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Distribution, source and transport of the aerosols over Central Asia
Accepted Manuscript Distribution, source and transport of the aerosols over Central Asia Y. Liu, Q. Zhu, R. Wang, K. Xiao, P. Cha PII:
S1352-2310(19)30279-1
DOI:
https://doi.org/10.1016/j.atmosenv.2019.04.052
Reference:
AEA 16680
To appear in:
Atmospheric Environment
Received Date: 10 October 2018 Revised Date:
23 April 2019
Accepted Date: 24 April 2019
Please cite this article as: Liu, Y., Zhu, Q., Wang, R., Xiao, K., Cha, P., Distribution, source and transport of the aerosols over Central Asia, Atmospheric Environment (2019), doi: https://doi.org/10.1016/ j.atmosenv.2019.04.052. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Distribution, Source and Transport of the Aerosols over Central Asia
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Y. Liu*, Q. Zhu, R. Wang, K. Xiao, P. Cha
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Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of
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Atmospheric Sciences, Lanzhou University, Lanzhou, 730000, China
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Corresponding author: Yuzhi Liu, E-mail: [email protected]
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ABSTRACT
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Limited by scarce observations, the sources and transport of aerosols over Central Asia
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are relatively unclear. In this study, using Terra and Aqua satellite images, Moderate
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Resolution Imaging Spectroradiometer (MODIS) data, Cloud-Aerosol Lidar and Infrared
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Pathfinder Satellite Observations (CALIPSO) satellite observations and meteorological
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reanalyze data, the distribution, source and transport of aerosols over Central Asia are
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investigated. We find that there are 227 aerosol events occurred in Central Asia during
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2000-2017 and the aerosols which can be transported from outside to Central Asia are
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dominated by dust and smoke (organic carbon and black carbon) particles. Statistical
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analyses show that the contribution of the sources outside of Central Asia (76 times) to all
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aerosol events (122 times) is greater than that of local emissions in Central Asia (46 times)
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in the spring and summer during 2000-2017. The smoke events (39 times), sourcing from
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Russia and Europe with strong northwest wind, account for 51.3% of total aerosol events
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contributed by sources outside of Central Asia. Additionally, the dust events (37 times),
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which mainly source from the northern Arabia Peninsula and North Africa with strong
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southwest wind, account for 48.7% of the total aerosol events contributed by the sources
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outside of Central Asia. On the contrary, the contribution of local emissions in Central
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Asia (90 times) to all aerosol events (105 times) is greater than that of outside sources (15
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times) in the autumn and winter. Result of clustering analyses for all 157 aerosol events
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during 2005-2017 is in agreement with the conclusion of statistical analyses based on
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observations. This study can provide some evidence to understand the aerosol properties
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over the Central Asia.
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Key words: dust, smoke, source, transport, Central Asia
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1. Introduction
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The atmospheric aerosol (Sokolik and Toon, 1996; Haywood and Boucher, 2000; Li,
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2004), which is composed of solid or liquid particles (Albrecht, 1989; Shi et al., 2005),
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plays an important role in affecting the energy balance and climate system through direct
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(Huang et al., 2007b, 2011; Ju and Han, 2011; Zhang et al., 2009; Liu et al., 2011, 2014),
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indirect and semi-direct effects (Sassen, 2002; Huang et al., 2010). In addition, driven by
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the atmospheric circulation, aerosols can influence the regional-scale air quality and even
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contribute to global climate change. (Kahn et al., 2008; Martin et al., 2009; Shao et al.,
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2011; Wang et al., 2013).
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Central Asia, located in the temperate desert belt of the Northern Hemisphere, is an
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important regional aerosol source due to long rainless periods, large areas of desert and
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salt lakes, low vegetation coverage and frequent windstorms (Issanova et al., 2015;
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Orlovsky and Indoitu, 2013; Sokolik et al., 2013; Shen et al., 2016). Recently, it was
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found that dust events in Central Asia have decreased for the period 1980-2000 relative to
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1936-1980 (Indoitu et al., 2012). Issanova et al. (2015) have come to a similar conclusion
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using weather station observations in Kazakhstan for 1970-2010. Supporting these
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observations, model simulations also suggested a significant decreasing trend of dust
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activity from 2000 to 2014 (Xi and Sokolik, 2016). Overall, cumulative evidence
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suggests that the frequency of dust storms in the Central Asia arid zone has dropped
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significantly in recent decades, especially in the Karakum Desert (the largest desert in
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Central Asia). A possible cause of the recent decrease in dust storms has been linked to
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the weakening of surface wind fields in the region and recovery of the vegetation cover
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(Shen et al., 2016).
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However, for aerosol events over Central Asia, the understanding of their sources is
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still relatively unknown (Miller-Schulze et al., 2011). In view of understanding the
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influence of aerosols over Central Asia on downstream regions, it is particularly
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important to clarify the distribution, source and transport of aerosols into and over
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Central Asia. In this study based on Cloud-Aerosol Lidar and Infrared Pathfinder Satellite
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Observations (CALIPSO) and Moderate Resolution Imaging Spectroradiometer (MODIS)
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Terra/Aqua satellites, reanalysis data and trajectory model simulations, we present
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extensive data on the sources and transport of these aerosols. The details of data sets are
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given in Section 2. In section 3, distribution of aerosols over Central Asia are discussed
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and identification of aerosol events are presented. Statistical analyses of all aerosol events
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and summary are presented in Section 4 and Section 5, respectively.
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2. Data sets and model description
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2.1 CALIPSO profiles
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CALIPSO, launched in 2006, is a satellite in the Earth System Science Pathfinder (ESSP)
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program of the National Aeronautics and Space Administration (NASA) of the United
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States. The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) sensor, the
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main equipment on the CALIPSO satellite, can provide the vertical distribution of
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extinction backscatter coefficients for both 532 nm and 1064 nm during day and night. In
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this study, data consisting of the total and perpendicular attenuated backscatter
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coefficients at 532 nm from CALIPSO Level 1B product and data comprising aerosol
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particle properties from the CALIPSO lidar Vertical Feature Mask (VFM) product
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version 4.10 are used to identify dust and smoke aerosols.
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2.2 MODIS data
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MODIS is an optical remote sensor on board the Terra and Aqua satellites which provides
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global observations of cloud, water vapor and aerosol. In this study, the images derived
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from Terra and Aqua MODIS products are used to identify the aerosols suspending over
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Central Asia. For the desert and semi-desert regions studied herein the Deep Blue aerosol
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optical depth (AOD) retrievals from the MOD08_M3 products with a latitudinal and
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longitudinal resolution of 1° × 1° are used to investigate the distribution of aerosols in
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each season over Central Asia. The MOD14 Level 3 Thermal Anomalies/Fire product,
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which is primarily derived from MODIS 4- and 11-µm radiances, contains the most basic
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level of MODIS fire data. In this study, the daily MOD14A1 product with a 1-km
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resolution is used to determine the locations of forest fires.
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2.3 AERONET data
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Aerosol Robotic Network (AERONET), which is composed of numerous ground-based
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remote sensing aerosol networks, can provide the real time AOD distribution at a global
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scale. In this study, AERONET Level 1.5 Version 2 data which are automatically cloud
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cleared at IASBS station are used.
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2.4 ECMWF data
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The European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim
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reanalysis data is used to investigate the transport mechanism of aerosols from a
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meteorological perspective. Daily mean meteorological contours of the U and V
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components of wind speed and the geopotential height from ECMWF are used. The
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reanalysis data have a spatial resolution of 0.5°×0.5° with a time interval of 6 hour (00:00,
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06:00, 12:00 and 18:00 UTC).
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2.5 HYSPLIT-4 model
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The HYSPLIT-4 model, provided by the National Oceanic and Atmospheric
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Administration (NOAA) Air Resources Laboratory and the Australian Meteorological
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Agency, can calculate the simple air mass trajectories and simulate complex diffusion and
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deposition. The meteorological data for the model have to be processed to a HYSPLIT
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compatible format. The 6-h-interval final archive data are generated from the NCEP
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(National Centers for Environmental Prediction) Global Data Assimilation System
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(GDAS) reanalysis 3-dimensional meteorological fields. In this study, the HYSPLIT-4
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model is used to verify the transport of aerosols and perform the clustering analysis of
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backward trajectories
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3. Aerosols transported from outside to Central Asia
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For the purposes of this study, Central Asia is defined as the region connecting East Asia
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and Europe comprised of Uzbekistan, Kyrgyzstan, Turkmenistan, Tajikistan and
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Kazakhstan extending over a latitude-longitude region between 35-57°N, 46-88°E as
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shown by the area enclosed within the purple line in Fig. 1.
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Figure 2 shows the distribution of AOD derived from MODIS products in each
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season during the period 2000-2017. As shown in Fig. 2, AODs in Central Asia are
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relatively higher in the spring and summer but lower in the autumn and winter. The
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aerosols loading in the atmosphere over Central Asia decrease gradually from west to east,
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the area from the Caspian Sea to Aral Sea is a center with high aerosol optical depth in
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Central Asia.
