Preprint Article Version 1 Preserved in Portico This version is not peer-reviewed

Application of HYSPLIT and WRF/Chem Models to Investigate the Dust Storm Episodes

Version 1 : Received: 15 October 2016 / Approved: 17 October 2016 / Online: 17 October 2016 (12:16:08 CEST)

How to cite: Broomandi, P.; Dabir, B.; Bonakdarpour, B.; Rashidi, Y. Application of HYSPLIT and WRF/Chem Models to Investigate the Dust Storm Episodes. Preprints 2016, 2016100068. https://doi.org/10.20944/preprints201610.0068.v1 Broomandi, P.; Dabir, B.; Bonakdarpour, B.; Rashidi, Y. Application of HYSPLIT and WRF/Chem Models to Investigate the Dust Storm Episodes. Preprints 2016, 2016100068. https://doi.org/10.20944/preprints201610.0068.v1

Abstract

Background: Long-range transport of dust aerosol has intense impacts on the atmospheric environment over wide areas. Methods: The annual and seasonal changes in meteorological parameters associated with the occurrence of dust storms were studied. The features of an intense dust storm and its transport characteristics were studied during June 7th to June 9th 2010 in Ahvaz city. Temporal and spatial distribution of Middle Eastern dust storm event was analyzed by models of HYSPLIT and WRF/Chem, and in- situ observations. Results: A disagreement between the occurrences of dust storms, temperature, relative humidity and rainfall, show the major source of dust storms over Ahvaz city are neighboring countries. Using HYSPLIT results, the dust particles are mainly transported from north western region of Iraq and eastern Syria to downward areas including Ahvaz city. The arrived Dust aerosols mixed with local anthropogenic emissions, led to the highest PM10 concentration of 4200 ppm. The model results were found to well reproduce temporal and spatial distribution of mineral dust concentrations according to in-situ measurements. Conclusion: The performance of WRF/Chem was acceptable for simulation of temporal and spatial distributions of dust storm events. Therefore, it can be taken as a reference in daily air quality forecasting.

Keywords

particulate matter; dust storm; meteorological parameter; HYSPLIT; WRF/Chem

Subject

Environmental and Earth Sciences, Environmental Science

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