclusion of our simulation of horizontal transport of the four species of pollu- 15 tants, we show that the mixings of desert dust plumes with the pollutants in East Asia seem to follow a spatially inhomogeneous process. As Zhang et al. (2005) record it at Qingdao in February and March 2002, mineral dust coming from the north of the country seems to be confined during several days in the post-frontal air mass whereas the anthropogenic pollutants are found in the pre-frontal boundary layer. The mixing -20 mineral/pollution -can take place within the interface of these air masses or through a slow diffusion process in a calmer air, as it seems to happen on 2 May. EGU maximum of 11 µg m −3 in SO 2 captured by dust at surface level, and this value will increase during the following days. On 29 April, both dust and free SO 2 surface plumes are more mixed and the overlapping zone shows a 13 µg m −3 maximum of captured SO 2 above the Bohai Sea. We find 44 µg m −3 on the West shore of South Korea while it is less than 4.4 µg m −3 over the Japan Sea, where, at the same time, "clean" min-5 eral dust concentration does not exceed 200 µg m −3 . The simulation showed a notable dust emission starting from the end of 30 April. On 1 May (Fig. 8a), as the horizontal gradients of surface concentration at the Southern and East dust front are very important, the mixture only takes place inside a bow-shaped area of approximately 200 km in depth. On 2 May, wind intensity decreases in the South and dust spreads over the 10 most polluted zone, so that an increasing fraction of SO 2 is captured by mineral particles. Maximum surface values from South to North of China Sea shoreline vary from 93 µg m −3 (Shangaï) to 41 µg m −3 (West of South Korea). We display on Fig. 8b a vertical zonal cross-section of the plumes sufficiently at the North of the simulated zone (pink line, Fig. 8a) so that the modelled vertical profiles are representative of transport likely to pollute Japan and illustrate a regional situation of quasi permanent pollution. Figure 8b superimposes the SO 2 concentrations captured by the mineral dust and isolines of mineral dust concentrations itselves. The 3-h sequence shows that, after the westerly dust front income, the mixing between SO 2 and mineral plumes (delineated by the minimum 50 µg m −3 red isoline), always occurs 20 between surface and 2000 m a.g.l. on 29 April and 30 April, and until approximately 4000 m on 1 May, with, at these altitudes, values of captured SO 2 concentrations about 0.1 µg m −3 . The captured SO 2 concentrations decrease very quickly with altitude, and more quickly, as a whole, than the concentrations of dust and free SO 2 do. In the lower layers, the maxima of captured SO 2 concentrations are found especially from North of

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In order to qualitatively illustrate the spatio-temporal capture mechanism, Fig. 9 displays the chronological evolution of the vertical distribution of SO 2 captured by dust above Beijing. The captured SO 2 concentrations (symbolized by full circular surfaces, with size proportional to captured SO 2 ) lie between 10 −3 and 0.5 µg m −3 (magnitudes are specified in some points). This figure gives an idea of the relative intensities of the 5 captures in time and altitude.
It is interesting to note that on April 28, when dust surface concentrations increase, the capture of SO 2 does not increase immediately and exhibits a rather homogeneous vertical profile between 100 m and 1000 m. The highest concentrations, located under 2000 m a.g.l., are found in the hours thet follow the dust surface maximum of 28 April. 10 The mixing process occurs in a deepening layer, which reaches 4000-5000 m on late 29 April (UTC). From 30 April, the mixing process interrupts by lack of dust.

Model concentrations and validations of mineral dust over Hohhot and Beijing
Hourly meteorological data are available on the general public site http://www. wunderground.com. For Hohhot, during local April 27 afternoon, South-Westerly wind 15 blew between 3 to 14 m s −1 in gusts and turned North from 23:00 LT with a visibility falling to 3 km before rising to 7 km after midnight (see http://www.wunderground. com/history/airport/ZBHH/2005/4/27/DailyHistory.html). From midnight to 07:00 LT on 28 April, the recorded visibility ranged between 300 and 1000 m under Northern and North-Westerly winds of 3 to 7 m s −1 . This first dataset confirms the occurrence of a 20 dust plume over Hohhot coming from North.

