Distribution Of Reconstruction, Based On Ftir Multi-component Technology, The Concentration Of Pollutant Gases

Remote Sensing Fourier Transform Infrared Spectrometry (RS-FTIR), for its unique advantages, has found increasing application for indoor, outdoor air monitoring. In this research, two strategies of Artificial Neural Network (ANN) models with Smooth Basis Function Minimization (SBFM) reconstruction algorithm were combined in RS-FTIR spectra analysis, for the purpose of monitoring multi-components Volatile Organic Compounds (VOCs) concentration distribution in the two-dimensional plane. The main work is shown below:1 Reconstruction of single-component VOC's concentration distributionPrevious studies showed that Optical Remote Sensing and Computed Tomography could be connected to measure the spatial distribution of single-component VOC concentration in atmosphere. In this research, chamber experiments were conducted to test the combination of mono-static RS-FTIR spectroscopy and SBFM algorithm with radial beam path design. Through chamber experiment, VOC's absorbance spectra were obtained, and input to SBFM reconstruction program with the optimizing algorithm of Simulated Annealing (SA). The reconstruction results showed excellent agreement with the ray integral concentrations measured by RS-FTIR. Meanwhile, three models' reconstruction results were compared, and the Double-Gaussian reconstruction model was found to fit the best to the current monitoring environment.2 Qualitative analysis of RS-FTIR spectraWith the combination of RS-FTIR and SA-SBFM, we could just monitor single gas contaminant's concentration distribution. For identifying and quantifying multi-component VOCs from the complicated mixture RS-FTIR spectra, we still needed the assistance of advanced spectra analyzing methods. In the last decade, the number of chemometric methods applied in the field of spectroscopy grew rapidly. In this research, we tested two ANN modeling strategies—perception neural network, and Back Propagation network, in use of RS-FTIR spectra analysis.Perception network was designed to identify each component from three-component VOCs mixture spectra containing chloroform, methanol and methylene chloride. The responses of FTIR spectra data were normalized and taken first derivation, then input to supervised training network. Its identifying accuracy is 100%.For analyzing more complicated and overlapped 6-component spectra containing Benzene Toluene Chlorobenzene, 1,2-diethylbenzene and Cyclohexane, Principal...