تحلیل فضایی مخاطرات محیطی

تحلیل فضایی مخاطرات محیطی

واکاوی و مقایسه تولیدات ماهواره‌ای و شبیه‌سازی شده AOD در تحلیل گردوغبارهای غرب ایران (2000-2018)

نویسندگان
کاوه محمدپور 1
محمد سلیقه 1
علی درویشی بلورانی 2
طیب رضیئی 3
1 دانشگاه خوارزمی تهران
2 دانشگاه تهران
3 مرکز تحقیقات حفاظت خاک و آبخیزداری کشور
10.29252/jsaeh.7.1.3
چکیده
گردوغبار، تحت تاثیر تعامل سیستم اتمسفر – زمین بوده و با تغییر در انرژی تابشی، شیمی و فیزیک اتمسفر، اقلیم یک منطقه را تحت تاثیر قرار می­دهد. بنابر ضرورت نقش گردوغبارها و پراکنش فضایی-دینامیکی گسترده آنها و نیز وجود تکنیک­های پیشرفته سنجش از دور و مدلسازی در شبیه­سازی گردوغبار، در پژوهش حاضر سعی در مقایسه، کمی­سازی و شبیه­سازی رفتار گردوغبار با استفاده از عمق نوری آئروسل (AOD) MODIS و MACC گردید. میزان همبستگی پیرسون بین داده­ها نشان داد که در منطقه مورد مطالعه بین سنجنده و مدل ارتباط معنی­داری وجود دارد و کمترین همبستگی در استان همدان مشاهده شد. توزیع سالانه AOD نمایان ساخت که مقدار گردوغبار دارای دو دوره فعال (2000-2010) و غیر فعال (2010-2018) بود. همچنین، توزیع ماهانه AOD نشان داد که منطقه مورد مطالعه در ماههای آوریل تا آگوست دارای بیشترین غلظت گردوغبار است؛ که همخوانی ماهانه AOD بین مدل و سنجنده به تفکیک استان در ماه­های مرطوب (دسامبر تا مارس) بیشتر از ماه­های خشک (آوریل تا نوامبر) است. توزیع مکانی گردوغبار در هر دو سنجنده و مدل دارای الگوی کلی مورب مکانی جنوبی-شمالی است و با افزایش عرض جغرافیایی از مقدار آن کاسته می­شود، اما این تغییرات در MODIS منظمتر از MACC است.
کلیدواژه‌ها
عمق نوری آئروسل (AOD)
MACC
MODIS
غرب ایران

عنوان مقاله English

Analysis and Comparing Satellite Products and Simulated of AOD in West Iran (2000-2018)

نویسندگان English

kaveh Mohammadpour 1
Mohammad Saligheh 1
Ali Darvishi Bloorani 2
Tayeb Raziei 3
1 Kharazmi University of Tehran
2 Tehran University
3 SCWMRI
چکیده English

Analysis and Comparing Satellite Products and Simulated

Of AOD in West Iran (2000-2018)



Kaveh Mohammadpour, Ph.D. Student in Climatology, Kharazmi University of Tehran

Mohammad Saligheh, Associate Professor in Climatology, Kharazmi University of Tehran

Ali Darvishi Bloorani, Assistant Professor in RS & GIS, Tehran University

Tayeb Raziei, Assistant Professor in Climatology, SCWMRI, Iran



Introduction

Dust are the main type of aerosols that affects directly and indirectly radiation budget. In addition, those affect the temperature change, cloud formation, convection, and precipitation. In recent years, the increase of different sensors and models has made possible to research the dust. The most important studies about dust analysis has been considered of Aerosol Optical Depth (AOD) as the most key parameter, which are based on the use of remote sensing technique and global models for analyzing the behavior and dynamics of dust in recent two decades. To achieve this, it has used of MODIS and MACC to study and identify the behavior of dust in the last two decades over west Iran.



Materials and methods

Areas in this study are Ilam, Kermanshah, Kurdistan, Lorestan and Hamedan provinces. The area has studied of two data series such as: first is MACC data with a spatial precision of 14 km2 and a 3-hour time scale; and other one is MODIS sensor production on the Terra satellite with a 10-square-kilometers resolution. In order to analyze the dust in the area in the period 2000 to 2018, statistical methods and simulation has used of the AOD parameter in MACC and MODIS. Before any processing, the data regraded to 0.2 × 0.2 degrees in order to compare the data. Then, the average daily AOD formed in a 22 × 23 matrix with 560 pixels that presented with 3653 × 560 for MACC during 2003 to 2012 and 6489 × 560 for MODIS during 2000-2018. Average of daily AOD obtained of MACC and MODIS calculated using of statistical equations. Then, the spatial distribution of AOD during the dusty months for synoptic stations and total province surface extracted using of R packages during the daily time series of the periods. Finally, the spatial distribution of the obtained AOD interpolated using the kriging function.



