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Article

The Role of Cloud in the Transportation of Dust into Basin Area: A Case Study in Sichuan Basin, Southwesten China

1
Department of Environmental Science and Engineering, Sichuan University, Chengdu 610065, China
2
National Engineering Research Center on Flue Gas Desulfurization, Chengdu 610065, China
3
Sichuan Eco-environment Monitoring Station, Chengdu 610095, China
4
National Meteorological Centre, Beijing 100080, China
5
Key Laboratory of Transportation Meteorology of China Meteorological Administration (CMA), Nanjing Joint Institute for Atmospheric Sciences, Nanjing 211512, China
*
Author to whom correspondence should be addressed.
Atmosphere 2022, 13(10), 1668; https://doi.org/10.3390/atmos13101668
Submission received: 17 September 2022 / Revised: 8 October 2022 / Accepted: 10 October 2022 / Published: 13 October 2022
(This article belongs to the Section Air Quality)

Abstract

:
The existing knowledge illustrated the role of surrounding mountains in the transportation of dust into a basin, including the blocking of low-layer dust and the allowance of elevated dust intrusion. Taking the Sichuan Basin in southwestern China as an example, we found the impact of clouds on the transportation process of dust in the basin area. If there were low-level clouds on the basin edges, the dust particles could not penetrate the cloud layers, but settled down from upper air into the basin in the cloudless regions. They could be transported beneath clouds in the basin. Considering that the upslope airflow accompanied by dust transportation was conducive to the low-level clouds on the basin edge, this mechanism further reduced the dust intrusion besides the shelter of the surrounding mountains.

1. Introduction

Mineral dust is one of the important components of atmospheric aerosol and plays a major role in the climate [1,2,3], air quality [4,5,6], and human health [7,8]. Dust particles can be lifted by strong winds and travel long distances, influencing a wide area. It not only can alter cloud properties [9,10] and change the Earth’s radiation [11]. Moreover, dust particles can be carried to downwind area and impact the characteristics of local atmospheric chemistry [12,13].
The Sichuan Basin (SB) is located in the eastern leeward region of the Qinghai-Tibet Plateau and surrounded by high-altitude mountains as shown in Figure 1. Moreover, Sichuan Basin is one of the most heavily polluted regions in China and its air quality is a research hotspot. Previous studies suggest that SB could also be influenced by long-range transported dust [14,15,16,17,18] and that the PM10 concentration more than 1000 μg/m3 was recorded when dust passed through the basin [14]. Some of these studies considered that the mountains make a great difference to the transportation of dust into the basin [14,15]. On one hand, the relatively lower altitude of the northern mountains allowed the intrusion of dust, and the dust air masses broke into the basin in the northeast direction after being elevated, and traveled around the mountains on the west side of the basin. On the other hand, the northern and western mountains sheltered the Sichuan Basin from more dust intrusions. Under this unique deep-basin topography, the convergence of northern and southern westerlies around the Tibetan Plateau leads to frequent cloud cover over the basin [19] and the climate cloud cover fraction is over 80% [20,21]. However, there still is no attention paid to the role of clouds in the transportation of dust into basin area. In this study, we explored the impact of clouds on the transportation of dust into the basin because it could provide insights into transportation mechanisms of dust in a basin area.

2. Materials and Methods

2.1. Ground Lidar Observations

The ground lidar measurements were conducted during the dust event from 19 March to 26 March 2021. The lidar station was located in the urban area of Chengdu (104.06° E, 30.70° N) as shown in Figure 1b. The lidar was manufactured by EVERISE TECHNOLOGY LTD. and equipped with a Mie-scattering polarized system at a wavelength of 532 nm. The temporal and vertical resolutions of the retrieved data were 5 min and 15 m, respectively. The retrieved extinction coefficients and depolarization ratios were used in this study to identify and investigate the vertical feature of transported dust. The depolarization ratio is related to the shape of the atmospheric particle and is widely used to distinguish smoke, dust, and clouds [13,22]. According to previous studies, the presence of dust particles is approved by the depolarization ratio greater than 0.1 at 532 nm [13,23,24]. Cloud layers are identified by a relatively smaller depolarization ratio [25], which is usually lower than 0.09. Moreover, the extinction coefficient of cloud is relatively higher and the vertical gradient of extinction coefficient cloud top is sharp [26,27].

