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Journal of Arid Land
Journal of Arid Land  2021, Vol. 13 Issue (1): 1-22    DOI: 10.1007/s40333-020-0079-5
Research article     
Spatial and temporal gradients in the rate of dust deposition and aerosol optical thickness in southwestern Iran
Mansour A FOROUSHANI*(), Christian OPP, Michael GROLL
Department of Geography, Philipps-Universität Marburg, Marburg 35037, Germany
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Abstract  

The southwestern Iran is one of the regions that are most prone to dust events. The objective of this study is the analysis of the spatial and temporal distributions of dust deposition rate as a key factor for finding the relative impact of the dust. First, the monthly mean aerosol optical thickness (AOT) from Moderate Resolution Imaging Spectroradiometer (MODIS) was analyzed and compared with the dust amount variations from ground deposition rate (GDR), and the results were further used to investigate the spatial and temporal distributions of dust events in southwestern Iran for the period between 2014 and 2015. Moving air mass trajectories, using the Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model, were proven to be a discriminator of their local and regional origin. The results from GDR analysis produced a correlation coefficient between dust event history and deposition rates at dust magnitudes of >0.93 that is meaningful at the 95% confidence level. Furthermore, the deposition rates varied from 3 g/m2 per month in summer to 10 g/m2 per month in spring and gave insight into the transport direction of the dust. Within the same time series, AOT correspondences with MODIS on Terra in four aerosol thickness layers (clean, thin, thick, and strong thick) were shown in relation to each other. The deepest mixed layers were observed in spring and summer with a thickness of approximately 3500 m above ground level in the study area. Investigations of ground-based observations were correlated with the same variations for each aerosol thickness layer from MODIS images and they can be applied to discriminate layers of aeolian dust from layers of other aerosols. Together, dust distribution plots from AOT participated to enhance mass calculations and estimation deposition rates from the thick and strong thick aerosol thickness layers using the results from GDR. Despite all the advances of AOT, under certain circumstances, ground-based observations are better able to represent aerosol conditions over the study area, which were tested in southwestern Iran, even though the low number of observations is a commonly acknowledged drawback of GDR.



Key words： aerosol optical thickness      ground deposition rate      HYSPLIT      dust deposition      Iran     
Received: 25 June 2019      Published: 10 January 2021
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About author: *Mansour A FOROUSHANI (E-mail: mforoushani@gmail.com)
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Cite this article:

Mansour A FOROUSHANI, Christian OPP, Michael GROLL. Spatial and temporal gradients in the rate of dust deposition and aerosol optical thickness in southwestern Iran. Journal of Arid Land, 2021, 13(1): 1-22.

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http://jal.xjegi.com/10.1007/s40333-020-0079-5     OR     http://jal.xjegi.com/Y2021/V13/I1/1

