期刊
REMOTE SENSING
卷 13, 期 6, 页码 -出版社
MDPI
DOI: 10.3390/rs13061056
关键词
lidars; dust storm; extinction coefficient; depolarization ratio; particulate concentration
类别
资金
- Foundation for National Natural Science Foundation of China [41805116, 42075105]
The study revealed that during a severe dust storm event, the ratio of PM2.5/PM10 was less than 0.2, with extinction coefficients greater than 1 km(-1) based on Lidar observations. Additionally, PM2.5 showed higher growth rates than PM10. Dust particles mainly concentrated at heights of 2 km, increasing in vertical height by 1-2 km after being transported about 200-300 km, with a marked decrease in concentration.
Dust storms have occurred frequently in northwest China and can dramatically reduce visibility and exacerbate air quality in downwind regions through long-range transport. In order to study the distribution characteristics of dust particles sizes, structures and concentrations in the process of dust storm, especially for the vertical distributions, the multi-observation platform composed of six Lidars and nine aerosol analytical instruments is first used to detect a severe dust storm event, which occurred in Northwest China on 3 May 2020. As a strong weather system process, the dust storm has achieved high intensity and wide range. When the intensity of a dust storm is at its strongest, the ratios of PM2.5 (particulate matter with diameter < 2.5 mu m) and PM10 (particulate matter with diameter < 10 mu m) (PM2.5/PM10) in cities examined were less than 0.2 and the extinction coefficients became greater than 1 km(-1) based on Lidar observations. In addition, the growth rates of PM2.5 were higher than that of PM10. The dust particles mainly concentrated at heights of 2 km, after being transported about 200-300 km, vertical height increased by 1-2 km. Meanwhile, the dust concentration decreased markedly. Furthermore, the depolarization ratio showed that dust in the Tengger Desert was dominated by spherical particles. The linear relationships between 532 nm extinction coefficient and the concentration of PM2.5 and PM10 were found firstly and their R-2 were 0.706 to 0.987. Our results could give more information for the physical schemes to simulate dust storms in specific models, which could improve the forecast of dust storms.
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