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Atmosphere
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Remote Sensing Applied in Atmosphere: Recent Trends, Current Progress and...
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Remote Sensing Applied in Atmosphere: Recent Trends, Current Progress and Future Directions

A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Atmospheric Techniques, Instruments, and Modeling".

Deadline for manuscript submissions: closed (1 July 2023) | Viewed by 16115

Special Issue Editors

Dr. Shaohua Zhao

E-Mail Website
Guest Editor
Ministry of Ecology and Environment Center for Satellite Application on Ecology and Environment, Beijing 100094, China
Interests: remote sensing of environment; carbon monitoring; global changes
Dr. Zhongting Wang

E-Mail Website
Guest Editor
Ministry of Ecology and Environment Center for Satellite Application on Ecology and Environment, Beijing 100094, China
Interests: air quality remote sensing; radiative transfer modeling; remote sensing for aerosol; particle matter; greenhouse gases
Dr. Minghui Tao

E-Mail Website
Guest Editor
School of Geography and Information Engineering, China University of Geosciences, Wuhan 430074, China
Interests: remote sensing of atmosphere; radiative transfer and particle scattering; air quality and climate change
Special Issues, Collections and Topics in MDPI journals
Dr. Mingmin Zou

E-Mail Website
Guest Editor
Institutes of Physical Science and Information Technology, Anhui University, Hefei 230039, China
Interests: retrieval of GHGs; air quality remote sensing; radiative transfer modeling; application of satellite remote sensing
Dr. Ying Zhang

E-Mail Website
Guest Editor
Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China
Interests: inversion of atmospheric aerosol characteristics; air quality remote sensing; radiative transfer modeling; remote sensing for particle nucleation; air pollution assimilation and forecasting
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Our atmosphere is closely related to the survival of our planet and the functioning of our daily lives. Satellite remote sensing techniques, which can effectively monitor the continuous and dynamic status of air over large areas, are widely applied in the field of atmospheric and environmental research around the world, and they have played an important role in air monitoring and evaluation in applications such as aerosols, clouds, air pollution, straw burning, dust storms, carbon emissions, pollution source detection, volcanic ash, etc. Recently, with the most rapid development of the economy and space technology seen in decades, especially for high-resolution satellites, many atmospheric problems must be detected by advanced satellite remote sensing. This Special Issue aims to showcase the recent trends, current progress and future research directions of remote sensing as applied in atmospheric research. Original results from ground experiments, model simulations and review papers related to these aspects are all welcome contributions. Authors are encouraged to present a section covering future issues, opportunities, and/or concerns related to their topics.

Dr. Shaohua Zhao
Dr. Zhongting Wang
Dr. Minghui Tao
Dr. Mingmin Zou
Dr. Ying Zhang
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Atmosphere is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • air pollution
  • carbon emission
  • satellite
  • observation
  • high resolution
  • collaborative control
  • multi-source data fusion

Published Papers (8 papers)

