An Empirical and Semi Blind Algorithm for Resolving Overlapped Peaks in Chromatography: Application to the Analysis of Environmental Samples

In this paper we describe a new algorithm for enhancing the resolution (i.e. deconvolution) of chromatographic peaks strongly overlapped among them, often observed in the analysis of complex environmental samples. The main characteristic of this algorithm is that it does not require an “a priori” knowledge of the statistic moments (i.e. width, retention time and height) of the peak to be quantified so that it is considered an empirical and semi-blind (ESB) algorithm. The efficiency of the ESB algorithm has been verified for synthetic overlapped peaks, for the gas chromatographic (GC) analysis of hydrocarbons from marine sediments and for the planar chromatographic analysis (TLC) of carbohydrates in marine organic matter samples. In all the examined cases, standard errors lower than 25% and quadratic (R2) correlation coefficients higher than 0.85 were obtained, showing the comparability of the ESB algorithm with other deconvolution methods reported in the related scientific literature.