Hohhot dust surface concentrations
We present the time serie of the surface mineral dust concentrations, on Fig. 10, modelled at Hohhot city. We superimpose the in situ recorded concentrations and the daily PM 10 concentrations deduced from the API data. On the same figure, as further dis-

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An intense dust episod is clearly identified in the morning of 28 April in local time (end of 27 April, UTC). The time serie of surface concentrations for 27 and 28 April presents a phase delay of a few hours as compared to the column loads. Thus, the model calculates a transport of dust occurring in a differentiated way according to altitude. The maximum surface concentration modelled for 30 April is synchronized with those 5 of the dust column loads: this second dust front was close to the surface. Modelled dust concentrations agree with in situ data and API data for the main tendencies but some discrepancies are found. The correlation coefficient between in situ data and model products is 0.49 which is significant with a real-time simulation using a 3 h output frequency. Model results underestimate the observations for the main event of 10 28 April, which was prolonged until 29 April, according to local measurements. The PM 10 values from API of 28 and 29 April approach the possible maximum values for the API indices. These PM 10 values must thus be considered as estimates of the lower limits of the actual average concentrations for these two days. For the second dust event, on 30 April, we note, contrary to the previous days, a model overestimation as 15 compared to in situ measurements, but a very good agreement with the estimate of the interpolated PM 10

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Hohhot in altitude before the dust transported to the surface does arrive on the city itself (which is probably an orography effect). At the end of 27 April, the simulated ground concentration is twice less than the 1000 m value. Six hours later, the profile shows an inversion of tendency near ground and this is completely marked on 28 April at 00:00 UTC where the concentrations decrease in a quasi-monotonous way with 5 altitude (about 700 µg m −3 at surface level and near 170 µg m −3 at 1000 m). On 30 April, at 00:00 UTC (08:00 LT), the second dust event is initially close to the ground, then the profile bends and a maximum appears between 1000 m and 2000 m 12 h later. As this event comes from North, we again hypothesize effects of relief in the abrupt variations in the shapes of the dust vertical profile. Figure 12a shows the LIDAR normalised Backscattering Intensities (hereafter referred to as BI) and Depolarization Ratios (DR) at 532 nm wavelength for the first 3000 m over Hohhot area from 27 April at 06:00 UTC, the atmosphere contains no depolarizing aerosols, i.e. mainly anthropogenic pollutants. The first event (27 April) exhibits a vertical extension higher than 2000 m, similar to model results (with a few 15 hours of delay). Then, LIDAR products show a transition with "mixed" aerosols, with a vertical extension exceeding 2500 m a.g.l. Just after 12:00 UTC, also on 27 April, LIDAR data show a brutal decrease in the BI level, that limits to the first hundreds meters: it indicates an aerosol plume at very low altitude, while the DR abruptly increases and reaches more than 30% between the ground and 1000 m, strongly suggesting that 20 there are mineral aerosols (depolarizing particles) brought by the sandstorm. On 29 April, we note a reduction in the BI and DR as well, indicating a less polluted day. On 30 April, around 00:00 UTC, the DR increase suggests a new arrival of mineral particles, also retrieved by the model. It is more difficult to interpret the form of this LIDAR observation, but it exhibits a vertical extension again exceeding 2000 m, which corroborates 25 our profiles calculations around 30 April at 12:00 UTC (Fig. 11a).
As a whole, our simulations at Hohhot roughly agree with the overall evolution of the LIDAR backscattering shape. , is related to the intense dust transport already mentioned at Hohhot (see above) for the same dates. The second episode was observed at Beijing rather than Hohhot. Figure 10b presents the time series of the simulated surface con-5 centrations as well as the estimates of the daily averages of the PM 10 concentrations derived from the API. For the first dust event, in situ measurement at 21:00 UTC on 27 April (i.e. approximately 05:00 LT, 28 April in the morning) is 510 µg m −3 , which closely agrees with model values: modelled maximum ground concentrations range from 570 to 10 620 µg m −3 . For 28 April, the average PM 10 from API is estimated at 480 µg m −3 . The duration of the episode is approximately 9-12 h according to our calculations, which correctly contain the peak of in situ measurements.

ACPD
After this dust event and until 30 April, Beijing is not concerned by substantial dust transport, but always remains with a non negligible background pollution content (see  In Beijing, the overall correlation coefficient between the results of 3 h real-time modelled surface concentrations and in situ measurements is 0.56.

