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Remote Sensing of Atmospheric Composition
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Remote Sensing of Atmospheric Composition

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Atmospheric Remote Sensing".

Deadline for manuscript submissions: closed (30 June 2023) | Viewed by 6304

Special Issue Editor

Dr. Sang Seo Park

E-Mail Website
Guest Editor
Department of Urban and Environmental Engineering, Ulsan National Institute of Science and Technology, Ulsan 44919, Korea
Interests: aerosol; retrieval algorithm; atmospheric radiation; air quality; trace gases

Special Issue Information

Dear Colleagues,

Remote sensing techniques for terrestrial, airborne, and satellite-based instruments are essential to detect and estimate the spatio-temporal variations of atmospheric composition. These observations can monitor both short-lived climate pollutants (SLCPs) and long-lived green-house gases (GHGs), and can be applied to identify source and sink processes, as well as long-range transport in the atmosphere. In addition, remote sensing techniques make it possible to create the synergies to understand key processes and trends of the Earth–atmosphere system using different observation platforms. Remote sensing observations make it possible to estimate quantitative values such as column integrated value, concentration, and vertical profile information for specific atmospheric compositions. However, the dependence on instrument specification and spectral coverage determines the accuracy of retrieval results.

This Special Issue is soliciting articles on topics including the performance of retrieval algorithms and results of atmospheric compositions based on all remote sensing instrument platforms. In particular, we welcome papers presenting inter-comparison results for the same physical amounts among different observation platforms, helping to understand the improvements of retrieval algorithms.  Based on the retrieval accuracy, studies for climate, air quality and other applications are also key foci of this Special Issue.

Dr. Sang Seo Park
Guest Editor

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. Remote Sensing is an international peer-reviewed open access semimonthly 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 2700 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 quality
  • retrieval algorithm
  • atmospheric composition
  • climate change
  • aerosol
  • trace gases
  • inter-comparison and validation

Published Papers (4 papers)

