Optical and Physical Characteristics of the Lowest Aerosol Layers Over the Yellow River Basin

atmosphere

Article Optical and Physical Characteristics of the Lowest Aerosol Layers over the Yellow River Basin

Miao Zhang 1,*, Jing Liu 2, Muhammad Bilal 3,* , Chun Zhang 1, Feifei Zhao 1, Xiaoyan Xie 4,5 and Khaled Mohamed Khedher 6,7 1 School of Environmental Science and Tourism, Nanyang Normal University, Wolong Road No.1638, Nan Yang 473061, China; [email protected] (C.Z.); zﬀ@nynu.edu.cn (F.Z.) 2 Lingnan College, Sun Yat-sen University, Guangzhou 510275, China; [email protected] 3 School of Marine Sciences, Nanjing University of Information Science & Technology, Nanjing 2100444, China 4 South China Sea Fisheries Research Institute, Chinese Academy of Fishery Sciences, Guangzhou 510300, China; [email protected] 5 College of Marine Science, Shanghai Ocean University, Shanghai 201306, China 6 Department of Civil Engineering, College of Engineering, King Khalid University, Abha 61421, Saudi Arabia; [email protected] 7 Department of Civil Engineering, Institut Superieur des Etudes Technologiques, Campus Universitaire Mrezgua, Nabeul 8000, Tunisia * Correspondence: [email protected] (M.Z.); [email protected] (M.B.)

Received: 17 September 2019; Accepted: 19 October 2019; Published: 22 October 2019

Abstract: Studying the presence of aerosols in different atmospheric layers helps researchers understand their impacts on climate change, air quality, and human health. Therefore, in the present study, the optical and physical properties of aerosol layers over the Yellow River Basin (YERB) were investigated using the CALIPSO Level 2 aerosol layer products from January 2007 to December 2014. The Yellow River Basin was divided into three sub-regions i.e., YERB1 (the plain region downstream of the YERB), YERB2 (the Loess Plateau region in the middle reaches of the YERB), and YERB3 (the mountainous terrain in the upper reaches of the YERB). The results showed that the amount (number) of aerosol layers (N) was relatively large (>2 layers) in the lower part of the YERB (YERB1), which was mainly caused by atmospheric convection. The height of the highest aerosol layer top (HTH) and the height of the lowest aerosol layers base (HB1) varied significantly with respect to the topography of the YERB. High and low values of aerosol optical depth (AOD) were observed over the YERB1 (plain area) and YERB3 (elevated area) regions, respectively. Population, economy, and agricultural activities might be the possible reasons for spatial variations in AOD. AOD values for the lowest aerosol layer were high—between 0.7 and 1.0 throughout the year—indicating that aerosols were mainly concentrated at the bottom layer of the atmosphere. In addition, the integrated volume depolarization ratio (0.15–0.2) and the integrated attenuated total color ratio (~0.1) were large during spring for the lowest aerosol layer due to the presence of dust aerosols. The thicknesses of the lowest aerosol layers (TL1) did not vary with respect to the topographic features of the YERB. Over the sub-regions of the YERB, a significant positive correlation between the AOD of the lowest aerosol layer (AOD1) and the thickness of the lowest aerosol layer (TL1) was found, which indicates that TL1 increases with the increase of AOD1. In the whole YERB, a positive linear correlation between the N and HTH was observed, whereas a negative correlation between N and the portion of AOD for the lowest aerosol layer (PAOD1) was found, which revealed that the large value of N leads to the small value of PAOD1. The results from the present study will be helpful to further investigate the aerosol behavior and their impacts on climate change, air quality, and human health over the YERB.

Keywords: aerosol layers; AOD; CALIPSO; Yellow River Basin

Atmosphere 2019, 10, 638; doi:10.3390/atmos10100638 www.mdpi.com/journal/atmosphere Atmosphere 2019, 10, 638 2 of 16

1. Introduction Aerosols are colloids of fine solid particles or droplets in the air [1–3] and can come from natural sources, such as fog, dust, and sea salt, or anthropogenic sources, such as haze, black carbon, and smoke [4–10]. The aerodynamic diameters of these solid or liquid particles mostly range between 0.001 and 100 µm, while larger particles can precipitate, resulting in suspension, and mixing in the atmosphere [11]. The World Health Organization pointed out that particulate matters with aerodynamic diameters less than 10 µm (PM10) can penetrate into the lungs to the deepest part of the bronchus (such as the bronchioles and alveoli), causing disease [12]. The previous study has pointed out a certain relationship between the aerosol extinction coefficient and lung cancer mortality [13]. Within the field of environmental science, the Intergovernmental Panel on Climate Change reported that atmospheric aerosols are responsible for one of the largest uncertainties in the estimation of climate forcing, and they can scatter and absorb solar shortwave and longwave radiation, directly affecting the Earth’s radiation balance [14]. They can also act as cloud condensation nuclei, changing the cloud’s physical characteristics, life cycle, and indirectly affecting the Earth’s climate system [15–17]. Therefore, the long-term, accurate, and regular monitoring of aerosol optical properties must be carried out continuously. In China, an increase in industrial activities and urbanizations was observed in recent years with the rapid economic development. Increasing numbers of aerosol particulates have been discharged into the atmosphere, leading to frequent air pollution incidents [18]. In recent years, severe regional haze pollution events have occurred in China’s Pearl River Delta, the Yangtze River Delta, the Beijing–Tianjin–Hebei city cluster (BTH), and the northwest region of China, and corresponding aerosol observations have been conducted [19–24]. Recently, China has experienced many severe air pollution events [9]; for example, the Yellow River Basin (YERB) has experienced serious local pollution emissions due to coal mining, urbanization, excessive coal consumption, and the development of heavy industry (such as iron, steel, and cement). However, scientific studies related to these events over the YERB are limited. Ground-based sun photometers such as the Aerosol Robotic Network (AERONET) and Chinese Aerosol Remote Sensing Network (CARSNET) provide continuous observation of the physical and optical properties of aerosols for a long period [25–28]. However, the vertical distribution of aerosols cannot be obtained using site measurements (sunphotometer, nephelometer, aethalometer, and aerosol spectrometer, etc.). These instruments provide point-based aerosol information; however, information about aerosol vertical distribution is very important for understanding the quantitative characteristics of aerosols. In contrast, aerosol characteristics cannot be obtained at a large scale using in situ measurements, as these measurements are limited to the point locations. For these reasons, Light Detection and Ranging (LiDAR) has gradually become the preferred remote sensing technology for atmospheric aerosol observations [29,30]. LiDAR is an active remote sensing detector, which emits laser beams and uses the echo signal by the scattering effect between the laser beam and atmospheric aerosol particles to perform quantitative retrieval [31–33]. Therefore, LiDAR operates continuously during the night and day and provides the vertical distributions of aerosol particles. In addition, LiDAR has a high spatial resolution (covering the range from the Earth’s surface to the stratosphere with meter resolution) and temporal resolution (repeating frequency can reach up to kilohertz). In addition, it has a high detection sensitivity, and the signal received range can reach more than 10 orders of magnitude [34,35]. NASA launched the Cloud-Aerosol LiDAR and Infrared Pathfinder Satellite Observation (CALIPSO), the first active remote sensing sensor in 2006. It acquires not only aerosol information over a large regional scale but also the vertical distribution of different layers of atmospheric aerosols, which provide a new outlook on aerosol observations [36,37]. Therefore, this study intends to use the CALIPSO satellite to investigate the optical and physical characteristics of the lowest aerosol layers over the YERB. As the lowest aerosol layers are close to the ground surface and strongly related to human activities, it is, therefore, necessary to understand the physical and optical characteristics of the lowest layers of aerosols. However, only a few studies have been conducted over the region using optical remote sensing data [38,39], and no one has focused on the vertical distributions of the physical and Atmosphere 2019, 10, 638 3 of 16

