Noise reduction of fast, repetitive GC/MS measurements using principal component analysis (PCA)

Principal component analysis (PCA) was applied to the noise reduction of lo w ppb level benzene, toluene, ethyl benzene, xylene (BTEX) type sas chromat ography/mass spectrometry (GC/MS) measurements (i,e, BTEX) with a fast, rep etitive GC/MS system. The first three principal components (PCs) accounting for approximately 60-80% of the total variance in the original data could be attributed to chemical components, whilst the remaining PCs were found t o be due to noise. Reconstruction of the data from the first three PCs resu lted in noise reduction with improved signal fidelity, The results of PCA w ere comparable with those achieved by a Fourier transform method. (C) 1999 Elsevier Science B.V. All rights reserved.