Results and Discussion

The average annual AOD obtained from Deep Blue algorithm from MODIS was less than MACC in all of the interested stations, except for Hamedan and Khorramabad stations, and provinces surfaces.

Correlation of AOD between MODIS and MACC shown that the correlations is high between model and sensor data (R2 = 59). In addition, the spatial correlation map shows 0.38 to 0.76 in which indicates a significant relationship between the MACC and MODIS pixels and the relationship is more in the western provinces of the area than the northeast of the region (Hamedan). The monthly comparison of the mean of AOD of the sensor and the model in the whole the area shows a highest correlation between the AOD in February and October.

The interpolation of the spatial distribution in the decade of the study (2003-2012) in MACC showed that the spatial variations of AOD is decreasing from the south of Ilam to the north of Kurdistan and reached the lowest level in the north of Kurdistan province. In general, the findings of annual and seasonal spatial distribution (dry period) of dust showed that MACC overestimated AOD compared to MODIS in the area. Nonetheless, the dust pattern in both of the sensor and the model increased from south to north. Although, the dust pattern is more regular in the sensor than the model. The spatial distribution of dust in Ilam, Kermanshah, and Kurdistan provinces in MODIS and MACC shows that dust in the southern point of the Ilam province has the highest concentration and the lowest is observed in the northeast of Kurdistan province. This spatial distribution of dust showed that dust in western provinces of the area follow latitudinal trend , in which is influenced by the high topography of Kermanshah and Kurdistan provinces and the proximity of Ilam province to dust sources in the distribution of dust intensity.



Conclusion

The results showed that there was a significant correlation between the sensor and the model and the coefficient was more than 0.4 in all months on the area. The findings of the annual amount of dust in MODIS showed that the amount of dust in the years 2000 to 2009 has increased in whole areas and from 2009 onwards, this annual trend has been reduced by 2018. MACC findings also showed that the AOD has been growing up in the period, although AOD amount have had a steep slope by 2010, but since 2010, dust has a steady slope. Therefore, West Iran has experienced two active (before 2010) and inactive (after 2010) periods in dust during an 18-years period on the area. The findings of MODIS and MACC in the study area indicate that the monthly distribution of dust from April to August has the highest concentration. In general, the annual and seasonal spatial distribution (months with the highest AOD) of dust indicates that the intensity of AOD in MACC was higher than MODIS in the area. Although the sensor and model has a roughly similar pattern and increases from south to north, but the trend in MODIS is more regular than MACC.



