Chemometric approach to optimize the operational parameters of ESI for the determination of contaminants of emerging concern in aqueous matrices by LC-IT-TOF-HRMS

Contaminants of emerging concern are organic compounds used in large quantities by the society for various purposes. They have shown biological activity at low concentrations, which gives great environmental relevance. The difficulty to detect and quantify contaminants of emerging concern in the environment stimulates the development of appropriate analytical methods. In this work a chemometric approach to positive and negative electrospray ionization (ESI) optimization for the simultaneous determination of contaminants of emerging concern in water samples by liquid chromatography-ion trap-time of flight-high resolution mass spectrometry (LC-IT-TOF-HRMS) was applied. Three types of phase modifiers were used: formic acid, ammonium hydroxide and formic acid/ammonium formate. The effects of operational parameters such as mobile phase modifier concentrations, mobile phase flow rate, heating block temperature and drying gas flow rate were evaluated by the 24 − 1 fractional factorial experimental design, resolution IV, in the screening phase and by Doehlert experimental design. Initial factorial experimental design studies indicated that the phase modifier ammonium hydroxide was more efficient compared to the other evaluated modifiers. It provided higher ion intensities to the majority of analytes. Doehlert experimental design allowed finding a region indicative of the optimum experimental conditions for most analytes. The best experimental condition observed was 3.5 mM ammonium hydroxide concentration; 0.0917 mL/min of mobile phase; 300 °C heating block temperature; and drying gas at 200 kPa. These optimized parameters resulted in decreased detection limits of the method. The optimized method was applied to the evaluation of water samples coming from the Rio Doce basin - Minas Gerais/Brazil utilizing multivariate exploratory techniques such as principal component analysis and Kohonen neural network. In this way, the use of chemometric approach showed to be a promising way to optimize the simultaneous determination of twenty-one contaminants of emerging concern in aqueous matrices by LC-IT-TOF-HRMS using ESI.