Fig. 1 Location of the study area (a) and the distribution of ground dust collectors (G01-G10) and altitudes in the study area (b). DEMs (digital elevation models) are globally affordable and have approximately 1 km resolution from GTOPO30 (a global DEM with a horizontal grid spacing of 30 arc seconds) through the USGS (U.S. Geological Survey) Explorer dataset GTOPO30 (ASTER Science Team, 2001).
No. Gauge site
number		 Latitude
(°N)		 Longitude
(°E)		 Environment Altitude
(m a.s.l.)		 Total distance
(km)
1 G01 34.000553 45.497595 Light industry and semi-desert 144 0
2 G02 34.007182 45.499075 Light industry and semi-desert 184 1
3 G03 34.393584 45.648174 Semi-desert 394 52
4 G04 34.423028 45.993753 Road traffic load 910 113
5 G05 34.353365 47.101335 Census densely occupied 1304 245
6 G06 33.024976 47.759393 Light industry and village 581 632
7 G07 32.380038 48.282664 Light industry and village 109 733
8 G08 31.445194 48.632398 Light industry and village 25 860
9 G09 30.584651 49.163632 Census occupied 6 991
10 G10 30.352411 48.292293 Road traffic load 2 1091
Table 1 Location of dust samplers in the study area
Fig. 2 Construction and collecting of samples from sampling points. Sampling process is represented in (a), (b), (c), and (d). Sampling begins from removing sampling plate (A and B) followed by replace filter, and packing samples with caution (C and D).
Dataset sensor, satellite, and bandwidth Platform Availability Spatial resolution Temporal resolution
MOD08_M3 v6.1 at 550 nm dark target, for land only Terra level 3 1 Mar 2000
1 Feb 2000		 0.1°×0.1°
(10 km×10 km)		 Daily, 8 d, and monthly
MOD08_M3 v6.1 at 550 nm deep blue aerosol, for land only Terra level 3 Giovanni 1.0°×1.0° Monthly
MOD08_M3 v6.1 at 550 nm deep blue aerosol, for land and ocean Terra level 3 Giovanni 1.0°×1.0° Monthly
MIL3MAE v4, MISR aerosol optical depth 555 nm Terra 1 Mar 2000
Giovanni		 0.5°×0.5° Daily and monthly
Table 2 Titles of Giovanni online data systems developed and maintained by National Aeronautics and Space Administration (NASA) Goddard Earth Sciences Data and Information Services Center (GES DISC)
Collection time Dust deposition rate (mg/cm2) Gauge site
(M.W.)
Year Month G10 G09 G08 G07 G06 G05 G04 G03 G02 G01 Total
2014 Mar 1.00 0.60 0.70 0.20 0.20 0.50 0.20 0.80 0.80 0.60 5.60 G10
Apr 0.80 0.90 0.50 1.00 0.20 0.20 2.00 0.50 2.00 2.60 10.70 G01
May 0.20 0.50 0.20 0.50 0.10 0.30 3.00 0.30 0.50 1.00 6.60 G04
Jun 1.00 1.00 0.60 0.50 0.20 1.00 0.20 0.80 0.80 1.50 7.60 G01
Jul 0.90 1.20 1.90 0.60 0.30 0.90 0.20 0.80 0.50 0.80 8.10 G08
Aug 2.10 1.80 2.00 0.30 0.60 2.00 0.00 0.90 1.00 1.50 12.20 G10
Sep 0.90 0.90 0.60 0.20 0.00 1.00 0.50 0.90 1.50 1.50 8.00 G01
Oct 0.30 0.30 0.30 0.20 0.00 0.10 0.20 0.20 0.60 0.90 3.10 G01
Nov 0.20 0.50 0.20 0.20 1.00 0.10 0.20 0.20 0.90 2.00 5.50 G01
Dec 1.00 0.30 0.30 0.90 0.20 0.20 0.20 0.10 0.20 1.50 4.90 G01
2015 Jan 3.10 2.50 2.00 2.50 0.30 0.20 0.60 0.80 1.00 1.80 14.80 G10
Feb 1.10 1.50 0.80 1.70 0.10 0.20 0.20 0.60 0.40 0.50 7.10 G07
Mar 2.10 0.70 0.90 1.00 0.20 0.60 0.50 0.40 0.30 0.80 7.50 G07
Dust deposition rate and dust event frequency
G10 G09 G08 G07 G06 G05 G04 G03 G02 G01 Total
Dust deposition rate in total (mg/cm2) 14.70 12.70 11.00 9.8 3.40 7.30 8.00 7.30 10.50 17.00 101.70
Date with the maximum dust deposition rate Jan
2015		 Jan
2015		 Jan
2015		 Jan
2015		 Nov
2014		 Aug
2014		 May
2014		 Sep
2014		 Apr
2014		 Apr
2014
Dust event frequency (times) 16 12 8 7 0 1 2 8 17 19
Statistics
G10 G09 G08 G07 G06 G05 G04 G03 G02 G01
Correlation coefficient 74% 93% 69% 85% - 35% 73% 81% 49% 96%
P-value 0.05 0.05 0.05 0.05 NA NA 0.05 0.05 0.05 0.05
Table 3 Description of dust deposition rates and dust event frequency
Fig. 3 Monthly average aerosol optical thickness (AOT; 550 nm dark target; 0.1° resolution) from March to July of 2014
