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Remote Sensing of Atmospheric Vertical Profile—Air Quality, Pollution and Aerosol Optical Properties

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

Deadline for manuscript submissions: 15 October 2025 | Viewed by 6033

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Special Issue Editors

Dr. Min Xie

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Guest Editor

School of Environment, Nanjing Normal University, Nanjing 210023, China
Interests: air quality monitoring and modelling; satellite data applications; urban air pollution

Dr. Jane Liu

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Guest Editor

Department of Geography & Planning, University of Toronto, Toronto, ON M5S 3G3, Canada
Interests: remote sensing of the atmosphere and land; atmospheric environment; atmosphere-biosphere interactions
Special Issues, Collections and Topics in MDPI journals

Dr. Bingliang Zhuang

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Guest Editor

School of Atmospheric Sciences, Nanjing University, Nanjing 210023, China
Interests: regional air pollution and climate change; remote sensing of aerosols

Special Issue Information

Dear Colleagues,

The atmospheric profile provides valuable information regarding the structure, composition, and dynamics of Earth’s atmosphere. Since the late 1970s, remote sensing sensors have been developed to measure atmospheric trace gases and aerosols, thereby enhancing our understanding of the optical properties of aerosols and the three-dimensional transportation of pollutants and their chemical reactions. Remote sensing techniques also contribute to a better knowledge of the impact of aerosols on the vertical layer structure of the atmosphere and climate change through direct and indirect effects. The integration of observed three-dimensional data into atmospheric models through data assimilation techniques can further improve the accuracy of weather forecasts and air quality predictions. The study of air pollution and aerosol optical properties through atmospheric vertical profile remote sensing is also of importance for understanding the climate effects of aerosols, implementing air pollution control measures, and enhancing air quality predictions.

The primary objective of this Special Issue is to delve into the capabilities, limitations, and recent advancements in remote sensing for atmospheric vertical profiles. It aims to unravel the complexity of atmospheric vertical structures and their interactions with aerosols through remote sensing data and analyses of the optical properties of aerosols.

Articles may address, but are not limited to, the following topics:

Remote sensing aerosol retrieval algorithms;
Machine learning in atmospheric profile retrieval;
Vertical distribution, transport, and diffusion of aerosols;
Optical properties and radiative effects of aerosols;
Aerosol–cloud microphysics effects;
Assimilation of atmospheric vertical profile observations;
Simulation and validation of atmospheric vertical profiles;
Variations in boundary-layer aerosols;
Three-dimensional remote sensing in cities.

Dr. Min Xie
Dr. Jane Liu
Dr. Bingliang Zhuang
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. 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

atmospheric vertical profile
aerosol optical properties
aerosol transportation
aerosol radiative effect
aerosol-cloud microphysics effects
boundary layer pollution
remote sensing retrieval algorithms
machine learning applications in remote sensing

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Published Papers (6 papers)

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21 pages, 40338 KiB

Open AccessArticle

Evaluation of Different Methods for Retrieving Temperature and Humidity Profiles in the Lower Atmosphere Using the Atmospheric Sounder Spectrometer by Infrared Spectral Technology

by Yue Wang, Wei Xiong, Hanhan Ye, Hailiang Shi, Xianhua Wang, Chao Li, Shichao Wu and Chen Cheng

Remote Sens. 2025, 17(8), 1440; https://doi.org/10.3390/rs17081440 - 17 Apr 2025

Viewed by 211

Abstract

The temperature and humidity profiles within the planetary boundary layer (PBL) are crucial for Earth’s climate research. The Atmospheric Sounder Spectrometer by Infrared Spectral Technology (ASSIST) measures downward thermal radiation in the atmosphere with high temporal and spectral resolution continuously during day and night. The physics-based retrieval method, utilizing iterative optimization, can obtain solutions that align with the true atmospheric state. However, the retrieval is typically an ill-posed problem and is affected by noise, necessitating the introduction of regularization. To achieve high-precision detection, a systematic evaluation was conducted on the retrieval performance of temperature and humidity profiles using ASSIST by regularization methods based on the Gauss–Newton framework, which include Fixed regularization factor (FR), L-Curve (LC), Generalized Cross-Validation (GCV), Maximum Likelihood Estimation (MLE), and Iterative Regularized Gauss–Newton (IRGN) methods, and the Levenberg–Marquardt (LM) method based on a damping least squares strategy. A five-day validation experiment was conducted under clear-sky conditions at the Anqing radiosonde station in China. The results indicate that for temperature profile retrieval, the IRGN method demonstrates superior performance, particularly below 1.5

k m

altitude, where the mean BIAS, mean RMSE, mean Degrees of Freedom for Signal (DFS), and mean residual reach 0.42