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In this study, the aerosol events linking with the sources outside of Central Asia can
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influence the aerosol loading in the atmosphere over large area, under the circumstance,
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CALIPSO satellite can easily observe these aerosols. However, as shown in Fig. 3, the
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aerosols during some events sourcing from local emission in Central Asia are constrained
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locally and can influence few areas, thus, such aerosol events cannot be observed well by
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CALIPSO satellite. Therefore, in this study, only the aerosol types during the events
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contributed by the sources outside of Central Asia are distinguished. Here, though the
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aerosol events contributed by local emissions are gathered statistics, the aerosol types are
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not identified.
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In the following, detecting and identifying the aerosol events contributed by the
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sources outside of Central Asia will be shown as examples of all events in statistical
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analysis. To identify the aerosols which can be transported from outside to Central Asia,
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three steps are performed. Firstly, the daily products of visible cloud images from
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MODIS observations are used to detect the aerosol events occurred over Central Asia.
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Next, the aerosol types in these events are identified. CALIPSO satellite can provide the
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vertical information for aerosols, which is very useful to identify the aerosol type. Since
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the CALIPSO satellite was launched in 2006, the aerosol types can be distinguished
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according to the CALIPSO satellite observations for the period 2006-2017, in which the
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determination of aerosol types from MODIS cloud images are verified by the CALIPSO
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satellite observations simultaneously. Based on verification of the MODIS cloud images
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by the CALIPSO observations, the grey and yellow plumes suspending over the vicinity
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of Central Asia in the MODIS cloud images are considered as smoke and dust aerosols,
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respectively. Correspondingly, for the period 2000-2005, the aerosol types are determined
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according to the plume colors in the cloud images observed by MODIS aboard on Terra
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and Aqua satellite. And then, according to the distribution of wind fields, the aerosol
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events contributed by the sources outside of Central Asia are finally confirmed. Basing on
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the identification of these aerosol events, we find the aerosols transported from outside to
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Central Asia are smoke and dust. Here we analyze statistically the smoke and dust events
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contributed by outside sources for the period 2000-2017. In the following, Section 3.1
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and 3.2 illustrate two examples of detecting aerosol events transported from outside to
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Central Asia.
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3.1 Detection of smoke aerosols transported from outside to Central Asia
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Figure 4 shows the cloud images obtained from Terra and Aqua MODIS observation over
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the study area on 28, 29 July and 1, 3, 5, 9 August, 2010. As shown in Fig. 4a, the
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aerosols suspended over the western Russia, and began to move eastward on 29 July (Fig.
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3b). From 1 to 5 August, 2010, the aerosols were continuously transported eastward and
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southward and spread over the north part of Kazakhstan on 5 August, 2010 (Fig. 4e). The
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movement of aerosols from Russia to Central Asia continued until 14 August.
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Furthermore, using the CALIPSO product, which detects aerosols over a bright
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surface and beneath thin clouds (Vaughan et al., 2004; Winker et al., 2006), aerosol
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categories can be identified. Fig. 5 shows the altitude-orbit cross-section of the total
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attenuated backscattering intensity (a1-a2), depolarization ratio (b1-b2), and distribution
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of cloud and aerosol types (c1-c2) on 28 July and 05 August, 2010. The satellite orbit
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paths are presented in red and blue lines in Fig. 1, respectively. In Fig. 5a1 and a2 the
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gray shading shows topography, the white parts denote clouds, the deep blue area denotes
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the region without signal because of cloud blocking and the green-yellow-orange color
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represents aerosols.
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As shown in Fig. 5a1 and b1, the total attenuated backscatter coefficient and volume
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depolarization ratio range from 0.003-0.005 km−1sr−1 and 0-0.4, respectively. In particular,
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over the area between 54°N and 70°N, the total attenuated backscatter values are large
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and the volume depolarization ratio ranges from 0.06 to 0.2. It was reported by Omar et
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al. (2009) that the total attenuated backscatter coefficient of aerosol at 532 nm is
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concentrated in the range from 0.003 to 0.009 km-1sr-1 whereas biomass burning smoke
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aerosol is determined when the depolarization ratio is within the range from 0.03 and
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0.11 (Chiang et al., 2007; Huang et al., 2007a; Xie et al., 2008), which are shown in Fig.
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5b1 and b2 as light blue and green parts. Therefore, combining the values of total
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attenuated backscatter coefficient at 532 nm and the depolarization ratio, it can be found
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that the main component of these detected aerosols over western Russia is smoke aerosol
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during this event. As shown in Fig. 5c1, smoke aerosols are observed over western Russia
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on 28 July 2010 simultaneously with polluted dust detected by CALIPSO. Similarly to
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the data presented in Fig. 5a1-c1, a large number of smoke aerosols are also detected on 5
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August (Fig. 5a2-c2) and covering the area from 60°N to 45°N, illustrating that smoke
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aerosols have spread from Russia to northern Kazakhstan at this time. Simultaneously,
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thermal anomalies and fires from the MOD14 data were analyzed. During the period of
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28 July to 4 August 2010, an accumulation of 4758 hot spots with highest credibility were
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detected, as shown in Fig. 1, in the vast area over western Russia. It confirms that the
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smoke is the dominant aerosol type during this event.
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As earlier studies have shown (Dirksen et al., 2009; Miller et al., 2011; Sang et al.,
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2011) the transport of aerosols is principally driven by atmospheric circulation. Figure 6
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displays the geopotential heights and wind vectors at 500 hPa during the period of 28
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July to 9 August, 2010 showing an anticyclone (high-pressure system) with an obvious
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center over the western Russia. From 28 July to 1 August, strong north wind ahead of
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anticyclone covering the area from western Russia to Central Asia drives the smoke
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plumes southward from western Russia to Central Asia, meanwhile, the high-pressure
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system extends towards east. On 3 August, the strength of high-pressure system center
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becomes to weaken, inducing the smoke particles are pervaded over the whole area of
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Central Asia. From 5 to 9, August, the anticyclone center moves away the Central Asia
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and locates over the north side of western Russia. The strong north winds ahead of the
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anticyclone continuously drive smoke aerosols to Central Asia. The simulations from the
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HYSPLIT-4 model verify the transport of smoke aerosols as shown in Fig. 7 from the
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cluster analysis of 72h backward trajectory from Aktobe and Astana in northern
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Kazakhstan. The simulation results verify that the aerosols at this time over northern
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Kazakhstan are transported from western Russia. As suggested earlier by Zhu et al.,
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(2018) who noted smoke aerosols from Siberian forest fires can be transported to Central
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Asia. Thus, it is postulated that the smoke aerosols transported from western Russian
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region are mainly produced by the forest fires.
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Based on the method of identifying the smoke aerosol events from the MODIS and
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CALIPSO satellite observations, all the smoke events transported from outside to Central
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Asia are distinguished for period 2000-2017. The statistical result is shown in Table 1. As
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listed in Table 1, there are totally 45 smoke events contributed by the sources outside of
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Central Asia, in which 35 and 10 events are from Russia and Europe, respectively. And
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these events mainly occur in the spring and summer.
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3.2 Detection of dust aerosols transported from outside to Central Asia
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Figure 8 shows the cloud images from MODIS products over the study area from 11 to
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14 April, 2011. On 12 April, aerosols can be found over Iraq. After a day, cumulative
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aerosols spread over the junction of Saudi Arabia and Iraq, in which a small number of
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aerosols cross Iran to the southern Caspian Sea. Figure 9 presents the altitude-orbit cross-
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section of the total attenuated backscattering intensity, depolarization ratio, spatial
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distribution of cloud and aerosol types on 12 April and 13 April, 2011, and the
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AERONET AOD at IASBS station locating in the path of dust transport from northern
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Arabian Peninsula during this event. The satellite orbit paths are presented in green and
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yellow lines in Fig. 1, respectively. Contrary to the smoke aerosols, the depolarization
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ratio of dust aerosols is generally greater than 0.2 even can reach over 0.4 in the severe
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sandstorms (Chiang et al., 2007; Huang et al., 2007a; Xie et al., 2008). The dust aerosols
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are presented in yellow, orange and red colors, as shown in Fig. 9b1 and b2. As given in
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Fig. 9a1 and b1, in the region ranging 27-36°N and 48.5-50.5°E, the total attenuated
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backscatter and volume depolarization ratio range from 0.003-0.008 km-1sr-1 and 0.2-0.5,
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respectively, indicating that the strong dust particles are the main aerosol component over
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Iraq. According to Fig. 9a2-c2, dense dust aerosols are observed over the region of 33-
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42°N and 50-54°E indicating the transport of dust aerosols from the northern Arabian
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Peninsula to Caspian Sea on 13 April, 2011. Simultaneously, the daily AOD (Fig. 8d)
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observed at the AERONET IASBS station (36.42°N, 48.30°E), which is adjacent to
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northern Arabian Peninsula and in the path of dust transport from northern Arabian
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Peninsula to Central Asia, during period 10 to 15 April indicates a peak value on 13 April.
