Abstract. This paper presents a bottom-up methodology based on the local emission factors, complemented with the widely used emission factors of Computer Programme to Calculate Emissions from Road Transport (COPERT) model and near-real-time traffic data on road segments to develop a vehicle emission inventory with high temporal-spatial resolution (HTSVE) for the Beijing urban area. To simulate real-world vehicle emissions accurately, the road has been divided into segments according to the driving cycle (traffic speed) on this road segment. The results show that the vehicle emissions of NO x , CO, HC and PM were 10.54 × 10 4 , 42.51 × 10 4 and 2.13 × 10 4 and 0.41 × 10 4 Mg respectively. The vehicle emissions and fuel consumption estimated by the model were compared with the China Vehicle Emission Control Annual Report and fuel sales thereafter. The gridbased emissions were also compared with the vehicular emission inventory developed by the macro-scale approach. This method indicates that the bottom-up approach better estimates the levels and spatial distribution of vehicle emissions than the macro-scale method, which relies on more information. Based on the results of this study, improved air quality simulation and the contribution of vehicle emissions to ambient pollutant concentration in Beijing have been investigated in a companion paper (He et al., 2016).

Based on the new-generation Global/Regional Assimilation and PrEdiction System (GRAPES) developed by the Numerical Prediction Research Center, China Meteorological Administration and the Chinese Unified Atmospheric Chemistry Environment for Dust Atmospheric Chemistry Module (CUACE/Dust) developed by the Centre for Atmosphere Watch and Services (CAWAS) of the Chinese Academy of Meteorological Sciences (CAMS), the China sand and dust storm forecasting system GRAPES /CUACE-Dust model has been established. The latest data of land desertification, optical properties of China sand and dust aerosols, daily soil moisture and snow cover over China main land was introduced in this system. The system showed good performance in mass conservation. The comparisons of real-time prediction outputs with surface observations and aerosol indices derived from TOMS ozone spectrophotometers (TOMS AI) indicate that the model can predict the outbreak, development, transport and depletion processes of sand and dust storms accurately over China and the East Asian region. The system makes real-time quantitative prediction of a series of elements including sand and dust injection from the surface, dry and wet deposition amount, dust concentration and optical depth. We selected 7 major dust storms occurring in April 2006 and analyzed the spatiotemporal distribution patterns of dust emission, dry and wet deposition and atmospheric load in this paper. The results showed that about 225 million tons of dust were emitted into the atmosphere from the deserts over east Asia in that month. The 3 major sand and dust sources were just as the following: The deserts in northern Inner Mongolia and the boundary area around China-Mongolia were the first dust sources with a contribution of 153 million tons accounting for 68% of the total emission. The Taklimakan Desert ranked second and contributed approximately 40 million tons accounting for 17% of the dust emission.The Onqin Daga Sandland emitted about 15 million tons or 7% of the total emission. The contributions from other deserts, sandy lands and abandoned farmlands were about only 8% of the total dust emission. The total deposition over the East Asian region in April 2006 was 136 million tons. The regional distribution of dust deposition showed that the 3 major sources were also the major deposition areas. The deposition amount in the 3 major sources accounted for 78% of the total with about 135 million tons falling back to the source regions. The secondary deposition area was the China mainland downriver, where more than 2 million tons deposited accounting for 16% of the total deposition. The deposition over the region east of 120°E including China off-shore regions, Korean Peninsula, Japan and the West Pacific took only 6% of the total deposition, which was about 850000 tons. The analysis on dry and wet deposition showed that dry deposition dominated in the process, accounting for 94% of the total sand and dust depositions in the period and wet deposition only was around for 6%, since it was general...

<p>A data assimilation system (DAS) was developed for the Chinese Unified Atmospheric Chemistry Environment– Dust (CUACE/Dust) forecast system and applied in the operational forecasts of sand and dust storm (SDS) in spring in Asia. The system is based on a three dimensional variational method (3D-Var) and uses extensively the measurements of surface visibility (phenomena) and dust loading retrieval from the Chinese geostationary satellite FY-2C. By a number of case studies, the DAS was found to provide corrections to both under- and over-estimates of SDS, presenting a major improvement to the forecasting capability of CUACE/Dust in the short-term variability in the spatial distribution and intensity of dust concentrations in both source regions and downwind areas.  By now The DAS was upgrade to assimilate FY-4A dust aerosol observations. The seasonal mean Threat Score (TS) over the East Asia in spring increased when DAS was used. The forecast results with DAS usually agree with the dust loading retrieved from FY and visibility distribution from surface meteorological stations, which indicates that the 3D-Var method is very powerful by the unification of observation and numerical model to improve the performance of forecast model.</p>