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The success of this application has benefited from computational workflow in Non\u2010Targeted Analysis, applied to the complex raw MS data to obtain qualitative and quantitative matrix information through deconvolution by MassHunter Unknowns Analysis software. Deconvolution is one of the most challenging steps in GC\u2010MS data processing reconstructing a pure mass spectrum for each component, permitting the identification of co\u2010eluted volatile organic compounds (VOCs) by both matching the electronic ionization (EI) mass spectra and the Linear Temperature\u2010Programmed Retention Index with reference values provided by spectral library. The described approach permitted a semi\u2010untargeted screening of VOCs in complex matrix by single quadrupole\u2010MS. Several oxygenated VOCs were found with relatively low abundances under the unresolved complex mixtures produced by co\u2010elution in the range between heptane and dodecane. Samples collected in typical asphalt production conditions produced between 2000 and 4500 deconvolution results, with 300 to 500 library hits considering a minimum match factor of 70\/100. Very VOCs resulted chromatographically resolved, while early eluting peaks were qualified by standard injection and single\u2010ion monitoring acquisition, since EI spectra of such light molecules are characterized by an insufficient number of peaks to achieve a deconvolution under the predominant early elution of carbon dioxide.<\/jats:p>","DOI":"10.1002\/jms.70063","type":"journal-article","created":{"date-parts":[[2026,4,28]],"date-time":"2026-04-28T11:31:20Z","timestamp":1777375880000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Solutions and Challenges in Focusing Trap and Spectral Deconvolution for Characterization of Odor Active VOCs in Hot Mix\u2010Asphalt"],"prefix":"10.1002","volume":"61","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-3078-7188","authenticated-orcid":false,"given":"S.","family":"Dugheri","sequence":"first","affiliation":[{"name":"Department of Life Sciences, Health and Health 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