Volume 10, Issue 1 (5-2023)
Journal of Spatial Analysis Environmental Hazards 2023, 10(1): 71-90 |
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Sheikh ghaderi S H, Alizadeh T, Ziaeian Firoozabadi P, Sharifi R. Temporal and spatial analysis of dust storms in Kermanshah. Journal of Spatial Analysis Environmental Hazards 2023; 10 (1) :71-90
URL: http://jsaeh.khu.ac.ir/article-1-3273-en.html
URL: http://jsaeh.khu.ac.ir/article-1-3273-en.html
1- , alizadehtoba@yahoo.com
Abstract: (2834 Views)
Abstract
The aim of this study was to analyze the temporal and spatial nature of dust storms during the period 2016 to 2018 in Kermanshah Using the HYSPLIT routing model and the MCD19A2 product, the Modis sensor was performed in the Google Earth web engine.In order to route the origin of dust particles, the Lagrangian method of HYSPLIT model was used in 48 hours before the occurrence of dust phenomenon in Kermanshah at three altitude levels of 200, 1000 and 1500 meters.Findings from HYSPLIT model tracking maps indicate that the general route for dust transfer to the study area is the north-west-southeast route with the origin of the deserts of Iraq and Syria at three altitudes of 200, 1000 and 1500 meters. On June 17, 2016 and October 27, 2018, as well as the southwest-west route originating in Kuwait, Northern Saudi Arabia and part of Iraq on November 2, 2017.The results of the maps obtained from the MCD19A2 product of the Modis sensor, especially the maps of periodicity, cumulative concentration, spatial variation and the highest AOD map, show a high correlation with the routed maps extracted from the HYSPLIT model. In general, based on the findings of the maps extracted from the product MCD19A2, Modis sensor during the period 2016 to 2018 in Kermanshah, the central and eastern regions have always been more affected by dust storms than in other parts of the city. On average, they were more exposed to dust pollution than other parts of the city. In this regard, the final results show a high correlation between the actual PM10 data and the AOD values derived from the MODIS sensor.
Keyword: Dust, AOD, Modis, HYSPLIT, Kermanshah, Google Earth Engine
Type of Study: Research |
Subject:
Special
Received: 2021/11/28 | Accepted: 2023/02/14 | Published: 2023/10/4
Received: 2021/11/28 | Accepted: 2023/02/14 | Published: 2023/10/4
References
1. ارجمند، مریم؛ علیرضا راشکی و حسین سرگزی. 1397. پایش زمانی و مکانی پدیده گردوغبار با استفاده از داده‌های ماهواره‌ای در جنوب شرق ایران، با تأکید بر منطقه جازموریان. فصلنامه علمی- پژوهشی اطلاعات جغرافیایی سپه.(106) 27:153-168.
2. رضوی زاده، سمانه؛ حمیدرضا عباسی و فاطمه درگاهیان. 1400. بررسی پدیده گردوغبار در استان گلستان، با تأکید بر شاخص عمق اپتیکی و سمت و سرعت باد. مجله علوم و مهندسی آبخیزداری ایران، (53) 15: 67-58.
3. شمسی‌پور، علی‌اکبر و طاهر صفر راد،. 1391. تحلیل ماهواره‌ای – همدیدی پدیده‌ی گردوغبار تیرماه 1388. مجله پژوهش‌های جغرافیای طبیعی، شماره 79: 111- 126.
4. علیزاده، طوبی، مجید رضایی بنفشه؛ غلامرضا گودرزی و سیدهدایت شیخ قادری. 1400. ردیابی و شبیه‌سازی عددی طوفان گردوغبار در شهر کرمانشاه، نشریه مدیریت بیابان، (2)9: 1- 14.
5. فاطمی، سیدباقر و یوسف رضایی. 1396. مبانی سنجش‌ازدور، چاپ پنجم، انتشارات آزاده، تهران.
6. میری، مرتضی. 1390. واکاوی – همدیدی پدیده گردوغبار در نیمه غربی ایران، پایان‌نامه کارشناسی ارشد، دانشکده جغرافیا، دانشگاه تهران.
7. ناصرپور، سمیه؛ بهلول علیجانی و پرویز ضیائیان. 1394. منشایابی توفان‌های گردوغبار در جنوب غرب ایران با استفاده از تصاویر ماهواره‌ای و نقشه‌های هوا. پژوهش‌های جغرافیای طبیعی (پژوهش‌های جغرافیایی).(1)47: 36-21.
8. Alam, K., T. Trautmann., T. Blaschke., and F. Subhan., 2014. Changes in aerosol optical properties due to dust storms in the Middle East and Southwest Asia. Remote Sensing of Environment, 143. 216-227.
9. Amani, M., S. Mahdavi., M. Afshar., B. Brisco., W. Huang., S. Mohammad Javad Mirzadeh., and C. Hopkinson. 2019. Canadian wetland inventory using Google Earth engine: the first map and preliminary results. Remote Sensing,11 (7), 842.
10. Behyar, M.B., 2015. Zoning the Degree of Risk of Fog and Dust Storms in the Country's road Network using Satellite data. Geographical Research Quarterly, 30(2), 105-125.
11. Boloorani, A.D., N.N. Samany., R., Papi and M. Soleimani. 2021. Dust source susceptibility mapping in Tigris and Euphrates basin using remotely sensed imagery. CATENA, 209, 105795.
12. Dey, S., S.N. Tripathi., R.P. Singh and B.N, Holben. 2004. Influence of dust storms on the aerosol optical properties over the Indo‐ Gangetic basin. Journal of Geophysical Research: Atmospheres, 109(20), 13-1.
