Application of WRF-Chem and HYSPLIT Models for Dust Storm Analysis in Central Iran (Case Study of Isfahan Province, 21–23 May 2016) DOI Creative Commons
Farshad Soleimani Sardoo, Nasim Hossein Hamzeh‎, Nir Y. Krakauer

et al.

Atmosphere, Journal Year: 2025, Volume and Issue: 16(4), P. 383 - 383

Published: March 27, 2025

Dust is one of the most important problems human societies in arid and semi-arid areas. This study analyzed rising propagation dust storm occurring from 21 to 23 May 2016 Isfahan province (Central Iran) by using WRF-Chem HYSPLIT models. The was visualized visible imagery coarse-mode aerosol optical depth data satellite sensor data, emission transport were simulated for Central Iran with AFWA GOCART schemes. results show that concentration Sistan Baluchistan Persian Gulf as high 2000 µg/m3, both schemes estimate highest amount emissions central parts eastern part province. PM10 Yazd station used verify model outputs, which showed scheme has a higher correlation coefficient observations (0.62) than scheme. case suggests simulate reasonably good reliability, though further determination enhancement are still required an accurate prediction extents.

Language: Английский

Long-Term Spatio-Temporal Analysis, Distribution, and Trends of Dust Events over Iran DOI Creative Commons

Abbas Ranjbar Saadat Abadi,

Nasim Hossein Hamzeh‎, Dimitris G. Kaskaoutis

et al.

Atmosphere, Journal Year: 2025, Volume and Issue: 16(3), P. 334 - 334

Published: March 16, 2025

This study provides a comprehensive evaluation of dust events over Iran, using synoptic data from 286 meteorological stations. The are classified according to codes as suspended and others (i.e., blowing dust, storms) based on their intensity with horizontal visibility ≤1, 3, 5, 10 km. Severe (visibility ≤ 1 km) (code 06) occurred primarily in the western parts while moderate or severe dominated south eastern thus revealing contrasting spatial distribution regarding type frequency events. Furthermore, distinct seasonality is revealed number events, since maximized SW Iran March July, highly associated Shamal winds, storms east April August. Zabol city, some stations along coast Arabian Sea impacted by this storm throughout year. Trend analysis notable increase during period 1994–2023, particularly part mostly attributed transboundary Mesopotamian plains. large activity 1994–2009 was followed decrease 2010s at many stations, differences were observed trends dust. An inverse correlation between precipitation anomalies observed, years abnormal (e.g., 2019; 138% increase) related substantial occurrence. Over an 11-year period, surface concentrations exceeded annual PM10 threshold 50 µg/m3 more than 800 days, maximum reaching up 1411 µg/m3. highlights urgent need for effective management strategies mitigate impacts air quality public health Iran.

Language: Английский

Citations

2
Application of WRF-Chem and HYSPLIT Models for Dust Storm Analysis in Central Iran (Case Study of Isfahan Province, 21–23 May 2016) DOI Creative Commons
Farshad Soleimani Sardoo, Nasim Hossein Hamzeh‎, Nir Y. Krakauer

et al.

Atmosphere, Journal Year: 2025, Volume and Issue: 16(4), P. 383 - 383

Published: March 27, 2025

Dust is one of the most important problems human societies in arid and semi-arid areas. This study analyzed rising propagation dust storm occurring from 21 to 23 May 2016 Isfahan province (Central Iran) by using WRF-Chem HYSPLIT models. The was visualized visible imagery coarse-mode aerosol optical depth data satellite sensor data, emission transport were simulated for Central Iran with AFWA GOCART schemes. results show that concentration Sistan Baluchistan Persian Gulf as high 2000 µg/m3, both schemes estimate highest amount emissions central parts eastern part province. PM10 Yazd station used verify model outputs, which showed scheme has a higher correlation coefficient observations (0.62) than scheme. case suggests simulate reasonably good reliability, though further determination enhancement are still required an accurate prediction extents.

Language: Английский

Citations

0