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Research

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12 pages, 4437 KiB  
Communication
Aerosol Information Retrieval from GF-5B DPC Data over North China Using the Dark Dense Vegetation Algorithm
by Ruijie Zhang, Wei Zhou, Hui Chen, Lianhua Zhang, Lijuan Zhang, Pengfei Ma, Shaohua Zhao and Zhongting Wang
Atmosphere 2023, 14(2), 241; https://doi.org/10.3390/atmos14020241 - 26 Jan 2023
Cited by 1 | Viewed by 2054
Abstract
A directional polarimetric camera (DPC) is a key payload on board China’s Gaofen 5B (hereafter denoted as GF-5B) satellite, a hyperspectral observation instrument for monitoring aerosols. On the basis of the dark dense vegetation (DDV) algorithm, this study applied DDV algorithm to DPC [...] Read more.
A directional polarimetric camera (DPC) is a key payload on board China’s Gaofen 5B (hereafter denoted as GF-5B) satellite, a hyperspectral observation instrument for monitoring aerosols. On the basis of the dark dense vegetation (DDV) algorithm, this study applied DDV algorithm to DPC measurements. First, the reflectance of vegetation in three channels (0.443, 0.49, and 0.675 μm) was analyzed, and inversion channels were identified. Subsequently, the decrease in normalized difference vegetation index associated with various view angles was simulated, and the optimal view angle for extracting dark pixels was determined. Finally, the top-of-atmosphere reflectance at different view angles was simulated to determine the optimal view angle for aerosol inversion. The inversion experiments were conducted by using DPC data collected over North China from November 2021 to January 2022. The results revealed that DDV algorithm could monitor pollution from 30 December 2021 to 4 January 2022, and the inversion results were strongly correlated with Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol product and AERONET station data (R > 0.85). Full article
(This article belongs to the Special Issue Remote Sensing Applied in Atmosphere: Recent Trends, Current Progress and Future Directions)
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20 pages, 74316 KiB  
Article
Retrieval of Volcanic Ash Cloud Base Height Using Machine Learning Algorithms
by Fenghua Zhao, Jiawei Xia, Lin Zhu, Hongfu Sun and Dexin Zhao
Atmosphere 2023, 14(2), 228; https://doi.org/10.3390/atmos14020228 - 23 Jan 2023
Viewed by 1557
Abstract
There are distinct differences between radiation characteristics of volcanic ash and meteorological clouds, and conventional retrieval methods for cloud base height (CBH) of the latter are difficult to apply to volcanic ash without substantial parameterisation and model correction. Furthermore, existing CBH inversion methods [...] Read more.
There are distinct differences between radiation characteristics of volcanic ash and meteorological clouds, and conventional retrieval methods for cloud base height (CBH) of the latter are difficult to apply to volcanic ash without substantial parameterisation and model correction. Furthermore, existing CBH inversion methods have limitations, including the involvement of many empirical formulae and a dependence on the accuracy of upstream cloud products. A machine learning (ML) method was developed for the retrieval of volcanic ash cloud base height (VBH) to reduce uncertainties in physical CBH retrieval methods. This new methodology takes advantage of polar-orbit active remote-sensing data from the Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP), from vertical profile information and from geostationary passive remote-sensing measurements from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) and the Advanced Geostationary Radiation Imager (AGRI) aboard the Meteosat Second Generation (MSG) and FengYun-4B (FY-4B) satellites, respectively. The methodology involves a statistics-based algorithm with hybrid use of principal component analysis (PCA) and one of four ML algorithms including the k-nearest neighbour (KNN), extreme gradient boosting (XGBoost), random forest (RF), and gradient boosting decision tree (GBDT) methods. Eruptions of the Eyjafjallajökull volcano (Iceland) during April-May 2010, the Puyehue-Cordón Caulle volcanic complex (Chilean Andes) in June 2011, and the Hunga Tonga-Hunga Ha’apai volcano (Tonga) in January 2022 were selected as typical cases for the construction of the training and validation sample sets. We demonstrate that a combination of PCA and GBDT performs more accurately than other combinations, with a mean absolute error (MAE) of 1.152 km, a root mean square error (RMSE) of 1.529 km, and a Pearson’s correlation coefficient (r) of 0.724. Use of PCA as an additional process before training reduces feature relevance between input predictors and improves algorithm accuracy. Although the ML algorithm performs well under relatively simple single-layer volcanic ash cloud conditions, it tends to overestimate VBH in multi-layer conditions, which is an unresolved problem in meteorological CBH retrieval. Full article
(This article belongs to the Special Issue Remote Sensing Applied in Atmosphere: Recent Trends, Current Progress and Future Directions)
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11 pages, 3747 KiB  
Article
GOSAT Mapping of Global Greenhouse Gas in 2020 and 2021
by Lianhua Zhang, Zhongting Wang, Wei Zhou, Xiaoyu Yang, Shaohua Zhao and Qing Li
Atmosphere 2022, 13(11), 1814; https://doi.org/10.3390/atmos13111814 - 31 Oct 2022
Cited by 4 | Viewed by 1919
Abstract
Carbon dioxide and methane are the two most important greenhouse gases and are closely related to global warming and extreme weather events. To master their spatial and temporal variations, the CO2 and CH4 concentration data monitored by the GOSAT satellite in [...] Read more.