Atmosphereoptical properties 2019, 10, x FOR of aerosol PEER REVIEW layers over the YERB. In addition, these have not characterized aerosols3 of 16 into different layers. To the best of our knowledge, this is the first study that has investigated different thisaerosol is the optical first propertiesstudy that and has their investigated vertical distributions.different aerosol Therefore, optical the properties objective and of this their study vertical is to distributions.provide an understanding Therefore, the of theobjective characteristics of this of study the lowest is to aerosol provide layers an overunderstanding the YERB using of the the characteristicsCALIPSO level of 2 aerosolthe lowest layer aerosol product layers from over 2007 the to 2014.YERB The using paper theis CALIPSO organized level as: the 2 aerosol study area layer is productdiscussed from in Section 2007 to2, 2014. the materials The paper and is methods organized are as: described the study in Sectionarea is 3discussed, the results in areSection discussed 2, the materialsin Section 4and, and methods the conclusions are described are provided in Section in Section 3, the 5results. are discussed in Section 4, and the conclusions are provided in Section 5. 2. Study Area 2. Study Area Figure1 shows a topographic map of the YERB region, which is located at 30◦ N–45◦ N, 95◦ E–120Figure◦ E1, shows including a topographic the plains map in the of downstreamthe YERB region, reaches which of theis located YERB at (YERB 30° N–45°1: 31◦ N,N–42 95°◦ E–N, 120°112◦ E,E–119 including◦ E), the the Loess plains plateau in the downstream region in the reaches middle of reachesthe YERB of (YERB the YERB1: 31° (YERB N–42°2 N,: 32 112°◦ N–43 E–119°◦ N , E),105 the◦ E–112 Loess◦ E plateau), and the region mountainous in the middle terrain reaches in the upstreamof the YERB reaches (YERB of the2: 32° YERB N–43° (YERB N, 105°3: 30 ◦E–112°N–39◦ E),N , and94◦ E–105the mountainous◦ E). The YERB terrain is the in second-longest the upstream reaches river in of China, the YERB which (YERB originates3: 30° from N–39° the N, northern 94° E–105° foot E).of theThe Bayan YERB Har is the Mountains second-longest on the Tibet river Plateau, in China, and which flows throughoriginates nine from provinces the northern including foot Qinghai, of the BayanSichuan, Har Gansu, Mountains Ningxia, on the Inner Tibet Mongolia, Plateau, Shanxi, and flows Shaanxi, through Henan, nine and provinces Shandong. including The basin Qinghai, area Sichuan,is 7.95 million Gansu, km Ningxia,2 and is Inner about Mongolia, 1900 km longShanxi, and Shaanxi, 1100 km Henan, wide. and The Shandong. YERB is a vastThe territorybasin area and is 7.95contains million many km mountains,2 and is about diff erent1900 km landforms, long and and 1100 a complicated km wide. The geographical YERB is aenvironment; vast territorythere and containsis also a many great disparitymountains, between different the landforms, east and west and [a40 complicated]. In addition, geographical the YERB isenvironment; located at middle there islatitudes, also a great and disparity the effects between of atmospheric the east circulationand west [40]. and In monsoon addition, circulation the YERB on is itlocated are complicated. at middle latitudes,Therefore, and the climatethe effects of di offf erentatmospheric regions incirculation the YERB and diff ersmonsoon significantly, circulation and the onannual it are complicated. and seasonal Therefore,changes of the climate climate elements of different are large regions [41]. in From the westYERB to differs east, the significantly, YERB includes and thethe easternannual Tibetand seasonalPlateau (upstream),changes of climate Loess Plateau elements (middle), are large and [41]. North From China west Plainto east, (downstream), the YERB includes and the the east-west eastern Tibetaltitude Plateau difference (upstream), is 4480 Loess m. Therefore, Plateau the(middle), study ofand the North optical China and Plain physical (downstream), characteristics and of the aerosols east- westin di ffaltitudeerent topographic difference is environments 4480 m. Therefore, of the YERB the study can helpof the to opti understandcal and physical the specific characteristics characteristics of aerosolsof aerosols in different and can providetopographic evidence environments for the study of the of aerosolYERB can radiation help to forcing, understand which the is ofspecific great characteristicsscientific significance. of aerosols and can provide evidence for the study of aerosol radiation forcing, which is of great scientific significance.

Figure 1. Geographical locations of the Yellow River Basin (YERB). The color bar represents the altitude (elevation). Figure 1. Geographical locations of the Yellow River Basin (YERB). The color bar represents the altitude (elevation).

