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Dust storm simulation over Iran using HYSPLIT.
Khosro Ashrafi, Majid Shafiepour-Motlagh, Alireza Aslemand1
1Graduate Faculty of Environment, University of Tehran, Tehran, Iran. aaslemand@ut.ac.ir.
Journal of Environmental Health Science & Engineering
|January 9, 2014
Summary
Dust storms originating from the Syrian Desert significantly impact Iran, causing high PM10 concentrations. This study identifies dust sources and simulates trajectories using the HYSPLIT model.
Area of Science:
- Environmental Science
- Atmospheric Science
- Geosciences
Background:
- Particulate matter poses significant risks to human health, the environment, and economies.
- Natural sources, particularly wind erosion in arid regions, are major contributors to atmospheric particulate matter.
- Increased dust events from Arabian countries are affecting Iran, leading to environmental challenges.
Purpose of the Study:
- To identify dust sources impacting Iran.
- To simulate the trajectory of dust storms using numerical models.
- To investigate the environmental impact of increased dust events.
Main Methods:
- Utilized the Hybrid Single Particle Lagrangian Integrated Trajectory (HYSPLIT) model's dust module.
- Employed a PM10 dust storm emission algorithm for desert land use.
- Analyzed two case studies from May and June 2010, simulating dust hotspots and trajectories.
Main Results:
- Identified dust storms originating from the western Syrian Desert (32.50°N–33.80°N, 38.00°E–38.80°E) due to high wind shear (>8.5 m/s).
- Simulated dust plumes traveled east and southeast, reaching Ahvaz on May 18th and June 8th, 2010.
- Recorded high average PM10 concentrations of 625 μgm³ and 494 μgm³ at Ahvaz monitoring stations, consistent with MODIS satellite imagery.
Conclusions:
- The HYSPLIT model effectively identifies dust sources and simulates trajectories of dust storms impacting Iran.
- The western Syrian Desert is a significant source of PM10 pollution affecting western Iran.
- Dust storm events have severe environmental consequences, evidenced by high PM10 levels in affected regions.
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