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Research

20 pages, 8231 KiB  
Article
Seasonal and Diurnal Changes of Air Temperature and Water Vapor Observed with a Microwave Radiometer in Wuhan, China
by Xinglin Guo, Kaiming Huang, Junjie Fang, Zirui Zhang, Rang Cao and Fan Yi
Remote Sens. 2023, 15(22), 5422; https://doi.org/10.3390/rs15225422 - 20 Nov 2023
Viewed by 888
Abstract
Based on Microwave Radiometer (MWR) observations in Wuhan over the course of 21 months, we compared the temperature and water vapor levels with those from radiosonde (RS) sounding data at 00:00 and 12:00 UTC, and then analyzed the seasonal and diurnal changes of [...] Read more.
Based on Microwave Radiometer (MWR) observations in Wuhan over the course of 21 months, we compared the temperature and water vapor levels with those from radiosonde (RS) sounding data at 00:00 and 12:00 UTC, and then analyzed the seasonal and diurnal changes of temperature and water vapor levels from the MWR data. The MWR and RS mean temperatures and dew points are roughly consistent with each other below 2 km, whereas above 2 km, the MWR temperature is slightly lower than the RS temperature. The difference in their water vapor densities decreases quickly with height, and the bias of their relative humidities is generally in the range of −15% to 20%. The MWR observations show that in autumn, the surface temperature is 6.8 K lower during precipitation events than during non-precipitation events, indicating that precipitation in autumn is mainly caused by cold air from the north. The relative humidity during precipitation events exceeds 90% from the ground to 5 km, which is obviously larger than during non-precipitation events. During non-precipitation events, the seasonal mean water vapor density at 0–1.0 km shows an approximately linear increase with the mean temperature; however, their diurnal changes are opposite due to the effect of the boundary layer. At 4.5–5.5 km and 8.5–9.5 km, the mean temperature shows a synchronized diurnal evolution, with the maximum value prior to that at 0–1.0 km, indicating the strong influence of the air–land interaction on the temperature near the ground. Hence, this study is helpful for deepening our understanding of temperature and humidity variabilities over Wuhan. Full article
(This article belongs to the Special Issue Remote Sensing of Atmospheric Composition)
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21 pages, 6874 KiB  
Article
Ground-Based Remote Sensing of Atmospheric Water Vapor Using High-Resolution FTIR Spectrometry
by Peng Wu, Changgong Shan, Chen Liu, Yu Xie, Wei Wang, Qianqian Zhu, Xiangyu Zeng and Bin Liang
Remote Sens. 2023, 15(14), 3484; https://doi.org/10.3390/rs15143484 - 11 Jul 2023
Cited by 3 | Viewed by 1239
Abstract
Understanding the distribution of atmospheric water vapor (H2O) is crucial for global warming studies and climate change mitigation. In this study, we retrieved the ground layer, tropospheric and total columns of H2O using ground-based high-resolution Fourier transform infrared spectrometry [...] Read more.
Understanding the distribution of atmospheric water vapor (H2O) is crucial for global warming studies and climate change mitigation. In this study, we retrieved the ground layer, tropospheric and total columns of H2O using ground-based high-resolution Fourier transform infrared spectrometry (FTIR). The H2O total columns are obtained from near-infrared (NIR) and mid-infrared (MIR) spectra, and the ground layer and tropospheric H2O columns are retrieved from the MIR spectrum. The total columns of H2O retrieved from NIR and MIR have a good consistency (R = 0.989). Additionally, the ground layer H2O columns have a similar seasonal variation to total columns and tropospheric columns but have a higher seasonal amplitude. The ground layer H2O columns are close to the total columns and tropospheric columns in winter; however, in summer, the average difference between the ground layer and total columns and the value between the ground layer and tropospheric columns are large. This is mostly due to temperature variation. The temperature has a linear response to H2O, and the relationship between surface temperature and ln(XH2O) values in the ground layer, the entire atmosphere and the troposphere show a significantly positive correlation, and the correlation coefficient R is 0.893, 0.882 and 0.683, respectively. Furthermore, we selected the HYSPLIT model to simulate the back trajectories of air parcels in the four seasons in Hefei and find that the air mass transport has a significant impact on the local H2O change. These results demonstrate that ground-based high-resolution FTIR technology has high accuracy and precision in observing the vertical distribution and seasonal changes of H2O in different atmospheres. Full article
(This article belongs to the Special Issue Remote Sensing of Atmospheric Composition)
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20 pages, 20166 KiB  
Article
Accounting for Non-Detects: Application to Satellite Ammonia Observations
by Evan White, Mark W. Shephard, Karen E. Cady-Pereira, Shailesh K. Kharol, Sean Ford, Enrico Dammers, Evan Chow, Nikolai Thiessen, David Tobin, Greg Quinn, Jason O’Brien and Jesse Bash
Remote Sens. 2023, 15(10), 2610; https://doi.org/10.3390/rs15102610 - 17 May 2023
Cited by 1 | Viewed by 1852
Abstract
Presented is a methodology to explicitly identify and account for cloud-free satellite measurements below a sensor’s measurement detection level. These low signals can often be found in satellite observations of minor atmospheric species with weak spectral signals (e.g., ammonia (NH3)). Not [...] Read more.
Presented is a methodology to explicitly identify and account for cloud-free satellite measurements below a sensor’s measurement detection level. These low signals can often be found in satellite observations of minor atmospheric species with weak spectral signals (e.g., ammonia (NH3)). Not accounting for these non-detects can high-bias averaged measurements in locations that exhibit conditions below the detection limit of the sensor. The approach taken here is to utilize the information content from the satellite signal to explicitly identify non-detects and then account for them with a consistent approach. The methodology is applied to the CrIS Fast Physical Retrieval (CFPR) ammonia product and results in a more realistic averaged dataset under conditions where there are a significant number of non-detects. These results show that in larger emission source regions (i.e., surface values > 7.5 ppbv) the non-detects occur less than 5% of the time and have a relatively small impact (decreases by less than 5%) on the gridded averaged values (e.g., annual ammonia source regions). However, in regions that have low ammonia concentration amounts (i.e., surface values < 1 ppbv) the fraction of non-detects can be greater than 70%, and accounting for these values can decrease annual gridded averaged values by over 50% and make the distributions closer to what is expected based on surface station observations. Full article
(This article belongs to the Special Issue Remote Sensing of Atmospheric Composition)
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17 pages, 12687 KiB  
Article
Retrieval of Stratospheric Ozone Profiles from Limb Scattering Measurements of the Backward Limb Spectrometer on Chinese Space Laboratory Tiangong-2: Preliminary Results
by Song Liu, Xuemei Zong, Congcong Qiao, Daren Lyu, Wenxing Zhang, Jinqiang Zhang, Hailei Liu and Minzheng Duan
Remote Sens. 2022, 14(19), 4771; https://doi.org/10.3390/rs14194771 - 23 Sep 2022
Viewed by 1399
Abstract
The Backward Limb Spectrometer (BLS) onboard the Tiangong-2 (TG-2) space laboratory, the first spaceborne limb sounding instrument of China, was successfully launched on 15 September 2016, and its measurements of scattered photons of sunlight along the limb line-of-sight (LOS) in the 290–1000 nm [...] Read more.
The Backward Limb Spectrometer (BLS) onboard the Tiangong-2 (TG-2) space laboratory, the first spaceborne limb sounding instrument of China, was successfully launched on 15 September 2016, and its measurements of scattered photons of sunlight along the limb line-of-sight (LOS) in the 290–1000 nm range could be used to derive the vertical distribution of stratospheric ozone with high vertical resolution. Ozone profiles with a vertical resolution of one km in 10–40 km and 30–50 km were retrieved by the triplet and pair methods, respectively, and the ozone profiles retrieved by the BLS were compared with the ozone sounding data over four sounding stations. Meanwhile, the Ozone Mapping and Profiler Suite Limb Profiler (OMPS/LP) version 2.5 (v2.5) stratospheric ozone profile product was also introduced for comparison. The retrieval results showed a good agreement with the ozone profiles of ozone sounding and the OMPS/LP v2.5 product, and the differences were basically within 25% above 20 km, while relatively larger differences occasionally occurred below 20 km. The case studies over four sites worldwide demonstrate that the BLS is capable of measuring stratospheric ozone profiles with high vertical resolution. Full article
(This article belongs to the Special Issue Remote Sensing of Atmospheric Composition)
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