Beijing dust vertical profiles
The column loads in mineral dust are also shown on Fig. 10b. The phase coincidence of the two curves -ground concentrations data and column load -suggests that the We present on Fig. 12b the LIDAR measurements (BI and DR) recorded at Beijing at the end of April 2005. Now, we compare these data to our simulations of dust vertical profiles. We find the confirmation of a relatively homogeneous vertical distribution between surface and 1500 m for the arrival of the 27. The intermediate DR (∼10%-15 20%) is the signature of a mixing of anthropogenic and dust aerosols. From April 27, 18:00 UTC, i.e. early local morning of 28 April, the BI grows suddenly, showing the arrival of the dust plume, initially near surface (maximum height ranging between 500 and 1000 m) as we calculated for 28 April, 00:00 UTC. During the day, the LIDAR patterns (BI) exhibit stratification around two layers (0-1000 m and 2000-3000 m) whereas the 20 DR strongly suggest a complex mixing of the aerosols shapes. The second event (on 30 April, between 0 and 12:00 UTC) appears localized lower than 1500 m a.g.l. The DR shows that this last event carries a load in mineral aerosols lower than the event of 28 April.
To conclude this part devoted to the results of real-time modelling from transport of mineral dust over Beijing, we estimate that they suitably represent the qualitative and even quantitative aspects of the event that really occurred.

) on Hohhot and Beijing
We now describe the modelled surface concentrations of the anthropogenic pollutants: BC, SO 2 and sulphates. We adopt a presentation by pollution species at the same dates in Hohhot and Beijing: BC on Fig. 13a, SO 2 on Fig. 13b and sulphates on Fig. 13c. We also show on these figures the respective column loads, which will be 5 further useful for the calculations of the optical thicknesses. Lastly, Table 2 summarizes some statistics of the representative values for all of the five simulated days, from 27 April (00:00 UTC) to 2 May (00:00 UTC) 2005. 10 We see in Beijing ( Fig. 13a)  First of all, it will be noticed (Fig. 13b) that SO 2 concentrations follow variations very close to those of BC. That is explained, on the one hand, by the common mode of injection for these two pollutants in the model, and, on the other hand, by the geographical 5 proximity of their emitting zones. The few differences of surface concentrations curves will thus be explained primarily by the very local differences in the atmospherical dynamics, throughout their respective ways (there is of course not an exact proportionality between the BC and SO 2 fluxes in each source pixel), like by the specific (model) behaviour of SO 2 . 10 Modelled SO 2 values (see Table 2) appear completely relevant in China, in Beijing like Hohhot, due to the presence of factories. Literature gives SO 2 orders of magnitude of several tens of µg m

Modelling mineral and anthropogenic pollutants in East Asia
F. Lasserre et al.  (Hatakeyama et al., 2005). During the period under study, we had no measurements in Beijing, but it has been possible to directly compare our model results with observation data from API measured at Tianjin (http://www.tjemc.org.cn), which is fairly representative of the Beijing area. Precisely, Tianjin city (117 E, 39 N) is located at the Western point of the Bo- 5 hai Sea and approximately 150 km South-East of Beijing. Here, API data does not refer to PM 10 aerosols (Sect. 4.2.2): in Tianjin, the API index specifically refers to SO 2 (as this pollutant was predominant). On 30 April, the local SO 2 estimates from API give a concentration of 111 µg m −3 , which compares with the model SO 2 results: 171±137 µg m −3 (average ± standard deviation). On 1 May 2005, the SO 2 -API index gives a concentration of about 60 µg m −3 , and the model calculates a SO 2 concentration of 65±43 µg m −3 . The model results in Tianjin thus seem to reflect in a correct way the reality of local SO 2 pollution during these two days.
We will discuss the vertical column load of SO 2 pollution as shown on Fig. 13b to compare it with the sulphate ones The sulphate ions SO 2− 4 are secondary pollutants resulting -in our simulation -from SO 2 oxidation. The SO 2− 4 columnar load bars (Fig. 13c), for both cities, closely follow the SO 2 bars and represent between the third and half of SO 2 loads. As regards 20 surface concentrations, both Figs. 13b and c show, over Beijing, a very emitting zone of pollutants, a marked temporal modulation in SO 2 , whereas the SO 2− 4 looks much smoothed in time.
In this study, we do not have any sulphate observational control values, so that we must limit to compare model results with literature data. Actually, sulphate concentrations are very dependent on the temperature and local RH: for instance, important relative moisture accelerates the SO 2 →SO 2− 4 conversion, which would, otherwise, fol-11925 Introduction EGU low a dry process (the only process taken into account in the model). This was shown in Beijing by Yao et al. (2003): according to these authors, sulphate concentration is higher in summer than in spring because of intra cloudy processes and higher temperature. So, they found summer concentration in secondary sulphates of 31.5 µg m −3 , which gives us an upper order of magnitude for Beijing. On 29 April 2005, the weather 5 was rather clear in Beijing with low relative moisture (35% on average). We simulate, for the following 24 h, a rise of the SO 2− 4 content from 4 to 17 µg m −3 . Our estimate, under conditions probably favourable to a dry conversion, thus agrees with Yao et al. (2003) orders of magnitude and consolidates the credibility of our results for the SO 2− 4 concentrations. 10