Keywords: Aerosol Optical Depth (AOD), MACC, MODIS, West Iran






کلیدواژه‌ها English

Aerosol Optical Depth (AOD)
MACC
MODIS
West Iran
1) Akbary M. and M. Farahbakhshi (2015), Analyzing and Tracing of Dust Hazard in Recent Years in Kermanshah Province, Int. J. Environ. Res., 9(2):673-682.
2) Arkian F. & S. E. Nicholson (2018), Long-term variations of aerosol optical depth and aerosol radiative forcing over Iran based on satellite and AERONET data, Environ Monit Assess 190: 1-15.
3) Ashrafi Khosro, Majid Shafiepour-Motlagh, Alireza Aslemand and Sarmad Ghader (2014), Dust storm simulation over Iran using HYSPLIT, Journal of Environmental Health Science and Engineering :1-9.
4) Bangert, M., and Coauthors (2012) Saharan dust event impacts on cloud formation and radiation over Western Europe, Atmos. Chem. Phys., 12: 4045–4063.
5) Chin, M., Diehl, T., Tan, Q., Prospero, J. M., Kahn, R. A., Remer, L. A., Yu, H., Sayer, A. M., Bian, H., Geogdzhayev, I. V., Holben, B. N., Howell, S. G., Huebert, B. J., Hsu, N. C., Kim, D., Kucsera, T. L., Levy, R. C., Mishchenko, M. I., Pan, X., Quinn, P. K., Schuster, G. L., Streets, D. G., Strode, S. A., Torres, O., and Zhao, X.-P. (2014), Multi-decadal aerosol variations from 1980 to 2009: a perspective from observations and a global model, Atmos. Chem. Phys., 14: 3657–3690, doi:10.5194/acp-14-3657-2014.
6) Gharibzadeh Maryam, Khan Alam, Abbasali Aliakbari Bidokhti, Yousefali Abedini, Amir Masoumi (2017), Radiative Effects and Optical Properties of Aerosol during Two Dust Events in2013 over Zanjan, Iran, Aerosol and Air Quality Research, 17: 888–898.
7) Harrison, S. P., K. E. Kohfeld, C. Roelandt, and T. Claquin (2001), The role of dust in climate changes today, at the last glacial maximum and in the future, Earth-Sci. Rev., 54 (1–3): 43–80
8) Haywood, J. M., and O. Boucher (2000), Estimates of the direct and indirect radiative forcing due to tropospheric aerosols: A review, Rev. Geophys., 38: 513–543.
9) Haywood, J., Pete Francis, Simon Osborne, Martin Glew,1Norman Loeb, Eleanor Highwood, Didier Tanre´, Gunnar Myhre, Paola Formenti, and Edwin Hirst (2003), Radiative properties and direct radiative effect of Saharan dust measured by the C-130 aircraft during SHADE: 1. Solar spectrum, J. Geophys. Res., 108, D188577, doi:10.1029/D2002JD002687.
10) IPCC: Climate Change (2013) The Physical Science Basis. Contribution of Working Group I to the Fifth Assessment Report of the Intergovernmental Panel on Climate Change, edited by: Stocker, T. F., Qin, D., Plattner, G.-K., Tignor, M., Allen, S. K., Boschung, J., Nauels, A., Xia, Y., Bex, V., and Midgley, P. M., Cambridge University Press, Cambridge, UK and New York, NY, USA, 1535 p., 2013.
11) Jayaraman, A., D. Lubin, S. Ramachndran, V. Ramanathan, E. Woodbridge, W. D. Collins, and K. S. Zalupuri (1998), Direct observation of aerosol radiative forcing over the tropical Indian Ocean during the January-February 1996 pre-INDOEX cruise, J. Geophys. Res., 103 (D12): 13827–13836.
12) Jayaraman, S., Y. Song, L. Vetrivel, L. Shankar, and A. S. Verkman (2001) Noninvasive in vivo fluorescence measurement of airway-surface liquid depth, salt concentration, and pH, J. Clin. Invest., 107: 317–324.
13) Kaufman, Y.J., Tanre, D., Boucher, O. (2002) A satellite view of aerosols in the climate system. Nature 419: 215–223.
14) Klingmüller, K., Pozzer, A., Metzger, S., Stenchikov, G. L., and Lelieveld, J.(2016), Aerosol optical depth trend over the Middle East, Atmos. Chem. Phys., 16: 5063–5073, doi:10.5194/acp-16-5063- 2016.
15) Levin, Z., E. Ganor, and V. Gladstein (1996), The effect of desert particles coated with sulfate on rain formation in the eastern Mediterranean, J. Appl. Meteor., 35: 1511–1523.
16) Levy, R. C., Remer, L. A., and Dubovik, O. (2007): Global aerosol optical properties and application to Moderate Resolution Imaging Spectroradiometer aerosol retrieval over land, J. Geophys. Res. Atmos., 112: D13210, doi:10.1029/2006JD007815.
17) Levy, R.C., Mattoo, S., Munchak, L.A., et al., (2013) The Collection 6 MODIS aerosol products over land and ocean.Atmos.Meas.Tech.6(11): 2989e3034.
18) Lohmann, U., Feichter, J., 2005. Global indirect aerosol effects: a review. Atmospheric Chemistry and Physics 5: 715–737.
19) Ma, Z.-W., Hu, X.-F., Sauer, A.M., et al., (2016), Satellite-based spatiotemporal trends in PM2.5 concentrations: China, 2004e2013. Environ. Health Perspect. 124 (2), 184e192. http://dx.doi.org/10.1289/ehp.1409481s.
20) Maley, J. (1982), Dust, clouds, rain types and climatic variations in tropical north Atlantic, Quat. Res., 18: 1–6.
21) Mao K.B., Y. Ma, L. Xia , Wendy Y. Chen , X.Y. Shen , T.J. He , T.R. Xu (2014), Global aerosol change in the last decade: An analysis based on MODIS data, Atmospheric Environment 94: 680-686.
