Reconstruction of Air Contaminant Concentration Distribution in a Two-dimensional Plane by Computed Tomography and Remote Sensing FTIR Spectroscopy

Abstract

This research combined open path FTIR (OP-FTIR) technique and computed tomography (CT) to reconstruct air contaminant concentration distribution in a two-dimensional plane. Remote sensing FTIR instrument was used to scan radial beam geometry and obtain path integrated concentration (PIC) data of acetone gas in the measuring plane. Smooth basis function minimization (SBFM) algorithm was adopted to reconstruct gaseous concentration distribution. For the purpose of finding out the preferable number of Gaussians used in SBFM algorithm, single-Gaussian, double-Gaussian, and three-Gaussian models were used respectively. Experimental results showed that the reconstruction result of acetone concentration distribution by SBFM algorithm with double-Gaussian model agreed with real distribution more qualitatively and quantitatively than single-Gaussian and three-Gaussian. Also, it has been proved that simulated annealing algorithm used in the optimization process of SBFM reconstruction was feasible and effective. Although computed tomography and remote sensing FTIR technique (CT-RS-FTIR) is still at the laboratory study stage, with further improvement of SBFM algorithm and beam geometry, it promises to be used in air pollution monitoring widely.

Keywords:

• Air contaminant monitoring
• Remote sensing FTIR
• CT reconstruction
• SBFM algorithm
• Simulated annealing algorithm

ACKNOWLEDGMENTS

This project was supported by Postdoctoral Foundation of Education Ministry of China and by Young Scholar Foundation of Nanjing University of Science and Technology (Njust200303).