Principles for the calculation of the Aerosol Optical Thickness
The simplified representation of the aerosols cycle taken into account in this study must find a validation in physical measurements also easily accessible. As stated above, we chose to compare our results with the radiometric data: Aerosol Optical Thicknesses 15 τ (AOT) and Angström Exponent α (AE), both characteristic of the aerosols present in the atmosphere.
In order to estimate the observed AOT, we adopt the following simplification: each of the four types of studied aerosols (mineral dust, BC, free SO 2− 4 and SO 2− 4 on dust issued from oxidation of the captured SO 2 ) is allotted a specific extinction section σ j ext , 20 in m 2 g −1 . The specific extinction section σ j ext cumulates, in a single physical variable, the specific aptitudes of the aerosol to absorb and scatter the solar radiation in the UV, visible and IR wavelengths. The essential interest of σ j ext consists in its easy-way to use, because it just needs to be multiplied by the vertical column load C j (in g m −2 ) of aerosol species j , to directly obtain the specific AOT for this aerosol

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Of course, this simplification is carried out to the detriment of a rigorous determination of σ j ext because, as e.g. explained by D' Almeida et al. (1991) or Seinfeld and Pandis (1998), this coefficient depends, in the low atmospheric layers, not only on the chemical nature of the aerosol but also, amongst other, on the wavelength (see also Fialho et al., 2005), on its real shape (granulometry size distributions, Chin et al., 2002;Kalash-5 nikova andSokolik, 2002, andindividual forms, Kasparian, 1997), and on how it can be agglomerated with other species in aqueous or solid phase (Martins et al., 1998;Ricard, 2001). Note that the sulphates have a diffusivity quickly increasing with RH (Lowenthal et al., 1995;Carrico et al., 2003) and that, if the sulphates are coated on a BC nucleus, the absorbing capacity of BC increases by a factor of 2 to 2.5 as compared 10 with BC alone (Sato et al., 2003). These remarks explain why the observed values of the extinction coefficients are highly scattered:

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We also model, inside the total AOT, the partition of the AOT related to each of the four aerosol species in order to estimate which one dominates the extinction of the solar radiation. Lastly, these modelled AOT are validated by comparison with the time series of the AOT and the AE data provided by the AERONET network of photometers, at five locations: Beijing, Dalanzadgad, Liangning, Gwangju and Osaka.

5
A study distinguishing four aerosols (mineral, sea salts, SO 2− 4 and BC) was carried out in order to compare model results and measurements (Takemura et al., 2003). In their study, the calculations concern the daily averages of the radiative effects over the East-Asian Seas and the Northern Pacific. At larger scales, comparison between model and data from photometers and satellites were also used to quantify the total 10 radiative impact over the Northern hemisphere, of the East-Asian aerosols produced in spring 2001 (Chin et al., 2004). On the other hand, our aim was not to compare average optical thicknesses with broad temporal and large space scales, but to directly confront the 3 h -real time model output with the instant data at each measurement site ( The AERONET AOT data are of three quality levels: 1.0, 1.5 and 2.0. Although it is recommended to publish results based on the level 2.0 values (Eck et al., 2005, and personal communication), we knowingly took the party (and risks too) to directly use the "rough" data of AOT of level 1.0 because postprocessings of levels 1.5 and 2.0 tend 20 to smooth the time variations of the AOT by removing certain high values (which could be due to clouds, but also to thick dust plumes). These levels prevent, in turn, from well taking into account, "in real time", of the transport of the Asian aerosols.
For clarity, we only use the AOT at 500 nm (Dalanzadgad, Liangning) or 675 nm (Beijing, Gwangju, Osaka) at each time step. However, in order to bring more information 25 about the nature of the aerosol via its spectral signature, we also plot the AE, defined by Angström (1964):

