Integrative investigation of dust emissions by dust storms and dust devils in North Africa

Lin Pan; Yongxiang Han; Zhengqi Lu; Jiaxin Li; Fei Gao; Zhaohuan Liu; Weijia Liu; Yangang Liu

doi:10.1016/j.scitotenv.2020.144128

Integrative investigation of dust emissions by dust storms and dust devils in North Africa

Sci Total Environ. 2021 Feb 20:756:144128. doi: 10.1016/j.scitotenv.2020.144128. Epub 2020 Nov 26.

Authors

Lin Pan¹, Yongxiang Han², Zhengqi Lu³, Jiaxin Li³, Fei Gao⁴, Zhaohuan Liu³, Weijia Liu⁵, Yangang Liu⁶

Affiliations

¹ Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044, China; Zhoushan Meteorological Bureau, Zhoushan 316000, China.
² Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044, China. Electronic address: han-yx66@126.com.
³ Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044, China.
⁴ Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044, China; Inner Mongolia Meteorological Service Center, Inner Mongolia 010051, China.
⁵ Collaborative Innovation Center on Forecast and Evaluation of Meteorological Disasters, Nanjing University of Information Science and Technology, Nanjing 210044, China; Brookhaven National Laboratory, Upton, NY, USA.
⁶ Brookhaven National Laboratory, Upton, NY, USA.

PMID: 33288262
DOI: 10.1016/j.scitotenv.2020.144128

Abstract

Dust aerosols in North Africa account for >50% of the global total; however dust emission areas are still unclear. Based on the analysis of dust storms simulated with the numerical Weather Research and Forecast (WRF) model, satellite aerosol index (AI), and the dust data observed at 300 meteorological stations over 20 years, the spatio-temporal distribution characteristics of dust storm, dust devil and AI are compared and analyzed. The results show that: 1) There are two dust emission mechanisms: the dynamically-dominated dust storm and thermally-dominated dust devil; 2) Dust storms occur most frequently in Spring and are concentrated in the areas of Grand Erg Occidental Desert to the Erg Chech-Adrar Desert, the northern part of Grand Erg Oriental, the Atouila Desert to the Ouarane Desert, the Mediterranean coast, the eastern side of Nubian Desert and Bodélé Depression; 3) Dust devils occur most frequently from April to August and are mainly concentrated in the central part of North Africa, especially in the southwest of Hoggar Mountains to the west of Air Mountains, the border area of Egypt - Sudan - Libya and the vicinity of Tibesti Plateau; 4) The spatio-temporal distribution of AI is correlated more with the dust devils emission whereas the annual average contributions by dust storms and dust devils are 61.3% and 38.7%, respectively. This study discovers a new area of dust emissions by dust devils, and provides a better explanation for the spatio-temporal distribution of AI in North Africa.

Keywords: Dust devil; Dust emission; Dust storm; North Africa; WRF model.