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Special Issue "Multi-Source Remote Sensing Observations of Aerosol Properties and Air Quality"

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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: 31 January 2024 | Viewed by 3339

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Special Issue Editors

Dr. Adrianos Retalis

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Guest Editor

National Observatory of Athens, Institute for Environmental Research and Sustainable Development, Athens, Greece
Interests: remote sensing; atmospheric correction algorithms; digital image processing; air pollution monitoring/assessment

Prof. Dr. Sonoyo Mukai

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Guest Editor

School of Applied Information Technology, The Kyoto College of Graduate Studies for Informatics, Kyoto 606-8225, Japan
Interests: radiative trasnfer; aerosol remote sensing

Special Issue Information

Dear Colleagues,

It is well known that aerosols play an important role in the Earth’s radiation system and atmospheric environment. Along with this, the difficulty in understanding aerosol characteristics, which are highly variable in space and time, is also well known. Remote sensing from satellites, airplanes, and the ground are the most powerful means of aerosol measurement.

There is no doubt that the global climate crisis and air pollution are worsening. Due to these trends, various aerosol and cloud sensors will be installed on the Earth observation satellites to be launched soon, such as EarthCARE, EPS-SG, PACE, MAIA and so on. Advanced meteorological satellites can also be considered aerosol sensors. Other sensors (MODIS, CALIPSO, Sentinel-5P) also provide valuable information on aerosol properties and air quality. The development of data analysis algorithms that can cope with the remarkable growth of these devices and the integrated use of multiple sensors is required.

Manuscripts from various perspectives, whether observational, theoretical, or experimental, are welcomed.

Dr. Adrianos Retalis
Prof. Dr. Sonoyo Mukai
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 particles
polarization
LIDAR
numerical model simulations
experiments
space- and ground-based remote sensing
air quality

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Research

23 pages, 9713 KiB

Open AccessArticle

Biomass Burning Plume from Simultaneous Observations of Polarization and Radiance at Different Viewing Directions with SGLI

Sonoyo Mukai

Souichiro Hioki

and

Makiko Nakata

Remote Sens. 2023, 15(22), 5405; https://doi.org/10.3390/rs15225405 - 17 Nov 2023

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Abstract

The Earth Observation Satellite Global Change Observation Mission—Climate (GCOM)-C (SHIKISAI in Japanese), carrying a second-generation global imager (SGLI), was launched in 2017 by the Japan Aerospace Exploration Agency. The SGLI performs wide-swath multi-spectral measurements in 19 channels, from near-ultraviolet to thermal infrared (IR), including the red (674 nm; PL1 channel) and near-IR (869 nm; PL2 channel) polarization channels. This work aimed to demonstrate the advantages of SGLI, particularly the significance of simultaneous off-nadir polarized and nadir multi-spectral observations. The PL1 and PL2 channels were tilted at 45° for the off-nadir measurements, whereas the other channels took a straight downward view for the nadir measurements. As a result, the SGLI provided two-directional total radiance data at two wavelengths (674 and 869 nm) that were included in both off-nadir and nadir observations. Using these bidirectional data, an algorithm was applied to derive the altitude of the aerosol plume. Furthermore, because of the significance of the simultaneous observation of polarized and non-polarized light, the sensitivity difference between the radiance and polarized radiance was demonstrated. Severe wildfire events in Indonesia and California were considered as examples of specific applications. Herein, we present the results of our analysis of optically thick biomass-burning aerosol events. The results of the satellite-based analysis were compared with those of a chemical transport model. Exploring the SGLI’s unique capability and continuous 5-year global record paves the way for advanced data exploitation from future satellite missions as a number of multi-directional polarization sensors are programmed to fly in the late 2020s. Full article

(This article belongs to the Special Issue Multi-Source Remote Sensing Observations of Aerosol Properties and Air Quality)

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12 pages, 4700 KiB

Open AccessCommunication

Analysis and Validation of the Aerosol Optical Depth of MODIS Products in Gansu Province, Northwest China

and

Remote Sens. 2023, 15(12), 2972; https://doi.org/10.3390/rs15122972 - 07 Jun 2023