22) Mei, Di, Xiushan, Lu, Lin, Sun, Ping, Wang. (2008). A Dust-Storm process dynamic monitoring with multi-temporal MODIS data, the international archives of the photogrammetric, Remote Sensing and Spatial Information Sciences. Vol. XXXVII, Part B7, Beijing, pp 965-970.
23) Morcrette, J.-J., Boucher, O., Jones, L., Salmond, D., Bechtold, P., Beljaars, A., Benedetti, A., Bonet, A., Kaiser, J. W., Razinger, M., Schulz, M., Serrar, S., Simmons, A. J., Sofiev, M., Suttie, M., Tompkins, A. M., and Untch, A. (2009), Aerosol analysis and forecast in the ECMWF integrated forecast system. Part I: Forward modelling, J. Geophys. Res., 114: D06206 doi:10.1029/2008JD011235.
24) Nakajima, T., A. Higurashi, K. Kawamoto, and J. E. Penner (2001), A possible correlation between satellite-derived cloud and aerosol microphysical parameters, Geophys. Res. Lett., 28: 1171–1174.
25) Namdari Soodabeh, Neamat Karimi, Armin Sorooshian, GholamHasan Mohammadie, Saviz Sehatkashani (2018), Impacts of climate and synoptic fluctuations on dust storm activity over the Middle East, Atmospheric Environment 173: 265–276.
26) Namdari1 S. & KK Valizade2 & A.A. Rasuly1,3 & B. Sari Sarraf1 (2016), Spatio-temporal analysis of MODIS AOD over western part of Iran, Arab J Geosci: 9:191.
27) Notaro, M., Yu, Y., and Kalashnikova, O. V. (2015), Regime shift in Arabian dust activity, triggered by persistent Fertile Crescent drought, J. Geophys. Res.-Atmos., 120: 10229–10249, doi:10.1002/2015JD023855.
28) Pan, L., H. Che, F. Geng, X. Xia, Y. Wang, C. Zhu, M. Chen, W. Gao and L. Guo, (2010), Aerosol optical properties based on ground measurements over the Chinese Yangtze Delta Region. Atmos Environ, 44: pp. 2587– 2596.
29) Penner, J. E., M. Andreae, H. Annegarn, L. Barrie, J. Feichter, D. Hegg, R. Leaitch, D. Murphy, J. Nganga, and G. Pitari (2001), Aerosols, their direct and indirect effects, in Climate Change 2001: The Scientific Basis, edited by J. T. Houghton et al., pp. 289 – 348, Cambridge Univ. Press, New York
30) Rosenfeld, D., Lohmann, U., Raga, G. B., O’Dowd, C. D., Kulmala, M., Fuzzi, S., Reissell, A., and Andreae, M. O.(2008), Flood or Drought: How do aerosols affect precipitation?, Science, 321: 1309–1313, doi:10.1126/science.1160606.
31) Rosenfeld, J. E., D. B. Considine, P. E. Meade, J. T. Bacmeister, C.H. Jackman, and M.R. Schoeberl (1997), Stratospheric effects of Mount Pinatubo aerosol studied with a coupled two-dimensional model, J. Geophys. Res., 102: 3649–3670.
32) Satheesh, S. K., and V. Ramanathan (2000), Large differences in tropical aerosol forcing at the top of the atmosphere and Earth’s surface, Nature, 405: 60–63.
33) Sayer, A.M., Hsu, N.C., Bettenhausen, C., et al., (2013), Validation and uncertainty estimates for MODIS Collection 6 “Deep Blue” aerosol data. J. Geophys. Res. Atmos. 118 (14), 7864e7872. http://dx.doi.org/10.1002/ jgrd.50600.
34) Sokolik, I. N., et al. (2001), Introduction to special section: Outstanding problems in quantifying the radiative impacts of mineral dust, J. Geophys. Res., 106 (D16): 18015–18028
35) Tegen, I., A. A. Lacis, and I. Fung (1996), The influence of mineral aerosols from disturbed soils on the global radiation budget, Nature, 380: 419–422, doi:10.1038/380419a0.
36) Tegen, I., P. Hollrig, M. Chin, I. Fung, D. Jacob, and J. Penner (1997), Contribution of different aerosol species to the global aerosol extinction optical thickness: Estimates from model results. J. Geophys. Res., 102 (D20): 23895–23916.
37) van Donkelaar, A., Martin, R.V., Brauer, M., et al., (2010), Global estimates of ambient fine particulate matter concentrations from satellite-based aerosol optical depth: development and application. Environ. Health Perspect. 118 (6): 847e855.
38) van Donkelaar, A., Martin, R.V., Brauer, M., et al., (2015), Use of satellite observations for long-term exposure assessment of global concentrations of fine particulate matter. Environ. Health Perspect. 123 (2): 135e143.
39) Wong Sun, Andrev E. Dessler , Natalie M. Mahowald Ping Yang and Qian Feng (2009), Maintenance of Lower Tropospheric Temperature Inversion in the Saharan Air Layer by Dust and Dry Anomaly, American Meteorological Society, Volume 22: 5149-5162, DOI: 10.1175/2009JCLI2847.1
40) Wong, S., and A. E. Dessler (2005), Suppression of deep convection over the tropical North Atlantic by the Saharan air layer, Geophys. Res. Lett., 32: L09808, doi:10.1029/2004GL022295.
41) Wurzler, S. C., T. G. Reisin, and Z. Levin (2000), Modification of mineral dust particles by cloud processing and subsequent effects on drop size distributions, J. Geophys. Res., 105 (D4): 4501–4512.
42) Xuemei Zong 1, Xiangao Xia 1,2, Huizheng Che (2015), Validation of aerosol optical depth and climatology of aerosol vertical distribution in the Taklimakan Desert, Atmospheric Pollution Research 6 : 239-244.