K

, 0.80

K

, 3.37, and

3.01 \times 10^{- 13}

(W / {c m}^{2} s r {c m}^{- 1})

, respectively. In contrast, other regularization methods exhibit over-regularization, leading to degraded information content. For humidity profile retrieval, below 1.5

k m

altitude, the LM method outperforms all regularization-based methods, with the mean BIAS, mean RMSE, mean DFS, and mean residual of 3.65

%

, 5.62

%

, 2.05, and

4.36 \times 10^{- 12}

(W / {c m}^{2} s r {c m}^{- 1})

, respectively. Conversely, other regularization methods exhibit strong prior dependence, causing retrieval to converge results toward the initial guess. Full article

(This article belongs to the Special Issue Remote Sensing of Atmospheric Vertical Profile—Air Quality, Pollution and Aerosol Optical Properties)

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17 pages, 4474 KiB

Open AccessArticle

Ground-Based LiDAR Analysis of Persistent Haze Pollution Events During Winter 2022 in Luohe City

by Wenyu Bai, Ran Dai, Chunmei Geng, Xinhua Wang, Nan Zhang, Jinbao Han and Wen Yang

Remote Sens. 2025, 17(5), 786; https://doi.org/10.3390/rs17050786 - 24 Feb 2025

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Abstract

Aerosol transport flux LiDAR was used to observe heavy pollution events in Luohe City during January 2022 and was combined with monitoring data of ground meteorological parameters and conventional pollutants to analyze the vertical optical properties of aerosols, transport sources, and causes of heavy pollution. Two pollution events (January 2nd–5th and 13th–20th, 2022) were effectively monitored and divided into four pollution phases according to PM_2.5 concentrations and relative humidity (RH). The results showed that all ground PM_2.5/PM₁₀ values were above 0.5 throughout the pollution, indicating a predominance of fine particulate matter. Analysis of the vertical distribution of aerosol flux LiDAR data showed that the inversion layer was distributed below 1 km; the vertical profile of extinction coefficient showed that all the pollution events were dominated by local emissions, while the contribution of regional transmission during the January 2nd to 5th was also quite prominent; kriging interpolation results showed that this pollution covered the most central and eastern regions of China during January 2022. The flux LiDAR monitoring results showed that there were three main transmission channels of PM_2.5: east (Zhoukou, Lu–Wan–Yu–Su junction), northeast (Lu–Yu junction), and southeast (YRD). The analysis of the clustered backward trajectories, potential source contribution function (PSCF), and concentration-weighted trajectory (CWT) models showed that the potential transmission sources of PM_2.5 were mainly in junction zones of Lu–Wan–Yu–Su as well as Shaanxi Province, with PSCF values above 0.7 and CWT values above 70 μg/m³. This study could provide a scientific basis for the prevention and control of local pollution. Full article

(This article belongs to the Special Issue Remote Sensing of Atmospheric Vertical Profile—Air Quality, Pollution and Aerosol Optical Properties)

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35 pages, 10328 KiB

Open AccessArticle

Aerosols in the Mixed Layer and Mid-Troposphere from Long-Term Data of the Italian Automated Lidar-Ceilometer Network (ALICENET) and Comparison with the ERA5 and CAMS Models

by Annachiara Bellini, Henri Diémoz, Gian Paolo Gobbi, Luca Di Liberto, Alessandro Bracci and Francesca Barnaba