Carbon dioxide and methane are the two most important greenhouse gases and are closely related to global warming and extreme weather events. To master their spatial and temporal variations, the CO2 and CH4 concentration data monitored by the GOSAT satellite in 2020 and 2021 were used to map and analyse the annual, seasonal and monthly changes in CO2 and CH4 concentrations in the world and major countries/regions. The results demonstrate that (1) in 2021, the average annual CO2 concentration over the global land area was 412.74 ppm, an increase in 0.64% compared with the same period last year, and there were spatial differences in the distribution of CO2 concentration, with high values mostly concentrated in the middle latitudes of the Northern Hemisphere; (2) compared with 2020, the CO2 concentration in China, the United States, India, the European Union and other countries/regions increased significantly; (3) in 2020 and 2021, the quarterly CO2 trend of the global and major countries/regions was the same, which was higher in the first (January, February, March) and second (April, May, June) quarters, significantly lower in the third (July, August, September) quarter, and gradually increased in the fourth (October, November, December) quarter. Further work on long time series and validation needs to be conducted. Full article
(This article belongs to the Special Issue Remote Sensing Applied in Atmosphere: Recent Trends, Current Progress and Future Directions)
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13 pages, 3026 KiB  
Article
Cloud Occlusion Probability Calculation Jointly Using Himawari-8 and CloudSat Satellite Data
by Xingfeng Chen, Limin Zhao, Haonan Ding, Donghong Wang, Jiaguo Li, Chen Cao, Fengjie Zheng, Zhiliang Li, Jun Liu and Shanwei Liu
Atmosphere 2022, 13(11), 1754; https://doi.org/10.3390/atmos13111754 - 25 Oct 2022
Cited by 1 | Viewed by 1263
Abstract
Cloud occlusion is an important factor affecting flight safety and scientific observation. The calculation of Cloud Occlusion Probability (COP) is significant for the planning of the flight time and route of aircraft. Based on Himawari-8 and CloudSat satellite data, we propose a method [...] Read more.
Cloud occlusion is an important factor affecting flight safety and scientific observation. The calculation of Cloud Occlusion Probability (COP) is significant for the planning of the flight time and route of aircraft. Based on Himawari-8 and CloudSat satellite data, we propose a method to calculate the COP. The COP statistics were carried out on different distances in 12 directions 6 km above Beijing Capital International Airport (BCIA), at different heights and directions in the Haiyang aerostat production base, and at different times and seasons in Mount Qomolangma. It was found that the COP going in the southern direction from BCIA was greater than that in the northern direction by 0.67–3.12%, which is consistent with the climate conditions of Beijing. In Haiyang, the COP for several seasons in the direction of land was higher than in the direction of the ocean. The maximum COP for the 6 km altitude is 29.63% (summer) and the minimum COP is 7.59% (winter). The aerostat flight test can be conducted in the morning of winter and the direction of the ocean. The best scientific observation time for Mount Qomolangma is between 02:00 and 05:00 UTC in spring. With the increase in altitude, the COP gradually decreases. The research in this paper provides essential support for flight planning. Full article
(This article belongs to the Special Issue Remote Sensing Applied in Atmosphere: Recent Trends, Current Progress and Future Directions)
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13 pages, 4428 KiB  
Article
The Impact of Long-Range Transport of Biomass Burning Emissions in Southeast Asia on Southern China
by Lijuan Zhang, Sijia Ding, Wenmin Qian, Aimei Zhao, Shimin Zhao, Yi Yang, Guoqing Weng, Minghui Tao, Hui Chen, Shaohua Zhao and Zhongting Wang
Atmosphere 2022, 13(7), 1029; https://doi.org/10.3390/atmos13071029 - 28 Jun 2022
Cited by 10 | Viewed by 1975
Abstract
The long-range transport of biomass burning pollutants from Southeast Asia has a significant impact on air quality in China. In this study, the Moderate Resolution Imaging Spectroradiometer (MODIS) fire data and aerosol optical depth (AOD) products and the Tropospheric Monitoring Instrument (TROPOMI) carbon [...] Read more.
The long-range transport of biomass burning pollutants from Southeast Asia has a significant impact on air quality in China. In this study, the Moderate Resolution Imaging Spectroradiometer (MODIS) fire data and aerosol optical depth (AOD) products and the Tropospheric Monitoring Instrument (TROPOMI) carbon monoxide (CO) data were used to analyze the impact of air pollution caused by biomass burning in Southeast Asia on southern China. Results showed that Yunnan, Guangdong and Guangxi were deeply affected by biomass burning emissions from March to April during 2016–2020. Comparing the data for fires on the Indochinese Peninsula and southern provinces of China, it is obvious that the contribution of pollutants emitted by local biomass burning in China to air pollution is only a small possibility. The distribution of CO showed that the overall emissions increased greatly from March to April, and there was an obvious transmission process. In addition, the MODIS AOD in areas close to the national boundary of China is at a high level (>0.6), and the AOD in the southwest of Guangxi province and the southeast of Yunnan Province is above 0.8. Combined with a typical air pollution event in southern China, the UVAI combined with wind direction and other meteorological data showed that the pollutants were transferred from the Indochinese Peninsula to southern China under the southwest monsoon. The PM2.5 data from ground-based measurements and backward tracking were used to verify the pollutant source of the pollution event, and it was concluded that the degree of pollution in Yunnan, Guangxi and Guangdong provinces was related to the distance from the Indochinese Peninsula. Results indicate that it is necessary to carry out in-depth research on the impact of cross-border air pollution transport on domestic air quality as soon as possible and to actively cooperate with foreign countries to carry out pollution source research and control. Full article