2.2. Satellite Observations

The observations from Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), a space-based lidar onboard Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) satellite, were retrieved to analyze Vertical Feature Mask (VFM) product (Version 4.20) with horizontal resolution of 5 km. It was used to identify the vertical structure of aerosols and clouds [28,29]. In addition, the Level-2 cloud products (MOD06_L2 and MYD06_L2) of Moderate-Resolution Imaging Spectroradiometer (MODIS) onboard Terra and Aqua satellites were used to analyze the distribution of cloud fractions [30,31].

2.3. Near Surface Meteorological and Air Quality Data

The fifth generation ECMWF reanalysis for the global climate and weather (ERA5) was used to retrieve meteorological parameters, including zonal and meridional winds, geopotential heights, and cloud cover fractions from 1000 hPa to 500 hPa [32]. The horizontal and temporal resolutions were 0.25° × 0.25° and 1 h, respectively. The surface meteorological observations at Chengdu retrieved from China Meteorological Data Network (http://data.cma.cn/, accessed on 29 March 2021) were used, including wind speed, wind direction, cloud height, and cloud cover frication. Furthermore, the hourly PM10 and PM2.5 concentrations were retrieved from the publishing website of China National Environmental Monitoring Center (https://air.cnemc.cn:18007/, accessed on 29 March 2021).

2.4. Backward Trajectories Simulation

The back trajectories, which were generated by the NOAA Hybrid Single-Particle Lagrangian Integrated Trajectory (HYSPLIT) model [33] and driven by the GDAS (Global Data Analysis System) meteorological data with spatial resolution of 1° × 1°, were used to trace the transportation path of dust.

3. Results

3.1. Overview of a Dust Event during March 2021

A strong sandstorm occurred during 14–18 March 2021 originating from the desert area of Mongolia and northwestern China. East Asia was influenced by the blowing sand in the following several days [34,35]. Affected by this strong sandstorm, the Sichuan Basin confronted severe dust pollution starting on 19 March 2021 (Figure S1). The air mass trajectory presented in Figure 2a revealed that this dust pollution could be ascribed to the transportation of desert area of northern China. The orientation of dust intrusion followed the air mass trajectories in the starting stage, but deviated in the following days. As shown in Figure 2b, the concentrations of coarse particles (PM10−PM2.5) increased sequentially from Mianyang in the north to Leshan in the South since the afternoon of 19 March. However, on 24 March, the influence of dust was obvious in the south part of the basin, but started dissipating in the north, as presented in Figure 2d. The causes for this difference were not apparently acquirable to our knowledge. Hence, taking this case as an example, we investigated the influencing factors of dust transportation in Sichuan Basin.