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The hourly mean AOD (Fig. 9e) suggests high values in the day of 13 April. Therefore,
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combining of satellite observation and ground-based monitoring confirms the dust
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aerosols over the Central Asia are transported from northern Arabian Peninsula. As shown in Fig. 10, a deep cyclone (low-pressure system) exists over western
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Russia and an anticyclone (high-pressure system) over the southern Arabia Peninsula
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during this dust event. The Central Asia locates in the junction of low-pressure and high-
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pressure systems. From 11 to 12 April, 2011, the low-pressure system extends into the
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northern Arabia Peninsula (Fig. 10a and b). As such, more strong southwesterly winds
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blow over the area from northern Arabian Peninsula to Central Asia, producing a strong
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dust storm in the northern Arabian Peninsula. With the persistence of the linked cyclone
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and anticyclone activity (Fig. 10c and d), dust aerosols are continuously transported from
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the Arabian Peninsula to Central Asia. Additionally, as shown in Fig. 11, the 36-hours
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forward trajectories also show that the dust aerosols originating from the Arabian
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Peninsula are being transported to Central Asia.
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According to the method of identifying the dust aerosol events from the MODIS and
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CALIPSO satellite observations, we distinguished all the dust events transported from
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outside to Central Asia for period 2000-2017, as listed in Table 2. The result shows that
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these dust events are mainly induced by the dust transport from northern Arabian
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Peninsula, especially in the spring. Among these dust events, 88% of events are sourcing
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from the northern Arabian Peninsula. Additionally, in the spring, the dust aerosols can be
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transported from North Africa.
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4. Source statistics for the aerosol events in Central Asia
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As described in the above two aerosol examples, combing daily images from
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MODIS observation, CALIPSO observations and meteorology fields, the aerosol events
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over Central Asia during 2000-2017 are detected. Based on the identifications of aerosol events during the period 2000-2017, these
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aerosol events over Central Asia are analyzed statistically. The frequencies of aerosol
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event and dominant aerosol types from 2000 to 2017 are shown in Fig. 12. From Fig. 12a,
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it can be seen that the 122 aerosol events occurring in Central Asia during the spring and
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summer, of which the aerosols in 46, 33, 31, 8 and 4 episodes source from local
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emissions, northern Arabian Peninsula, Russia, Europe (except for the European part of
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Russia) and North Africa, respectively. The type of the aerosols sourcing from Russia and
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Europe is mainly smoke aerosol (as shown in Section 3.1), and the aerosol transported
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from the northern Arabian Peninsula and North Africa is mainly dust aerosol (as shown in
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Section 3.2). The total dust and smoke events sourcing from outside of Central Asia are
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37 and 39 times, respectively. Additionally, 62.3% of total aerosol events source from
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outside of Central Asia, in which 84.2% are from the northern Arabian Peninsula and
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Russia. As shown in Fig. 12b, the smoke events sourcing from Russian mainly occur in
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the periods 2000-2004 and 2012-2013, and the smoke events originating from the
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northern Arabian Peninsula mainly occur in the period 2008-2012. Besides, the aerosol
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events with complicated aerosol type due to local emission in the Central Asia account
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for about 37.7% of total aerosol events. On the contrary, comparing with the spring and
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summer, 90 aerosol events are contributed by the local sources in all the 105 aerosol
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events in the autumn and winter, accounting for about 85.7% of total aerosol events
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because of local emissions. Among all the aerosol events, there are only 9, 4 and 2
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aerosol events sourcing from northern Arabian Peninsula, Russia and Europe (except for
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the European part of Russia), respectively. As shown in Fig. 12e, the aerosol events
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occurring in the spring is the most in all seasons, followed by autumn, and the least in the
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winter. Figure 13 shows the clustering analysis of 72h backward trajectories for all 157
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aerosol events during 2005-2017 at Nukus. The clustering analysis is performed for the
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period 2005-2017 because the 6-h-interval data from NCEP (input to the HYSPLIT
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model) are from 2005. The simulations from the HYSPLIT-4 model show of all the
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backward trajectories, 8%, 11%, 12%, 26% and 43% of trajectories are from North Africa,
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Russia, Europe, northern Arabian Peninsula and Central Asia (Fig. 13), respectively. The
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statistical results of all 157 aerosol events during 2005-2017 indicate 2%, 12%, 4%, 24%
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and 57% of all the aerosol events are from North Africa, Russia, Europe, northern
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Arabian Peninsula and Central Asia, respectively. Although there are some differences
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between the results of model and observations, the simulation results show that the
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aerosols occurred in Central Asia are mainly from North Africa, Russia, Europe, northern
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Arabian Peninsula and local emissions.
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Figure 14 shows the distributions of daily mean wind vectors (arrows) and
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geopotential heights (colors) at 850 hPa and 500 hPa during 42 dust events sourcing from
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the northern Arabian Peninsula and 4 dust events sourcing from North Africa. As shown
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in Fig. 14a and b, the dust aerosols can be transported from the northern Arabian
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Peninsula to Central Asia under the control of the low-pressure system (trough line at
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500hpa is located at 35°E). With the extension of the low-pressure system to the northern
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Arabian Peninsula, strong southwest winds induced by the trough of low-pressure carry
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the dust aerosols northeastward to Central Asia. The dust aerosols transported from North
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Africa to Central Asia are also assisted by a deep cyclone (low-pressure system) located
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further to the west. As shown in Fig. 14c, an obvious cyclone is located over southern
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Europe to western Russia at 850 hPa. As shown in Fig. 14d, under the control of the low-
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pressure system (trough line at 500hpa is located at 15°E), the dust aerosols are
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transported northeastward across the Arabian Peninsula to Central Asia with the strong
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southwest winds.
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Fig. 15 shows the distributions of the daily mean wind vectors (arrows) and
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geopotential heights (colors) at 850 hPa and 500 hPa during 35 and 10 smoke events
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sourcing from Russia and Europe, respectively showing that. The smoke aerosols are
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mainly transported from Russia and Europe under the control of a high-pressure system
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at 850 hPa (Fig. 15a and c). As shown in Fig 15a, controlled by the anticyclone locating
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at northwestern Central Asia, a strong northwest wind directed from western Russia to
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northern Kazakhstan drives the smoke aerosols into Central Asia. As shown in Fig 15c,
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there is an anticyclone extending from Eastern Europe to the Aral Sea a weak trough over
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Eastern Europe and a low-pressure system over the western Russia. Under the control of
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these three weather systems, the smoke aerosols originating from Europe are efficiently
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transported to Central Asia.
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5. Conclusions
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In this study, using cloud images from Terra and Aqua MODIS observations, CALIPSO
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satellite observations and meteorological data, aerosol events appearing in Central Asia
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were detected. The two typical dust and smoke aerosol events traversing Central Asia
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were investigated in detail. It was found that there were 227 aerosol events occurred in
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Central Asia from 2000 to 2017, including 75 in the spring, 47 in the summer, 70 in the
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autumn and 35 in the winter. Of all aerosol events, 60% were source from local emissions
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and 40% were source from outside of Central Asia. In the spring and summer, 63% of
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aerosol events observed in Central Asia were transported there from outside the region,
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the main aerosol types of these aerosol are smoke and dust. The dust aerosols were
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mainly transported from the northern Arabian Peninsula and North Africa in strong
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southwest winds associated with the formation and development of low-pressure systems
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over western Siberia. Smoke emissions observed in Central Asia were from Russia and
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Europe transported in strong northwest winds associated with anticyclones in northern
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Europe and Russia. Contrarily, in the autumn and winter, 85.7 percent of aerosol events
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observed in Central Asia are sourced from local emissions.
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Acknowledgements
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This research was mainly supported by the Strategic Priority Research Program of
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Chinese Academy of Sciences (Grant No. XDA2006010301), and jointly supported by
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National Natural Science Foundation of China (91737101 and 91744311).
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ACCEPTED MANUSCRIPT Table Captions: Table 1. Frequencies of smoke events transported from outside to Central Asia during period 2000-2017. Table 2. Frequencies of dust events transported from outside to Central Asia during period
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Season
Source Spring
Summer
Autumn
Winter
Russia
35
12
19
4
0
Europe
10
4
4
2
0
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Season
Source Northern Arabian
Total
Spring
Summer
Autumn
Winter
42
27
6
8
1
4
4
0
0
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North Africa
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ACCEPTED MANUSCRIPT Figure Captions: Figure 1. Topography over Central Asia with contours of terrain height in km (above mean sea level). The area enclosed by thick purple solid line indicates Central Asia for the purposes of the data presented in this paper. The red, blue, green and yellow lines indicate the CALIPSO orbit paths on 28 July 2010, 5 August 2010, 12 and 13 April 2011 respectively. Red dots denote the
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fire hot spots. Blue triangle denotes AERONET site. Figure 2. Distribution of the seasonal mean AOD obtained from MODIS during 2000-2017. Panel (a) for spring (March to May), (b) for summer (June to August), (c) for autumn (September to November), (d) for winter (December to February).
Figure 3. Cloud images derived from Terra and Aqua MODIS observation over the study area
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on 14 October, 2004, 15 June, 2005, 2 April, 2009 and 22 April, 2014.
Figure 4. Cloud images derived from Terra and Aqua MODIS observation over the study area
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on 28, 29 July and 1, 3, 5, 9 August, 2010.
