Hydrophysics

Hydrophysics

Monitoring Dry Deposition of Dust Particles in the Persian Gulf and the Strait of Hormuz Using the WRF‑Chem Model and Comparison with CAMS (Case Study: 28–31 July 2018)

Document Type : Original Article

Authors
Roohollah Davoodi 1
Hossein Malakooti 2
Sara Karami 3
1 Department of Marine and Atmospheric Science (non-Biologic), University of Hormozgan, Bandar Abbas, Iran
2 Professor, Department of Marine and Atmospheric Sciences (Non-Biological), University of Hormozgan, Bandar Abbas, Iran
3 Assistant Professor of Meteorology, Air Pollution and Dust Group, Atmospheric Sciences and Meteorology Research Center (ASMERC), Tehran, Iran,
Abstract
Dust is one of the most important atmospheric pollutants and has significant impacts on air quality, human health, and marine and terrestrial ecosystems in West Asia. In this study, the dry deposition of dust particles during a dust storm over the Persian Gulf and the Strait of Hormuz from 28 to 31 July 2018 is investigated as a case study. To simulate dry deposition, the WRF‑Chem model was employed, and the results were compared with CAMS reanalysis data. During this period, the dust storm originated from the desert regions of southwest Asia, particularly the Arabian Peninsula, and was associated with prevailing northwesterly (Shamal) winds. The results indicate that the maximum deposition flux coincided with increased surface particulate matter concentrations and intensified wind speeds. The spatial pattern of maximum deposition in the northern and northwestern parts of the Persian Gulf shows that dust transport pathways are consistent with the prevailing atmospheric dynamical conditions. WRF‑Chem outputs exhibit good agreement with CAMS data in terms of the temporal and spatial distribution of dry deposition, although some differences are evident, especially at the peak dust concentration. A strong correlation between the two datasets (R = 0.76) demonstrates that WRF‑Chem successfully captures the temporal variability of dry dust particle deposition. These findings highlight the importance of accurate numerical simulations and the use of reanalysis datasets to improve understanding and assessment of mineral inputs to the marine ecosystems of the Persian Gulf.
Keywords
Dust particles
dry deposition
Persian Gulf
WRF-CHEM
CAMS
Subjects

1.       Seinfeld JH, Pandis SN. Atmospheric chemistry and physics: From air pollution to climate change. 3rd ed. Hoboken (NJ): John Wiley & Sons; 2016. doi:10.1002/9781119221166.

2.       Textor C, Schulz M, Guibert S, Kinne S, Balkanski Y, Bauer S, et al. Analysis and quantification of the diversities of aerosol life cycles within AeroCom. Atmospheric Chemistry and Physics. 2006;6:1777‑1813. doi:10.5194/acp-6-1777-2006.

3.       Prospero JM, Ginoux P, Torres O, Nicholson SE, Gill TE. Environmental characterization of global sources of atmospheric soil dust. Reviews of Geophysics.2002;40(1):1002. doi:10.1029/2000RG000095.

4.       Jickells TD, An ZS, Andersen KK, Baker AR, Bergametti G, Brooks N, et al. Global iron connections between desert dust and ocean biogeochemistry. Science.2005;308(5718): 67‑71. doi:10.1126/science.1105959.

5.       Alizadeh Choobari O, Zawar‑Reza P, Sturman A. Dust storms in the Middle East: Dynamics and modeling. Atmos Environmental. 2014;82:343‑353. doi:10.1016/j.atmosenv.2013.10.031.

6.       Yu Y, Notaro M, Kalashnikova OV, Garay MJ. The climatology of Shamal wind events over the Persian Gulf. Journal of Geophysical Research: Atmospheres.2016;121(1):289‑305. doi:10.1002/2015JD024063.

7.       Grell GA, Peckham SE, Schmitz R, McKeen SA, Frost G, Skamarock WC, et al. Fully coupled online chemistry within the WRF model. Atmos Environmental. 2005;39(37):6957‑75. doi:10.1016/j.atmosenv.2005.04.027.

8.       Zhang L, Gong S, Padro J, Barrie L. A size‑segregated particle dry deposition scheme for an atmospheric aerosol module. Atmos Environmental. 2001;35(3):549‑60. doi:10.1016/S1352-2310(00)00426-0.

9.       Inness A, Ades M, Agustí‑Panareda A, Barré J, Benedictow A, Blechschmidt AM, et al. The CAMS reanalysis of atmospheric composition. Atmospheric Chemistry and Physics. 2019;19:3515-56.  doi:10.5194/acp-19-3515-2019.