3.2. Two Dust Transportation Mechanisms

Figure 3a,b shows the vertical characteristics of extinction coefficients and depolarization ratios from lidar at Chengdu from 19 March to 26 March, 2021. It could be found that Chengdu was covered by clouds during most of the dust event. Accompanied by different status of cloud cover, two mechanisms of dust transportation were identified. In the beginning of dust intrusion (around 18 p.m. BJT on 19 March), the cloud base was located at heights between 1500 m to 3500 m. Beneath the cloud layer, the extinction coefficients and depolarization ratios increased abruptly. The maximum depolarization ratio exceeded 0.3 and the highest extinction coefficients concentrated from 500 m to 1000 m above ground level. As shown in Figure S1, the concentrations of coarse particles (PM10−PM2.5) near the surface increased simultaneously with the extinction coefficients in the upper air. Furthermore, northerly winds prevailed in Chengdu before 20 p.m. on 20 March as shown in Figure 3c. These results indicated that the dust particles affecting Chengdu were mainly transported into the basin in the whole layer beneath the clouds during the beginning stage of this dust event.
The second mechanism occurred over cloudless areas and was characterized by settling down from upper air. As seen in Figure 3, during cloudless periods the extinction coefficients were non-negligible and depolarization ratios were greater than 0.2 in the upper air (up to 5 km above ground), which revealed that many dust particles suspended there. Along with the dissipation of clouds, these dust particles settled down without the obstruction of clouds starting at 22:00. on 21 March and 00:00 on 23 March, respectively. Correspondingly, the concentrations of near surface coarse particles increased and PM2.5/PM10 ratios decreased several hours later, as shown in Figure S1.
Once the dust particles intruded the basin through these two mechanisms, they could also be transported in the basin area. In Figure 3a,b some discrete patterns with high extinction coefficients and depolarization ratios were found, such as the results during 06:00–12:00 on 22 March and 00:00–06:00 on 24 March. Meanwhile, more southerly winds were recorded in these periods as shown in Figure 3c. Hence, it was reasonable to assume that these discrete patterns were caused by the advection of dust particles in the basin.

3.3. Typical Transportation Cases

We took the transportation processes at 18:00. on 19 March and 04:00 on 24 March as typical cases representing the first and second mechanisms, respectively. Figure 4 presents characteristics of meteorological parameters for these two cases. On 19 March, an extremely high-pressure system located to the north of the Sichuan Basin, led to strong northerly winds prevailing in the basin area. This is consistent with the trajectories presented in Figure 2. Meanwhile, the whole basin was covered by clouds with cloud bases at 1000–2000 m above ground as shown in Figure 4a. The gap between the topography and cloud bases in the northern edge of the basin allowed the northerly winds to bring dust particles into the basin (the first mechanism).

4. Conclusions

In this study, we found that the existence of low-level clouds on the north and west edge of the basin could also prevent the dust breaking into the basin through the northern and northwestern pathways. In this case, the dust particles in the upper layer could settle down in the cloudless area and transport to other regions beneath the clouds. The Sichuan Basin was the region with the highest cloud amount in China, especially in spring [21]. In addition to the mountains around the basin, the clouds over the Sichuan Basin might be another import factor influencing the transportation of northern dust into the basin.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/atmos13101668/s1, Figure S1: Temporal evolution of PM10 and PM2.5 concentrations from 19 March to 26 March 2021 in Mianyang, Chengdu, and Meishan.

Author Contributions

Conceptualization, G.S.; methodology, G.S. and Y.L.; investigation, Y.L.; resources, Y.D. and W.Z.; writing—original draft preparation, Y.L.; writing—review and editing, G.S. and M.L.; supervision, F.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the National Key R&D Program of China (2018YFC0214002 and 2018YFC0214001), the Key S&T Program of Sichuan Province (2018SZDZX0023), the Beijige Open Research Fund of Jiangsu Meteorological Bureau (BJG201904), the National Natural Science Foundation of China (22076129), the Fundamental Research Funds for the Central Universities (YJ201871 and YJ201891).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

Open Research

The PM10 and PM2.5 concentrations are publicly available on the website of China National Environmental Monitoring Center via https://air.cnemc.cn:18007/, accessed on 6 October 2022. The meteorological parameters are publicly available on the website of China Meteorological Data Service Centre via http://data.cma.cn/, accessed on 6 October 2022. These data in the latest 7 days can be retrieved from these two websites. The authors routinely retrieved and processed relevant data. The above mentioned and the ground lidar data used for characterizing the vertical features of extinction coefficients and depolarization ratios in the study are available at zenodo via http://doi.org/10.5281/zenodo.6654701, accessed on 6 October 2022. The CALIOP data are available through NASA’s Atmospheric Science Data Center via https://doi.org/10.5067/CALIOP/CALIPSO/CAL_LID_L2_VFM-Standard-V4-21 [36]. The MODIS data are available through NASA’s Earth Science Data Systems via http://doi.org/10.5067/MODIS/MYD06_L2.006 [37]. The ERA5 data are available through ECMWF’s Climate Data Store via https://doi.org/10.24381/cds.bd0915c6 [32].