3. Materials and Methods

Atmosphere 2019, 10, 638 4 of 16

3. Materials and Methods CALIPSO is a small earth-probing satellite project jointly carried out by NASA’s Langley Research Center (LaRC) and the National Space Research Center of France in 2002 [42]. CALIPSO was launched on 28 April 2006 and can provide not only aerosol and cloud characteristics that vary with latitude and longitude, but also information about the vertical distribution of aerosols and clouds. CALIPSO can identify aerosol types and cloud water/ice phase states and can obtain vital data such as radiation flux and atmospheric state. This data can be used to assess the impact of aerosols and clouds on radiation, and thus improve the ability to predict climate change [43,44]. The orbital altitude of the CALIPSO satellite is 705 km and the dip angle is 98.2◦, which has the advantage of a wide field of view. CALIOP is the most important piece of detection equipment on the CALIPSO satellite, including the laser transmitting and receiving system, which is located on a T-type optical platform, thus ensuring the stability of the system. The CALIOP telescope receives backscattered signals divided into three channels. One channel measures the backscattering intensity of 1064 nm, while the other two channels measure the orthogonal polarization backscattering signal of 532 nm. CALIOP can obtain the backscattering coefficients of two wavelengths (532 and 1064 nm) during the day and night, and can also provide vertical profiles of the 532-nm volume depolarization ratio, which is the ratio of the 532-nm vertical backscattering intensity to the 532-nm parallel backscattering intensity. It reflects the irregularity in the measured particles. CALIOP can also provide the color ratio, which is the ratio of the 1064-nm backscattering intensity to the 532-nm total backscattering intensity. The size of the particles can be identified by this color ratio [45,46]. The CALIPSO dataset is processed, stored in a hierarchical data format, and released by the Atmospheric Sciences Data Center of Langley. CALIPSO datasets are mainly composed of two levels, i.e., Level 1 and Level 2 data products [44], whereas, in this study, Level 2 aerosol layer products at 532 nm were used. The CALIPSO aerosol Level 2 products include aerosol layers, aerosol classifications, and aerosol profile products. The horizontal resolution of the aerosol layer products is 5 km, and the revisit time is 16 days. The aerosol layer products are generated based on the raw CALIPSO profile data using the selective iterated boundary locator (SIBYL) algorithm. Using SIBYL, the feature layers are detected in each raw profile data, and then the amount (number) of aerosol feature layers (N), and the height of the feature layer’s base (HB ) and top (HT ) is obtained. The data contain at most eight vertical layers (N 8) in the whole N N ≤ atmosphere in every raw profile data. During the next time, the Scene Classification Algorithm (SCA) is applied on each vertical layer to classify into six different species, including clean marine aerosol, dust aerosol, polluted continent aerosol, clean continent aerosol, polluted dust aerosol, and smoke aerosol. Different species in different layers are endowed with different LiDAR ratios and retrieved to extinction coefficient δ(z) and backscatter coefficient β(z) profiles based on Hybrid Extinction Retrieval Algorithms (HERAs). Each raw profile dataset has different aerosol feature layers, and each feature layer has an extinction coefficient profile. Hence, the aerosol optical depth (AOD) of the Nth aerosol layer (AODN) is calculated as the integral of the extinction coefficient in different layers (Equation (1)). Then, the integrated volume depolarization ratio of the Nth aerosol layer (DRN) and the integrated attenuated total color ratio of the Nth aerosol layer (CRN) can also be calculated using Equations (2) and (3), respectively. The uncertainty analysis of AODN, DRN, and CRN are also performed based on a relative error, and the results are stored in the data products with respect to different quality flags. In this study, only the highest quality (uncertainty 3) datasets were considered and resampled at ≤ 1 1 spatial resolution. ◦ × ◦ This study aimed to explore the vertical physical and optical characteristics of the aerosol layers, and the variables used include the amount (number) of aerosol feature layers (N), the height of the highest aerosol layer top (HTH), the height of the highest aerosol layer base (HBH), the AOD of the Nth aerosol layer (AODN), the sum of the AOD from all the aerosol layers (AODs, Equation (4)), the AOD proportion of the nth aerosol layer (PAODN, Equation (5)), the integrated volume depolarization ratio Atmosphere 2019, 10, 638 5 of 16

of the Nth aerosol layer (DRN), and the integrated attenuated total color ratio of the Nth aerosol layer (CRN). The details of every variable can be found in Abbreviations.

HBZ N AODN = δ(z)dz; N = 1, 2, ... , 7, 8 (1)

HTN

PHBN β532, (z) HTN ⊥ DRN = ;N = 1, 2, ... , 7, 8 (2) PHBN β532, (z) HTN k

PHBN β1064(z) HTN CRN = ;N = 1, 2, ... , 7, 8 (3) PHBN β532(z) HTN XN AODs = AODN;N = 1, 2, ... , 7, 8 (4) 1

AODN PAODN = ;N = 1, 2, ... , 7, 8 (5) AODs

In this study, the AOD of the lowest aerosol layer (AOD1) and the AOD proportion of the lowest aerosol layer (PAOD1) were mainly analyzed in the next section. The mean annual and seasonal values of each variable over the diﬀerent sub-regions of the YERB were calculated to investigate the interannual and seasonal variations and characteristics of the aerosol layers.

4. Results and Discussions

4.1. Interannual Variations and Characteristics of Aerosol Layers over the YERB

Figure2a shows that the annual mean values of AOD S were high over the YERB1 (0.4–0.6) compared to the YERB2 (0.2–0.3) and YERB3 (0.1–0.2) regions. This might be due to a large urban population, relatively developed economy, and large aerosol emissions, as YERB1 is located in the North China Plain (NCP) [47] and close to urban agglomerations of the BTH region, which is one of the most polluted regions with high aerosol contents in China [48,49]. These results are consistent with the previous study, which has reported a mean AOD mean value of 0.5 over the Beijing and XiangHe AERONET sites [50]. YERB3 is located in the upstream region of the YERB, including the eastern Tibet Plateau, which is sparsely populated; therefore, low aerosol contents were expected [51–53]. The previous study of aerosol layers over the Tibet Plateau has reported mean AOD values less than 0.2 due to low aerosol loadings over the region [54]. Annual mean AOD values were between 0.2 and 0.3 over the YERB2, which were close to those observed at the Semi-Arid Climate and Environment Observatory of Lanzhou University (SACOL) station. At SACOL, AOD observations from a sky radiometer were between the 0.2 and 0.4 range at SACOL station during spring [55], and annual mean AOD was observed between 0.3 and 0.4 at SACOL [56]. AOD values at SACOL represented the single point location, whereas the AOD over YERB2 was the average of a specific region, which might be the reason for differences between annual mean AOD values at SCAOL and YERB2. Furthermore, the geographical environment of SACOL is a semi-arid climate with high-frequency sandstorms. Thus, the AOD values are slightly higher in SACOL compared to the values observed over the YERB2 [57]. The values of N exhibit strong regional characteristics (Figure2b). The highest values of N (2.1 to 2.4) were observed over the YERB1 compared to the YERB2 (1.7–2.0) and YERB3 (1.4–1.6). This might have happened as YERB1 is located in the monsoon climate region; the air temperature is relatively high and the atmosphere aerosol loadings are relatively large, which might lead to aerosol vertical stratifications in the atmosphere [58,59]. However, YERB3 is located at the eastern edge of the Tibet Plateau, and the underlying surfaces are mainly composed of mountains and plateaus, where aerosol loadings are relatively low, and the air temperature also remains low [60]. Thus, this scenario might Atmosphere 2019, 10, 638 6 of 16 have very little chance for aerosol vertical stratifications in the atmosphere. Therefore, low values of N were observed over the YERB3. The HTH vary significantly with respect to the topography of the three sub-regions; i.e., YERB3 Atmosphere 2019, 10, x FOR PEER REVIEW 6 of 16 has relatively high altitudes because of the plateaus and mountains (Figure2c). Therefore, the annual mean values of HT were between 6.0 and 7.5 km over the YERB followed by YERB (4.5–5.5 km) mean values of HTH were between 6.0 and 7.5 km over the YERB3 followed by YERB2 (4.5–5.5 km) and YERB (3.5–5 km). and YERB1 (3.5–5 km).

