Orthogonal Background Suppression Technique for EPA's Field Infrared Data ProcessingEPA Grant Number: R825366
Title: Orthogonal Background Suppression Technique for EPA's Field Infrared Data Processing
Investigators: Liu, Xu , Dybdahl, A. W. , Murcray, F. J.
Current Investigators: Blatherwick, R. D.
Institution: University of Denver
EPA Project Officer: Hiscock, Michael
Project Period: October 1, 1996 through September 30, 1999 (Extended to September 30, 2000)
Project Amount: $248,743
RFA: Analytical and Monitoring Methods (1996) RFA Text | Recipients Lists
Research Category: Water , Land and Waste Management , Air , Ecological Indicators/Assessment/Restoration , Environmental Statistics
One of the major obstacles in using Fourier transform infrared (FTIR) spectroscopic remote sensing of air pollutants in the ambient environment is removing the interferences in the spectroscopic data due to the presence of atmospheric gaseous constituents: water vapor and to a lesser degree, carbon dioxide. The University of Denver's (DU) orthogonal background suppression spectral data analysis technique uses orthogonal principal components to remove the background contributions from the FTIR spectra in essentially real time. A multivariant technique that employs principal component analysis (PCA) will be used to model the variability of water vapor spectral features as a function of concentration, air temperature and atmospheric pressure, both under laboratory conditions and in ambient air. The resulting principal components will be used to effectively remove the water vapor features in the field FTIR spectra, thereby unmasking the spectral features of pollutant gases and thus significantly increase the sensitivity of analysis.
The final result expected, which is most significant in the processing of FTIR spectra, is the following: For point and area pollutant sources, the PCA-generated background set of spectra, obtained from field clear air spectra, not containing these sources, will provide the suppression or the characterization of the background spectral features in the source spectra containing pollutant gases. When uncontaminated background (clear air) spectra cannot be obtained, as is the case in many industrial sites, PCA-generated water vapor spectra will be used to remove the water vapor interference from the pollutant quantification process. The PCA technique can also be employed to further remove the variable spectral features that occur for CO2, N2O and CH4.