Viewed by 769

Abstract

The accurate determination of aerosol optical depth (AOD) is of great importance for climate change research and environmental monitoring. To understand the applicability of the MODIS aerosol product inversion algorithm in Gansu Province, this work uses ground-based solar photometer AOD observation data to validate the MODIS C6 version of the AOD product. Additionally, the retrieval accuracy of MODIS C6 Deep Blue (DB) algorithm AOD products and Deep Blue and Dark Target Fusion (DB–DT combined) algorithm AOD products for Gansu Province when setting different spatial sampling windows is compared and analyzed. Meanwhile, the monitoring effects of these two AOD algorithms in typical polluted atmospheric conditions in Gansu Province are compared. The results show that (1) the correlation between the MODIS AOD products of the two algorithms and the ground-based observation data decreases with an increasing spatial sampling window size. When the spatial sampling window of the two algorithms is set at 30 km × 30 km, it is more representative of the AOD value in Gansu Province, thus reflecting local characteristics. (2) When the spatial sampling window is set at 30 km × 30 km, the inversion effect of the DB algorithm AOD is better than that of the DB–DT combined algorithm AOD on different underlying surfaces. (3) The seasonal variability in the inversion accuracy of the DB algorithm AOD is less than that of the DB–DT combined algorithm, and it has inversion advantages in spring, autumn and winter, while the DB–DT combined algorithm outperforms the DB algorithm only in winter. The inversion effect of the two algorithms on AOD is influenced by the spatial sampling window setting. (4) Both the DB algorithm AOD and the DB–DT combined algorithm AOD can monitor the distribution of AOD in the central and western regions of Gansu, especially for high values of AOD under polluted atmospheric conditions, which represents a good monitoring effect. However, the two algorithms perform poorly in monitoring the southeast region of Gansu, while there is a discontinuous AOD distribution in the northwest region of Gansu. Overall, the MODIS DB algorithm AOD product has higher applicability in Gansu Province. This work provides a good reference for local air pollution and climate prediction. Full article

(This article belongs to the Special Issue Multi-Source Remote Sensing Observations of Aerosol Properties and Air Quality)

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24 pages, 8895 KiB

Open AccessArticle

Investigating the Potential Climatic Effects of Atmospheric Pollution across China under the National Clean Air Action Plan

and

Remote Sens. 2023, 15(8), 2084; https://doi.org/10.3390/rs15082084 - 14 Apr 2023

Cited by 1 | Viewed by 1568

Abstract

To reduce air pollution, China adopted rigorous control mechanisms and announced the Air Pollution Prevention and Control Action Plan (APPCAP) in 2013. Here, using OMI satellite, the NASA Socioeconomic Data and Application Center (SEDAC), and Fifth ECMWF (ERA5) data at a 0.25° × 0.25° resolution, we explored changes in NO₂, PM, SO₂, and O₃ and climatology over China in response to the Action Plan between 2004 and 2021. This study attempts to investigate the long term trend analysis of air pollution and climatic variations during two scenarios before (2004–2013) and after (2013–2021) APPCAP. We investigated the climatic effects of air pollution in China before and after APPCAP adoption using geographically weighted regression (GWR) and differential models to assess the contribution of air pollution. The spatial representation analysis demonstrated how air pollution affected climatic factors before and after the APPCAP. Several important findings were derived: (1) the APPCAP significantly influenced air pollution reduction in China post-scenario (2013–2021); (2) the Mann Kendall test investigated that all pollutants showed an increasing trend pre-APPCAP, while they showed a decreasing trend, except for O₃, post-APPCAP; (3) for climatic factors, the MK test showed an increasing trend of precipitation and mean minimum air temperature t_min post-APPCAP; (4) innovative trend analysis (ITA) showed a reduction in NO₂, SO₂, and PM, although O₃ showed no trend post-APPCAP; and (5) pre-scenario, NO₂ contributed to an increase in the mean maximum air temperature (t_max) by 0.62 °C, PM contributed to raising t_min by 0.41 °C, while O₃ reduced the t_max(t_min) by 0.15 °C (0.05 °C). PM increased t_max and precipitation with a magnitude 0.38 °C (7.38 mm), and NO₂ contributed to increasing t_min by (0.35 °C), respectively, post-scenario. In particular, post-scenario led to an increase in t_min and precipitation across China. The results and discussion presented in this study can be beneficial for policymakers in China to establish long-term management plans for air pollution and climatological changes. Full article

(This article belongs to the Special Issue Multi-Source Remote Sensing Observations of Aerosol Properties and Air Quality)

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