Remote Sens. 2025, 17(3), 372; https://doi.org/10.3390/rs17030372 - 22 Jan 2025

Viewed by 884

Abstract

Aerosol vertical stratification significantly influences the Earth’s radiative balance and particulate-matter-related air quality. Continuous vertically resolved observations remain scarce compared to surface-level and column-integrated measurements. This work presents and makes available a novel, long-term (2016–2022) aerosol dataset derived from continuous (24/7) vertical profile observations from three selected stations (Aosta, Rome, Messina) of the Italian Automated Lidar-Ceilometer (ALC) Network (ALICENET). Using original retrieval methodologies, we derive over 600,000 quality-assured profiles of aerosol properties at the 15 min temporal and 15 metre vertical resolutions. These properties include the particulate matter mass concentration (PM), aerosol extinction and optical depth (AOD), i.e., air quality legislated quantities or essential climate variables. Through original ALICENET algorithms, we also derive long-term aerosol vertical layering data, including the mixed aerosol layer (MAL) and elevated aerosol layers (EALs) heights. Based on this new dataset, we obtain an unprecedented, fine spatiotemporal characterisation of the aerosol vertical distributions in Italy across different geographical settings (Alpine, urban, and coastal) and temporal scales (from sub-hourly to seasonal). Our analysis reveals distinct aerosol daily and annual cycles within the mixed layer and above, reflecting the interplay between site-specific environmental conditions and atmospheric circulations in the Mediterranean region. In the lower troposphere, mixing processes efficiently dilute particles in the major urban area of Rome, while mesoscale circulations act either as removal mechanisms (reducing the PM by up to 35% in Rome) or transport pathways (increasing the loads by up to 50% in Aosta). The MAL exhibits pronounced diurnal variability, reaching maximum (summer) heights of >2 km in Rome, while remaining below 1.4 km and 1 km in the Alpine and coastal sites, respectively. The vertical build-up of the AOD shows marked latitudinal and seasonal variability, with 80% (30%) of the total AOD residing in the first 500 m in Aosta-winter (Messina-summer). The seasonal frequency of the EALs reached 40% of the time (Messina-summer), mainly in the 1.5–4.0 km altitude range. An average (wet) PM > 40 μg m⁻³ is associated with the EALs over Rome and Messina. Notably, 10–40% of the EAL-affected days were also associated with increased PM within the MAL, suggesting the entrainment of the EALs in the mixing layer and thus their impact on the surface air quality. We also integrated ALC observations with relevant, state-of-the-art model reanalysis datasets (ERA5 and CAMS) to support our understanding of the aerosol patterns, related sources, and transport dynamics. This further allowed measurement vs. model intercomparisons and relevant examination of discrepancies. A good agreement (within 10–35%) was found between the ALICENET MAL and the ERA5 boundary layer height. The CAMS PM₁₀ values at the surface level well matched relevant in situ observations, while a statistically significant negative bias of 5–15 μg m⁻³ in the first 2–3 km altitude was found with respect to the ALC PM profiles across all the sites and seasons. Full article

(This article belongs to the Special Issue Remote Sensing of Atmospheric Vertical Profile—Air Quality, Pollution and Aerosol Optical Properties)

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23 pages, 4830 KiB

Open AccessArticle

Vertical Profiles of Aerosol Optical Properties (VIS/NIR) over Wetland Environment: POLIMOS-2018 Field Campaign

by Michal T. Chilinski, Krzysztof M. Markowicz, Patryk Poczta, Bogdan H. Chojnicki, Kamila M. Harenda, Przemysław Makuch, Dongxiang Wang and Iwona S. Stachlewska

Remote Sens. 2024, 16(23), 4580; https://doi.org/10.3390/rs16234580 - 6 Dec 2024

Viewed by 890

Abstract

This study aims to present the benefits of unmanned aircraft systems (UAS) in atmospheric aerosol research, specifically to obtain information on the vertical variability of aerosol single-scattering properties in the lower troposphere. The results discussed in this paper were obtained during the Polish Radar and Lidar Mobile Observation System (POLIMOS) field campaign in 2018 at a wetland and rural site located in the Rzecin (Poland). UAS was equipped with miniaturised devices (low-cost aerosol optical counter, aethalometer AE-51, RS41 radiosonde) to measure aerosol properties (scattering and absorption coefficient) and air thermodynamic parameters. Typical UAS vertical profiles were conducted up to approximately 1000 m agl. During nighttime, UAS measurements show a very shallow inversion surface layer up to about 100–200 m agl, with significant enhancement of aerosol scattering and absorption coefficient. In this case, the Pearson correlation coefficient between aerosol single-scattering properties measured by ground-based equipment and UAS devices significantly decreases with altitude. In such conditions, aerosol properties at 200 m agl are independent of the ground-based observation. On the contrary, the ground observations are better correlated with UAS measurements at higher altitudes during daytime and under well-mixed conditions. During long-range transport of biomass burning from fire in North America, the aerosol absorption coefficient increases with altitude, probably due to entrainment of such particles into the PBL. Full article

