Original Research

Determination of dust storms by Hoffman index in Tehran, Iran and compare with remote sensing, and responsible organizations from March 2014 through March 2015

Abstract

Introduction: The occurrence of dust storms in recent years, has led to the use of data recorded in ground measurements stations to determine the sources and investigate the occurrence of these storms in the past; however, it is associated with the possibility of measurement errors or failures in some cases.
Materials and methods: In this study, using the data records by synoptically stations, dust storms that occurred in Tehran during March 21, 2014 to March 20, 2015 were determined.
To verify the detected cases of dust storms through the index, satellite imagery was collected and analyzed on the days. For remote sensing, Modis Level 1 images were processed using the ENVI 5.3. In order to show dust, NDDI, BTD (32-31), and BTD (20-31) indices were used.  Finally, the sensitivity and specificity of all two items were compared with the weather data announced on these days; using R software.
Results: Results indicate, compared to actual observations, that the sensitivity of this method was 100% and its specificity was 98%.
Conclusion: Because the index used in this study consisted of three parameters of wind speed, PM10 concentration, and horizontal visibility, it minimized the possibility of mistakes due to the simultaneous use of all three parameters to show dust storms.

1. Samadi M, Boloorani AD, Alavipanah SK, Mohamadi H, Najafi MS. Global dust Detection Index (GDDI); a new remotely sensed methodology for dust storms detection. Journal of Environmental Health Science and Engineering. 2014;12(1):1.
2. Esmaili O, Tajrishy M, Arasteh PD, editors. Evaluation of dust sources in Iran through remote sensing and synoptical analysis. Atlantic Europe conference on remote imaging and, spectroscopy; 2006.
3. Company AQC. Tehran Annual Air Quality Report Period of March 2014-March 2015. Air Quality Control Company. 2015 QM94/02/02(U)/1.
4. Cuevas E. Establishing a WMO sand and dust storm warning advisory and assessment system regional node for West Asia: current capabilities and needs. WMO Technical Report. 2013.
5. Hejazi SAM, MR. Majidi, D. Using satellite imagery to calculate the horizontal visibility of the atmosphere. Climatology research Journal. 2014. [In Persian].
6. Tan M, Li X, Xin L. Intensity of dust storms in China from 1980 to 2007: A new definition. Atmospheric Environment. 2014;85:215-22.
7. Meddleton NJ. A geography of dust storm in south-west Asia. Journal of Climatology. 1986;6(2):183-96.
8. Shao Y. Physics and modelling of wind erosion: Springer Science & Business Media; 2008.
9. Rashki A, Kaskaoutis D, Francois P, Kosmopoulos P, Legrand M. Dust-storm dynamics over Sistan region, Iran: Seasonality, transport characteristics and affected areas. Aeolian Research. 2015;16:35-48.
10. Rashki A, Rautenbach CD, Eriksson PG, Kaskaoutis DG, Gupta P. Temporal changes of particulate concentration in the ambient air over the city of Zahedan, Iran. Air Quality, Atmosphere & Health. 2013;6(1):123-35.
11. Yang KL. Spatial and seasonal variation of PM10 mass concentrations in Taiwan. Atmospheric Environment. 2002;36(21):3403–11.
12. Shahsavani A. Analysis of Dust Storms Entering Iran with Emphasis on Khuzestan Province. Hakim Research Journal. 2012; 15(3): 192- 202. 2012.
13. Ardehjani SS. IR of Iran National Report on Regional Action Plan to combat dust and sand storm. International Cooperative for Aerosol Prediction (ICAP) 4th Workshop: Aerosol Emission and Removal Processes. 2012 (PP.14-17).
14. Hoffmann C, Funk R, Sommer M, Li Y. Temporal variations in PM10 and particle size distribution during Asian dust storms in Inner Mongolia. Atmospheric Environment. 2008;42(36):8422-31.
15. NNDC Climate Data online [Internet]. NOAA. Available from: http://www7.ncdc.noaa.gov/CDO/cdoselect.cmd.
16. Li X, Song W. Dust Storm Detection Based on Modis Data. International Conference on Geo-spatial Solutions for Emergency Management and the 50th Anniversary of the Chinese Academy of Surveying and Mapping; Beijing, China 2009 Sep 14 (pp. 14-19).
17. Bertina H. Detection of the dust masses of the Middle East on the basis of spectral data MODIS. The Study of Natural Geography. 2013.
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IssueVol 4 No 4 (2019): Autumn 2019 QRcode
SectionOriginal Research
DOI https://doi.org/10.18502/japh.v4i4.2200
Keywords
Dust storm; Hoffman index; PM10 concentration

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Creative Commons License This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
How to Cite
1.
Zeydabadi A, Naddafi K, Nabizadeh R, Hassanvand MS, Golpayegani A. Determination of dust storms by Hoffman index in Tehran, Iran and compare with remote sensing, and responsible organizations from March 2014 through March 2015. JAPH. 2020;4(4):261-268.