New method for aerosol size distribution retrieval based on anomalous diffraction approximation

2001 ◽  
Author(s):  
Ghislan R. Franssens
Keyword(s):  
Size Distribution ◽  
New Method ◽  
Aerosol Size Distribution ◽  
Anomalous Diffraction ◽  
Anomalous Diffraction Approximation

scholarly journals Simplified representation of atmospheric aerosol size distributions using absolute principal component analysis

2007 ◽  
Vol 7 (3) ◽  
pp. 875-886 ◽  
Author(s):  
T. W. Chan ◽  
M. Mozurkewich
Keyword(s):  
Principal Component Analysis ◽  
Size Distribution ◽  
Principal Component ◽  
Original Data ◽  
Component Analysis ◽  
New Method ◽  
Aerosol Size Distribution ◽  
Distribution Data ◽  
Complex Data ◽  
Data Set

Abstract. Principal component analysis provides a fast and robust method to reduce the data dimensionality of an aerosol size distribution data set. Here we describe a methodology for applying principal component analysis to aerosol size distribution measurements. We illustrate the method by applying it to data obtained during five field studies. Most variations in the sub-micrometer aerosol size distribution over periods of weeks can be described using 5 components. Using 6 to 8 components preserves virtually all the information in the original data. A key aspect of our approach is the introduction of a new method to weight the data; this preserves the orthogonality of the components while taking the measurement uncertainties into account. We also describe a new method for identifying the approximate number of aerosol components needed to represent the measurement quantitatively. Applying Varimax rotation to the resultant components decomposes a distribution into independent monomodal distributions. Normalizing the components provides physical meaning to the component scores. The method is relatively simple, computationally fast, and numerically robust. The resulting data simplification provides an efficient method of representing complex data sets and should greatly assist in the analysis of size distribution data.

scholarly journals Simplified representation of atmospheric aerosol size distributions using absolute principal component analysis

2006 ◽  
Vol 6 (5) ◽  
pp. 10463-10492
Author(s):  
T. W. Chan ◽  
M. Mozurkewich
Keyword(s):  
Principal Component Analysis ◽  
Size Distribution ◽  
Principal Component ◽  
Original Data ◽  
Component Analysis ◽  
New Method ◽  
Aerosol Size Distribution ◽  
Distribution Data ◽  
Complex Data ◽  
Data Set

Abstract. Principal component analysis provides a fast and robust method to reduce the data dimensionality of an aerosol size distribution data set. Here we describe a methodology for applying principal component analysis to aerosol size distribution measurements. We illustrate the method by applying it to data obtained during five field studies. Most variations in the sub-micrometer aerosol size distribution over periods of weeks can be described using 5 components. Using 6 to 8 components preserves virtually all the information in the original data. A key aspect of our approach is the introduction of a new method to weight the data; this preserves the orthogonality of the components while taking the measurement uncertainties into account. We also describe a new method for identifying the approximate number of aerosol components needed to represent the measurement quantitatively. Applying Varimax rotation to the resultant components decomposes a distribution into independent monomodal distributions. Normalizing the components provides physical meaning to the component scores. The method is relatively simply, computationally fast, and numerically robust. The resulting data simplification provides an efficient method of representing complex data sets and should greatly assist in the analysis of size distribution data.

scholarly journals Optimal wavelength selection algorithm of non-spherical particle size distribution based on the light extinction data

2012 ◽  
Vol 16 (5) ◽  
pp. 1353-1357 ◽  
Author(s):  
Hong Tang
Keyword(s):  
Particle Size ◽  
Particle Size Distribution ◽  
Size Distribution ◽  
Approximation Method ◽  
Spherical Particles ◽  
Selection Algorithm ◽  
Wavelength Selection ◽  
Anomalous Diffraction ◽  
Optimal Wavelength ◽  
Anomalous Diffraction Approximation

In this paper, the anomalous diffraction approximation method is improved for calculating the extinction efficiency of non-spherical particles. Through this step, the range of the refractive index of particles can be enlarged, and the improved anomalous diffraction approximation method can be applied easily to the calculation of extinction efficiency for the most kinds of non-spherical particles. Meanwhile, an optimal wavelength selection algorithm is proposed for the inversion of non-spherical particle size distribution in the dependent mode. Through the improved anomalous diffraction approximation method, the computation time is substantially reduced compared with the rigorous methods, and a more accurate inversion result of particle size distribution is obtained using the optimal wavelength selection method.

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