Inversion algorithm for non-spherical dust particle size distributions
- 3 Downloads
Dust particles are the main aerosol component of the atmosphere, and can influence human, environmental, and ecological health. Particle size distribution is an important aerosol micro-physical parameter that denotes the concentration distribution of particles of different radii and can determine the extinction characteristics of these particles. In traditional inversion algorithms, the aerosol is generally assumed to be spherical according to Mie theory, and the relationship between aerosol optical thickness and particle size distribution is described by the Fredholm integral equation of the first kind. For non-spherical dust particles, this spherical assumption is obviously unreasonable and yields unreliable results. Therefore, we developed an algorithm assuming non-spherical particles for inversion of dust particle size distributions. In the case of non-spherical particles, the extinction efficiency factor kernel functions of the ellipsoid were calculated using the anomalous diffraction approximation method, and the kernel function of Mie scattering theory was substituted with these new kernel functions. Moreover, the Phillips–Twomey method was employed to solve the Fredholm integral equation of the first kind using aerosol optical thickness data from a CE-318 sun photometer. To verify the feasibility of the anomalous diffraction approximation method, experiments were carried out under sunny, dusty, windy and hazy weather conditions. These experiments showed that the extinction kernel function for non-spherical particles obtained using the anomalous diffraction approximation method is suitable for inversion of non-spherical dust particle size distributions under different weather conditions in the Yinchuan area.
KeywordsDust aerosol Non-spherical particle Anomalous diffraction approximation Particle size distribution
This work was supported by the National Natural Science Foundation of China (No. 61765001 and 61565001), Leading Talents of Scientific and Technological Innovation of Ningxia, Plan for Leading Talents of the State Ethnic Affairs Commission of the People’s Republic of China, Scientific Research Project of North Minzu University (No. 2016GQR07) and the Innovation Team of Lidar Atmosphere Remote Sensing of Ningxia.
Compliance with ethical standards
Conflict of interest
The authors declare that they have no conflicts of interest.
- 1.Toledo, F., Garrido, C., Díaz, M., Rondanelli, R., Jorquera, S., Valdivieso, P.: AOT retrieval procedure for distributed measurements with low-cost sun photometers. J. Geophys. Res. 123(2), 1113–1131 (2018)Google Scholar
- 4.Jia, X., Wang, W., Chen, Y., Huang, J., Chen, J., Zhang, H., Bai, H., Zhang, P.: Influence of dust aerosols on cloud radiative over Northern China. China Environ. Sci. 30(8), 1009–1014 (2010)Google Scholar
- 6.Holben, B.N., Eck, T.F., Slutsker, I., Tanre, D., Buis, J.P., Setzer, A., Vermote, E., Reagan, J.A., Kaufman, Y.J., Nakajima, T., Lavenu, F., Jankowiak, I., Smirnov, A.: AERONET-A federated instrument network and data archive for aerosol characterization. Rem. Sens. Environ. 66(1), 1–16 (1998)ADSCrossRefGoogle Scholar
- 8.Uchiyama, A., Yamazaki, A., Togawa, H., Asano, J.: Characteristics of aeolian dust observed by sky-radiometer in the Intensive observation period 1 (IOP1). J. Meteor. Soc. Jpn. 83A(3), 91–305 (2005)Google Scholar
- 9.Wehrli, C., Calibration of filter radiometers for the GAW Aerosol Optical Depth network at Jungfraujoch and Mauna Loa. In: Proceedings of ARJ workshop, SANW congress, Davos, Switzerland, 70–71: (2002)Google Scholar
- 11.Song, Y., Lu, L., Li, S., Xin, W., Yan, Q., Hua, D.: Analysis of light scattering properties of non-spherical aerosol particles. J. Xi’an Univ. Technol. 33(2), 233–239 (2017)Google Scholar
- 12.Zhang, H., Zhao, W., Ren, D., Qu, Y., Song, B.: Improved algorithm of Mie scattering parameter based on matlab. J. Light Scatt., 20 (2), 102–110 (2008)Google Scholar
- 16.Van de Hulst, H.C.: Light Scattering by Small Particles. Dover, New York (1981)Google Scholar
- 17.Ghislan, R.F.: A new method for aerosol size distribution retrieval based on the anomalous diffraction approximation. In: Proc. SPIE, 4168, pp. 243–248: (2000)Google Scholar
- 20.Tang, H., Sun, X., Yuan, G.: Application on circular cylinder particle size distribution based on anomalous diffraction approximation. Chin. J. Lasers 34(3), 411–416 (2007)Google Scholar
- 21.Tang, H.: Study of inversion algorithm of particle size distribution using total light scattering method. PhD thesis, Harbin: Harbin Institute of Technology. 2008.10Google Scholar
- 28.Twomey, S.: Introduction to the Mathematics of inversion in Remote Sensing and Indirect Measurements. Dover publication Inc., New York (1977)Google Scholar
- 29.Qiu, J., Wang, H., Zhou, X., lv, D.: Experimental study of remote sensing atmospheric aerosol size distribution by combined solar extinction and forward scattering method. Adv. Atmos. Sci. 7(1), 33–41 (1983)Google Scholar
- 30.Li, F., Liu, J., Lv, D.: Analyses of composite observation of optical properties of atmospheric aerosols in the late summer over some areas of North China. Sci. Atmospherica Sin. 19(2), 235–242 (1995)Google Scholar
- 32.Vitale, V., Tomasi, C., Lupi, A., Cacciari, A., Marani, S.: Retrieval of columnar aerosol size distributions and radiative forcing evaluations from sun photo metric measurements taken during the CLEARCOLUMN (ACE2) experiment. Atoms. Environ. 34(29–30), 5095–5105 (2000)Google Scholar
- 35.Ren, Y., Li, X., Lu, M., Hu, X.: Application prospect measurement by sun photometer CE318 and retrieval methodology. Meteorol. Sci. Technol. 34(3), 349–352 (2006)Google Scholar