Abstract

Wuhan is the biggest city in China that has been facing an increasingly serious problem of air pollution in the recent years. In order to understand the mechanism of haze formation and diffusion, it is very important to obtain multiple atmospheric parameters. Columnar aerosol volume size distribution (AVSD) is an important atmospheric parameter in this regard, and utilizing CIMEL sun-photometer data to obtain this parameter has become the most popular method. However, currently, the widely used retrieval algorithms cannot be accessed using an open source code, and thus the retrieval of columnar AVSD is still a challenging task.. In this article, we introduce a new method that combines partial least squares (PLS) and genetic algorithm (GA) for the retrieval of columnar AVSD. By using this new method, we could obtain credible results even during hazy periods, despite the fact that our sun-photometer did not participate in the AERONET program and we did not use an official data processing method. First, it was assumed that columnar AVSD obeys the double logarithmic normal distribution function. Second, the relationship between the columnar AVSD and the AVSD on earth's surface was established using the partial least squares (PLS) method. Finally, the initial distribution parameters were adjusted through GA to obtain an optimal solution. This new method can improve the accuracy and reduce the computational difficulties faced in the retrieval of columnar AVSD in the absence of AREONET-based algorithm.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.