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where τ λ 1 (resp. τ λ 2 ) is the AOT corresponding to the wavelength λ 1 (resp. λ 2 ). We used AE data with λ 1 =500 nm and λ 2 =870 nm. When α ends towards zero, the size of the aerosols is often in the accumulation or the coarse mode. Otherwise, when α increases, say of the order of 1, the size of the aerosols tends towards very fine modes, even molecular dimensions. Generally, 5 AERONET provides AE (α) ranging from 0 (or even slightly negative) to 0.7-0.9 for mineral particles, from the desert zones to the area where they first mix with other aerosols, and in an interval from 1.2 to 2.5 for urban pollution aerosols (Dubovik et al., 2002;Smirnov et al., 2002). When mixing is present, intermediate values may be found: for example, a value of α=0.95-1.02 was measured in December 2000 by Sano 10 et al. (2003) at Amami-Oshima island (Southern Japan), indicating a mixing of small and large particles; in the same experiment, these authors found a lower average of 0.66 when the desert dust ratio was increased.
(i) Beijing Figure 14a shows the time series of modelled AOT over Beijing and the corresponding 15 AOT and AE (α) AERONET data.
The AOT, for five days, is modelled as τ Beijing =0.74±0.36 (average ± standard deviation), with a minimum at 0.22 before the first dust event, and a maximum at 1.99 on 27 April, 18:00 UTC (02:00 LT, 28 April) during the desert dust storm. In rather comparable conditions, during spring 2001, Xia et al. (2005) found a mean AOT (500 nm) ranging 20 between 0.68±0.06 and 0.81±0.70. We are not far from this magnitude. Finally, our results agree very well with the monthly mean of about 0.6 for April-May recorded by Qiu and Yang (2000) from 1980to 1994 AERONET data are diurnal observations, so note that we have constraint points only during approximately half of the studied days. However, the observed shape during 25 the local day (since 00:00 UTC to 12:00 UTC roughly) is roughly retrieved, day after day, by the model AOT. The observed and modelled values of April 28 and 30 are in agreement in the evening. Moreover, the model AOT lower than 0.6, before and after 11929 Introduction EGU the dust events, agree very well with data of Beijing, but AERONET data for the 29 April are higher than our calculations. The AE observed in Beijing suggest that the hourly contribution calculated for each aerosol is relevant. In the hours before the first sandstorm, the AOT between 0.2 and 0.6 show a composition of an air rather little polluted, and the AE values (around 0.5) 5 suggest that this pollution is an anthropogenic and mineral mixing, but dominated by mineral. 24 h later, the AE are weak or even negative: the aerosol dominates in the coarse mode, which is a proof of the mineral plume, as simulated by the modelled partition of the AOT peak. On 29 April, and even more on 30 April, the increase in modelled anthropogenic contributions is clear and is underlined by the significant increase of the AE data. Lastly, after the second dust plume, on 1 May, we find the optical characteristics of a mixed aerosol (α ranging between -0.2 and 0.5).
In conclusion, our simplified restitution of the optical characterization of the cycle of the natural and anthropogenic aerosols over Beijing seems to be relevant.

15
This AERONET site is located South of Mongolia, close to the emitting dust deserts. It is thus unsurprising to model AOT values with a major part of dust contribution (Fig. 14b).
Our AOT estimates correctly agree with the observed tendencies for the first dust event of 27-28 April. On 28 April, the low AE values (α∼0) confirm the mineral promi-20 nence within the aerosol plume. On the other hand, we underestimate the dust quantity itself because the observed AOT are twice more important than the modelled AOT, with some hours in advance.
About the real-time discrepancies, we think that the short distance between the desert source and the AERONET site must be seen as the main cause of the de- 25 lay between the extremes of observed and modelled AOT. The measurement site can detect some much localized epiphenomena that our spatio-temporal resolution cannot take it into account.