Fig. 4 Monthly average AOT (550 nm dark target; 0.1° resolution) from August to December of 2014
Fig. 5 Monthly average AOT (550 nm dark target; 0.1° resolution) from January to March of 2015
Fig. 6 Temporal monthly means of dark target MODIS AOT (dimensionless) from March to November of 2014. The left Y axis shows modified pixel values which represent the minimum, maximum, median, and standard deviation (SD) values of AOT. The right Y axis shows the relative counted value (counting pixel value) of AOT for each class. For the horizontal axis, 1, 2, 3, and 4 represent the clean, thin, thick, and strong thick layers, respectively.
Fig. 7 Temporal monthly means of dark target MODIS AOT (dimensionless) from December 2014 to February 2015. The left Y axis shows modified pixel values which represent the minimum, maximum, median, and standard deviation (SD) values of AOT. The right Y axis shows the relative counted value (counting pixel values) of AOT for each class. For the horizontal axis, 1, 2, 3, and 4 represent the clean, thin, thick, and strong thick layers, respectively.
Fig. 8 Model output from Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) for Section A (a), Section B (b), and Section C (c). Transport history relative on dust event frequency was simulated four days backward trajectories for an ending time at 1000 UTC (Universal Time Coordinated) in January and February of 2015, and March, April, and May of 2014. AGL, above ground level.
Fig. 9 Model output simulated four days backward trajectories from HYSPLIT in March, April, and May of 2014. It is based on updrafts loaded for 100, 500, and 1000 m above ground level, with respect to the above ground surface level. Flows in March, April, and May of 2014 reached Section A, Section B, and Section C from the same direction. In April, however, Section C was more influenced from local processes. High fluctuation intensities were observed with a steady decline to ending points in March 2014. More intensity in vertical velocity was observed in April and May of 2014.
Fig. 10 Model output simulated four days backward trajectories from HYSPLIT in January and February of 2015. It is based on updrafts loaded for 100, 500, and 1000 m above ground level, with respect to the above ground surface level. Transport history relative to dust event frequency showed an ending time at 1000 UTC on 29 January and 22 February, 2015. For all sections (A, B, and C), high fluctuation intensities were observed in February 2015.
Fig. 11 AOT of Multi-angle Imaging SpectroRadiometer (MISR) images with a spatial resolution of 0.5° in March, May, and April of 2014 (a1, a2, and a3, respectively), and scattering plots showing the correlation between two sets of AOT from MISR and MODIS in March, May, and April of 2014 (b1, b2, and b3, respectively). Latitude: 30.5°-34.5°N; longitude: 45.5°-49.5°E.
Fig. 12 AOT of MISR images with a spatial resolution of 0.5° in January, February, and March of 2015 (a1, a2, and a3), and scattering plots showing the correlation between two sets of AOT from MISR and MODIS in January, February, and March of 2015 (b1, b2, and b3). Latitude: 30.5°-34.5°N; longitude: 45.5°-49.5°E.
Fig. 13 Thickness properties by courtesy of NASA for AOT user manual retrieved from Collection 6.0 MODIS data in a publication of Levy and Hsu (2015). AE, angstrom exponent.
Fig. 14 Plotting spatial gradient in AOT compared with the fluctuation values of ground deposition rate (GDR)
Fig. 15 Correlation between atmospheric dust loading and dust accumulation. Layers are classified in clean (a), thin (b), thick (c), and strong thick (d) from March 2014 to 2015
Fig. 16 Plotting AOT (thick and strong thick aerosol thickness layers) with the fluctuation values of GDR
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