Three-Dimensional Physical and Optical Characteristics of Aerosols over Central China from Long-Term CALIPSO and HYSPLIT Data

Lu, Xin; Mao, Feiyue; Pan, Zengxin; Gong, Wei; Wang, Wei; Tian, Liqiao; Fang, Shenghui

doi:10.3390/rs10020314

Cited by 32 publications

(19 citation statements)

References 47 publications

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“…We used Level 2 (version 4) CALIPSO aerosol products and vertical feature mask (VFM) data with a horizontal resolution of 5 km and a vertical resolution of 30 m below 8.2 km, 60 m for 8.2-20.2 km, and 180 m for 20.2-30.1 km [26]. To ensure the quality of CALIPSO data, several quality control flags contained in the Level 2 aerosol products were applied following quality assurance procedures [45][46][47], including only data points with uncertainty of extinction coefficient less than 99.9 km −1 and extinction quality control flags with values of 0 or 1. The CALIPSO cloud-aerosol discrimination (CAD) algorithm separates clouds (i.e., positive CAD score) and aerosols (i.e., negative CAD score), providing a measure of the confidence level for the identification of aerosol types (high confidence: |CAD score| ≥ 70, medium confidence: 50 ≤ |CAD score| < 70, low confidence: 20 ≤ |CAD score| < 50, and no confidence: |CAD score| textless 20) [48,49].…”

Section: Atmospheric Datamentioning

confidence: 99%

Spring 2018 Asian Dust Events: Sources, Transportation, and Potential Biogeochemical Implications

et al. 2019

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The input of aeolian mineral dust to the oceans is regarded as the major source in supplying bioavailable iron for phytoplankton growth. Severe dust events swept over East Asia during the 26 March to the 4 April 2018, decreasing air quality to hazardous levels, with maximum PM10 mass concentrations above 3000 μg m−3 in northern China. Based on a comprehensive approach that combines multiple satellite measurements, ground observations, and model simulation, we revealed that two severe Asian dust events originating from the Taklimakan and Gobi deserts on 26 March and 1 April, were transported through northern China and the East/Japan Sea, to the North Pacific Ocean by westerly wind systems. Transportation pathways dominated by mineral dust aerosols were observed at altitudes of 2–7 km in the source regions, and then ascending to 3–10 km in the North Pacific Ocean, with relatively denser dust plumes within the second dust episode than there were during the first. Our results suggest that mineral dust emitted from the Taklimakan and Gobi deserts could increase ocean primary productivity in the North Pacific Ocean by up to ~50%, compared to average conditions. This emphasizes the potential importance of the deposition of Asian mineral dust over the North Pacific Ocean for enhancing the biological pump.

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Section: Atmospheric Datamentioning

confidence: 99%

Spring 2018 Asian Dust Events: Sources, Transportation, and Potential Biogeochemical Implications

et al. 2019

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“…Figure 9 shows the distribution of the daily trajectory of the air mass from 15-19 August 2018, in Wuqing District, Tianjin. The backward trajectory model we mentioned in this paper was generated by using the HYSPLIT-4 model [46]. It was developed by the National Oceanic and Atmospheric Administration.…”

Section: Discussionmentioning

confidence: 99%

Regional Atmospheric Aerosol Pollution Detection Based on LiDAR Remote Sensing

Wang

Han

et al. 2019

Remote Sensing

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Atmospheric aerosol is one of the major factors that cause environmental pollution. Light detection and ranging (LiDAR) is an effective remote sensing tool for aerosol observation. In order to provide a comprehensive understanding of the aerosol pollution from the physical perspective, this study investigated regional atmospheric aerosol pollution through the integration of measurements, including LiDAR, satellite, and ground station observations and combined the backward trajectory tracking model. First, the horizontal distribution of atmospheric aerosol wa obtained by a whole-day working scanning micro-pulse LiDAR placed on a residential building roof. Another micro-pulse LiDAR was arranged at a distance from the scanning LiDAR to provide the vertical distribution information of aerosol. A new method combining the slope and Fernald methods was then proposed for the retrieval of the horizontal aerosol extinction coefficient. Finally, whole-day data, including the LiDAR data, the satellite remote sensing data, meteorological data, and backward trajectory tracking model, were selected to reveal the vertical and horizontal distribution characteristics of aerosol pollution and to provide some evidence of the potential pollution sources in the regional area. Results showed that the aerosol pollutants in the district on this specific day were mainly produced locally and distributed below 2.0 km. Six areas with high aerosol concentration were detected in the scanning area, showing that the aerosol pollution was mainly obtained from local life, transportation, and industrial activities. Correlation analysis with the particulate matter data of the ground air quality national control station verified the accuracy of the LiDAR detection results and revealed the effectiveness of LiDAR detection of atmospheric aerosol pollution.

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“…Based on analysis of pollution features and meteorological factors influencing a rare color haze episode in Nanjing in December 2015, Liu et al [26] discussed the possible reasons and used the HYSPLIT model to analyze the pollution transportation of this purple haze. Lu et al [27] analyzed the optical characteristics of aerosol particles in central China by using Cloud-Aerosol Lidar observation data and the HYSPLIT model.…”

Section: Introductionmentioning

confidence: 99%

Air Quality in Ningbo and Transport Trajectory Characteristics of Primary Pollutants in Autumn and Winter

Yao

et al. 2019

Atmosphere

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By using meteorology and pollution observation data from Zhejiang province, and data from the National Centers for Environmental Prediction’s Global Data Assimilation System from 1 June 2013, to 31 May 2016, we analyzed air quality characteristics in Ningbo and applied the HYSPLIT model to do backward trajectory clustering statistics for pollution cases of moderate, heavy and severe (henceforth referred to as moderate-and-above) levels. The results indicated that the percentage of moderate-and-above pollution was approximately 6%, which mostly occurred from November to February, with the primary pollutant being particulate matter with a diameter of ≤2.5 μm; Moderate-and-above pollution was mainly caused by pollutants from three types of trajectories (type mx, type 1, and type 2), with type 2 differing significantly from types 1 and mx. Type 2 occurred in stable boundary layers, whereas types mx and 1 occurred in unstable and conditionally unstable layers respectively. These three trajectory types were all related to cold air, but type 2 was weaker than the other two. Analysis of typical cases of various pollution types revealed that a heavy pollution outbreak was due to continuous superposition of pollutants. The input particles most likely originated from the northwest. The upstream situation was the focus of investigation to assist in local pollution forecasting.

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Three-Dimensional Physical and Optical Characteristics of Aerosols over Central China from Long-Term CALIPSO and HYSPLIT Data

Cited by 32 publications

References 47 publications

Spring 2018 Asian Dust Events: Sources, Transportation, and Potential Biogeochemical Implications

Spring 2018 Asian Dust Events: Sources, Transportation, and Potential Biogeochemical Implications

Regional Atmospheric Aerosol Pollution Detection Based on LiDAR Remote Sensing

Air Quality in Ningbo and Transport Trajectory Characteristics of Primary Pollutants in Autumn and Winter

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