New inventory of dust sources in Central Asia derived from the daily MODIS imagery

Abstract

This paper presents the first inventory of dust emission sources in Central Asia and western China (35-50°N, 50-100°E) derived from the twice daily MODIS imagery from 2003-2012. The high-resolution (1 km) dust enhancement product was generated and used to produce maps of dust point sources and gridded data sets of dust emission frequencies. The most active dust emissions were observed in the eastern part of the Tarim basin (Lop Nur salt lake) followed by the Aralkum. A high frequency of dust emissions was recorded in the regions which were not reported in literature to date: the upper Amudarya region in northern Afghanistan and the Pre-Aral region (from the Ustyurt Plateau to the Betpak Dala desert). Dust emissions were associated mainly with the fluvial features (dry river beds and lakes), agricultural activities and fire damage to vegetation. In the eastern and northern parts of the study region and in the Aralkum, dust emissions peaked in spring while in the western and southern parts, they peaked in summer. The Aralkum exhibited a consistent growth in the frequency and intensity of dust emissions and similar but weaker trends were observed in the Karakum and Kyzylkum.

Physical and chemical properties of dust in the Pre-Aral region of Uzbekistan

“…The salts from the Aralkum are coming by sandstorm every year and the ecology is fragile. High frequency and intensity dust emissions are reported (Nobakht et al 2019) in the Pre-Aral region from the Aralkum, Karakum, and Kyzylkum Deserts. So, occurrence of respiratory diseases in this area resulting from air pollution can be quite substantial.…”

Evaluating dust emission model performance using dichotomous satellite observations of dust emission

“…Their sun-synchronous orbits permit repeat observations at the same mean solar time, with Terra and Aqua spacecraft crossing the equator at 10:30 am and 1:30 pm (local time) respectively. For dust plume identification, a dust enhancement product is produced using brightness temperature differences (BTD) between a combination of visible bands (B1 (v. red: 0.645 μm), B3 (v. blue: 0.470 μm), B4 (v. green: 0.555 μm)), near infrared (NIR) (B26: 1.375 μm) and TIR bands (B31: 11.03 μm and B32: 12.02 μm) to distinguish dust plumes from the surface and other atmospheric conditions (e.g., clouds, biomass burning) (Nobakht et al, 2019). These BTDs distinguish the elevated plume as a thermal anomaly from the desert surface below, the calculated value (dimensionless) is included as the red beam of a RGB false colour composite (FCC) image, with blue and green beams using visible bands B3 and B4 (Fig.…”

“…Our new evaluation is based on two novel approaches. The first is the collation of satellite observed dust emission point source (DPS) data from nine peer-reviewed studies (Baddock et al, 2009;Bullard et al, 2008;Eckardt et al, 2020;Hennen et al, 2019;Kandakji et al, 2020;Lee et al, 2012;Nobakht et al, 2019;Schepanski et al, 2007;von Holdt et al, 2017). DPS data describe dichotomous (presence=1 or absence=0) dust emission for selected regions and selected times.…”