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Advances and Challenges in Remote Sensing of Atmospheric Mineral Dust

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

Deadline for manuscript submissions: closed (1 December 2023) | Viewed by 4271

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Dr. Xiaoguang Richard Xu

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Guest Editor

Earth and Space Institute, University of Maryland Baltimore County, Baltimore, MD 21250, USA
Interests: aerosol and cloud remote sensing; radiative transfer; chemistry transport modeling; SmallSat and CubeSat observations
Special Issues, Collections and Topics in MDPI journals

Dr. Olga Kalashnikova

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Guest Editor

Jet Propulsion Laboratory, Pasadena, CA 91011, USA
Interests: modeling of aerosol optics; light scattering by irregular particles; remote sensing of aerosol optical properties
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Atmospheric mineral dust particles contribute over half of the mass of terrestrial aerosols, playing an important role in Earth’s climate and biogeochemistry. Over the last two decades, remote sensing observations from space have provided a critical global perspective for understanding the distribution, variability, and trend of mineral aerosols, and have transformed our knowledge on how mineral aerosols affect Earth’s climate and environment. This Special Issue aims to highlight the recent advances and remaining challenges in remote sensing of atmospheric mineral aerosols. We encourage submissions of research papers and review articles focusing on theoretical investigations, retrieval algorithm developments, and corresponding applications relevant to dust aerosol remote sensing, including (but not limited to) the following:

Advances in the optical modeling of complex, non-spherical aerosols, and the theoretical aerosol remote sensing approaches for characterization of mineral dust source composition and atmospheric mineral dust property evolution;
Development of retrieval algorithms and/or evaluation of dust aerosol products obtained from various (passive and/or active) satellite, airborne, or ground-based remote sensing instruments;
Application of dust remote sensing products to characterize dust properties, to constrain dust emissions, to improve air quality monitoring and forecast, or to quantify the impacts of mineral dust to Earth’s climate, etc.

Dr. Xiaoguang Richard Xu
Dr. Olga Kalashnikova
Guest Editors

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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.

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Keywords

mineral aerosols
dust aerosols
satellite remote sensing
dust optical property
aerosol retrieval algorithm
radiative transfer
aerosol radiative effect

Published Papers (3 papers)

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Research

22 pages, 8381 KiB

Open AccessArticle

Long-Term Spatiotemporal Characteristics and Influencing Factors of Dust Aerosols in East Asia (2000–2022)

by Yanjiao Wang, Jiakui Tang, Wuhua Wang, Zhao Wang, Jiru Wang, Shunbo Liang and Bowen Chu

Remote Sens. 2024, 16(2), 318; https://doi.org/10.3390/rs16020318 - 12 Jan 2024

Cited by 1 | Viewed by 799

Abstract

The Taklamakan Desert Region (TDR) and the Gobi Desert Region (GDR) in East Asia significantly impact air quality, human health, and climate through dust aerosols. Utilizing the MERRA-2 dataset’s long-term dust aerosol optical depth (DAOD) at 550 nm from 2000 to 2022, we systematically monitored the spatiotemporal dynamics of DAOD. Our analysis covered annual, seasonal, and monthly scales, employing geographical detector analyses to investigate the impact of eight factors on DAOD distribution. Over the 23-year period, the interannual variability in DAOD across East Asia was not pronounced, but a discernible decreasing trend was observed, averaging an annual decrease of −0.0002. The TDR had higher DAOD values (0.337) than the GDR (0.103). The TDR showed an average annual increase of 0.004, while the GDR exhibited an average annual decrease of −0.0003. The spatial distribution displayed significant seasonal variations, with peak values in spring, although the peak months varied between the TDR and GDR. The driving factor analysis revealed that relative humidity and soil moisture significantly impacted the DAOD spatial distribution in East Asia, which were identified as common driving factors for both the region and the major dust sources. Complex mechanisms influenced the variation in DAOD, with interactions between variables having a greater impact than individual effects. The geodetector-derived interaction q-value identified the collective impact of soil temperature and relative humidity (0.896) as having the highest impact on the spatial and temporal DAOD distribution. The overall spatial pattern exhibited a nonlinear enhancement trend, with the TDR and GDR showing bilinear enhancement patterns. These findings contribute to a better understanding of the factors influencing DAOD, offering a theoretical basis for atmospheric pollution control in East Asia. Full article

(This article belongs to the Special Issue Advances and Challenges in Remote Sensing of Atmospheric Mineral Dust)

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24 pages, 7714 KiB

Open AccessArticle

A New Risk-Based Method in Decision Making to Create Dust Sources Maps: A Case Study of Saudi Arabia

by Yazeed Alsubhi, Salman Qureshi and Muhammad Haroon Siddiqui

Remote Sens. 2023, 15(21), 5193; https://doi.org/10.3390/rs15215193 - 31 Oct 2023

