A model tool for assessing real-time mixing of mineral and anthropogenic pollutants in East Asia: a case study of April 2005
1Laboratoire de Météorologie Physique, Université Blaise Pascal, Complexe scientifique des Cézeaux, BP 45, 63170, Aubière, France
2Sino-Japan Friendship Center for Environmental Protection, Beijing 100029, China
3Advanced Environment Monitoring Research Center, Department of Environmental Science and Engineering, Gwangju Institute of Science and Technology, 1 Oryong-dong, Gwangju 500-712, Korea
4National Institute for Environmental Studies, 16-2 Onogawa, Tsukuba, Ibaraki 305-8506, Japan
Abstract. In order to assess the complex mixing of atmospheric anthropogenic and natural pollutants over the East Asian region, we present a modelling tool which takes into account the main aerosols which are to be found simultaneously over China, Korea and Japan during springtime. Using the mesoscale RAMS (Regional Atmospheric Modeling System) tool, we present a simulation of natural (desert) dust events along with some of the most critical anthropogenic pollutants over East Asia, sulphur elements (SO2 and SO2-4) and Black Carbon (BC).
As regards a one-week case study of dust events which occurred during late April 2005 over an area extending from the Gobi deserts to the Japan surroundings, we satisfactorily model the behaviours of the different aerosol plumes. We focus on possible dust mixing with the anthropogenic pollutants from megacities. For both natural and anthropogenic pollution, the model results are in fairly good agreement with the horizontal and vertical distributions of concentrations as measured by in situ LIDAR, and as observed in remote data, PM10 data and literature. In particular, we show that a simplified chemistry approach of this complex issue is sufficient to model this event, with a real-time step of 3 h. The model reproduces the main patterns and orders of magnitude for Aerosol Optical Thickness (AOT) and species contributions (via the Angström Exponent) when compared with the AErosol RObotic NETwork (AERONET) data.