Inversion of the haze aerosol sky columnar AVSD in central China by combining multiple ground observation equipment.

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.

[1]  Xuejiao Deng,et al.  Vertical distribution characteristics of PM in the surface layer of Guangzhou , 2015 .

[2]  Jinyuan Xin,et al.  Observation of aerosol optical properties and particulate pollution at background station in the Pearl River Delta region , 2014 .

[3]  C. Böckmann Hybrid regularization method for the ill-posed inversion of multiwavelength lidar data in the retrieval of aerosol size distributions. , 2001, Applied optics.

[4]  Wei Gong,et al.  Measurement and estimation of photosynthetically active radiation from 1961 to 2011 in Central China , 2013 .

[5]  Tahir Mehmood,et al.  A review of variable selection methods in Partial Least Squares Regression , 2012 .

[6]  Lunche Wang,et al.  Long-term observations of aerosol optical properties at Wuhan, an urban site in Central China , 2015 .

[7]  Darrell Whitley,et al.  A genetic algorithm tutorial , 1994, Statistics and Computing.

[8]  S. C. Liu,et al.  Case study of the effects of atmospheric aerosols and regional haze on agriculture: an opportunity to enhance crop yields in China through emission controls? , 1999, Proceedings of the National Academy of Sciences of the United States of America.

[9]  Yeli Yuan,et al.  Three‐dimensional structure of the summertime circulation in the Yellow Sea from a wave‐tide‐circulation coupled model , 2006 .

[10]  Michael D. King,et al.  A flexible inversion algorithm for retrieval of aerosol optical properties from Sun and sky radiance measurements , 2000 .

[11]  Xiangao Xia,et al.  Aerosol optical properties under the condition of heavy haze over an urban site of Beijing, China , 2014, Environmental Science and Pollution Research.

[12]  Michael D. King,et al.  Aerosol size distributions obtained by inversion of spectral optical depth measurements , 1978 .

[13]  T. Eck,et al.  Variability of Absorption and Optical Properties of Key Aerosol Types Observed in Worldwide Locations , 2002 .

[14]  B. Holben,et al.  Use of sky brightness measurements from ground for remote sensing of particulate polydispersions. , 1996, Applied optics.

[15]  Peng Wang,et al.  Aerosol optical properties of regional background atmosphere in Northeast China , 2010 .

[16]  P. Goloub,et al.  Instrument calibration and aerosol optical depth validation of the China Aerosol Remote Sensing Network , 2009 .

[17]  Tarun Gupta,et al.  Harmonisation of nanoparticle concentration measurements using GRIMM and TSI scanning mobility particle sizers , 2012, Journal of Nanoparticle Research.

[18]  B. Kowalski,et al.  Partial least-squares regression: a tutorial , 1986 .

[19]  Dimitris G. Kaskaoutis,et al.  Seasonal Variability of Atmospheric Aerosol Parameters over Greater Noida Using Ground Sunphotometer Observations , 2014 .

[20]  S. Wold,et al.  PLS-regression: a basic tool of chemometrics , 2001 .

[21]  Michael Taylor,et al.  Multi-modal analysis of aerosol robotic network size distributions for remote sensing applications: dominant aerosol type cases , 2013 .

[22]  Wei Gong,et al.  Aerosol Optical Properties and Determination of Aerosol Size Distribution in Wuhan, China , 2014 .