Figure 5. Altitude-orbit cross-sections of the total attenuated backscattering (a1-a2), depolarization ratio (b1-b2) and classified particles (c1-c2) on 28 July and 5 August 2010 along the CALIPSO orbit path over Russia and Central Asia.
Figure 6. Distributions of daily mean wind vectors (arrows) and geopotential heights (colors, blue for low and red for high) at 500 hPa derived from ERA-Interim reanalysis data.
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Figure 7. Clustering analysis of the backward trajectories at Aktobe (a) and Astana (b) during the period from 1-14 August, 2010. The lines denote different trajectories with the percentage in the bracket indicating the percentage of a certain backward trajectories in the total number of trajectories.
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Figure 8. Cloud images derived from Terra and Aqua MODIS observation over the study area on 11, 12, 13 and 14 April, 2011.
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Figure 9. Altitude-orbit cross-sections of the total attenuated backscattering (a1-a2), depolarization ratio (b1-b2) and classified particles (c1-c2) on 12 and 13 April, 2011 along the CALIPSO satellite orbit path over the Arabian Peninsula and Central Asia. Panel (d) is the time series of daily mean AERONET AOD at IASBS station locating in the path of dust transport from northern Arabian Peninsula during period 10 to 15 April, 2011. Panel (e) is the time series of hourly averaged AERONET AOD at IASBS on 13 April, 2011. Figure 10. Distributions of daily mean wind vectors (arrows) and geopotential heights (colors, blue for low and red for high) at 500 hPa derived from ERA-Interim reanalysis data on 11, 12, 13 and 14 April, 2011. Figure 11. The forward trajectories of the Northern Arabia Peninsula from 12:00UTC 12 April to 00:00UTC 14 April, 2011.
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Figure 13. Clustering analysis of the backward trajectories at Nukus for all 157 aerosol events during the period 2005-2017.
Figure 14. Spatial distributions of daily mean wind vectors (arrows) and geopotential heights (colors, blue for low and red for high) at 850 hPa (a and c) and 500 hPa (b and d) from ERA-
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Interim reanalysis data during dust events over Central Asia during period from 2000-2017.
Panel (a) is the average during the dust events sourcing from the northern Arabian Peninsula (42 events), (b) is same as in (a) but for 500 hPa, (c) is the average during the during the dust events
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sourcing from North Africa (4 events), (d) is same as in (c) but for 500 hPa.
Figure 15. Spatial distributions of daily mean wind vectors (arrows) and geopotential heights (colors, blue for low and red for high) at 850 hPa (a and c) and 500 hPa (b and d) from ERAInterim reanalysis data during smoke events over Central Asia during period from 2000-2017. Panel (a) is the average during the smoke events sourcing from sourcing from Russia (35 events), (b) is same as in (a) but for 500 hPa, (c) is the average during the during the smoke events
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sourcing from Europe (10 events), (d) is same as in (c) but for 500 hPa.
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Figure 1. Topography over Central Asia with contours of terrain height in km (above mean sea level). The area enclosed by thick purple solid line indicates Central Asia for the purposes of the data presented in this paper. The red, blue, green and yellow lines indicate the CALIPSO orbit paths on 28 July 2010, 5 August 2010, 12 and 13
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April 2011 respectively. Red dots denote the fire hot spots. Blue triangle denotes AERONET site.
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Figure 2. Distribution of the seasonal mean AOD obtained from MODIS products during 2000-2017. Panel (a) for spring (March to May), (b) for summer (June to August), (c) for autumn (September to November), (d) for (December
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winter
to
February).
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Figure 3. Cloud images derived from Terra and Aqua MODIS observation over the study area on 14 October,
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2004, 15 June, 2005, 2 April, 2009 and 22 April, 2014.
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Figure 4. Cloud images derived from Terra and Aqua MODIS observation over the study area on 28, 29 July and
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Figure 5. Altitude-orbit cross-sections of the total attenuated backscattering (a1-a2), depolarization ratio (b1-b2) and classified particles (c1-c2) on 28 July and 5 August, 2010 along the CALIPSO orbit path over Russia and
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Central Asia.
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Figure 6. Distributions of daily mean wind vectors (arrows) and geopotential heights (colors, blue for low and
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red for high) at 500 hPa derived from ERA-Interim reanalysis data.
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Figure 7. Clustering analysis of the backward trajectories at Aktobe (a) and Astana (b) during the period from 114 August, 2010. The lines denote different trajectories with the percentage in the bracket indicating the a
certain
backward
trajectories
in
the
total
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Figure 8. Cloud images derived from Terra and Aqua MODIS observation over the study area on 11, 12, 13 and
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14 April, 2011.
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Figure 9. Altitude-orbit cross-sections of the total attenuated backscattering (a1-a2), depolarization ratio (b1-b2) and classified particles (c1-c2) on 12 and 13 April, 2011 along the CALIPSO orbit path over the Arabian Peninsula and Central Asia. Panel (d) is the time series of daily mean AERONET AOD at IASBS station locating in the path of dust transport from northern Arabian Peninsula during period 10 to 15 April, 2011. Panel (e) is the series
of
hourly
averaged
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AERONET
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IASBS
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2011.
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Figure 10. Distributions of daily mean wind vectors (arrows) and geopotential heights (colors, blue for low and
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red for high) at 500 hPa derived from ERA-Interim reanalysis data on 11, 12, 13 and 14 April, 2011.
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Figure 11. The forward trajectories of the Northern Arabia Peninsula from 12:00UTC 12 April to 00:00UTC 14
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Figure 12. Frequencies of aerosol events and dominant types of aerosols from different sources surrounding Central Asia in the spring and summer (a) and autumn and winter (c). Time series of annual frequencies of aerosol events sourcing from local (red line), Russia (purple line), Europe (green line), North Africa (blue line) and the northern Arabian Peninsula (yellow line) in the spring and summer (b) and autumn and winter (d) for the
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period 2000-2017. Frequencies of aerosol events in different seasons (e).
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Figure 13. Clustering analysis of the backward trajectories at Nukus for all 157 aerosol events during the period
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2005-2017.
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Figure 14. Spatial distributions of daily mean wind vectors (arrows) and geopotential heights (colors, blue for low and red for high) at 850 hPa and 500 hPa from ERA-Interim reanalysis data during dust events over Central
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Asia during period from 2000-2017. Panel (a) is the average during the dust events sourcing from the northern Arabian Peninsula (42 events), (b) is same as in (a) but for 500 hPa, (c) is the average during the during the dust sourcing
from
North
Africa
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(d)
is
same
as
in
(c)
but
for
500
hPa.
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Figure 15. Spatial distributions of daily mean wind vectors (arrows) and geopotential heights (colors, blue for low and red for high) at 850 hPa and 500 hPa from ERA-Interim reanalysis data during smoke events over Central Asia during period from 2000-2017. Panel (a) is the average during the smoke events sourcing from sourcing from Russia (35 events), (b) is same as in (a) but for 500 hPa, (c) is the average during the during the
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Dear Editor of the Atmospheric Environment,
Please find enclosed the manuscript: " Distribution, Source and Transport
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of the Aerosols over Central Asia ", by Liu et al., to be submitted to the Atmospheric Environment. We think the novelty of this work includes the following aspect:
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All the time, the sources and transport of aerosols over Central Asia are
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unknown and few analyzed because of limitation by scarce observations. However, the aerosols over the Central Asia have a potential influence to the downwind areas including East Asia. This study can show a situation of aerosol distribution over Central Asia and the transports from sources.
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1. Firstly, the aerosol sources transported to Central Asia are analyzed. The study area includes Central Asia, Russia, Arabia Peninsula, Europe and North Africa.
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2. Combining MODIS and CALIPSO observations, trajectory mode and
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meteorological reanalyze data, we investigate the frequency, source and transport of the dominant aerosol types over Central Asia in detail.
3. The meteorological conditions for controlling aerosols transport to Central Asia are also analyzed.
We deeply appreciate your consideration of our manuscript, and we look forward to receiving comments from the reviewers. If you have any
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queries, please don't hesitate to contact me at the address below. Thank you and best regards. Yours sincerely,
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Yuzhi Liu
Corresponding author:
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Name: Yuzhi Liu
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Tel: +86-931-8914282
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E-mail: [email protected]
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Dear Editor of the Atmospheric Environment,
Please find enclosed the manuscript: " Distribution, Source and Transport
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of the Aerosols over Central Asia ", by Liu et al., to be submitted to the Atmospheric Environment. No conflict of interest exits in the submission of this manuscript, and manuscript is approved by all authors for
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publication.
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I would like to declare on behalf of my co-authors that the work has not been published previously, and not under consideration for publication elsewhere, in whole or in part. All the authors listed have approved the manuscript that is enclosed.
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We deeply appreciate your consideration of our manuscript, and we look forward to receiving comments from the reviewers. If you have any
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queries, please don't hesitate to contact me at the address below.
