Add time:09/30/2019         Source:sciencedirect.com

In this study we examine the application of a factor analysis technique for datasets recorded by the chemical ionization instrument Proton Transfer Reaction - Time-of-Flight - Mass Spectrometer (PTR-ToF-MS). Numerical simulations were carried out to test and optimize the performance of the factorization method Multivariate Curve Resolution - Alternating Least Squares (MCR-ALS). The simulations demonstrated that the choice of initial estimates for the factor analysis are crucial for the outcome of the factorization. For this purpose we describe a new method based on the Pearson correlation coefficient which, compared to the other tested methods, yields the best factorization results. Overlapping contributions of different substances to a certain mass bin and large uncertainties in the data deteriorate the performance of the factor analysis. The deconvolution technique was also applied to data obtained with a PTR-ToF-MS employed at a smog chamber. The response from single substances (fragmentation patterns) such as α-pinene, α-pinene oxide and pinonaldehyde as well as a more complex experiment involving the ozonolysis of α-pinene are investigated. For the single substances, the factorization method points to the presence of impurities which could be differentiated from the masses affiliated with the actual substances. The α-pinene ozonolysis experiment was analysed with the factorization technique and yielded four factors, one representing the decay of the reactant and three different products. The matrix factorization technique appeared to be a valuable tool allowing for a detailed analysis of complex mass spectra without the need of any prior information.

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