In the span of three decades, Central Asia witnessed a notable surge in dust emissions, directly correlated with the drying of the Aral Sea, Phys.org reports. Research reveals a staggering 7% rise in dust levels over this period, with emissions from the expanding Aralkum Desert nearly doubling from 14 mn tons to 27 mn tons between 1984 and 2015.
These findings, presented during the Second Central Asian Dust Conference (CADUC-2) in Nukus, Uzbekistan, underscore the environmental ramifications of the Aral Sea's depletion.
Research conducted by the Leibniz Institute for Tropospheric Research (TROPOS) and the Free University of Berlin suggests that traditional satellite observations, often hindered by cloud cover, likely underestimated these emissions. As a result, two-thirds of the actual dust swirls up unnoticed under cloudy conditions, complicating accurate measurement.
The increase in dust not only threatens local inhabitants by reducing air quality, especially in urban areas like the capitals of Tajikistan and Turkmenistan but also contributes to the accelerated melting of glaciers. This exacerbates the ongoing water scarcity issues in the region. The Aral Sea, formerly the globe’s fourth-largest lake, has been reduced substantially by agricultural water diversion, leading to the Aralkum Desert’s emergence.
The COSMO-MUSCAT atmospheric dust model was utilized by researchers to simulate dust emissions and their impacts. This study identified that dust from the Aralkum Desert may have a dual effect on climate:
- it cools the surface during the day by blocking sunlight;
- it warms it at night by reflecting long-wave radiation.
Additionally, changes in dust emissions might influence regional weather patterns, potentially strengthening the Siberian high in winter and weakening the Central Asian heat low during summer months.
Despite the strides in understanding, many aspects of Aralkum dust and its broader climatic effects remain unclear. Scientists are advocating for more detailed studies on the dust's optical properties to enhance satellite detection and forecasting accuracy.
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