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Thank you and best regards. Yours sincerely, Yuzhi Liu
Corresponding author: Name: Yuzhi Liu E-mail: [email protected]
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Tel: +86-931-8914282
S1352-2310(19)30279-1
DOI:
https://doi.org/10.1016/j.atmosenv.2019.04.052
Reference:
AEA 16680
To appear in:
Atmospheric Environment
Received Date: 10 October 2018 Revised Date:
23 April 2019
Accepted Date: 24 April 2019
Please cite this article as: Liu, Y., Zhu, Q., Wang, R., Xiao, K., Cha, P., Distribution, source and transport of the aerosols over Central Asia, Atmospheric Environment (2019), doi: https://doi.org/10.1016/ j.atmosenv.2019.04.052. This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
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Distribution, Source and Transport of the Aerosols over Central Asia
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Y. Liu*, Q. Zhu, R. Wang, K. Xiao, P. Cha
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Key Laboratory for Semi-Arid Climate Change of the Ministry of Education, College of
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Atmospheric Sciences, Lanzhou University, Lanzhou, 730000, China
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Corresponding author: Yuzhi Liu, E-mail: [email protected]
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ABSTRACT
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Limited by scarce observations, the sources and transport of aerosols over Central Asia
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are relatively unclear. In this study, using Terra and Aqua satellite images, Moderate
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Resolution Imaging Spectroradiometer (MODIS) data, Cloud-Aerosol Lidar and Infrared
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Pathfinder Satellite Observations (CALIPSO) satellite observations and meteorological
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reanalyze data, the distribution, source and transport of aerosols over Central Asia are
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investigated. We find that there are 227 aerosol events occurred in Central Asia during
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2000-2017 and the aerosols which can be transported from outside to Central Asia are
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dominated by dust and smoke (organic carbon and black carbon) particles. Statistical
34
analyses show that the contribution of the sources outside of Central Asia (76 times) to all
35
aerosol events (122 times) is greater than that of local emissions in Central Asia (46 times)
36
in the spring and summer during 2000-2017. The smoke events (39 times), sourcing from
37
Russia and Europe with strong northwest wind, account for 51.3% of total aerosol events
38
contributed by sources outside of Central Asia. Additionally, the dust events (37 times),
39
which mainly source from the northern Arabia Peninsula and North Africa with strong
40
southwest wind, account for 48.7% of the total aerosol events contributed by the sources
41
outside of Central Asia. On the contrary, the contribution of local emissions in Central
42
Asia (90 times) to all aerosol events (105 times) is greater than that of outside sources (15
43
times) in the autumn and winter. Result of clustering analyses for all 157 aerosol events
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during 2005-2017 is in agreement with the conclusion of statistical analyses based on
45
observations. This study can provide some evidence to understand the aerosol properties
46
over the Central Asia.
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Key words: dust, smoke, source, transport, Central Asia
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1. Introduction
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The atmospheric aerosol (Sokolik and Toon, 1996; Haywood and Boucher, 2000; Li,
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2004), which is composed of solid or liquid particles (Albrecht, 1989; Shi et al., 2005),
51
plays an important role in affecting the energy balance and climate system through direct
52
(Huang et al., 2007b, 2011; Ju and Han, 2011; Zhang et al., 2009; Liu et al., 2011, 2014),
53
indirect and semi-direct effects (Sassen, 2002; Huang et al., 2010). In addition, driven by
54
the atmospheric circulation, aerosols can influence the regional-scale air quality and even
55
contribute to global climate change. (Kahn et al., 2008; Martin et al., 2009; Shao et al.,
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2011; Wang et al., 2013).
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Central Asia, located in the temperate desert belt of the Northern Hemisphere, is an
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important regional aerosol source due to long rainless periods, large areas of desert and
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salt lakes, low vegetation coverage and frequent windstorms (Issanova et al., 2015;
60
Orlovsky and Indoitu, 2013; Sokolik et al., 2013; Shen et al., 2016). Recently, it was
61
found that dust events in Central Asia have decreased for the period 1980-2000 relative to
62
1936-1980 (Indoitu et al., 2012). Issanova et al. (2015) have come to a similar conclusion
63
using weather station observations in Kazakhstan for 1970-2010. Supporting these
64
observations, model simulations also suggested a significant decreasing trend of dust
65
activity from 2000 to 2014 (Xi and Sokolik, 2016). Overall, cumulative evidence
66
suggests that the frequency of dust storms in the Central Asia arid zone has dropped
67
significantly in recent decades, especially in the Karakum Desert (the largest desert in
68
Central Asia). A possible cause of the recent decrease in dust storms has been linked to
69
the weakening of surface wind fields in the region and recovery of the vegetation cover
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(Shen et al., 2016).
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However, for aerosol events over Central Asia, the understanding of their sources is
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still relatively unknown (Miller-Schulze et al., 2011). In view of understanding the
73
influence of aerosols over Central Asia on downstream regions, it is particularly
74
important to clarify the distribution, source and transport of aerosols into and over
75
Central Asia. In this study based on Cloud-Aerosol Lidar and Infrared Pathfinder Satellite
76
Observations (CALIPSO) and Moderate Resolution Imaging Spectroradiometer (MODIS)
77
Terra/Aqua satellites, reanalysis data and trajectory model simulations, we present
78
extensive data on the sources and transport of these aerosols. The details of data sets are
79
given in Section 2. In section 3, distribution of aerosols over Central Asia are discussed
80
and identification of aerosol events are presented. Statistical analyses of all aerosol events
81
and summary are presented in Section 4 and Section 5, respectively.
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2. Data sets and model description
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2.1 CALIPSO profiles
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CALIPSO, launched in 2006, is a satellite in the Earth System Science Pathfinder (ESSP)
85
program of the National Aeronautics and Space Administration (NASA) of the United
86
States. The Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) sensor, the
87
main equipment on the CALIPSO satellite, can provide the vertical distribution of
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extinction backscatter coefficients for both 532 nm and 1064 nm during day and night. In
89
this study, data consisting of the total and perpendicular attenuated backscatter
90
coefficients at 532 nm from CALIPSO Level 1B product and data comprising aerosol
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particle properties from the CALIPSO lidar Vertical Feature Mask (VFM) product
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version 4.10 are used to identify dust and smoke aerosols.
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2.2 MODIS data
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MODIS is an optical remote sensor on board the Terra and Aqua satellites which provides
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global observations of cloud, water vapor and aerosol. In this study, the images derived
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from Terra and Aqua MODIS products are used to identify the aerosols suspending over
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Central Asia. For the desert and semi-desert regions studied herein the Deep Blue aerosol
98
optical depth (AOD) retrievals from the MOD08_M3 products with a latitudinal and
99
longitudinal resolution of 1° × 1° are used to investigate the distribution of aerosols in
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each season over Central Asia. The MOD14 Level 3 Thermal Anomalies/Fire product,
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which is primarily derived from MODIS 4- and 11-µm radiances, contains the most basic
102
level of MODIS fire data. In this study, the daily MOD14A1 product with a 1-km
103
resolution is used to determine the locations of forest fires.
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2.3 AERONET data
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Aerosol Robotic Network (AERONET), which is composed of numerous ground-based
106
remote sensing aerosol networks, can provide the real time AOD distribution at a global
107
scale. In this study, AERONET Level 1.5 Version 2 data which are automatically cloud
108
cleared at IASBS station are used.
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2.4 ECMWF data
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The European Centre for Medium-Range Weather Forecasts (ECMWF) ERA-Interim
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reanalysis data is used to investigate the transport mechanism of aerosols from a
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meteorological perspective. Daily mean meteorological contours of the U and V
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components of wind speed and the geopotential height from ECMWF are used. The
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reanalysis data have a spatial resolution of 0.5°×0.5° with a time interval of 6 hour (00:00,
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06:00, 12:00 and 18:00 UTC).
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2.5 HYSPLIT-4 model
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The HYSPLIT-4 model, provided by the National Oceanic and Atmospheric
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Administration (NOAA) Air Resources Laboratory and the Australian Meteorological
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Agency, can calculate the simple air mass trajectories and simulate complex diffusion and
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deposition. The meteorological data for the model have to be processed to a HYSPLIT
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compatible format. The 6-h-interval final archive data are generated from the NCEP
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(National Centers for Environmental Prediction) Global Data Assimilation System
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(GDAS) reanalysis 3-dimensional meteorological fields. In this study, the HYSPLIT-4
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model is used to verify the transport of aerosols and perform the clustering analysis of
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backward trajectories
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3. Aerosols transported from outside to Central Asia
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For the purposes of this study, Central Asia is defined as the region connecting East Asia
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and Europe comprised of Uzbekistan, Kyrgyzstan, Turkmenistan, Tajikistan and
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Kazakhstan extending over a latitude-longitude region between 35-57°N, 46-88°E as
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shown by the area enclosed within the purple line in Fig. 1.
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Figure 2 shows the distribution of AOD derived from MODIS products in each
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season during the period 2000-2017. As shown in Fig. 2, AODs in Central Asia are
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relatively higher in the spring and summer but lower in the autumn and winter. The
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aerosols loading in the atmosphere over Central Asia decrease gradually from west to east,
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the area from the Caspian Sea to Aral Sea is a center with high aerosol optical depth in
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Central Asia.
