Applicability Analysis of Vegetation Condition and Dryness for Sand and Dust Storm (SDS) Risk Reduction in SDS Source and Receptor Region

Aeolian disaster risk evaluation in the African Sahel

The Sahel is facing a serious environmental crisis due to aeolian disaster that has seriously affected the local development and survival of residents. Thus, evaluating the aeolian disaster risk levels and their variation in the Sahel is important. This study established an optimal model by evaluating the applicability of different models in the aeolian disaster risk determination in the Sahel. Using this model, the spatiotemporal changes in the risk subsystem of aeolian disaster (hazard, sensitivity, vulnerability, and restorability) and the aeolian disaster risk in the Sahel from 2000 to 2020 were analyzed. Based on this analysis, the impact of climate change and human activities on the aeolian disaster risk in the Sahel was evaluated. Results revealed that the variable fuzzy recognition (VFR) based on the aeolian disaster risk index (ADRI) model had the highest accuracy, reaching 89.72 %. The middle of the Sahel, located in the desert-grassland transition zone, exhibited a high hazard, sensitivity, and vulnerability, rendering it highly susceptible to aeolian disaster. The proportion of areas with very low and very high aeolian disaster risk levels decreased from 2000 to 2020, while those with low and high levels increased, and the change in moderate risk level areas remained relatively stable. Areas of low, moderate, and high risk are more sensitive to climate change and human activities and are subjected to greater pressure for change. Human activities were the main factor for the change of ADRI in the Sahel, accounting for 69.74 and 58.19 % of the increased and decreased areas of ADRI, respectively. This study evaluated the level of aeolian disaster risk in the Sahel and identified the main driving factors, providing a reference for Sahel countries to better implement the Green Great Wall (GGW) program in Africa, thereby mitigating the adverse effects of aeolian disaster.

Assessing the impact of sand and dust storm on agriculture: Empirical evidence from Mongolia

Assessing the economic impact of sand and dust storms provides critical insights to policy development and reforms; a subject that is gaining more attention as risk management becomes the dominant approach for hazard mitigation policies. To assess the causal impact of sand and dust storms on agriculture, specifically on crop and livestock revenue and physical production, random year-to-year variations in dust exposure were analyzed using a fixed effect regression. To complete this analysis, weather and climate data from the on-ground meteorological stations was combined with the household level socioeconomic surveys conducted by Mongolia's National Statistics Office (NSO) over a decade. The descriptive statistics of the meteorological data collected over the eight years period show that, on average, 29 dust events have occurred every year across the country, with greater variation among provinces (Aimags) and regions, reaching up to 108 events in a year in some provinces. The overall trend reveals a slight decrease in the dust events from 2009 to 2019. The econometric results show that value of crop and livestock production (gross income) and physical yields significantly decline in response to higher frequencies of sand and dust storms events. During this period, Mongolia experienced a 2.7% decline in crop revenue as a result of additional sand and dust storms. Assuming 2.7% constant decline in revenues across all agricultural sub-sectors and regions or Aimags, this could lead to about $37.8 million in losses to the economy, which is equivalent to about 0.27% of the national GDP of Mongolia. Increases in the frequency of sand and dust storms could reduce agricultural productivity by between 1.5% to 24%, depending on the crop. Estimates from the modelling exercise are robust to potential endogeneity bias in the measure of sand and dust storms; different specification and identification approaches accounting for the endogeneity bias consistently reveal negative and qualitatively similar impacts of sand and dust storms on crop and livestock productivity.

Insights into Variations and Potential Long-Range Transport of Atmospheric Aerosols from the Aral Sea Basin in Central Asia

The dramatic shrinkage of the Aral Sea in the past decades has inevitably led to an environmental calamity. Existing knowledge on the variations and potential transport of atmospheric aerosols from the Aral Sea Basin (ASB) is limited. To bridge this knowledge gap, this study tried to identify the variations and long-range transport of atmospheric aerosols from the ASB in recent years. The Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model and Cloud–Aerosol Lidar and Infrared Pathfinder Satellite Observations (CALIPSO) data were used to gain new insight into the types, variation and long-range transport of atmospheric aerosols from the ASB. The results showed five types of tropospheric aerosols and one type of stratospheric aerosol were observed over the ASB. Polluted dust and dust were the dominant subtypes through the year. Sulfate/other was the only stratospheric aerosol detected. The occurrence frequency of aerosols over the ASB showed obvious seasonal variation. Maximum occurrence frequency of dust appeared in spring (MAM) and that of polluted dust peaked in summer (JJA). The monthly occurrence frequency of dust and polluted dust exhibited unimodal distribution. Polluted dust and dust were distributed over wide ranges from 1 km to 5 km vertically. The multi-year average thickness of polluted dust and dust layers was around 1.3 km. Their potential long-range transport in different directions mainly impacts Uzbekistan, Turkmenistan, Kazakhstan and eastern Iran, and may reach as far as the Caucasus region, part of China, Mongolia and Russia. Combining aerosol lidar, atmospheric climate models and geochemical methods is strongly suggested to gain clarity on the variations and long-range transport of atmospheric aerosols from the Aral Sea Basin.