Optimizing the implementation of the PARAFAC method for near‐real time calibration of excitation–emission fluorescence analysis

A field‐portable, single‐exposure excitation–emission matrix (EEM) fluorometer is used in conjunction with parallel factor analysis (PARAFAC) for sub‐ppb polycyclic aromatic hydrocarbon (PAH) determinations in the presence of spectral interferents. Several strategies for bringing multiway calibration methods such as PARAFAC into the field were explored. It was shown that automated methods of PARAFAC model selection can be as effective as manual selection. In addition, it was found that there is not always a single best model to employ for prediction. Second, the effect that reducing data density by systematically decreasing calibration set size and spectral resolution has on PARAFAC speed and prediction accuracy was investigated. By decreasing data density, the computational intensity of the PARAFAC algorithm can be reduced to increase the plausibility of on‐the‐fly data analysis. It was found that reducing eight sample PAH calibration sets to two or three calibration standards significantly decreased computation intensity yet generated adequate predictions. It was also found that spectral resolution can be decreased to reach an optimal compromise between calibration accuracy and analysis speed while minimizing instrumental requirements.