“PAW” a smart analytical process assessing lipophilicity of solutes in mixtures

Abstract

BackgroundThe analysis of mixtures of contaminants remains a challenging task in many fields, including water quality and waste management. For example, the degradation of industrial waste such as plastics, leads to complex mixtures with hundreds of organic contaminants and often non-referenced analytes. In such cases, non-targeted or effects-based analyses provide complementary information to classical targeted-analyses, regarding contaminants nature or properties (molecular mass, lability, toxicity). In this study, a novel analytical method is proposed to characterise mixtures of unknown organic contaminants, with a focus on the lipophilicity of solutes. ResultsThe proposed process, named “PAW“ (Partition of Aqueous Waste), aims at the quantification of octanol-water partition coefficients (POW) of mixed organic analytes. The process is based on sequential liquid-liquid partition equilibria. The output result is a lipophilicity histogram of the solutes, screened according to the chosen detection method. The process quantifies the distribution of analytes as a function of their octanol-water partition coefficients, without requiring any identification or prior knowledge. The PAW process is applicable with various detectors (UV–Visible, total carbon, liquid scintillation, etc.) allowing to focus on specific families of contaminants (e.g. organic solutes, colloids, 14C-bearing, etc.). Experimental proofs of concept are proposed, illustrating process implementation and possible fields of application. The first example deals with purity analysis of synthetic radiolabeled compounds. The second example aims the monitoring of cellulose degradation and quantification of the lipophilicity of degradation products. SignificanceThe PAW analytical process seems especially useful for characterisation of mixtures containing both hydrophilic and lipophilic compounds, e.g. neutral and ionizable organic contaminants, hardly characterisable simultaneously by chromatographic methods. It could be complementary to more detailed targeted or screening analysis of samples and effluents. For example it may help assessing the composition and environmental fate of mixtures of unknown analytes, thus facilitating waste management or mitigation strategies.