1.2 3.6 12 YERB YERB YERB 1.0 a 3 b 3 c 3 YERB2 3.0 YERB2 YERB2 0.8 9 YERB1 YERB1 YERB1 0.6 2.4 S 6

(KM) N 0.4 1.8 H AOD 0.2 HT 3 1.2 0.0 -0.2 0.6 0 0 008 2006 2008 2010 2012 2014 2006 2008 2010 2012 2014 2006 2 201 2012 2014

1.0 1.2 YERB YERB YERB 3 3 8 3 0.8 d YERB e YERB f YERB 2 1.0 2 2 YERB 6 0.6 1 YERB1 YERB1 1 1 0.4 0.8 4

(KM) 1 AOD

0.2 PAOD

HB 2 0.6 0.0 0 -0.2 0.4 0 008 2006 2008 2010 2012 2014 2006 2008 2010 2012 2014 2006 2 201 2012 2014

2.5 0.24 3.0 YERB YERB3 YERB3 3 g 0.20 h i YERB 2.0 YERB2 YERB2 2 YERB YERB1 0.16 YERB1 1.5 1 1.5

1 0.12 1

(KM) 1

1.0 DR CR 0.08 0.0 TL 0.5 0.04

0.0 0.00 -1.5 0 008 2006 2008 2010 2012 2014 2006 2008 2010 2012 2014 2006 2 201 2012 2014

Figure 2. Interannual variation in optical and physical properties of the lowest aerosol layers in three Figure 2. Interannual variation in optical and physical properties of the lowest aerosol layers in three sub-regions of the Yellow River Basin (YERB): (a) sum of aerosol optical depths (AODs) from all aerosol sub-regions of the Yellow River Basin (YERB): (a) sum of aerosol optical depths (AODs) from all layers, (b) amount (number) of aerosol feature layers (N), (c) height of the highest aerosol layer top aerosol layers, (b) amount (number) of aerosol feature layers (N), (c) height of the highest aerosol (HTH), (d) AOD of the lowest aerosol layer (AOD1), (e) AOD proportion of the lowest aerosol layer layer top (HTH), (d) AOD of the lowest aerosol layer (AOD1), (e) AOD proportion of the lowest aerosol (PAOD1), (f) height of the lowest aerosol layer base (HB1), (g) thickness of the lowest aerosol layer layer (PAOD1), (f) height of the lowest aerosol layer base (HB1), (g) thickness of the lowest aerosol (TL1), (h) depolarization ratio of the lowest aerosol layer (DR1), and (i) color ratio of the lowest aerosol layer (TL1), (h) depolarization ratio of the lowest aerosol layer (DR1), and (i) color ratio of the lowest layer (CR1), from January 2007 to December 2014 (the wavelength is 532 nm). aerosol layer (CR1), from January 2007 to December 2014 (the wavelength is 532 nm).

Similar to the integrated AOD, the highest values of AOD1 (0.3–0.4) were observed over YERB1 Similar to the integrated AOD, the highest values of AOD1 (0.3–0.4) were observed over YERB1 compared to the YERB2 (0.1–0.2) and YERB3 (~0.1) (Figure2d). Figure2e shows that the PAOD 1 values comparedwere very to large the (0.7YERB to20.85) (0.1–0.2) over and all theYERB sub-regions,3 (~0.1) (Figure which 2d). indicates Figure 2e that shows atmospheric that the PAOD aerosols1 values were were very large (0.7 to 0.85) over all the sub-regions, which indicates that atmospheric aerosols were mainly concentrated in the bottom atmospheric layer. The PAOD1 values over YERB3 (0.8–0.85) were mainly concentrated in the bottom atmospheric layer. The PAOD1 values over YERB3 (0.8–0.85) were large compared to YERB2 (0.72–0.77) and YERB1 (0.72–0.75). This phenomenon might be due to the large compared to YERB2 (0.72–0.77) and YERB1 (0.72–0.75). This phenomenon might be due to the high altitudes and low temperatures in the YERB3 region, or due to the weak effects of aerosol vertical high altitudes and low temperatures in the YERB3 region, or due to the weak effects of aerosol vertical convection and aerosol stratification [53,54,60]. Figure2f shows that the values of HB 1 significantly convection and aerosol stratification [53,54,60]. Figure 2f shows that the values of HB1 significantly change with respect to the topography, as the highest values of HB1 (4–5 km) were observed over the change with respect to the topography, as the highest values of HB1 (4–5 km) were observed over the YERB3 region compared to the YERB2 (2–3 km) and YERB1 (1–2 km) regions. As shown in Figure2g, YERB3 region compared to the YERB2 (2–3 km) and YERB1 (1–2 km) regions. As shown in Figure 2g, the the values of TL1 were slightly higher over YERB3 (1.2–1.4 km) than those observed over the YERB2 values of TL1 were slightly higher over YERB3 (1.2–1.4 km) than those observed over the YERB2 (1.15– (1.15–1.2 km) and YERB1 (1.14–1.2 km) regions. This might be due to the vertical convection effects and 1.2 km) and YERB1 (1.14–1.2 km) regions. This might be due to the vertical convection effects and stratifications of the aerosol layer, which were stronger over YERB1 and YERB2 than YERB3 [56–59]. stratificationsThe aerosol of the layer-integrated aerosol layer, which volume were stronger depolarization over YERB ratio1 and can YERB reflect2 thanthe YERB non-spherical3 [56–59]. The aerosol layer-integrated volume depolarization ratio can reflect the non-spherical characteristics of aerosol particles. Higher values of DR1 (0.095–0.12) were observed over YERB3 and characteristics of aerosol particles. Higher values of DR1 (0.095–0.12) were observed over YERB3 and YERB2, indicating the non-spherical characteristics of the lowest aerosol layers. This might be because YERB2, indicating the non-spherical characteristics of the lowest aerosol layers. This might be because of dust aerosols, which occur more frequently in the eastern edge of the Tibet Plateau (YERB3) and the Loess plateau (YERB2), leading to more priority being given to those aerosol types regarding the dust over those regions [53–57]. In addition, the shapes of the dust particles are non-spherical; therefore, DR1 values were large over these regions. These results were consistent with the previous study [61]. Further, small values of DR1 (0.07–0.09) were small over the YERB1, indicating spherical characteristics of the lowest aerosol layers. The aerosol layer-integrated attenuated total color ratio

Atmosphere 2019, 10, 638 7 of 16

of dust aerosols, which occur more frequently in the eastern edge of the Tibet Plateau (YERB3) and the Loess plateau (YERB2), leading to more priority being given to those aerosol types regarding the dust over those regions [53–57]. In addition, the shapes of the dust particles are non-spherical; therefore, DR1 values were large over these regions. These results were consistent with the previous study [61]. Further, small values of DR1 (0.07–0.09) were small over the YERB1, indicating spherical characteristics of the lowest aerosol layers. The aerosol layer-integrated attenuated total color ratio can reﬂect the size of the aerosol layer particles. Figure2i shows the interannual variations in the integrated attenuated total color ratio of the lowest aerosol layers (CR1) over the YERB. The CR1 values were lower (0.45–0.6) over YERB3 than those observed over YERB2 (0.55–0.7) and YERB1 (0.6–0.7). These results suggested that the lowest aerosol layer contains aerosol particles with a small size over YERB3 compared to YERB2 and YERB1. This might be because the aerosol loadings of the eastern main body of the Tibet Plateau (YERB3) are low all year round [53,54].