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Figure 1. The geographical location (a) and topography (b) of the study area. The blue square marks the ground lidar station. The black line gives the isoline with a topographic elevation of 750 m above sea level. The city acronyms of MY, DY, CD, MS, and LS represent Mianyang, Deyang, Chengdu, Meishan, and Leshan, respectively.
Figure 1. The geographical location (a) and topography (b) of the study area. The blue square marks the ground lidar station. The black line gives the isoline with a topographic elevation of 750 m above sea level. The city acronyms of MY, DY, CD, MS, and LS represent Mianyang, Deyang, Chengdu, Meishan, and Leshan, respectively.
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Figure 2. The 72-h backward trajectories starting at 300 m and 1500 m above ground level at 08:00 on 20 March 2021 (a) and 04:00 on 24 March 2021 (c) in Chengdu, and the concentrations of coarse particles (PM10−PM2.5) in Chengdu during 18:00 on 19 March and 10:00 on 20 March 2021 (b) and during 00:00 and 18:00 on 24 March (d).
Figure 2. The 72-h backward trajectories starting at 300 m and 1500 m above ground level at 08:00 on 20 March 2021 (a) and 04:00 on 24 March 2021 (c) in Chengdu, and the concentrations of coarse particles (PM10−PM2.5) in Chengdu during 18:00 on 19 March and 10:00 on 20 March 2021 (b) and during 00:00 and 18:00 on 24 March (d).
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Figure 3. The extinction coefficients (a) and depolarization ratios (b) measured by ground lidar and near surface meteorological parameters (c) at Chengdu from 19 March to 26 March 2021.
Figure 3. The extinction coefficients (a) and depolarization ratios (b) measured by ground lidar and near surface meteorological parameters (c) at Chengdu from 19 March to 26 March 2021.
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Figure 4. The cross-section of cloud fractions along the red line (a), the geopotential heights and horizontal wind fields at 850 hPa (c), and 925 hPa (e) at 18 p.m. BJT on 19 March 2021 from ERA5 reanalysis data. Panels (b,d) and (f) present the same contents as (a,c) and (e), respectively, but at 04:00 on 24 March 2021. The wind barbs in panels (a) and (b) were horizontal winds. Each red line presented the path of CALIPSO sub-satellite point around 03:38 BJT on 24 March 2021. On 24 March, the transportation of dust was more complex. The vertical mask features from CALIOP around 03:38on 24 March are presented in Figure 5 to examine the dust distribution across the basin rather than at a fixed location. The clouds on the northern edge were much lower and the gap between the topography and cloud bases disappeared. In this case, although obvious dust layers located in the northern area outside the basin as shown in Figure 5, dust particles could not penetrate the cloud layers into the basin. Hence, the first transportation mechanism did not occur efficiently. In the middle and southern part of the basin, the second mechanism worked and made the whole layer up to 5 km was filled with polluted dust particles. Consequently, PM2.5/PM10 ratios in a northern city (Mianyang) were obviously higher than those in southern city (Meishan) as shown in Figure S1, and the concentration of coarse particles in a northern city were obviously lower than those in southern city, as shown in Figure 2d. Moreover, the dust particles settled down from upper air in the cloudless area might be transported to the cloudy area in lower layers. As shown in Figure 5a, Chengdu was in the connection zone between cloudy and cloudless areas. Meanwhile, the high pressure system in the north of the basin as shown in Figure 4c,e moved to the southeast of the basin (Figure 4d,f), resulting in southwesterly winds on 850 hPa (about 1000 m above ground) and southeasterly winds on 925 hPa (about 400 m above ground), respectively. This advection feature might be the cause of the observed discrete dust pattern in Figure 3a,b.