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We correctly model a dust plume, over Dalanzadgad area, during 29 April. For the following days, we also correctly retrieve the quick variations of AOT, but smoothed in time, with a dominant presence of mineral dust.

(iii) Liangning
Liangning, a Chinese city located on the North shore of the Bohai Sea, is polluted by 5 local anthropogenic emissions, and by mineral dust coming from the close East Gobi deserts (Horqin, Otindag and Hulun Buir as well). Figure 14c shows, for 27 and 28 April, some modelled AOT with an opposite tendency compared to the few data we can compare. AE data suggest a mineral mixed aerosol. We probably underestimate a dust plume crossing over Liangning during 27 April, a hypothesis sustained by the 10 MODIS imagery but not confirmed by the TOMS Aerosol Index for that day. Another possibility is that the model drives the dust plume too much Northerly than it actually was, so that we miss Liangning. The last hypothesis is that the few level 1.0 data are inappropriate because of clouds, which would be a limit for our methodology.
The days of 29 and 30 April are, on the contrary, much better described by the 15 AERONET data. We can see that the modelled AOT follow the observed tendency, concerning the time series and the order of magnitude itself. We probably underestimate the mineral load carried to Liangning on 30 April, as the model reaches half of the observed AOT peak at the same time. This model delay explains why, in opposite way, we overestimate the AOT 24 h later with a major mineral composition whereas the 20 AE (α) suggest finer aerosol inside the plume. The model estimates a major arrival of sulphates on 30 April but we can not discuss further this relative contribution to the total AOT because, as we said above, we underestimate the mineral contribution on the same time.
To sum up the Liangning case, the model AOT ranges between 0.07 and 2.01 (in 25 average τ Liangning =0.84±0.56) and agree with the mean orders of AOT observed over the five days. In magnitudes, for example, Xia et al. (2005) give an average AOT of 0.

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However, even though the mean orders of magnitude are relevant, our results exhibit time discrepancies compared to the actual events, which should incriminate the local dust source accuracy for the desert area close to Liangning.

(iv) Gwangju and Osaka
Gwangju city is localized in South Korea. We display AOT and AE on Fig. 14d. The 5 contribution of SO 2− 4 is prominent in the simulated AOT since they contribute on average to 60% of the total mean AOT of τ Gwangju =0.43±0.17. BC also continuously takes a significant part in the total AOT (5 days average: 21%). The very absorbing character of BC, even compared to the SO 2− 4 , is counterbalanced by the much higher concentrations of the latter compared to the former. 10 Here we note a very satisfactory agreement between modelled and AERONET AOT, in the time variations and magnitude as well. Moreover, the two dust episodes are correctly retrieved by the model. When the two dust events occur over the Korean peninsula (29 April and since 1 May), the mineral contribution to the AOT is significant and AE tends to decrease. Note the (small) contribution of coating SO 2− 4 on dust 15 around 12:00 UTC, 1 May (vertical black and white strips). The same remarks are also applicable, as a whole, to our simulations in Osaka (Fig. 14e), Japan, except for the tendency observed for 1 May (here we do not have observational data). Average AOT over the 5 days is τ Osaka =0.34±0.19 with values ranging between extremes of 0.09 and 0.77. With our estimates, the sulphates contri-20 bution is 71% of the average AOT over 5 days. The peak in AOT (29 to 30 April) occurs 24 h later than the same peaks modelled over the continent, due to the travel duration. Lastly, we recall that, above Osaka, the permanence of anthropogenic pollution compared to the intermittency of natural dust pollution is logically explained by the long range transport for dust whereas anthropogenic pollutants are locally produced with a 25 constant flow.
We can thus easily give the orders of magnitude for the relative AOT contributions in BC and sulphates on the two cities located in Korea and Japan, both far away 11932 Introduction EGU from the sources of mineral pollution, but themselves sources of anthropogenic pollutants. Over 5 days, contributions of BC and sulphates are more clearly dissociated in Osaka, where on average the sulphates contribute to AOT four times more than BC (AOT SO4 /AOT BC =0.24/0.06∼4). This ratio in favour of the sulphates is also modelled in Gwangju, with, on average over five days, AOT SO4 /AOT BC =0.26/0.09∼3.
Our estimates in Korea and Japan range between those of Aoki et al. (2005): AOT SO4 /AOT BC =0.075/0.04∼19, concerning the overall Japan, and the order of magnitude of AOT SO4 /AOT BC ∼2, evaluated during April-May, at Tsukuba, Niigata and Sapporo cities (Japan), by Takemura et al. (2001). Lastly, we find that, even in the presence of a desert dust transported from the continent, the total average AOT at Gwangju and 10 Osaka is mainly of anthropogenic origin, which agrees with the global assessment of Takemura et al. (2003) about the ACE-Asia area.