4.2. Seasonal Variations and Characteristics of Aerosol Layers over the YERB

Seasonal variations were analyzed in AODS over the three sub-regions of the YERB (Figures3a and4a,b). During each season, the seasonal mean AOD S values were high over the YERB1 (0.4–0.6) region compared to the YERB3 (0.12–0.2) region. This might be due to the regional effects, as the YERB1 at the North China Plain (NCP) is close to the BTH, which is a region of high aerosol loadings [24,47–49]. Therefore, the seasonal mean values of AODS were high over YERB1. However, YERB3 is located at the eastern Tibet Plateau, which is a region of low aerosol emissions that led to low mean AODS values [52,54,60]. Overall, the values of AODS were higher in summer (~0.6) (Figure4b) followed by autumn (~0.5) (Figure4c), winter (~0.4) (Figure4d), and spring (~0.4) (Figure4a) over the YERB 1 region. This might be due to the large relative humidity in summer [9,39,62]. Figures3b and4e–h show the seasonal variations in N over the three sub-regions of the YERB, and the seasonal mean values of N were greater than or equal to 2 over YERB1 (2.0–3.0) compared to YERB2 (1.7–2.0) and YERB3 (1.4–1.7). YERB1 is located in a region with a temperate monsoon climate, and the atmosphere possesses a stronger vertical movement than that over YERB3 and YERB2, which leads to a clear vertical stratification of the atmosphere and increases the amount of aerosol stratification [50,58,59,63,64]. However, YERB3 is located at the eastern edge of the Tibet Plateau, which is mainly composed of mountains and plateaus with low air temperature and weak atmospheric vertical convection [51,65]. In addition, the values of N were larger in spring (Figure4e) followed by summer (Figure4f), autumn (Figure4g), and winter (Figure4h). Especially over the YERB 1 region, N was significantly greater (~2.5) in spring compared to the other regions. This might be due to high temperature and strong vertical convection, which led to a significant stratification of aerosols, resulting in greater values of N over YERB1 [24,48,49,58]. Similarly, the greater values of N were observed over YERB2 compared to YERB3, which might be due to the frequently occurred sandstorms over the Loess Plateaus and a significant effect of atmospheric convection [55,57]. The seasonal mean values of HTH (6–7.5 km) over the YERB3 during each season were greater than those values observed over the YERB2 (4–5 km) and YERB1 (3–5 km) due to the high altitudes of the plateaus (Figures3c and4i–l) [ 47,53,54,57]. At the seasonal scale, large values of HTH were observed in spring and summer, whereas small values were observed in autumn and winter. This might be due to the frequently occurred straw burning phenomena, which led to large aerosol emissions and increased the HTH [9,63,66]. Similar to the integrated AODS, high seasonal mean AOD1 values were found over the YERB1 compared to the other sub-regions (Figures3d and4m–p). At the seasonal scale, seasonal mean values of AOD1 were higher in summer (~0.4) followed by autumn (~0.38), winter (~0.35), and spring (~0.28) over the YERB1. This might be due to the grain harvest season and straw-burning activities, which frequently occur in summer and autumn [24,47]. The seasonal mean values of PAOD1 were large over the YERB1 region compared to the other sub-regions (Figures3e and5a–d). These results indicate that atmospheric aerosols were mainly concentrated in the lowest aerosol layer over the sub-regions. Atmosphere 2019, 10, 638 8 of 16

It was noticed that the PAOD1 slightly decreased over the YERB2 and YERB1 regions in spring and summer,Atmosphere 2019 which, 10, mightx FOR PEER be due REVIEW to the large values of N, as discussed above. However, large values8 of of16 PAOD1 (0.79–0.83) were observed in autumn and winter over all the sub-regions, which might be due

Atmosphere 2019, 10, x FOR PEER REVIEW 8 of 16 to low temperature1.2 and weak vertical convection3.6 and aerosol stratiﬁcation12 [51,57,58]. YERB YERB 3 3 YERB3 1.0 a YERB YERB YERB 2 3.0 b 2 c 2 YERB YERB 9 YERB 0.8 1 1 1 1.2 3.6 12 YERB YERB YERB 0.6 3 2.4 3 3 S 1.0 a YERB YERB YERB 2 b 2 c 6 2 3.0 (KM) N

0.4 YERB YERB H 9 YERB 0.8 1 1.8 1 1 AOD

0.2 HT 0.6 2.4 3 S 1.2 6 0.0 (KM) N 0.4 1.8 H AOD -0.2 0.6 0 0.2 spring summer autumn winter spring summer autumn winter HT 3 spring summer autumn winter 1.2 0.0

-0.21.0 1.20.6 0 YERB YERB YERB spring summer autumn winter 3 spring summer autumn winter 3 8 spring summer autumn winter 3 YERB YERB YERB 0.8 d 2 e 2 f 2 YERB YERB1 1.0 1 YERB1 0.61.0 1.2 6 YERB YERB3 3 YERB3

1 8 1 YERB YERB YERB 0.40.8 2 0.8 e 2 4 2 d f YERB (KM) YERB1 1.0 1 1 YERB1

AOD 6

0.20.6 PAOD

HB 2

1 0.6 1 0.4 0.8 4 0.0 (KM)

1 0 AOD

-0.20.2 PAOD 0.4

HB 2 spring summer autumn winter 0.6 spring summer autumn winter spring summer autumn winter 0.0 0 -0.22.5 0.240.4 3.0 YERB spring summer autumn winter YERB3 spring summer autumn winter YERB3 spring summer autumn winter 3 YERB YERB YERB 2.0 j 2 0.20 h 2 i 2 YERB YERB1 YERB1 1 2.5 0.160.24 1.53.0 YERB 1.5 YERB3 YERB3 3 YERB

YERB 1 YERB 1 2 0.120.20 2 i 2 2.0 j h (KM) YERB YERB YERB 1 1 1 1 1.0 DR CR 0.080.16 0.01.5 TL 1.5 0.5 1 0.12 1 0.04 (KM) 1

1.0 DR CR 0.0 0.000.08 -1.50.0 TL spring summer autumn winter spring summer autumn winter spring summer autumn winter 0.5 0.04 0.0 0.00 -1.5 spring summer autumn winter spring summer autumn winter spring summer autumn winter Figure 3. Seasonal variations in optical and physical properties of the lowest aerosol layers in three Figuresub-regions 3. Seasonal of the YERB: variations (a) AOD in opticalS, (b) N, and (c)physical HTH, (d) propertiesAOD1, (e) PAOD of the lowest1, (f) HB aerosol1, (g) TL layers1, (h) DR in three1 and Figure 3. Seasonal variations in optical and physical properties of the lowest aerosol layers in three sub-regions(i) CR1, from of January the YERB: 2007 (a )to AOD DecemberS,(b) N, 2014 (c) HT (theH ,(wavelengthd) AOD1,( eis) PAOD532 nm).1,( f) HB1,(g) TL1,(h) DR1 and sub-regions of the YERB: (a) AODS, (b) N, (c) HTH, (d) AOD1, (e) PAOD1, (f) HB1, (g) TL1, (h) DR1 and (i) CR1, from January 2007 to December 2014 (the wavelength is 532 nm). (i) CR1, from January 2007 to December 2014 (the wavelength is 532 nm).