(This article belongs to the Special Issue Remote Sensing Applied in Atmosphere: Recent Trends, Current Progress and Future Directions)
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17 pages, 3787 KiB  
Article
Ozone Pollution in Chinese Cities: Spatiotemporal Variations and Their Relationships with Meteorological and Other Pollution Factors (2016–2020)
by Qiang Ge, Xusheng Zhang, Kun Cai and Yang Liu
Atmosphere 2022, 13(6), 908; https://doi.org/10.3390/atmos13060908 - 03 Jun 2022
Cited by 4 | Viewed by 3054
Abstract
With the acceleration of urbanization, ozone (O3) pollution has become increasingly serious in many Chinese cities. This study analyzes the temporal and spatial characteristics of O3 based on monitoring and meteorological data for 366 cities and national weather stations throughout [...] Read more.
With the acceleration of urbanization, ozone (O3) pollution has become increasingly serious in many Chinese cities. This study analyzes the temporal and spatial characteristics of O3 based on monitoring and meteorological data for 366 cities and national weather stations throughout China from 2016 to 2020. Least squares linear regression and Spearman’s correlation coefficient were computed to investigate the relationships of O3 with various pollution factors and meteorological conditions. Global Moran’s I and the Getis–Ord index Gi* were adopted to reveal the spatial agglomeration of O3 pollution in Chinese cities and characterize the temporal and spatial characteristics of hot and cold spots. The results show that the national proportion of cities with an annual concentration exceeding 160 μg·m−3 increased from 21.6% in 2016 to 50.9% in 2018 but dropped to 21.5% in 2020; these cities are concentrated mainly in Central China (CC) and East China (EC). Throughout most of China, the highest seasonal O3 concentrations occur in summer, while the highest values in South China (SC) and Southwest China (SWC) occur in autumn and spring, respectively. The highest monthly O3 concentration reached 200 μg·m−3 in North China (NC) in June, while the lowest value was 60 μg·m−3 in Northeast China (NEC) in December. O3 is positively correlated with the ground surface temperature (GST) and sunshine duration (SSD) and negatively correlated with pressure (PRS) and relative humidity (RHU). Wind speed (WIN) and precipitation (PRE) were positively correlated in all regions except SC. O3 concentrations are significantly differentiated in space: O3 pollution is high in CC and EC and relatively low in the western and northeastern regions. The concentration of O3 exhibits obvious agglomeration characteristics, with hot spots being concentrated mainly in NC, CC and EC. Full article
(This article belongs to the Special Issue Remote Sensing Applied in Atmosphere: Recent Trends, Current Progress and Future Directions)
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15 pages, 4113 KiB  
Article
Evaluation of TROPOMI and OMI Tropospheric NO2 Products Using Measurements from MAX-DOAS and State-Controlled Stations in the Jiangsu Province of China
by Kun Cai, Shenshen Li, Jibao Lai, Yu Xia, Yapeng Wang, Xuefei Hu and Ang Li
Atmosphere 2022, 13(6), 886; https://doi.org/10.3390/atmos13060886 - 30 May 2022
Cited by 3 | Viewed by 2147
Abstract
The tropospheric vertical column density of NO2 (Trop NO2 VCD) can be obtained using satellite remote sensing, but it has been discovered that the Trop NO2 VCD is affected by uncertainties such as the cloud fraction, terrain reflectivity, and aerosol [...] Read more.
The tropospheric vertical column density of NO2 (Trop NO2 VCD) can be obtained using satellite remote sensing, but it has been discovered that the Trop NO2 VCD is affected by uncertainties such as the cloud fraction, terrain reflectivity, and aerosol optical depth. A certain error occurs in terms of data inversion accuracy, necessitating additional ground observation verification. This study uses surface NO2 mass concentrations from the China National Environmental Monitoring Center (CNEMC) sites in Jiangsu Province, China in 2019 and the Trop NO2 VCD measured by MAX-DOAS, respectively, to verify the Trop NO2 VCD product (daily and monthly average data), that comes from the TROPOspheric Monitoring Instrument (TROPOMI) and Ozone Monitoring Instrument (OMI). The results show that the spatial distributions of NO2 in TROPOMI and OMI exhibit a similar tendency and seasonality, showing the characteristics of being high in spring and winter and low in summer and autumn. On the whole, the concentration of NO2 in the south of Jiangsu Province is higher than that in the north. The Pearson correlation coefficient (r) between the monthly average TROPOMI VCD NO2 and the CNEMC NO2 mass concentration is 0.9, which is greater than the r (0.78) between OMI and CNEMC; the r (0.69) between TROPOMI and the MAX-DOAS VCD NO2 is greater than the r (0.59) between OMI and the MAX-DOAS. As such, the TROPOMI is better than the previous generation of OMI at representing the spatio-temporal distribution of NO2 in the regional scope. On the other hand, the uncertainties of the satellite products provided in this study can constrain regional air quality forecasting models and top-down emission inventory estimation. Full article
(This article belongs to the Special Issue Remote Sensing Applied in Atmosphere: Recent Trends, Current Progress and Future Directions)
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Review