Viewed by 915

Abstract

Dust storms are one of the major causes of the destruction of natural ecosystems and human infrastructure worldwide. Therefore, the identification and mapping of susceptible regions to dust storm formation (SRDSFs) is of great importance. Determining SRDSFs by considering the concept of risk in the decision-making process and the kind of manager’s attitude and planning can be very valuable in dedicating financial resources and time to identifying and controlling the negative impacts of SRDSFs. The purpose of this study was to present a new risk-based method in decision making to create SRDSF maps of pessimistic and optimistic scenarios. To achieve the purpose of this research, effective criteria obtained from various sources were used, including simulated surface data, satellite products, and soil data of Saudi Arabia. These effective criteria included vegetation cover, soil moisture, soil erodibility, wind speed, precipitation, and absolute air humidity. For this purpose, the ordered weighted averaging (OWA) model was employed to generate existing SRDSF maps in different scenarios. The results showed that the wind speed and precipitation criteria had the highest and lowest impact in identifying dust centers, respectively. The areas identified as SRDSFs in very pessimistic, pessimistic, neutral, optimistic, and very optimistic scenarios were 85,950, 168,275, 255,225, 410,000, and 596,500 km², respectively. The overall accuracy of very pessimistic, pessimistic, neutral, optimistic, and very optimistic scenarios were 84.1, 83.3, 81.6, 78.2, and 73.2%, respectively. The very pessimistic scenario can identify the SRDSFs in the study area with higher accuracy. The overall accuracy of the results of these scenarios compared to the dust sources obtained from the previous studies were 92.7, 94.2, 95.1, 88.4, and 79.7% respectively. The dust sources identified in the previous studies have a higher agreement with the results of the neutral scenario. The proposed method has high flexibility in producing a wide range of SRDSF maps in very pessimistic to very optimistic scenarios. The results of the pessimistic scenarios are suitable for risk-averse managers with limited financial resources and time, and the results of the optimistic scenarios are suitable for risk-taking managers with sufficient financial resources and time. Full article

(This article belongs to the Special Issue Advances and Challenges in Remote Sensing of Atmospheric Mineral Dust)

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20 pages, 5914 KiB

Open AccessArticle

Quantifying the Impact of Dust Sources on Urban Physical Growth and Vegetation Status: A Case Study of Saudi Arabia

by Yazeed Alsubhi, Salman Qureshi, Mazen E. Assiri and Muhammad Haroon Siddiqui

Remote Sens. 2022, 14(22), 5701; https://doi.org/10.3390/rs14225701 - 11 Nov 2022

Cited by 1 | Viewed by 1976

Abstract

Recently, dust has created many problems, including negative effects on health, and environmental and economic costs, for people who live both near to and far from sources of dust. The aim of this study is to evaluate and quantify the impact of dust sources located inside Saudi Arabia on the physical growth and vegetation status of cities. In order to do so, satellite data sets, simulated surface data, and soil data for Saudi Arabia from 2000 to 2021 were used. In the first step, a dust sources map of the study area was generated using multi-criteria decision analysis. Land surface temperature (LST), vegetation cover, soil moisture, precipitation, air humidity, wind speed, and soil erodibility factors were considered as effective criteria in identifying dust sources. In the second step, built-up land and vegetation status maps of major cities located at different distances from dust sources were generated for different years based on spectral indicators. Then, the spatiaotemporal change of built-up land and vegetation status of the study area and major cities were extracted. Finally, impacts of major dust sources on urban physical growth and vegetation were quantified. The importance degrees of soil erodibility, wind speed, soil moisture, vegetation cover, LST, air humidity, and precipitation to identify dust sources were 0.22, 0.20, 0.16, 0.15, 0.14, 0.07, and 0.05, respectively. Thirteen major dust sources (with at least 8 years of repetition) were identified in the study area based on the overlap of the effective criteria. The identified major dust sources had about 300 days with Aerosol Optical Depth (AOD) values greater than 0.85, which indicates that these dust sources are active. The location of the nine major dust sources identified in this study corresponds to the location of the dust sources identified in previous studies. The physical growth rates of cities located <400 km or >400 km from a major dust source (DMDS) are 46.2% and 95.4%, respectively. The reduction rates of average annual normalized difference vegetation index (NDVI) in these sub-regions are 0.006 and 0.002, respectively. The reduction rate of the intensity of vegetation cover in the sub-region close to dust sources is three times higher than that of the sub-region farther from dust sources. The coefficients of determination (R²) between the DMDS and urban growth rate and the NDVI change rate are 0.52 and 0.73, respectively, which indicates that dust sources have a significant impact on the physical growth of cities and their vegetation status. Full article

(This article belongs to the Special Issue Advances and Challenges in Remote Sensing of Atmospheric Mineral Dust)

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