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Non-target screening consists in searching a sample for all presentsubstances, suspected or unknown, with very little prior knowledge about thesample. This approach has been introduced more than a decade ago in the fieldof water analysis, together with dedicated compound identification tools, butis still very scarce for indoor and atmospheric trace gas measurements, despitethe clear need for a better understanding of the atmospheric trace gascomposition.For a systematic detection of emerging trace gases in theatmosphere, a new and powerful analytical method is gas chromatography (GC) ofpreconcentrated samples, followed by electron ionisation, high resolution massspectrometry (EI-HRMS). In this work, we present data analysis tools to enableautomated fragment formula annotation for unknown compounds measured byGC-EI-HRMS. Based on co-eluting mass/charge fragments, we developed aninnovative data analysis method to reliably reconstruct the chemical formulaeof the fragments, using efficient combinatorics and graph theory. The methoddoes not require the presence of the molecular ion, which is absent in ~40% ofEI spectra. Our method has been trained and validated on \textgreater50halocarbons and hydrocarbons, with 3 to 20 atoms and molar masses of 30 to 330g mol-1, measured with a mass resolution of approx.~3500. For 90% of thecompounds, more than 90% of the annotated fragment formulae are correct. Casesof wrong identification can be attributed to the scarcity of detected fragmentsper compound or the lack of isotopic constraint (no minor isotopoculedetected).Our method enables to reconstruct most probable chemical formulaeindependently from spectral databases. Therefore, it demonstrates thesuitability of EI-HRMS data for non-target analysis and paves the way for theidentification of substances for which no EI mass spectrum is registered indatabases. We illustrate the performances of our method for atmospheric tracegases and suggest that it may be well suited for many other types of samples.The L-GPL licenced Python code is released under the name ALPINAC forALgorithmic Process for Identification of Non-targeted Atmospheric Compounds.

Automated fragment identification for electron ionisation mass spectrometry: application to atmospheric measurements of halocarbons