Jump to: Research

17 pages, 14085 KiB  
Review
Research Progress and Trends in the Field of Satellite Ozone from 2005 to 2023: A Bibliometric Review
by Yin Liu
Atmosphere 2023, 14(8), 1245; https://doi.org/10.3390/atmos14081245 - 04 Aug 2023
Viewed by 940
Abstract
Ozone, an important atmospheric constituent, affects various processes in the troposphere–stratosphere region and significantly contributes to climate and environmental change. The advancement of meteorological satellite technology has enabled the deployment of ozone detection instruments in space, providing accurate and global satellite ozone data [...] Read more.
Ozone, an important atmospheric constituent, affects various processes in the troposphere–stratosphere region and significantly contributes to climate and environmental change. The advancement of meteorological satellite technology has enabled the deployment of ozone detection instruments in space, providing accurate and global satellite ozone data in all weather conditions. This study employs scientometric methods, such as collaboration analysis, co-citation analysis, and keyword co-occurrence analysis to investigate the current status, trends, and future directions of satellite ozone research, with a broader search scope and more objective results compared with a manual review. Analyzing a dataset of 5320 bibliographic records from the WoS core collection database reveals the key intellectual frameworks shaping this field during the period from 2005 to 2023. The findings indicate that leading nations, like the United States, Germany, France, and China, along with their respective institutions and authors, spearhead satellite ozone research. Collaborative partnerships between the United States and European countries play a crucial role in advancing research efforts. Moreover, 20 distinct co-citation clusters identify the knowledge framework within the field, demonstrating a consistent progression over time. The focus has expanded from satellite ozone observation instruments to encompass broader areas, such as atmospheric pollution and environmental conditions, with “air quality” emerging as a prominent research area and future trend. Based on these insights, four major research directions are proposed: understanding atmospheric pollution mechanisms, improving ozone detection technologies, utilizing satellite ozone data for weather, and climate phenomena. This study aims to assist scholars by providing a comprehensive understanding of the developmental trajectory of satellite ozone research. Its results can serve as a valuable reference for researchers to identify relevant publications and journals efficiently. Policymakers can also utilize this systematic review as a structured point of reference. Full article
(This article belongs to the Special Issue Remote Sensing Applied in Atmosphere: Recent Trends, Current Progress and Future Directions)
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