(This article belongs to the Special Issue Remote Sensing of Atmospheric Vertical Profile—Air Quality, Pollution and Aerosol Optical Properties)

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27 pages, 11457 KiB

Open AccessArticle

From Polar Day to Polar Night: A Comprehensive Sun and Star Photometer Study of Trends in Arctic Aerosol Properties in Ny-Ålesund, Svalbard

by Sandra Graßl, Christoph Ritter, Jonas Wilsch, Richard Herrmann, Lionel Doppler and Roberto Román

Remote Sens. 2024, 16(19), 3725; https://doi.org/10.3390/rs16193725 - 7 Oct 2024

Viewed by 1853

Abstract

The climate impact of Arctic aerosols, like the Arctic Haze, and their origin are not fully understood. Therefore, long-term aerosol observations in the Arctic are performed. In this study, we present a homogenised data set from a sun and star photometer operated in the European Arctic, in Ny-Ålesund, Svalbard, of the 20 years from 2004–2023. Due to polar day and polar night, it is crucial to use observations of both instruments. Their data is evaluated in the same way and follows the cloud-screening procedure of AERONET. Additionally, an improved method for the calibration of the star photometer is presented. We found out, that autumn and winter are generally more polluted and have larger particles than summer. While the monthly median Aerosol Optical Depth (AOD) decreases in spring, the AOD increases significantly in autumn. A clear signal of large particles during the Arctic Haze can not be distinguished from large aerosols in winter. With autocorrelation analysis, we found that AOD events usually occur with a duration of several hours. We also compared AOD events with large-scale processes, like large-scale oscillation patterns, sea ice, weather conditions, or wildfires in the Northern Hemisphere but did not find one single cause that clearly determines the Arctic AOD. Therefore the observed optical depth is a superposition of different aerosol sources. Full article

(This article belongs to the Special Issue Remote Sensing of Atmospheric Vertical Profile—Air Quality, Pollution and Aerosol Optical Properties)

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14 pages, 3542 KiB

Open AccessTechnical Note

Study on Daytime Atmospheric Mixing Layer Height Based on 2-Year Coherent Doppler Wind Lidar Observations at the Southern Edge of the Taklimakan Desert

by Lian Su, Haiyun Xia, Jinlong Yuan, Yue Wang, Amina Maituerdi and Qing He

Remote Sens. 2024, 16(16), 3005; https://doi.org/10.3390/rs16163005 - 16 Aug 2024

Cited by 2 | Viewed by 1028

Abstract

The long-term atmospheric mixing layer height (MLH) information plays an important role in air quality and weather forecasting. However, it is not sufficient to study the characteristics of MLH using long-term high spatial and temporal resolution data in the desert. In this paper, over the southern edge of the Taklimakan Desert, the diurnal, monthly, and seasonal variations in the daytime MLH (retrieved by coherent Doppler wind lidar) and surface meteorological elements (provided by the local meteorological station) in a two-year period (from July 2021 to July 2023) were statistically analyzed, and the relationship between the two kinds of data was summarized. It was found that the diurnal average MLH exhibits a unimodal distribution, and the decrease rate in the MLH in the afternoon is much higher than the increase rate before noon. From the seasonal and monthly perspective, the most frequent deep mixing layer (>4 km) was formed in June, and the MLH is the highest in spring and summer. Finally, in terms of their mutual relationship, it was observed that the east-pathway wind has a greater impact on the formation of the deep mixing layer than the west-pathway wind; the dust weather with visibility of 1–10 km contributes significantly to the formation of the mixing layer; the temperature and relative humidity also exhibit a clear trend of a concentrated distribution at about the height of 3 km. The statistical analysis of the MLH deepens the understanding of the characteristics of dust pollution in this area, which is of great significance for the treatment of local dust pollution. Full article

(This article belongs to the Special Issue Remote Sensing of Atmospheric Vertical Profile—Air Quality, Pollution and Aerosol Optical Properties)

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