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In this study, the aerosol events linking with the sources outside of Central Asia can
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influence the aerosol loading in the atmosphere over large area, under the circumstance,
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CALIPSO satellite can easily observe these aerosols. However, as shown in Fig. 3, the
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aerosols during some events sourcing from local emission in Central Asia are constrained
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locally and can influence few areas, thus, such aerosol events cannot be observed well by
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CALIPSO satellite. Therefore, in this study, only the aerosol types during the events
144
contributed by the sources outside of Central Asia are distinguished. Here, though the
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aerosol events contributed by local emissions are gathered statistics, the aerosol types are
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not identified.
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In the following, detecting and identifying the aerosol events contributed by the
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sources outside of Central Asia will be shown as examples of all events in statistical
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analysis. To identify the aerosols which can be transported from outside to Central Asia,
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three steps are performed. Firstly, the daily products of visible cloud images from
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MODIS observations are used to detect the aerosol events occurred over Central Asia.
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Next, the aerosol types in these events are identified. CALIPSO satellite can provide the
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vertical information for aerosols, which is very useful to identify the aerosol type. Since
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the CALIPSO satellite was launched in 2006, the aerosol types can be distinguished
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according to the CALIPSO satellite observations for the period 2006-2017, in which the
156
determination of aerosol types from MODIS cloud images are verified by the CALIPSO
157
satellite observations simultaneously. Based on verification of the MODIS cloud images
158
by the CALIPSO observations, the grey and yellow plumes suspending over the vicinity
159
of Central Asia in the MODIS cloud images are considered as smoke and dust aerosols,
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respectively. Correspondingly, for the period 2000-2005, the aerosol types are determined
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according to the plume colors in the cloud images observed by MODIS aboard on Terra
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and Aqua satellite. And then, according to the distribution of wind fields, the aerosol
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events contributed by the sources outside of Central Asia are finally confirmed. Basing on
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the identification of these aerosol events, we find the aerosols transported from outside to
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Central Asia are smoke and dust. Here we analyze statistically the smoke and dust events
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contributed by outside sources for the period 2000-2017. In the following, Section 3.1
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and 3.2 illustrate two examples of detecting aerosol events transported from outside to
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Central Asia.
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3.1 Detection of smoke aerosols transported from outside to Central Asia
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Figure 4 shows the cloud images obtained from Terra and Aqua MODIS observation over
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the study area on 28, 29 July and 1, 3, 5, 9 August, 2010. As shown in Fig. 4a, the
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aerosols suspended over the western Russia, and began to move eastward on 29 July (Fig.
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3b). From 1 to 5 August, 2010, the aerosols were continuously transported eastward and
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southward and spread over the north part of Kazakhstan on 5 August, 2010 (Fig. 4e). The
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movement of aerosols from Russia to Central Asia continued until 14 August.
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Furthermore, using the CALIPSO product, which detects aerosols over a bright
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surface and beneath thin clouds (Vaughan et al., 2004; Winker et al., 2006), aerosol
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categories can be identified. Fig. 5 shows the altitude-orbit cross-section of the total
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attenuated backscattering intensity (a1-a2), depolarization ratio (b1-b2), and distribution
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of cloud and aerosol types (c1-c2) on 28 July and 05 August, 2010. The satellite orbit
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paths are presented in red and blue lines in Fig. 1, respectively. In Fig. 5a1 and a2 the
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gray shading shows topography, the white parts denote clouds, the deep blue area denotes
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the region without signal because of cloud blocking and the green-yellow-orange color
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represents aerosols.
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As shown in Fig. 5a1 and b1, the total attenuated backscatter coefficient and volume
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depolarization ratio range from 0.003-0.005 km−1sr−1 and 0-0.4, respectively. In particular,
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over the area between 54°N and 70°N, the total attenuated backscatter values are large
189
and the volume depolarization ratio ranges from 0.06 to 0.2. It was reported by Omar et
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al. (2009) that the total attenuated backscatter coefficient of aerosol at 532 nm is
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concentrated in the range from 0.003 to 0.009 km-1sr-1 whereas biomass burning smoke
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aerosol is determined when the depolarization ratio is within the range from 0.03 and
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0.11 (Chiang et al., 2007; Huang et al., 2007a; Xie et al., 2008), which are shown in Fig.
194
5b1 and b2 as light blue and green parts. Therefore, combining the values of total
195
attenuated backscatter coefficient at 532 nm and the depolarization ratio, it can be found
196
that the main component of these detected aerosols over western Russia is smoke aerosol
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during this event. As shown in Fig. 5c1, smoke aerosols are observed over western Russia
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on 28 July 2010 simultaneously with polluted dust detected by CALIPSO. Similarly to
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the data presented in Fig. 5a1-c1, a large number of smoke aerosols are also detected on 5
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August (Fig. 5a2-c2) and covering the area from 60°N to 45°N, illustrating that smoke
201
aerosols have spread from Russia to northern Kazakhstan at this time. Simultaneously,
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thermal anomalies and fires from the MOD14 data were analyzed. During the period of
203
28 July to 4 August 2010, an accumulation of 4758 hot spots with highest credibility were
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detected, as shown in Fig. 1, in the vast area over western Russia. It confirms that the
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smoke is the dominant aerosol type during this event.
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As earlier studies have shown (Dirksen et al., 2009; Miller et al., 2011; Sang et al.,
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2011) the transport of aerosols is principally driven by atmospheric circulation. Figure 6
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displays the geopotential heights and wind vectors at 500 hPa during the period of 28
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July to 9 August, 2010 showing an anticyclone (high-pressure system) with an obvious
210
center over the western Russia. From 28 July to 1 August, strong north wind ahead of
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anticyclone covering the area from western Russia to Central Asia drives the smoke
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plumes southward from western Russia to Central Asia, meanwhile, the high-pressure
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system extends towards east. On 3 August, the strength of high-pressure system center
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becomes to weaken, inducing the smoke particles are pervaded over the whole area of
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Central Asia. From 5 to 9, August, the anticyclone center moves away the Central Asia
216
and locates over the north side of western Russia. The strong north winds ahead of the
217
anticyclone continuously drive smoke aerosols to Central Asia. The simulations from the
218
HYSPLIT-4 model verify the transport of smoke aerosols as shown in Fig. 7 from the
219
cluster analysis of 72h backward trajectory from Aktobe and Astana in northern
220
Kazakhstan. The simulation results verify that the aerosols at this time over northern
221
Kazakhstan are transported from western Russia. As suggested earlier by Zhu et al.,
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(2018) who noted smoke aerosols from Siberian forest fires can be transported to Central
223
Asia. Thus, it is postulated that the smoke aerosols transported from western Russian
224
region are mainly produced by the forest fires.
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Based on the method of identifying the smoke aerosol events from the MODIS and
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CALIPSO satellite observations, all the smoke events transported from outside to Central
227
Asia are distinguished for period 2000-2017. The statistical result is shown in Table 1. As
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listed in Table 1, there are totally 45 smoke events contributed by the sources outside of
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Central Asia, in which 35 and 10 events are from Russia and Europe, respectively. And
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these events mainly occur in the spring and summer.
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3.2 Detection of dust aerosols transported from outside to Central Asia
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Figure 8 shows the cloud images from MODIS products over the study area from 11 to
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14 April, 2011. On 12 April, aerosols can be found over Iraq. After a day, cumulative
234
aerosols spread over the junction of Saudi Arabia and Iraq, in which a small number of
235
aerosols cross Iran to the southern Caspian Sea. Figure 9 presents the altitude-orbit cross-
236
section of the total attenuated backscattering intensity, depolarization ratio, spatial
237
distribution of cloud and aerosol types on 12 April and 13 April, 2011, and the
238
AERONET AOD at IASBS station locating in the path of dust transport from northern
239
Arabian Peninsula during this event. The satellite orbit paths are presented in green and
240
yellow lines in Fig. 1, respectively. Contrary to the smoke aerosols, the depolarization
241
ratio of dust aerosols is generally greater than 0.2 even can reach over 0.4 in the severe
242
sandstorms (Chiang et al., 2007; Huang et al., 2007a; Xie et al., 2008). The dust aerosols
243
are presented in yellow, orange and red colors, as shown in Fig. 9b1 and b2. As given in
244
Fig. 9a1 and b1, in the region ranging 27-36°N and 48.5-50.5°E, the total attenuated
245
backscatter and volume depolarization ratio range from 0.003-0.008 km-1sr-1 and 0.2-0.5,
246
respectively, indicating that the strong dust particles are the main aerosol component over
247
Iraq. According to Fig. 9a2-c2, dense dust aerosols are observed over the region of 33-
248
42°N and 50-54°E indicating the transport of dust aerosols from the northern Arabian
249
Peninsula to Caspian Sea on 13 April, 2011. Simultaneously, the daily AOD (Fig. 8d)
250
observed at the AERONET IASBS station (36.42°N, 48.30°E), which is adjacent to
251
northern Arabian Peninsula and in the path of dust transport from northern Arabian
252
Peninsula to Central Asia, during period 10 to 15 April indicates a peak value on 13 April.
