Basic considerations to minimize bias in collection and analysis of volatile methyl siloxanes in environmental samples.

Monitoring studies that aim to quantify volatile methyl siloxanes (VMS) in environmental matrices may encounter a multitude of issues, most of which relate to the unique combination of physical-chemical characteristics of VMS that distinguish them from other classes of organic compounds. These properties, which are critical to their function in various applications, also control their fate and distribution in the environment, as well as the analytical chemistry of their measurement. Polycondensation and rearrangement reactions of VMS oligomers are possible during sample storage and analysis. Thus, care should be exercised to suppress these types of reactions by avoiding any catalytic substances or surfaces in sample collection and analysis equipment. Another factor complicating sample integrity in the analysis of trace levels of VMS, is their ubiquitous presence in many common products and components of instrumentation in the laboratory. For example, some gas chromatography columns and inlet septa have been identified as sources of VMS due to surface-catalyzed transformation of silicones to VMS promoted by moisture under high temperature in some silicone-based GC columns. Possible chemical transformation of the analytes, contamination from other sources, and potential loss of analytes need to be assessed throughout all aspects of the study, from sample collection through analysis, by establishing a rigorous quality assurance and quality control program. The implementation of such a robust QA/QC program facilitates the identification and minimization of potential analytical biases and ensures the validity and usability of data generated from environmental monitoring campaigns for VMS. The objective of this paper is to focus on aspects of collection, processing, and analysis of environmental samples that may influence the quality of the VMS analytical results. This information should then be employed in the design and implementation of future monitoring studies and can used to assess the validity of analytical results from VMS monitoring studies.