FraMiTrACR: A Sustainable and Economical Technology for Analytical Sample Preparation

Abstract

Background There are several globally recognized methods for preparing laboratory samples. Of these, the QuEChERS and QuPPe methods are commonly used for food laboratory sample preparation. As an alternative, we developed the fractionation method using FraMiTrACR. Objective We present a life cycle assessment for the QuEChERS-, QuPPe- and FraMiTrACR methods. Our objective was to collect data to evaluate the carbon footprint of each method. However, as the ecological factors alone do not inform suitability of any given method, we also evaluated economic factors. Methods Our life cycle assessments followed ISO 14040/44 to determine the carbon footprint of each method. Also, we have analyzed existing data to support our comparison of all three methods. Results The mass of consumables and packaging for our FraMiTrACR method was observed to decrease by 45% and 34% from those required for the QuPPe and QuEChERS methods, respectively. Furthermore, we calculated a 43% reduction in carbon footprint when using FraMiTrACR compared to QuPPe and a 31% reduction compared to QuEChERS. In addition, we determined that our method offers time savings >87% and >71% compared to QuEChERS and QuPPe, respectively. The main economic benefit of FraMiTrACR comes from 84% and 70% labor cost savings compared to QuEChERS and QuPPe, respectively. The laboratory using fractionation method can process 320 samples with FraMiTrACR within 8 hours, an 87% increase in potential compared to QuEChERS and a 71% increase compared to QuPPe. Conclusions Fractionation using FraMiTrACR is a more sustainable method for analytical sample preparation, offering the same quality of results and far-reaching economic advantages. Highlights In comparison, FraMiTrACR uses up to 45% less consumables and packaging by weight and a reduction in kg CO2eq of up to 43%. In addition, the fractionation method offers up to 85% time savings and up to an 84% reduction in labor cost per sample.