Figure 4. Seasonal distributions of AODS (a–d), N (e–h), HTH (i–l), and AOD1 (m–p) over the YERB region. Figure 4. Seasonal distributions of AODS (a–d), N (e–h), HTH (i–l), and AOD1 (m–p) over the YERB region.

Figure 4. Seasonal distributions of AODS (a–d), N (e–h), HTH (i–l), and AOD1 (m–p) over the YERB region.

Atmosphere 2019, 10, x 638 FOR PEER REVIEW 99 of of 16 16

Figure 5. Seasonal distribution of PAOD1 (a–d), HB1 (e–h), TL1 (i–l), DR1 (m–p), and CR1 (q–t) in the YERB. Figure 5. Seasonal distribution of PAOD1, HB1, TL1, DR1, and CR1 in the YERB.

High seasonal meanmean valuesvalues ofof HBHB11were were observed observed over over the the YERB YERB3 (4–4.63 (4–4.6 km) km) region region compared compared to tothe the YERB YERB2 (2–2.42 (2–2.4 km) km) and and YERB YERB1 (1–1.51 (1–1.5 km) km) regions regions (Figures (Figures3f and 3f5 ande–h). 5e–h). At the At seasonal the seasonal scale, highscale, highvalues values of HB 1ofwere HB1observed were observed in spring inand spring summer, and summer, whereas lowwhereas values low were values observed were in observed autumn and in autumnwinter. Inand spring winter. and In summer, spring airand temperature summer, air is temperature relatively high is comparedrelatively high to autumn compared and winterto autumn with andstrong winter vertical with convectional strong vertical eﬀects, convectional which increased effects, thewhich height increased of the lowestthe height aerosol of the layer lowest base aerosol [58,66]. layerNo signiﬁcant base [58,66]. variations No significant in TL1 were variations observed in with TL respect1 were toobserved topographical with respect variations to (Figurestopographical3j and variations5i–l). Seasonal (Figures variations 3j and showed5i–l). Seasonal large values variations of TL showed1 in spring large (1.35 values to 1.5 of km) TL1 followedin spring by(1.35 summer to 1.5 km)(1.2–1.4 followed km), andby summer autumn (1.2–1.4 and winter km), (0.9–1.2 and autumn km). and winter (0.9–1.2 km). Seasonal variations showed high values of DR11 in spring (0.12–0.13) overover thethe YERBYERB22 and YERB3 regions,regions, which indicate the non-spherical non-spherical characteristics of the lowest lowest aerosol aerosol layers. layers. However, However, lower lower values werewere observed observed in in summer summer (0.06–0.08), (0.06–0.08), autumn autumn (0.07–0.1), (0.07–0.1), and winter and (0.09–0.12),winter (0.09–0.12), which indicates which indicatesspherical shapesspherical of theshapes aerosols of the in aerosols the lowest in aerosolthe lowest layers. aerosol Seasonal layers. variations Seasonal of variations CR1 showed of highCR1 showedvalues in high spring values (0.7) in over spring the (0.7) YERB over1 and the YERB YERB2,1 whichand YERB indicate2, which the indicate large size the of large aerosol size particles of aerosol in particlesthe lowest in layers. the lowest However, layers. relative However, small valuesrelative were small observed values for were other observed seasons, for especially other seasons, over the especiallyYERB3 (0.5–0.6). over the YERB3 (0.5–0.6).

4.3. The The Correlations Correlations of of the the Lowest Lowest Aerosol Aerosol Properties over the YERB InIn order order to to better better understand understand the the seasonal seasonal spatial spatial characteristics characteristics of of aerosol aerosol layers layers over over the the YERB, YERB, correlation analyses analyses of of aerosol aerosol la layeryer parameters are are worth worth studying studying at at seasonal seasonal and and regional regional scales, scales, which can help to better understand the causes of spatiotemporal characteristics of aerosol layers

Atmosphere 2019, 10, 638 10 of 16

Atmosphere 2019, 10, x FOR PEER REVIEW 10 of 16 which can help to better understand the causes of spatiotemporal characteristics of aerosol layers 1 1 overover thethe YERB.YERB. CorrelationCorrelation analysesanalyses werewere performedperformed betweenbetween AODAOD1 andand TLTL1 overover eacheach sub-regionsub-region 1 1 (Figure(Figure6 ),6), which which showed showed the the direct direct relationship, relationship, i.e., i.e., the thickerthe thicker the TL the1 ,TL the, higherthe higher the AOD the AOD1. This. wasThis consistentwas consistent with theoreticalwith theoretical understanding, understanding, as AOD as isAO theD integral is the integral of extinction of extinction coeﬃcients coefficients with respect with 1 torespect altitude, to altitude, so the thicker so the the thicker TL1, thethe greaterTL , the the greater integral the distances, integral distances, and the higher and the the higher values the of AODvalues1. 1 1 1 Accordingof AOD . According to previously to previously discussed discussed results, AOD results,1 was AOD high overwas high the YERB over 1theregion; YERB therefore, region; therefore, a higher 1 2 2 correlationa higher correlation was expected was overexpected the YERB over 1the. Figure YERB6 showed. Figure a6 highershowed correlation a higher correlation (R ) of 0.59 (R in) spring,of 0.59 1 0.58in spring, in summer, 0.58 in 0.78 summer, in autumn, 0.78 andin autumn, 0.76 in winter and 0.76 over in thewinter YERB over1 sub-region the YERB compared sub-region to thecompared YERB2 2 3 andto the YERB YERB3 regions. and YERB These regions. results These were results consistent were andconsistent supported and supported by the previous by the studyprevious over study the Tibetover Plateauthe Tibet [54 Plateau]. [54].

12 12 y=2.53+0.38ln(x+0.01) R2=0.16 y=2.57+0.43ln(x) R2=0.35 a YERB b YERB 2 3 y=2.18+0.30ln(x+0.01) R2=0.16 2 y=2.18+0.40ln(x+0.02) R =0.36 2 2 9 y=1.75+0.20ln(x) R =0.13 9 y=1.96+0.34ln(x) R =0.34 y=1.79+0.23ln(x) R2=0.14 y=-167.24+42.97ln(x+50.05) R2=0.46

6 6

(km) (km) 1 1 spring spring TL 3 summer TL 3 summer autumn autumn winter winter 0 0 0123401234 AOD AOD 12 1 1 c YERB y=2.24+0.76ln(x+0.10) R2=0.59 1 y=1.55+0.53ln(x+0.18) R2=0.58 2 9 y=1.52+0.43ln(x+0.12) R =0.78 y=1.15+1.06ln(x+0.67) R2=0.76

(km) 1 spring TL 3 summer autumn winter 0 01234 AOD 1

FigureFigure 6.6. CorrelationCorrelation betweenbetween AODAOD ofof thethe lowestlowest aerosolaerosol layerlayer (AOD(AOD11)) andand thicknessthickness ofof thethe lowestlowest

aerosolaerosol layerlayer (TL(TL11)) overover YERB.YERB. WhereWhere ((aa)) isis forfor YERBYERB33,(, (b)) isis forfor YERBYERB22, and (c) is for YERB1..