Conclusions
The objectives of our work were multiple and complementary. To sum up, we wished to develop the modelling of the cycle of the natural and anthropogenic aerosols in an 15 area appearing increasingly implied in pollution problems, Eastern Asia. The interest of this approach is to build and to take advantage of a tool usable to study the chemical and radiative consequences of these pollutants of various origins. In a former paper (Lasserre et al., 2005), we had built a mineral dust source according the Dust Production Model (DPM) of Marticorena and Bergametti (1995) and Marti-20 corena et al. (1997a, b). We present the specific elements of the East-Asian desert mineral source in China and Mongolia, coupled online with the RAMS mesoscale model. This coupling enables us to simulate desert dust events, including rising, transport and the deposition (dry and wet).
Results EGU load of mineral dust and the results agree with the visibility analysis, the satellite imagery and the in situ observations. In this study, we differ from most of other model works because we propose a study "in real time", and not on average over a period of at least several weeks, as the majority of other work proposes it. The limits of the model are perceptible when one seeks a perfect synchronization between results and 5 observations, but the short-time tendencies are fairly well reproduced as a whole. The surface concentrations are in good agreement with observations in China (Hohhot and Beijing). The studies of the vertical profiles show that the dust transports take place below 3000-4000 m agl. These profiles present very quick and clear variations in structure, alternating between homogeneous and stratified forms. The model profiles above 10 Hohhot and Beijing are confirmed by local LIDAR data of backscattering intensities and depolarisation ratio on semi quantitative grounds. We choose aerosols (BC and sulphates) along with an anthropogenic pollution gas (SO 2 , a sulphate precursor) in addition to the mineral aerosols, in order to model and to easily interpret the coexistence of these species and the consequences, mainly the 15 optical signatures of the aerosols. For anthropogenic pollutants emissions, GEIA (BC) and EDGAR (SO 2 ) databases are used. Dynamic parameterizations (deposition rates) and chemistry of the anthropogenic pollutants are drastically simplified as compared to the specialized studies which we recall in the bibliography. Our parameterizations are very simple, but they are efficient enough to model the atmospheric cycles. 20 We describe the pollution observed on the quasi-continuum of metropoles of East China and Korea and above the seas which separate them from Japan. Maximum surface concentrations of several tens of µg m −3 of BC and of SO 2− 4 , and several hundreds of µg m −3 of SO 2 , are modelled over the largest cities such as Shanghai, Beijing and Seoul, in agreement with the literature data. We show moreover that the dust aerosol 25 mix initially with the anthropogenic ones in the frontal region of the desert dust plume. Next, the mixing takes place preferentially with the mineral particles already located above the sources of anthropogenic pollution. Afterwards these mixed particles move to Japan, taking part to a pollution of continental origin.

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Using AERONET optical measurements performed above five sites located along the aerosols pathways, we test our estimates of Aerosols Optical Thicknesses (AOT). The surface extinction for BC, sulphates (free and captured on dust) and mineral particles were derived from literature: 12 m 2 g −1 , 8 m 2 g −1 and 1.2 m 2 g −1 respectively. The total AOT, calculated as the sum of the contributions of the four species are then compared 5 with the AERONET AOT real time data. We also display the AERONET Angstrom Exponent (AE), which helps characterizing the nature of the aerosols. The orders of magnitude of the modelled AOT are always coherent with the orders of magnitude of the averaged observations. Especially, we retrieve a realistic evolution of AOT as compared with the AERONET time-series from 27 April to 2 May. We also show that the 10 modelled relative abundances in aerosols are frequently compatible with the magnitudes of the AE. Such agreement of the AERONET AOT and AE suggests that our simplified tool is suitable for real-time aerosol studies in a complex environment.