Remote sensing of aerosol properties during intense smog events over Lahore (Pakistan)
In recent years, smog has been one of the main concerns in heavily populated urban areas like Lahore and Kanpur. Atmospheric pollutants like aerosols play an important role in smog. In this paper, aerosol types in smog episode are identified, based on AERONET data, for 4-year period i.e. 2015-2018....
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| Main Authors: | , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Elsevier
2021-08-01
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| Series: | Kuwait Journal of Science |
| Subjects: | |
| Online Access: | https://journalskuwait.org/kjs/index.php/KJS/article/view/10407 |
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| Summary: | In recent years, smog has been one of the main concerns in heavily populated urban areas like Lahore and Kanpur. Atmospheric pollutants like aerosols play an important role in smog. In this paper, aerosol types in smog episode are identified, based on AERONET data, for 4-year period i.e. 2015-2018. For winters we take four months January, October, November, December and May, June, July August for summer duration. The data is then classified in different aerosol types on the basis of fine mode fraction (FMF) and single scattering albedo (SSA). One of the main aerosol types which is abundant in every smog episode is black carbon (BC) aerosol while other types such as dust, were present throughout the year. Black carbon is responsible for radiation imbalance, so considered as main component in climate changes at regional and global level. Furthermore, aerosol optical depth (AOD) time series in smog episodes is used to make sure the presence of smog as AOD evaluates total burden of aerosol in atmosphere. Backward trajectories from HYSPLIT model are used to trace the origin of aerosols in maximum AOD days of smog episodes.
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| ISSN: | 2307-4108 2307-4116 |