2 Figure7 showed a significant positive linear correlation (R 2 0.90) between N and HTH over all Figure 7 showed a significant positive linear correlation (R≥ ≥ 0.90) between N and HTH over all thethe sub-regionssub-regions of of the the YERB. YERB. These These results results were expected were expected because ofbecause significantly of significantly vertically distributed vertically aerosol layers in the whole atmosphere, which led to the higher values of HT . distributed aerosol layers in the whole atmosphere, which led to the higher valuesH of HTH. Similarly, a significant negative correlation was observed between N and PAOD over the YERB Similarly, a significant negative correlation was observed between N and PAOD11 over the YERB regionregion (Figure(Figure8 8).). This This was was expected expected because, because, for for a a large large amount amount (number) (number) of of aerosol aerosol feature feature layers layers (N), small values of PAOD were observed, which led to a significant negative correlation. (N), small values of PAOD11 were observed, which led to a significant negative correlation. Figure9 shows the probability distribution scatter diagram between DR and CR over the YERB, Figure 9 shows the probability distribution scatter diagram between DR11 and CR11 over the YERB, andand thethe colorcolor barbar representsrepresents thethe probabilityprobability values.values. ItIt cancan bebe noticednoticed thatthat thethe datadata pointspoints werewere mainlymainly concentrated in the lower-left corner over each region during each season. The range of DR and CR concentrated in the lower-left corner over each region during each season. The range of DR11 and CR11 waswas betweenbetween 00 andand 0.2,0.2, andand 00 andand 1,1, respectively.respectively. TheseThese resultsresults indicateindicate smallersmaller particleparticle sizessizes withwith non-spherical shapes in the lowest aerosol layers over the whole YERB. However, the CR values over non-spherical shapes in the lowest aerosol layers over the whole YERB. However, the CR11 values over allall thethe sub-regionssub-regions werewere generallygenerally higherhigher inin springspring (1–1.5)(1–1.5) comparedcomparedto tothe theother otherseasons. seasons. ThisThis mightmight bebe duedue toto thethe presencepresence ofof dustdust aerosolsaerosols withwith largelarge particleparticle sizessizes overover thethe YERB.YERB. ItIt isis well-knownwell-known thatthat dustdust layerslayers generallygenerally existexist atat highhigh altitudes with large particle sizes with non-spherical characteristics.

Atmosphere 2019, 10, x FOR PEER REVIEW 11 of 16

Atmosphere 2019,, 10,, 638x FOR PEER REVIEW 11 of 16

20 20 2 a YERB y=5.89+0.71x R2=0.99 b YERB y=4.35+0.68x R =0.82 3 2 2 2 16 y=5.65+1.02x R =0.93 16 y=3.08+1.16x R =0.61 20 20 y=2.49+0.92x R2=0.98 y=5.40+0.35xy=5.89+0.71x R2=0.95=0.99 y=4.35+0.68x R2=0.82 a YERB b YERB 2 3 2 2 y=2.40+0.99x R2=0.97 1216 y=5.51+0.43xy=5.65+1.02x R =0.90=0.93 1216 y=3.08+1.16x R =0.61 y=2.49+0.92x R2=0.98 y=5.40+0.35x R2=0.95 (km) (km)

H 8 H 8 2 12 2 12 y=2.40+0.99x R =0.97 y=5.51+0.43x spring R =0.90 spring HT HT

summer summer (km) 4 (km) 4 H 8 autumn H 8 autumn spring spring

HT winter HT winter 0 summer 0 summer 4 4 0 4 8 12 autumn 16 0 4 8 12 autumn 16 N N 20 winter winter 0 2 0 0c YERB 4 8 y=3.21+0.87x 12 R =0.98 16 0 4 8 12 16 1 2 16 N y=2.90+0.87x R =0.92 N 20 c YERB y=1.51+0.93xy=3.21+0.87x R2=0.98 1 2 1216 y=2.49+0.72xy=2.90+0.87x R =0.92 2 y=1.51+0.93x R =0.98 (km)

H 8 12 y=2.49+0.72x R2=0.92 spring HT

summer (km) 4 H 8 autumn spring

HT winter 0 summer 4 0 4 8 12 autumn 16 N winter 0 0 4 8 12 16 N Figure 7. The correlations between the height of the highest aerosol layer top (HTH) and amount (number)Figure 7. ofThe aerosol correlations feature betweenlayers (N) the over height TP. (a of) is the for highest YERB3,aerosol (b) is for layer YERB top2, and (HT (Hc) is and for amount YERB1. Figure 7. The correlations between the height of the highest aerosol layer top (HTH) and amount (number) of aerosol feature layers (N) over TP. (a) is for YERB3,(b) is for YERB2, and (c) is for YERB1. (number) of aerosol feature layers (N) over TP. (a) is for YERB3, (b) is for YERB2, and (c) is for YERB1.

1.5 1.5 2 a YERB y=0.74-0.31ln(x-0.56) R =0.99 b YERB y=0.74-0.29ln(x-0.59) R2=0.99 3 2 2 2 1.2 y=0.59-0.21ln(x-0.85) R =0.99 1.2 y=0.59-0.17ln(x-0.91) R =0.91 1.5 2 1.5 y=0.56-0.12ln(x-0.98) R2=0.78 y=0.60-0.17ln(x-0.90) R2=0.81 y=0.74-0.31ln(x-0.56) R =0.99 y=0.74-0.29ln(x-0.59) R2=0.99 a YERB 2 b YERB 2 0.9 3 y=0.72-0.28ln(x-0.64) R2=0.95 0.9 2 y=0.84-0.32ln(x-0.39) R2=0.93 1 1.2 y=0.59-0.21ln(x-0.85) R =0.99 1.2 y=0.59-0.17ln(x-0.91) R =0.91 2 y=0.56-0.12ln(x-0.98) R =0.78 y=0.60-0.17ln(x-0.90) R2=0.81 0.6 2 0.6 0.9 y=0.72-0.28ln(x-0.64) R =0.95 0.9 y=0.84-0.32ln(x-0.39) R2=0.93

