Satellite Remote Sensing of Atmospheric Aerosols for Air Quality Applications (Second Edition)
A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Atmospheric Remote Sensing".
Deadline for manuscript submissions: 15 December 2024 | Viewed by 1740
Special Issue Editors
2. Goddard Space Flight Center, NASA, Greenbelt, MD 20771, USA
Interests: aerosols; air quality monitoring; forecasting; PM2.5; NO2; O3; remote sensing; satellites, machine leaning; deep learning
Interests: satellite remote sensing; aerosols; air quality; wild fire; urban heatwave; drought; artificial intelligence; machine learning; deep learning
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
Long-term exposure to air pollution not only adversely affects human health but also has serious impacts on the climate and ecosystems. It is important to continuously monitor and predict air quality to assess its impact on human health and the environment. Air quality monitoring is usually conducted through point-based in situ measurements, but the spatial coverage is limited due to the lack of stations covering a large area. Satellite-based aerosol information is widely used as the key parameter to monitor and forecast air quality, not only the local scale but also on the global scale. Many previous studies have adopted various approaches (e.g., data assimilations (DA), artificial intelligence (AI), and a combination of DA and AI) to improve the their model’s performance. The aim of this Special Issue is to explore the latest advancements in satellite remote sensing of atmospheric aerosols for air quality applications. We invite submissions that showcase innovative methodologies, techniques, and applications related to remote sensing analysis in the context of aerosol monitoring. We welcome research articles, reviews, and case studies that address the following topics:
- Satellite remote sensing data acquisition and preprocessing techniques for aerosol monitoring.
- Development and validation of algorithms and models for satellite-based retrieval of aerosol properties.
- Integration of remote sensing data with other sources of information, such as ground-based observations, for comprehensive aerosol assessments.
- Applications of satellite remote sensing in air quality monitoring, including source attribution and regional-scale variability analysis.
- Evaluation of the effectiveness of satellite remote sensing in informing regulatory and policy actions to reduce air pollution.
Dr. Seohui Park
Prof. Dr. Jungho Im
Guest Editors
Manuscript Submission Information
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Keywords
- satellite remote sensing
- atmospheric aerosols
- air pollution
- PM2.5
- O3
- NO2
- methane
- air quality monitoring and forecasting
- atmospheric components
- artificial intelligence
- machine learning
- deep learning
- data assimilation
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