Mass spectrometry parameters optimization for the 46 multiclass pesticides determination in strawberries with gas chromatography ion-trap tandem mass spectrometry

Multiclass analysis method was optimized in order to analyze pesticides traces by gas chromatography with ion-trap and tandem mass spectrometry (GC-MS/MS). The influence of some analytical parameters on pesticide signal response was explored. Five ion trap mass spectrometry (IT-MS) operating parameters, including isolation time (IT), excitation voltage (EV), excitation time (ET),maximum excitation energy or “q” value (q), and isolationmass window (IMW) were numerically tested in order to maximize the instrument analytical signal response. For this, multiple linear regression was used in data analysis to evaluate the influence of the five parameters on the analytical response in the ion trap mass spectrometer and to predict its response. The assessment of the five parameters based on the regression equations substantially increased the sensitivity of IT-MS/MS in the MS/MS mode. The results obtained show that for most of the pesticides, these parameters have a strong influence on both signal response and detection limit.Using the optimized method, a multiclass pesticide analysis was performed for 46 pesticides in a strawberry matrix. Levels higher than the limit established for strawberries by the European Union were found in some samples.

Analysis of PCBs in soils and sediments by microwave-assisted extraction, headspace-SPME and high resolution gas chromatography with ion-trap tandem mass spectrometry

A procedure for the determination of seven indicator PCBs in soils and sediments using microwave-assisted extraction (MAE) and headspace solid-phase microextraction (HS-SPME) prior to GC-MS/MS is described. Optimization of the HS-SPME was carried out for the most important parameters such as extraction time, sample volume and temperature. The adopted methodology has reduced consumption of organic solvents and analysis runtime. Under the optimized conditions, the method detection limit ranged from 0.6 to 1 ng/g when 5 g of sample was extracted, the precision on real samples ranged from 4 to 21% and the recovery from 69 to 104%. The proposed method, which included the analysis of a certified reference material in its validation procedure, can be extended to several other PCBs and used in the monitoring of soil or sediments for the presence of PCBs.

Cleanup of industrial effluents containing heavy metals: a new opportunity of valorising the biomass produced by brewing industry

Heavy metal pollution is a matter of concern in industrialised countries. Contrary to organic pollutants, heavy metals are not metabolically degraded. This fact has two main consequences: its bioremediation requires another strategy and heavy metals can be indefinitely recycled. Yeast cells of Saccharomyces cerevisiae are produced at high amounts as a by-product of brewing industry constituting a cheap raw material. In the present work, the possibility of valorising this type of biomass in the bioremediation of real industrial effluents containing heavy metals is reviewed. Given the autoaggregation capacity (flocculation) of brewing yeast cells, a fast and off-cost yeast separation is achieved after the treatment of metal-laden effluent, which reduces the costs associated with the process. This is a critical issue when we are looking for an effective, eco-friendly, and low-cost technology. The possibility of the bioremediation of industrial effluents linked with the selective recovery of metals, in a strategy of simultaneous minimisation of environmental hazard of industrial wastes with financial benefits from reselling or recycling the metals, is discussed.