Multiwavelength Multistatic Optical Scattering for Aerosol Characterization

Document ID: 88

Brown, Andrea M.

Doctoral Dissertation

 The Pennsylvania State University
 The Graduate School
 Department of Electrical Engineering
 

Abstract

The main focus of this research is the development of a technique to remotely characterize aerosol properties, such as particle size distribution, concentration, and refractive index as a function of wavelength, through the analysis of optical scattering measurements. The proposed technique is an extension of the multistatic polarization ratio technique that has been developed by prior students at the Penn State Lidar Lab to include multiple wavelengths. This approach uses the ratio of polarized components of the scattering phase functions at multiple wavelengths across the visible region of the electromagnetic spectrum to extract the microphysical and optical properties of aerosols. The scattering intensities at each wavelength are vertically separated across the face of the imager using a transmission diffraction grating, so that scattering intensities for multiple wavelengths at many angles are available for analysis in a single image. The ratio of the scattering phase function intensities collected using parallel and perpendicular polarized light are formed for each wavelength and analysis of the ratio is used to determine the microphysical properties of the aerosols.

One contribution of the present work is the development of an inversion technique based on a genetic algorithm that retrieves lognormal size distributions from scattering measurements by minimizing the squared error between measured polarization ratios and polarization ratios calculated using the Mie solution to Maxwell’s equations. The opportunities and limitations of using the polarization ratio are explored, and a genetic algorithm is developed to retrieve single mode and trimodal lognormal size distributions from multiwavelength, angular scattering data. The algorithm is designed to evaluate particles in the diameter size range of 2 nm to 60 µm, and uses 1,000 linear spaced diameters within this range to compute the modeled polarization ratio. The algorithm returns geometric mean radii and geometric standard deviations within 2% of the correct value when inverting a single lognormal probability size distribution from simulated polarization ratios that include random Gaussian noise added to limit the signal-to-noise ratio to 25. The genetic algorithm performed reasonably well when retrieving results using a single complex refractive index for all three wavelengths while finding the lognormal particle size parameters. Three inversion runs of the algorithm on simulated noisy data showed that the algorithm could retrieved a trimodal size distribution and a single complex refractive index that produced a very good fit between the simulated noisy polarization ratios and the forward-calculated polarization ratios.

A significant contribution of the present work is a set of tests conducted at the Environmental Protection Agency’s (EPA) Aerosol Test Facility (ATF), which is a controlled environment, where direct measurements of the size distribution and concentration of the scattering volume are available. The aerosol size distribution results obtained from inversion of the measured scattering phase functions, a lognormal size distribution with a geometric mean diameter of ~450 nm and a geometric standard deviation of ~1.3, compare favorably with measurements from an aerodynamic particle sizer and a condensation particle counter. This is one of the first large scale experiments where a comparison between multistatic inversion results and known properties of the interrogated volume of aerosols are made under controlled conditions.

The eventual goal is to develop a prototype sensor and an analysis approach to provide an important and useful tool to better define the atmospheric aerosol properties.

 

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Citation:        A. M. Brown, "Multiwavelength Multistatic Optical Scattering for Aerosol Characterization", The Pennsylvania State University, Doctoral Dissertation, 2010, 180 pages