Portable gas chromatography–mass spectrometry method for the in-field screening of organic pollutants in soil and water at pollution incidents

Abstract

Environmental pollution incidents generate an emergency response from regulatory agencies to ensure that the impact on the environment is minimised. Knowing what pollutants are present provides important intelligence to assist in determining how to respond to the incident. However, responders are limited in their in-field capabilities to identify the pollutants present. This research has developed an in-field, qualitative analytical approach to detect and identify organic pollutants that are commonly detected by regulatory environmental laboratories. A rapid, in-field extraction method was used for water and soil matrices. A coiled microextraction (CME) device was utilised for the introduction of the extracted samples into a portable gas chromatography–mass spectrometry (GC–MS) for analysis. The total combined extraction and analysis time was approximately 6.5 min per sample. Results demonstrated that the in-field extraction and analysis methods can screen for fifty-nine target organic contaminants, including polyaromatic hydrocarbons, monoaromatic hydrocarbons, phenols, phthalates, organophosphorus pesticides, and organochlorine pesticides. The method was also capable of tentatively identifying unknown compounds using library searches, significantly expanding the scope of the methods for the provision of intelligence at pollution incidents of an unknown nature, although a laboratory-based method was able to provide more information due to the higher sensitivity achievable. The methods were evaluated using authentic casework samples and were found to be fit-for-purpose for providing rapid in-field intelligence at pollution incidents. The fact that the in-field methods target the same compounds as the laboratory-based methods provides the added benefit that the in-field results can assist in sample triaging upon submission to the laboratory for quantitation and confirmatory analysis.