10.    Eskes H, Huijnen V, Arola A, Benedictow A, Blechschmidt AM, Bouarar I, et al. Validation of the CAMS global reanalysis. Atmospheric Measurement Techniques.2020;13(6):2961-87. doi:10.5194/amt-13-2961-2020.

11.    Benedetti A, Morcrette JJ, Boucher O, Dethof A, Engelen RJ, Fisher M, et al. Aerosol analysis and forecast in the ECMWF Integrated Forecast System. Journal of Geophysical Research: Atmospheres - AGU Journals. 2009;114:D13210. doi:10.1029/2008JD011235.

12.    Wesely ML. Parameterization of surface resistances to gaseous dry deposition. Atmos Environmental. 1989;23(6):1293‑1304. doi:10.1016/0004-6981(89)90153-4.

13.    Slinn WGN. Predictions for particle deposition to vegetative canopies. Atmos Environmental. 1982;16(7):1785‑94. doi:10.1016/0004-6981(82)90271-2.

14.    Zhang L, Brook JR, Vet R. A revised parameterization for gaseous dry deposition in air quality models. Atmospheric Chemistry and Physics.  2003;3:2067‑82. doi:10.5194/acp-3-2067-2003.

15.    Fast JD, Gustafson WI Jr, Easter RC, Zaveri RA, Barnard JC, Chapman EG, et al. Evolution of ozone, particulates, and aerosol direct radiative forcing near Houston. Journal of Geophysical Research: Atmospheres - AGU Journals. 2006;111:D24S19. doi:10.1029/2005JD006721.

16.    Hersbach H, Bell B, Berrisford P, Hirahara S, Horányi A, Muñoz‑Sabater J, et al. The ERA5 global reanalysis. Quarterly Journal of the Royal Meteorological Society. 2020;146(730):1999‑2049. doi:10.1002/qj.3803.

17.    Ginoux P, Chin M, Tegen I, Prospero JM, Holben B, Dubovik O, et al. Sources and distributions of dust aerosols simulated with the GOCART model. Journal of Geophysical Research: Atmosphere. 2001;106(D17):20255‑73. doi:10.1029/2000JD000053.

18.    Chin M, Ginoux P, Kinne S, Holben BN, Duncan BN, Martin RV, et al. Tropospheric aerosol optical thickness from the GOCART model. Journal of the Atmospheric Sciences. 2002;59(3):461‑83. doi:10.1175/1520-0469(2002)059<0461:TAOTFT>2.0.CO;2.

19.    Eskes H, Benedictow A, Blechschmidt AM, Chabrillat S, Christophe Y, Cuevas E, et al. CAMS atmospheric composition reanalysis 2003–2018. Atmospheric Chemistry and Physics.  2020;20:3515‑56. doi:10.5194/acp-20-3515-2020.

20.    Inness A, Ades M, Agustí‑Panareda A, Barré J, Benedictow A, Blechschmidt AM, et al. CAMS reanalysis of atmospheric composition (update). Atmospheric Chemistry and Physics.  2022;22:4617‑4660. doi:10.5194/acp-22-4617-2022.

21.    Parajuli SP, Yang ZL, Kocurek G. Dust emission and transport modeling with WRF‑Chem. Atmos Environmental. 2020;224:117220. doi:10.1016/j.atmosenv.2019.117220.

22.    Nabavi SO, Haimberger L, Samimi C. Dust transport pathways and synoptic patterns over the Middle East. ATMOS Research. 2021;249:105550. doi:10.1016/j.atmosres.2021.105550.

23.    Alizadeh Choobari O, Ghanei M, Middleton N, Prospero JM. Meteorological drivers of dust storms over the Middle East. Aeolian Research.2023;63:100879. doi:10.1016/j.aeolia.2023.100879.

24.    Qin Y, Lin J, Chen Y, Fu TM, Zhuang B, Zhang L. A revised mineral dust emission scheme in GEOS‑Chem. Atmospheric Chemistry and Physics.  2021;21:4319‑39. doi:10.5194/acp-21-4319-2021.

25.    Chen Y, Liu Y, Ma S, Kok JF, Li Q. Impacts of dynamic dust sources coupled with WRF‑Chem 3.9.1 on dust simulation over East Asia. Geoscientific Model Development 2023;16(4):1233‑54. doi:10.5194/gmd-16-1233-2023.

26.Kaskaoutis DG, Houssos EE, Rashki A, Legrand M, Dumka UC, Mofidi A, et al. Long‑term variability of dust events in southwestern Iran. Atmosphere. 2021;12(10):1350. doi:10.3390/atmos12101350.

Hydrophysics
Volume 11, Issue 1 - Serial Number 20
September 2025
Pages 47-56

  • Receive Date 16 February 2026
  • Revise Date 19 March 2026
  • Accept Date 01 April 2026