13. Dong, Z., X. Yu., X. Li and J. Dai. 2013. Analysis of variation trends and causes of aerosol optical depth in Shaanxi Province using MODIS data. Chinese Science Bulletin, 58(35), 4486-4496.
14. Gorelick, N., M. Hancher., M. Dixon., S. Ilyushchenko., D. Thau and R. Moore. 2017. Google Earth Engine: Planetary-scale geospatial analysis for everyone. Remote sensing of Environment, 202, 18-27.
15. Goudie, A.S and N.J. Middleton. 2000. Dust storms in southwest Asia. Acta Universitatis Carolinae, Supplement, 7383.
16. Goudie, A.S and N.J. Middleton. 2001. Saharan dust storms: nature and consequences. Earth-science reviews, 56(1-4), 179-204.
17. Ichoku, C., L. A. Remer., Y. J. Kaufman., R. Levy., D. A. Chu., D. Tanré and B. N. Holben. 2003. MODIS observation of aerosols and estimation of aerosol radiative forcing over southern Africa during SAFARI 2000. Journal of geophysical research: atmospheres, 108 (13).
18. Kaskaoutis, D. G., P. Kosmopoulos.. H. D. Kambezidis and P. T. Nastos. 2007. Aerosol climatology and discrimination of different types over Athens, Greece, based on MODIS data. Atmospheric Environment, 41(34), 7315-7329.
19. Klingmüller, K., A. Pozzer., S. Metzger., G.L. Stenchikov and J. Lelieveld. 2016. Aerosol optical depth trend over the Middle East. Atmospheric Chemistry and Physics, 16(8), 5063-5073.
20. Kumar, L and O. Mutanga. 2018. Google Earth Engine applications since inception: Usage, trends, and potential. Remote Sensing, 10(10), 1509.
21. Lin, C., Y. Li., A.K. Lau., X. Deng., K. Tim., J.C. Fung., C. Li., Z. Li., X. Lu and X. Zhang. 2016. Estimation of long-term population exposure to PM 2.5 for dense urban areas using 1-km MODIS data. Remote Sensing of Environment, 179: 13-22.
22. Lyapustin, A and Y. Wang. 2018. MODIS Multi-Angle Implementation of Atmospheric Correction (MAIAC) Data User’s Guide. NASA: Greenbelt, MD, USA.
23. Mehta, M., R. Singh. A. Singh and N. Singh. 2016. Recent global aerosol optical depth variations and trends-A comparative study using MODIS and MISR level 3 datasets. Remote Sensing of Environment, 181: 137-150.
24. Mahmoudi, P and C.H. Allahbakhsh Rigi. 2019. Analyzing the time series changes trend of the Aerosol Optical Depth (AOD) index of Terra satellite’s MODIS sensor for Jazmorian basin in the southeast of Iran during.
25. Morcrette, J. J., O. Boucher., L. Jones., D. Salmond., P. Bechtold., A, Beljaars and A. Untch. 2009. Aerosol analysis and forecast in the European Centre for medium‐range weather forecasts integrated forecast system: Forward modeling. Journal of Geophysical Research: Atmospheres, 114(6), 17-1.
26. Namdari, S., K. K. Valizade., A. A. Rasuly and B. S. Sarraf. 2016. Spatio-temporal analysis of MODIS AOD over western part of Iran. Arabian Journal of Geosciences, 9(3), 191.
27. Qi, Y., J. Ge and J. Huang. 2013. Spatial and temporal distribution of MODIS and MISR aerosol optical depth over northern China and comparison with AERONET. Chinese Science Bulletin, 58(94): 2497-2506.
28. Rashki, A., D.G. Kaskaoutis., P.G. Eriksson., C.D.W. Rautenbach., C. Flamant and F. A. Vishkaee. 2014. Spatio-temporal variability of dust aerosols over the Sistan region in Iran based on satellite observations. Natural hazards, 71(1), 563-585.
29. Ranjan, A. K., A. K. Patra and A. K. Gorai. (2020). Effect of lockdown due to SARS COVID-19 on aerosol optical depth (AOD) over urban and mining regions in India. Science of the Total Environment, 745, 141024.
30. Sharma, D., D., Singh and D.G. Kaskaoutis. 2012. Impact of two intense dust storms on aerosol characteristics and radiative forcing over Patiala, northwestern India. Advances in Meteorology, 2012.
31. Silakhori, E., H.N. Gharemakhor and A. Aghtabai. 2018. Desertification risk assessment of Incheh-broun area in Golestan province using ESAs model. Iranian Journal of Range and Desert Research, 25(1).63-75.
32. Sorek-Hamer, M., I. Kloog., P. Koutrakis., A. W. Strawa., R. Chatfield., A. Cohen and D. M. Broday, 2015. Assessment of PM2. 5 concentrations over bright surfaces using MODIS satellite observations. Remote Sensing of Environment, 163, 180-185.
33. Tamiminia, H., B. Salehi., M. Mahdianpari., L. Quackenbush., S. Adeli and B. Brisco. 2020. Google Earth Engine for geo-big data applications: A meta-analysis and systematic review. ISPRS Journal of Photogrammetry and Remote Sensing, 164, 152-170.
34. Vijayakumar, K., P.C.S. Devara., S.V.B. Rao and C.K. Jayasankar. 2016. Dust aerosol characterization and transport features based on combined ground-based, satellite and model-simulated data. Aeolian Research, 21: 75-85.
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