Particulate air pollution in Durban: Characteristics and its relationship with 1 km resolution satellite aerosol optical depth

Mahesh, B.; Sivakumar, Venkataraman; Kulkarni, Padmavati; Sreekanth, V.

doi:10.1016/j.asr.2022.04.053

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Published Research On Air Quality In Africa: a Results Of En...1

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Cited by 4 publications

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“…The concentration of PM2.5 in African countries is ten times higher than the WHO recommended levels (WHO, 2021). Air quality studies are limited in Africa (Mahesh et al, 2022). It is crucial to assess the current state of knowledge on air quality in Africa and its evolution over the last decades.…”

Section: Published Research On Air Quality In Africa: a Results Of En...mentioning

confidence: 99%

RICTA2024: 8th Iberian Meeting on Aerosol Science and Technology

2024

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Section: Published Research On Air Quality In Africa: a Results Of En...mentioning

confidence: 99%

RICTA2024: 8th Iberian Meeting on Aerosol Science and Technology

2024

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Development of Land Use Regression (LUR) models and high-resolution spatial mapping of criteria air pollutants: Leveraging Delhi's continuous air monitoring network and remote sensing data

Agrawal,

Upadhya,

et al. 2024

Journal of Atmospheric and Solar-Terrestrial Physics

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Research progress, challenges, and prospects of PM_2.5 concentration estimation using satellite data

et al. 2023

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Satellite data are vital for understanding the large-scale spatial distribution of PM2.5 due to their low cost, wide coverage, and all-weather capability. Estimation of particulate matter (PM2.5) using satellite aerosol optical depth (AOD) product is a popular method. In this paper, we review the PM2.5 estimation process based on satellite AOD data in terms of data sources (i.e., inversion algorithms, data sets and interpolation methods), estimation models (i.e., statistical regression, chemical transport models, machine learning and combinatorial analysis) and modeling validation (i.e., four types of cross-validation (CV) methods). We found that the accuracy of time-based CV is less than others. We found significant differences in modeling accuracy between different seasons (p<0.01) and different spatial resolutions (p<0.01). We explained these phenomena. Finally, we summarized the research process, present challenges and future directions in this field. We opined that low-cost mobile devices combined with transfer learning or hybrid modeling offered research opportunities in areas with limited PM2.5 monitoring stations and historical PM2.5 estimation. These methods can be a good choice for air pollution estimation for developing countries. The purpose of this study is to provide a basic framework for future researchers to conduct relevant research, enabling them to understand current research progress and future research directions.

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Particulate air pollution in Durban: Characteristics and its relationship with 1 km resolution satellite aerosol optical depth

Cited by 4 publications

References 33 publications

RICTA2024: 8th Iberian Meeting on Aerosol Science and Technology

RICTA2024: 8th Iberian Meeting on Aerosol Science and Technology

Development of Land Use Regression (LUR) models and high-resolution spatial mapping of criteria air pollutants: Leveraging Delhi's continuous air monitoring network and remote sensing data

Research progress, challenges, and prospects of PM_2.5 concentration estimation using satellite data

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Particulate air pollution in Durban: Characteristics and its relationship with 1 km resolution satellite aerosol optical depth

Cited by 4 publications

References 33 publications

RICTA2024: 8th Iberian Meeting on Aerosol Science and Technology

RICTA2024: 8th Iberian Meeting on Aerosol Science and Technology

Development of Land Use Regression (LUR) models and high-resolution spatial mapping of criteria air pollutants: Leveraging Delhi's continuous air monitoring network and remote sensing data

Research progress, challenges, and prospects of PM2.5 concentration estimation using satellite data

Contact Info

Product

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Research progress, challenges, and prospects of PM_2.5 concentration estimation using satellite data