253
The hourly mean AOD (Fig. 9e) suggests high values in the day of 13 April. Therefore,
254
combining of satellite observation and ground-based monitoring confirms the dust
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aerosols over the Central Asia are transported from northern Arabian Peninsula. As shown in Fig. 10, a deep cyclone (low-pressure system) exists over western
257
Russia and an anticyclone (high-pressure system) over the southern Arabia Peninsula
258
during this dust event. The Central Asia locates in the junction of low-pressure and high-
259
pressure systems. From 11 to 12 April, 2011, the low-pressure system extends into the
260
northern Arabia Peninsula (Fig. 10a and b). As such, more strong southwesterly winds
261
blow over the area from northern Arabian Peninsula to Central Asia, producing a strong
262
dust storm in the northern Arabian Peninsula. With the persistence of the linked cyclone
263
and anticyclone activity (Fig. 10c and d), dust aerosols are continuously transported from
264
the Arabian Peninsula to Central Asia. Additionally, as shown in Fig. 11, the 36-hours
265
forward trajectories also show that the dust aerosols originating from the Arabian
266
Peninsula are being transported to Central Asia.
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According to the method of identifying the dust aerosol events from the MODIS and
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CALIPSO satellite observations, we distinguished all the dust events transported from
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outside to Central Asia for period 2000-2017, as listed in Table 2. The result shows that
270
these dust events are mainly induced by the dust transport from northern Arabian
271
Peninsula, especially in the spring. Among these dust events, 88% of events are sourcing
272
from the northern Arabian Peninsula. Additionally, in the spring, the dust aerosols can be
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transported from North Africa.
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4. Source statistics for the aerosol events in Central Asia
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As described in the above two aerosol examples, combing daily images from
277
MODIS observation, CALIPSO observations and meteorology fields, the aerosol events
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over Central Asia during 2000-2017 are detected. Based on the identifications of aerosol events during the period 2000-2017, these
280
aerosol events over Central Asia are analyzed statistically. The frequencies of aerosol
281
event and dominant aerosol types from 2000 to 2017 are shown in Fig. 12. From Fig. 12a,
282
it can be seen that the 122 aerosol events occurring in Central Asia during the spring and
283
summer, of which the aerosols in 46, 33, 31, 8 and 4 episodes source from local
284
emissions, northern Arabian Peninsula, Russia, Europe (except for the European part of
285
Russia) and North Africa, respectively. The type of the aerosols sourcing from Russia and
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Europe is mainly smoke aerosol (as shown in Section 3.1), and the aerosol transported
287
from the northern Arabian Peninsula and North Africa is mainly dust aerosol (as shown in
288
Section 3.2). The total dust and smoke events sourcing from outside of Central Asia are
289
37 and 39 times, respectively. Additionally, 62.3% of total aerosol events source from
290
outside of Central Asia, in which 84.2% are from the northern Arabian Peninsula and
291
Russia. As shown in Fig. 12b, the smoke events sourcing from Russian mainly occur in
292
the periods 2000-2004 and 2012-2013, and the smoke events originating from the
293
northern Arabian Peninsula mainly occur in the period 2008-2012. Besides, the aerosol
294
events with complicated aerosol type due to local emission in the Central Asia account
295
for about 37.7% of total aerosol events. On the contrary, comparing with the spring and
296
summer, 90 aerosol events are contributed by the local sources in all the 105 aerosol
297
events in the autumn and winter, accounting for about 85.7% of total aerosol events
298
because of local emissions. Among all the aerosol events, there are only 9, 4 and 2
299
aerosol events sourcing from northern Arabian Peninsula, Russia and Europe (except for
300
the European part of Russia), respectively. As shown in Fig. 12e, the aerosol events
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occurring in the spring is the most in all seasons, followed by autumn, and the least in the
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winter. Figure 13 shows the clustering analysis of 72h backward trajectories for all 157
304
aerosol events during 2005-2017 at Nukus. The clustering analysis is performed for the
305
period 2005-2017 because the 6-h-interval data from NCEP (input to the HYSPLIT
306
model) are from 2005. The simulations from the HYSPLIT-4 model show of all the
307
backward trajectories, 8%, 11%, 12%, 26% and 43% of trajectories are from North Africa,
308
Russia, Europe, northern Arabian Peninsula and Central Asia (Fig. 13), respectively. The
309
statistical results of all 157 aerosol events during 2005-2017 indicate 2%, 12%, 4%, 24%
310
and 57% of all the aerosol events are from North Africa, Russia, Europe, northern
311
Arabian Peninsula and Central Asia, respectively. Although there are some differences
312
between the results of model and observations, the simulation results show that the
313
aerosols occurred in Central Asia are mainly from North Africa, Russia, Europe, northern
314
Arabian Peninsula and local emissions.
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Figure 14 shows the distributions of daily mean wind vectors (arrows) and
316
geopotential heights (colors) at 850 hPa and 500 hPa during 42 dust events sourcing from
317
the northern Arabian Peninsula and 4 dust events sourcing from North Africa. As shown
318
in Fig. 14a and b, the dust aerosols can be transported from the northern Arabian
319
Peninsula to Central Asia under the control of the low-pressure system (trough line at
320
500hpa is located at 35°E). With the extension of the low-pressure system to the northern
321
Arabian Peninsula, strong southwest winds induced by the trough of low-pressure carry
322
the dust aerosols northeastward to Central Asia. The dust aerosols transported from North
323
Africa to Central Asia are also assisted by a deep cyclone (low-pressure system) located
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further to the west. As shown in Fig. 14c, an obvious cyclone is located over southern
325
Europe to western Russia at 850 hPa. As shown in Fig. 14d, under the control of the low-
326
pressure system (trough line at 500hpa is located at 15°E), the dust aerosols are
327
transported northeastward across the Arabian Peninsula to Central Asia with the strong
328
southwest winds.
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Fig. 15 shows the distributions of the daily mean wind vectors (arrows) and
330
geopotential heights (colors) at 850 hPa and 500 hPa during 35 and 10 smoke events
331
sourcing from Russia and Europe, respectively showing that. The smoke aerosols are
332
mainly transported from Russia and Europe under the control of a high-pressure system
333
at 850 hPa (Fig. 15a and c). As shown in Fig 15a, controlled by the anticyclone locating
334
at northwestern Central Asia, a strong northwest wind directed from western Russia to
335
northern Kazakhstan drives the smoke aerosols into Central Asia. As shown in Fig 15c,
336
there is an anticyclone extending from Eastern Europe to the Aral Sea a weak trough over
337
Eastern Europe and a low-pressure system over the western Russia. Under the control of
338
these three weather systems, the smoke aerosols originating from Europe are efficiently
339
transported to Central Asia.
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5. Conclusions
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In this study, using cloud images from Terra and Aqua MODIS observations, CALIPSO
343
satellite observations and meteorological data, aerosol events appearing in Central Asia
344
were detected. The two typical dust and smoke aerosol events traversing Central Asia
345
were investigated in detail. It was found that there were 227 aerosol events occurred in
346
Central Asia from 2000 to 2017, including 75 in the spring, 47 in the summer, 70 in the
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autumn and 35 in the winter. Of all aerosol events, 60% were source from local emissions
348
and 40% were source from outside of Central Asia. In the spring and summer, 63% of
349
aerosol events observed in Central Asia were transported there from outside the region,
350
the main aerosol types of these aerosol are smoke and dust. The dust aerosols were
351
mainly transported from the northern Arabian Peninsula and North Africa in strong
352
southwest winds associated with the formation and development of low-pressure systems
353
over western Siberia. Smoke emissions observed in Central Asia were from Russia and
354
Europe transported in strong northwest winds associated with anticyclones in northern
355
Europe and Russia. Contrarily, in the autumn and winter, 85.7 percent of aerosol events
356
observed in Central Asia are sourced from local emissions.
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Acknowledgements
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This research was mainly supported by the Strategic Priority Research Program of
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Chinese Academy of Sciences (Grant No. XDA2006010301), and jointly supported by
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National Natural Science Foundation of China (91737101 and 91744311).
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ACCEPTED MANUSCRIPT Table Captions: Table 1. Frequencies of smoke events transported from outside to Central Asia during period 2000-2017. Table 2. Frequencies of dust events transported from outside to Central Asia during period
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Season
Source Spring
Summer
Autumn
Winter
Russia
35
12
19
4
0
Europe
10
4
4
2
0
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Season
Source Northern Arabian
Total
Spring
Summer
Autumn
Winter
42
27
6
8
1
4
4
0
0
0
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North Africa
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Peninsula
ACCEPTED MANUSCRIPT Figure Captions: Figure 1. Topography over Central Asia with contours of terrain height in km (above mean sea level). The area enclosed by thick purple solid line indicates Central Asia for the purposes of the data presented in this paper. The red, blue, green and yellow lines indicate the CALIPSO orbit paths on 28 July 2010, 5 August 2010, 12 and 13 April 2011 respectively. Red dots denote the
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fire hot spots. Blue triangle denotes AERONET site. Figure 2. Distribution of the seasonal mean AOD obtained from MODIS during 2000-2017. Panel (a) for spring (March to May), (b) for summer (June to August), (c) for autumn (September to November), (d) for winter (December to February).
