Retrieval of aerosol optical constants from angular light-scattering measurement signals using principal component analysis approach

An angular light-scattering measurement (ALSM) method combined with the probability density function-bmsed ant colony optimization algorithm (PDF-ACO) is proposed for retrieval of aerosol optical constants. An optimal measurement angle selection method using a principal component analysis (PCA) approach is developed to improve retrieval accuracy. Results indicate that optimized angle selection can ensure retrieval accuracy. The aerosol optical constants over Beijing, China, which are available from the Aerosol Robotic Network (AERONET), are then rec on structed. The ALSM method's con vergence properties are also studied via comparison w让h those of the light reflection-transmittance measurement (LRTM) method. Results retrieved using the ALSM method show better convergence speed and accuracy than those retrieved using the LRTM method because the ALSM method does not require solution of the radiative transfer equation and allows more useful signals to be obtained. Additionally, the inverse accuracy of the refractive index results is better than that of the absorption index results;this is attributed to differences between the monodromic characteristics of the refractive index and absorption index retrieval results. All results confirm that the combination of the ALSM method w让h the PDF-ACO algorithm and the optimal measurement angle selection method provides effective and reliable aerosol optical constant reconstructio n.

Retrieval of aerosol size distribution using improved quantum-behaved particle swarm optimization on spectral extinction measurements

An improved quantum-behaved particle swarm optimization （IQPSO） algorithm is employed to deter- mine aerosol size distribution （ASD）. The direct problem is solved using the anomalous diffraction approximation and Lambert-Beer＇s Law. Compared with the standard particle swarm optimization algo- rithm, the stochastic particle size optimization algorithm and the original QPSO, our IQPSO has faster convergence speed and higher accuracy within a smaller number of generations. Optimization param- eters for the IQPSO were also evaluated; we recommend using four measurement wavelengths and S0 particles. Size distributions of various aerosol types were estimated using the IQPSO under dependent and independent models. Finally, experimental ASDs at different locations in Harbin were recovered using the IQPSO. All our results confirm that the IQpSO algorithm is an effective and reliable technique for estimatinz ASD.