Prioritizing Chemical Features in Non-targeted Analysis through Spatial Trend Analysis: Application to the Identification of Organic Chemicals Subject to Mountain Cold-Trapping

One of the challenges arising during non-targeted analysis (NTA) is that the number of detected chemical features is generally too large for detailed processing and interpretation. Here, we illustrate how the analysis of spatial trends in peak intensities can be an effective tool to prioritize chemical features in NTA. Specifically, features detected by gas chromatography and high-resolution mass spectrometry in soil and air samples, collected along an altitudinal transect on an urban mountain in Canada, were successfully grouped into different categories based on spatial trends with site altitude. The motivation was to identify features whose abundance increases in soil with increasing elevation, as the ability for amplification at higher elevations could characterize contaminants of concern to mountain ecosystems. Potential matching candidates were first selected by comparing empirically detected accurate masses and isotope distributions of chemical features with those in chemical databases. These potential candidates were then ranked by comparing MSMS spectra with fragments predicted in silico. Several highly ranked matches, as well as structurally related compounds, which were largely halogenated methoxylated benzenes and organochlorine pesticides, were then subjected to targeted analysis with analytical standards. Several of these compounds, including pentachloroanisole, tricamba, and 3,4,5-trichloroveratrole, were identified as having spatial patterns consistent with mountain cold-trapping, as evidenced by organic carbon-normalized soil concentrations that show a significant increase with elevation. Our study clearly demonstrated that spatial trend analysis holds considerable promise as a tool to guide chemical identification and prioritization during NTA.