Figure 3. Cloud images derived from Terra and Aqua MODIS observation over the study area
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on 14 October, 2004, 15 June, 2005, 2 April, 2009 and 22 April, 2014.
Figure 4. Cloud images derived from Terra and Aqua MODIS observation over the study area
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on 28, 29 July and 1, 3, 5, 9 August, 2010.
Figure 5. Altitude-orbit cross-sections of the total attenuated backscattering (a1-a2), depolarization ratio (b1-b2) and classified particles (c1-c2) on 28 July and 5 August 2010 along the CALIPSO orbit path over Russia and Central Asia.
Figure 6. Distributions of daily mean wind vectors (arrows) and geopotential heights (colors, blue for low and red for high) at 500 hPa derived from ERA-Interim reanalysis data.
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Figure 7. Clustering analysis of the backward trajectories at Aktobe (a) and Astana (b) during the period from 1-14 August, 2010. The lines denote different trajectories with the percentage in the bracket indicating the percentage of a certain backward trajectories in the total number of trajectories.
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Figure 8. Cloud images derived from Terra and Aqua MODIS observation over the study area on 11, 12, 13 and 14 April, 2011.
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Figure 9. Altitude-orbit cross-sections of the total attenuated backscattering (a1-a2), depolarization ratio (b1-b2) and classified particles (c1-c2) on 12 and 13 April, 2011 along the CALIPSO satellite orbit path over the Arabian Peninsula and Central Asia. Panel (d) is the time series of daily mean AERONET AOD at IASBS station locating in the path of dust transport from northern Arabian Peninsula during period 10 to 15 April, 2011. Panel (e) is the time series of hourly averaged AERONET AOD at IASBS on 13 April, 2011. Figure 10. Distributions of daily mean wind vectors (arrows) and geopotential heights (colors, blue for low and red for high) at 500 hPa derived from ERA-Interim reanalysis data on 11, 12, 13 and 14 April, 2011. Figure 11. The forward trajectories of the Northern Arabia Peninsula from 12:00UTC 12 April to 00:00UTC 14 April, 2011.
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Figure 13. Clustering analysis of the backward trajectories at Nukus for all 157 aerosol events during the period 2005-2017.
Figure 14. Spatial distributions of daily mean wind vectors (arrows) and geopotential heights (colors, blue for low and red for high) at 850 hPa (a and c) and 500 hPa (b and d) from ERA-
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Interim reanalysis data during dust events over Central Asia during period from 2000-2017.
Panel (a) is the average during the dust events sourcing from the northern Arabian Peninsula (42 events), (b) is same as in (a) but for 500 hPa, (c) is the average during the during the dust events
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sourcing from North Africa (4 events), (d) is same as in (c) but for 500 hPa.
Figure 15. Spatial distributions of daily mean wind vectors (arrows) and geopotential heights (colors, blue for low and red for high) at 850 hPa (a and c) and 500 hPa (b and d) from ERAInterim reanalysis data during smoke events over Central Asia during period from 2000-2017. Panel (a) is the average during the smoke events sourcing from sourcing from Russia (35 events), (b) is same as in (a) but for 500 hPa, (c) is the average during the during the smoke events
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sourcing from Europe (10 events), (d) is same as in (c) but for 500 hPa.
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Figure 1. Topography over Central Asia with contours of terrain height in km (above mean sea level). The area enclosed by thick purple solid line indicates Central Asia for the purposes of the data presented in this paper. The red, blue, green and yellow lines indicate the CALIPSO orbit paths on 28 July 2010, 5 August 2010, 12 and 13
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April 2011 respectively. Red dots denote the fire hot spots. Blue triangle denotes AERONET site.
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Figure 2. Distribution of the seasonal mean AOD obtained from MODIS products during 2000-2017. Panel (a) for spring (March to May), (b) for summer (June to August), (c) for autumn (September to November), (d) for (December
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winter
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February).
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Figure 3. Cloud images derived from Terra and Aqua MODIS observation over the study area on 14 October,
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2004, 15 June, 2005, 2 April, 2009 and 22 April, 2014.
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Figure 4. Cloud images derived from Terra and Aqua MODIS observation over the study area on 28, 29 July and
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Figure 5. Altitude-orbit cross-sections of the total attenuated backscattering (a1-a2), depolarization ratio (b1-b2) and classified particles (c1-c2) on 28 July and 5 August, 2010 along the CALIPSO orbit path over Russia and
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Central Asia.
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Figure 6. Distributions of daily mean wind vectors (arrows) and geopotential heights (colors, blue for low and
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red for high) at 500 hPa derived from ERA-Interim reanalysis data.
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Figure 7. Clustering analysis of the backward trajectories at Aktobe (a) and Astana (b) during the period from 114 August, 2010. The lines denote different trajectories with the percentage in the bracket indicating the a
certain
backward
trajectories
in
the
total
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Figure 8. Cloud images derived from Terra and Aqua MODIS observation over the study area on 11, 12, 13 and
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Figure 9. Altitude-orbit cross-sections of the total attenuated backscattering (a1-a2), depolarization ratio (b1-b2) and classified particles (c1-c2) on 12 and 13 April, 2011 along the CALIPSO orbit path over the Arabian Peninsula and Central Asia. Panel (d) is the time series of daily mean AERONET AOD at IASBS station locating in the path of dust transport from northern Arabian Peninsula during period 10 to 15 April, 2011. Panel (e) is the series
of
hourly
averaged
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Figure 10. Distributions of daily mean wind vectors (arrows) and geopotential heights (colors, blue for low and
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Figure 11. The forward trajectories of the Northern Arabia Peninsula from 12:00UTC 12 April to 00:00UTC 14
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Figure 12. Frequencies of aerosol events and dominant types of aerosols from different sources surrounding Central Asia in the spring and summer (a) and autumn and winter (c). Time series of annual frequencies of aerosol events sourcing from local (red line), Russia (purple line), Europe (green line), North Africa (blue line) and the northern Arabian Peninsula (yellow line) in the spring and summer (b) and autumn and winter (d) for the
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period 2000-2017. Frequencies of aerosol events in different seasons (e).
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Figure 13. Clustering analysis of the backward trajectories at Nukus for all 157 aerosol events during the period
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2005-2017.
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Figure 14. Spatial distributions of daily mean wind vectors (arrows) and geopotential heights (colors, blue for low and red for high) at 850 hPa and 500 hPa from ERA-Interim reanalysis data during dust events over Central
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Asia during period from 2000-2017. Panel (a) is the average during the dust events sourcing from the northern Arabian Peninsula (42 events), (b) is same as in (a) but for 500 hPa, (c) is the average during the during the dust sourcing
from
North
Africa
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(d)
is
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in
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500
hPa.
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Figure 15. Spatial distributions of daily mean wind vectors (arrows) and geopotential heights (colors, blue for low and red for high) at 850 hPa and 500 hPa from ERA-Interim reanalysis data during smoke events over Central Asia during period from 2000-2017. Panel (a) is the average during the smoke events sourcing from sourcing from Russia (35 events), (b) is same as in (a) but for 500 hPa, (c) is the average during the during the
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Dear Editor of the Atmospheric Environment,
Please find enclosed the manuscript: " Distribution, Source and Transport
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of the Aerosols over Central Asia ", by Liu et al., to be submitted to the Atmospheric Environment. We think the novelty of this work includes the following aspect:
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All the time, the sources and transport of aerosols over Central Asia are
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unknown and few analyzed because of limitation by scarce observations. However, the aerosols over the Central Asia have a potential influence to the downwind areas including East Asia. This study can show a situation of aerosol distribution over Central Asia and the transports from sources.
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1. Firstly, the aerosol sources transported to Central Asia are analyzed. The study area includes Central Asia, Russia, Arabia Peninsula, Europe and North Africa.
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2. Combining MODIS and CALIPSO observations, trajectory mode and
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meteorological reanalyze data, we investigate the frequency, source and transport of the dominant aerosol types over Central Asia in detail.
3. The meteorological conditions for controlling aerosols transport to Central Asia are also analyzed.
We deeply appreciate your consideration of our manuscript, and we look forward to receiving comments from the reviewers. If you have any
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queries, please don't hesitate to contact me at the address below. Thank you and best regards. Yours sincerely,
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Yuzhi Liu
Corresponding author:
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Name: Yuzhi Liu
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Tel: +86-931-8914282
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E-mail: [email protected]
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Dear Editor of the Atmospheric Environment,
Please find enclosed the manuscript: " Distribution, Source and Transport
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of the Aerosols over Central Asia ", by Liu et al., to be submitted to the Atmospheric Environment. No conflict of interest exits in the submission of this manuscript, and manuscript is approved by all authors for
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publication.
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I would like to declare on behalf of my co-authors that the work has not been published previously, and not under consideration for publication elsewhere, in whole or in part. All the authors listed have approved the manuscript that is enclosed.
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We deeply appreciate your consideration of our manuscript, and we look forward to receiving comments from the reviewers. If you have any
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queries, please don't hesitate to contact me at the address below.
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Thank you and best regards. Yours sincerely, Yuzhi Liu
Corresponding author: Name: Yuzhi Liu E-mail: [email protected]
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Tel: +86-931-8914282