Non-target and suspect characterisation of organic contaminants in Arctic air – Part 2: Application of a new tool for identification and prioritisation of chemicals of emerging Arctic concern in air

Abstract

Abstract. The Norwegian Arctic possesses a unique environment for the detection of new potential chemicals of emerging Arctic concern (CEACs) due to remoteness, sparse population and the low number of local contamination sources. Hence, a contaminant present in Arctic air is still considered a priority indication for its environmental stability and environmental mobility. Today, legacy persistent organic pollutants (POPs) and related conventional environmental pollutants are already well-studied because of their identification as Arctic pollutants in the 1980s. Many of them are implemented and reported in various national and international monitoring activities including the Arctic Monitoring and Assessment Programme (AMAP). These standard monitoring schemes, however, are based on compound-specific quantitative analytical methods. Under such conditions, the possibility for the identification of hitherto unidentified contaminants is limited and random at best. Today, new and advanced technological developments allow a broader, unspecific analytical approach as either targeted multicomponent analysis or suspect and non-target screening strategies. In order to facilitate such a wide range of compounds, a wide-scope sample clean-up method for high-volume air samples based on a combination of adsorbents was applied, followed by comprehensive two-dimensional gas chromatography separation and low-resolution time-of-flight mass spectrometric detection (GC × GC-LRMS). During the study reported here, simultaneous non-target and suspect screening were applied. The detection of over 700 compounds of interest in the particle phase and over 1200 compounds in the gaseous phase is reported. Of those, 62 compounds were confirmed with reference standards and 90 compounds with a probable structure (based upon mass spectrometric interpretation and library spectrum comparison). These included compounds already detected in Arctic matrices and compounds not detected previously (see also Fig. 1). In addition, 241 compounds were assigned a tentative structure or compound class. Hitherto unknown halogenated compounds, which are not listed in the mass spectral libraries used, were also detected and partly identified.

Non-target and suspect characterisation of organic contaminants in ambient air – Part 1: Combining a novel sample clean-up method with comprehensive two-dimensional gas chromatography

“…The combination of columns applied in this study (medium-polar combined with non-polar) had an improved matrix separation from compounds of interest compared to the most common combination (non-polar combined with medium-polar). However, as stated by Röhler et al (2020), this column combination is not suitable to use with any available retention indices for further identification confidence. The most comprehensive databases are available for non-polar (5 % phenyl) columns, whereas this study used a medium-polar column.…”

“…The level classification concept, developed from Schymanski et al (2015), describing the levels of classification and identification confidence is currently a gold standard used for reporting results from SUS and NTS data evaluation. However, the scheme was developed with the LC-HRMS data in mind and is therefore not directly applicable to the data produced with GC-MS-based methods (Rostkowski et al, 2019). The combination of columns applied in this study (medium-polar combined with non-polar) had an improved matrix separation from compounds of interest compared to the most common combination (non-polar combined with medium-polar).…”

“…The defined confidence levels by Schymanski et al (2015) cover identification criteria from accurate mass identification of a compound (Level 5, L5) to directly match with a reference standard (Level 1, L1). As proposed by Rostkowski et al (2019), the original version of Schymanski et al is not directly applicable for GC-HRMS, mainly due to different data filtration strategies compared to LC-HRMS. Additionally, in contrast to other previously reported SUS and NTS studies, our work is based on LRMS data and thus cannot provide accurate masses of compounds of interest.…”

“…2, Level 0), whereas for SUS and NTS a more general sample clean-up procedure is necessary, which often does not remove all interfering matrix. These SUS and NTS results are identified as extensive lists of relevant peaks (often ≥ 20 000 peaks), typically detected via retention time (RT) and full-scan mass spectra information (Rostkowski et al, 2019). Usually, the original peak list identified automatically by the analytical software needs to be systematically reduced and categorised according to the confidence identification criteria described above L. Röhler et al: Non-target and suspect characterisation of organic contaminants in ambient air (Fig.…”

“…Today, the combination of unspecific sample extraction and clean-up, together with high-resolution chromatographic and detection methods, is considered a prerequisite for NTS and SUS strategies. In particulate, the application of ultrahigh-resolution chromatographic methods (either liquid or gas chromatographic) in combination with high-resolution mass spectrometry (HRMS) enabled the identification and characterisation of hitherto unknown environmental contaminants in different matrices (López Zavala and Reynoso-Cuevas, 2015;Alygizakis et al, 2016;Hernández et al, 2015;Masiá et al, 2014;Al-Qaim et al, 2014;Hernández et al, 2007;Rostkowski et al, 2019;Schymanski et al, 2015). Another advanced analytical tool for non-targetspecific analysis of environmental samples is comprehensive two-dimensional gas chromatography (GC × GC) coupled to either low-resolution or high-resolution time-of-flight mass spectrometry (GC × GC-LRMS or GC × GC-HRMS, respectively).…”