Air Pollution in Asia
A special issue of Atmosphere (ISSN 2073-4433). This special issue belongs to the section "Air Quality".
Deadline for manuscript submissions: closed (15 October 2024) | Viewed by 20305
Special Issue Editors
Interests: air quality modeling; inverse model; satellite data; source apportionment
Special Issues, Collections and Topics in MDPI journals
Interests: air pollution
Interests: atmospheric modeling and forecasting; emission inventory; acid rain; source apportionment
Special Issues, Collections and Topics in MDPI journals
Special Issue Information
Dear Colleagues,
The aim of this Special Issue is to provide recent research activities in the field of air pollution in Asia, including particulate matter, ozone and other air pollutants. In Asia, anthropogenic emissions have sharply increased in recent years as a result of high economic growth with rapid industrialization, urbanization, and motorization, as well as agricultural activities. Enhanced emissions are always associated with the degradation of air quality, and have negative impacts on human health and climate. A great deal of research has recently been conducted in the field of air pollution mitigation and climate change in Asia. The contents of this Special Issue favor, but are not limited to, air quality measurements; air quality modeling involving mainstream models such as CALPUFF, CMAQ, CAMx, etc.; source apportionment analysis and control policy; satellite data application; and climate change. The latest applications of big data and deep learning technology in the atmospheric field are also favored and considered.
Topics of interest for the Special Issue include, but are not limited to:
- Air quality measurement and modeling.
- Source apportionment analysis and control policy.
- The applications of satellite data in air quality.
- The applications of big data and deep learning technology in the atmospheric field.
- Interaction between climate change and air quality.
Dr. Wei Tang
Dr. Cheol-Hee Kim
Dr. Fan Meng
Guest Editors
Manuscript Submission Information
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Keywords
- air pollution
- source apportionment
- satellite data
- climate change
- deep learning technology
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