Figure 4. The cross-section of cloud fractions along the red line (a), the geopotential heights and horizontal wind fields at 850 hPa (c), and 925 hPa (e) at 18 p.m. BJT on 19 March 2021 from ERA5 reanalysis data. Panels (b,d) and (f) present the same contents as (a,c) and (e), respectively, but at 04:00 on 24 March 2021. The wind barbs in panels (a) and (b) were horizontal winds. Each red line presented the path of CALIPSO sub-satellite point around 03:38 BJT on 24 March 2021. On 24 March, the transportation of dust was more complex. The vertical mask features from CALIOP around 03:38on 24 March are presented in Figure 5 to examine the dust distribution across the basin rather than at a fixed location. The clouds on the northern edge were much lower and the gap between the topography and cloud bases disappeared. In this case, although obvious dust layers located in the northern area outside the basin as shown in Figure 5, dust particles could not penetrate the cloud layers into the basin. Hence, the first transportation mechanism did not occur efficiently. In the middle and southern part of the basin, the second mechanism worked and made the whole layer up to 5 km was filled with polluted dust particles. Consequently, PM2.5/PM10 ratios in a northern city (Mianyang) were obviously higher than those in southern city (Meishan) as shown in Figure S1, and the concentration of coarse particles in a northern city were obviously lower than those in southern city, as shown in Figure 2d. Moreover, the dust particles settled down from upper air in the cloudless area might be transported to the cloudy area in lower layers. As shown in Figure 5a, Chengdu was in the connection zone between cloudy and cloudless areas. Meanwhile, the high pressure system in the north of the basin as shown in Figure 4c,e moved to the southeast of the basin (Figure 4d,f), resulting in southwesterly winds on 850 hPa (about 1000 m above ground) and southeasterly winds on 925 hPa (about 400 m above ground), respectively. This advection feature might be the cause of the observed discrete dust pattern in Figure 3a,b.
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Figure 5. The distribution of MODIS Cloud fractions and the path of CALIPSO sub-satellite point (a) and the vertical mask features from CALIOP (b) around 03:38 a.m. BJT on 24 March 2021. The red line was the same as those in Figure 4.
Figure 5. The distribution of MODIS Cloud fractions and the path of CALIPSO sub-satellite point (a) and the vertical mask features from CALIOP (b) around 03:38 a.m. BJT on 24 March 2021. The red line was the same as those in Figure 4.
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Liu, Y.; Shi, G.; Du, Y.; Lyu, M.; Zhang, W.; Yang, F. The Role of Cloud in the Transportation of Dust into Basin Area: A Case Study in Sichuan Basin, Southwesten China. Atmosphere 2022, 13, 1668. https://doi.org/10.3390/atmos13101668

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Liu Y, Shi G, Du Y, Lyu M, Zhang W, Yang F. The Role of Cloud in the Transportation of Dust into Basin Area: A Case Study in Sichuan Basin, Southwesten China. Atmosphere. 2022; 13(10):1668. https://doi.org/10.3390/atmos13101668

Chicago/Turabian Style

Liu, Yuelin, Guangming Shi, Yunsong Du, Mengyao Lyu, Wei Zhang, and Fumo Yang. 2022. "The Role of Cloud in the Transportation of Dust into Basin Area: A Case Study in Sichuan Basin, Southwesten China" Atmosphere 13, no. 10: 1668. https://doi.org/10.3390/atmos13101668

APA Style

Liu, Y., Shi, G., Du, Y., Lyu, M., Zhang, W., & Yang, F. (2022). The Role of Cloud in the Transportation of Dust into Basin Area: A Case Study in Sichuan Basin, Southwesten China. Atmosphere, 13(10), 1668. https://doi.org/10.3390/atmos13101668

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