1 spring spring PAOD

summer 0.3 0.3 summer 0.6 autumn 0.6 autumn spring spring PAOD winter winter 0.0 summer 0.0 summer 0.3036912 0.3036912 autumn autumn 1.5 winter2 N winter 0.0 y=0.85-0.30ln(x-0.37) R =0.99 0.0 036912c YERB1 2 036912 1.2 y=0.71-0.17ln(x-0.83) R =0.84 1.5 y=0.66-0.09ln(x-0.98) R2=0.62 y=0.85-0.30ln(x-0.37) R2=0.99 N 2 0.9 c YERB1 y=0.69-0.11ln(x-0.94) R2=0.62 1 1.2 y=0.71-0.17ln(x-0.83) R =0.84 2 y=0.66-0.09ln(x-0.98) R =0.62 0.6 2 0.9 y=0.69-0.11ln(x-0.94) spring R =0.62 1 PAOD summer 0.3 0.6 autumn spring

PAOD winter 0.0 summer 0.3036912 autumn N winter 0.0 036912 Figure 8. The correlations betweenN PAOD1 and layer amount (N) over TP. Where (a) is for YERB3, Figure 8. The correlations between PAOD1 and layer amount (N) over TP. Where (a) is for YERB3, (b) (b) is for YERB2, and (c) is for YERB1. is for YERB2, and (c) is for YERB1. Figure 8. The correlations between PAOD1 and layer amount (N) over TP. Where (a) is for YERB3, (b)

is for YERB2, and (c) is for YERB1.

Atmosphere 2019, 10, 638x FOR PEER REVIEW 12 of 16

Figure 9. Probability distribution diagram of correlations between DR1 and CR1 over YERB. Figure 9. Probability distribution diagram of correlations between DR1 and CR1 over YERB. 5. Conclusions 5. Conclusions In this study, the optical and physical properties of the aerosol layers over the YERB were investigatedIn this study, using the the CALIPSO optical and Level physical 2 layer products properti fromes of Januarythe aerosol 2007 tolayers December over 2014.the YERB This paperwere investigatedcan be a reference using tothe further CALIPSO investigation Level 2 layer of the products physical from and opticalJanuary properties 2007 to December of aerosols 2014. over This the paperYERB orcan over be a the reference other regions. to further The investigation main outcomes of are:the physical and optical properties of aerosols over the YERB or over the other regions. The main outcomes are: (a) AODS values and relative large values of aerosol amount (N > 2) were observed over the YERB1 (a) AODS values and relative large values of aerosol amount (N > 2) were observed over the YERB1 region, as YERB1 is the most polluted region, and the atmosphere possesses strong vertical region,movement, as YERB which1 is can the lead most to apolluted clear vertical region, stratification. and the atmosphere possesses strong vertical movement, which can lead to a clear vertical stratification. (b) High values of the HTH were observed over the YERB. In addition, the HTH and the HB1 (b) High values of the HTH were observed over the YERB. In addition, the HTH and the HB1 significantly vary with respect to the topography and seasons as high values observed in spring significantly vary with respect to the topography and seasons as high values observed in spring and summer compared to autumn and winter. However, the TL1 did not vary with topographical and summer compared to autumn and winter. However, the TL1 did not vary with features, and low values of the TL1 values (approximately 1–1.5 km) were observed over the YERB. topographical features, and low values of the TL1 values (approximately 1–1.5 km) were (c) PAOD was quite large (0.7–1.0) over the YERB, which suggested that atmospheric aerosols were observed1 over the YERB. primarily concentrated in the bottom layer. (c) PAOD1 was quite large (0.7–1.0) over the YERB, which suggested that atmospheric aerosols were (d) The values of DR (0.15–0.2) and CR (~1) were large over the YERB in spring because of primarily concentrated1 in the bottom layer.1 dust aerosols. (d) The values of DR1 (0.15–0.2) and CR1 (~1) were large over the YERB in spring because of dust (e) aerosols.A positive correlation between AOD1 and TL1 and A and HTH was observed over the whole YERB, whereas N and PAOD showed a significant log-negative correlation. (e) A positive correlation between1 AOD1 and TL1 and A and HTH was observed over the whole YERB,Overall, whereas this study N and provides PAOD a1 showed better understanding a significant log-negative of air pollution correlation. in the YERB region. In the futureOverall, study, aerosolthis study types provides and their a better microphysical understanding properties of air over pollution the region in the will YERB be considered. region. In Also, the futurethe vertical study, feature aerosol mask types (VFM) and their products microphysical of CALIPSO properties will be considered over the regi to investigateon will be considered. the vertical Also,structure the andvertical layer feature stratification mask (VFM) characteristics products of of di ffCALIPSOerent aerosol will species.be considered to investigate the vertical structure and layer stratification characteristics of different aerosol species. Author Contributions: M.Z. and J.L. conceived and designed the experiments; M.Z. performed the experiments; J.L. and M.B. analyzed the data; C.Z. contributed analysis tools; M.Z. wrote the paper; M.B., X.X., K.M.K., and F.Z. Authorrevised Contributions: the manuscript. M.Z. and J.L. conceived and designed the experiments; M.Z. performed the experiments; J.L. and M.B. analyzed the data; C.Z. contributed analysis tools; M.Z. wrote the paper; M.B., X.X., K.M.K, and Funding: This research was funded by the National Natural Science Foundation of China (No. 41801282), F.Z.the Programsrevised the for manuscript. Science and Technology Development of Henan Province (No. 192102310008), the Key Funding:Scientific ResearchThis research Project was of funded Henan by Institutions the National of HigherNatural Learning Science Foundation (No. 18B170007), of China the (No. Nanyang 41801282), Normal the University Scientific Research Project (No. ZX2017014), the Science and Technology Project of Nanyang City Programs(No. 2017JCQY017), for Science the and Special Technology Project of Development Jiangsu Distinguished of Henan Professor Province (No. (No. 1421061801003 192102310008), and the 1421061901001), Key Scientific Researchand the Deanship Project of of Henan Scientific Institutions Research, of King Higher Khalid Learning University, (No. Kingdom18B170007), of Saudithe Na Arabianyang (RGP2 Normal/54 /University40). Scientific Research Project (No. ZX2017014), the Science and Technology Project of Nanyang City (No.

Atmosphere 2019, 10, 638 13 of 16

Acknowledgments: We also thank the NASA Langley Research Center for providing the experimental data. We will also like to thank the editors for modifying and revising this manuscript. Conﬂicts of Interest: The authors declare no conﬂict of interest.

Abbreviations The following abbreviations are used in this manuscript:

Lon longitude Lat latitude AODN The AOD of the nth aerosol layer; N = 1, 2, ... , 7, 8 AODS The sum of AODs from all aerosol layers HTN The height of the nth aerosol layer top; N = 1, 2, ... , 7, 8 HBN The height of the nth aerosol layer base; N = 1, 2, ... , 7, 8 HTH The height of the highest aerosol layer top TLN The thickness of the nth aerosol layer; N = 1, 2, ... , 7, 8 N The amounts of all aerosol layers PAODN The AOD proportion of the nth aerosol layer; N = 1, 2, ... , 7, 8 DRN The integrated volume depolarization ratio of the nth aerosol layer; N = 1, 2, ... , 7, 8 CRN The integrated attenuated total color ratio of the nth aerosol layer; N = 1, 2, ... , 7, 8

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