Transboundary transport of non-east and East Asian dust observed at Dunhuang, northwest China

Abstract

Long-range transport of North African and Middle Eastern dust has been frequently observed in East Asia. However, understanding of their characteristics and effects in this region is insufficient. In this study, the transboundary transport of multi-source dust was captured by a polarized micro-pulse lidar from April 5 to 10, 2012, during a field campaign in Dunhuang, northwest China. Six dust plumes (DN1-DN6) were selected based on the spatiotemporal evolution of the depolarization ratio. Furthermore, the source, vertical characteristics of the coarse and fine components and their contributions were investigated by combining lidar observation with the WRF-Chem model simulation. The results indicated that DN1 was from Central Asia and it took approximately 4–5 days. DN2 originated from sources in North Africa and the Middle East and took approximately 6–7 days to reach Dunhuang. Samples DN3-DN6 originated from the Taklimakan and Gobi deserts in East Asia. A noticeable contrast was observed in the vertical distribution of the coarse and fine components between the long-range transported (DN1∼DN2) and fresh (DN3∼DN6) dust plumes. DN1 and DN2 presented comparable dust components (DD = Dc + Df, where Dc and Df are coarse- and fine-mode dust, respectively) and non-dust (ND) component contributions and a high predominance of Dc particles was present with at least 40% of total components in DN3-DN4. The contribution of ND particles was nearly negligible in DN5 and DN6. Lidar observations and model simulation both indicated that the maximum contribution of North African and Middle Eastern dust to the local aerosol loading exceeded 58%. However, the model simulation underestimated the contribution of DN1 by an average of 18% compared to lidar observations because DN1 was not reproduced well. This implies that the vertical distribution of dust should be carefully considered when dust impacts (e.g., radiation effects and air quality) are finely assessed using a model on a regional scale.