Forensic Tracing of Unknown Compounds at the Human–Environment Interface: An All-in-One LC–HRMS Strategy Guided by a Curated Methodological Database
Abstract
The detection and identification of unknown organic pollutants in complex environmental and forensic samples remain major analytical challenges. While numerous finely tuned liquid chromatography-mass spectrometry (LC-MS) methods exist for specific compound classes, no transversal strategy has been proposed to date. Here we propose an “all-in-one” LC-MS strategy that is robust enough to handle the unknown and broad enough to encompass multiple chemical families within a single analytical framework. Our approach combines a structured, literature-derived analysis of LC-based methods with experimental validation on model mixtures and real forensic samples. From a systematic review of hundreds of reported conditions, we established a structured database of key LC parameters for selected pesticides, household products, and dyes. This enabled the design of a cross-family LC-MS method validated on representative compounds and successfully applied to authentic casework, including suspicious delivery packages and household cleaning agents in forensic investigations. Rather than relying on novel instrumentation, this work provides the first literature-driven, experimentally validated workflow for broad-spectrum, nontargeted LC-MS detection. This strategy, widely applicable across environmental and forensic applications, is a valuable resource for harmonization, spectral library growth, and automated annotation. Moreover, the compiled reference database of chromatographic conditions serves as a unique tool for method development in the community.
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BibTeX
@article{munoz2026forensic,
title = {{Forensic Tracing of Unknown Compounds at the Human–Environment Interface: An All-in-One LC–HRMS Strategy Guided by a Curated Methodological Database}},
author = {Alix Munoz and Jeanne Brotier and Laetitia Barthe and Guénaël Thiault and Joëlle Vinh},
journal = {ACS Omega},
year = {2026},
month = may,
doi = {10.1021/acsomega.6c00585},
url = {https://hal.science/hal-05733252v1},
note = {CC BY-NC-ND 4.0},
}
RIS
TY - JOUR
TI - Forensic Tracing of Unknown Compounds at the Human–Environment Interface: An All-in-One LC–HRMS Strategy Guided by a Curated Methodological Database
AU - Alix Munoz
AU - Jeanne Brotier
AU - Laetitia Barthe
AU - Guénaël Thiault
AU - Joëlle Vinh
PY - 2026
DA - 2026/05/27
JO - ACS Omega
DO - 10.1021/acsomega.6c00585
UR - https://hal.science/hal-05733252v1
AB - The detection and identification of unknown organic pollutants in complex environmental and forensic samples remain major analytical challenges. While numerous finely tuned liquid chromatography-mass spectrometry (LC-MS) methods exist for specific compound classes, no transversal strategy has been proposed to date. Here we propose an “all-in-one” LC-MS strategy that is robust enough to handle the unknown and broad enough to encompass multiple chemical families within a single analytical framework. Our approach combines a structured, literature-derived analysis of LC-based methods with experimental validation on model mixtures and real forensic samples. From a systematic review of hundreds of reported conditions, we established a structured database of key LC parameters for selected pesticides, household products, and dyes. This enabled the design of a cross-family LC-MS method validated on representative compounds and successfully applied to authentic casework, including suspicious delivery packages and household cleaning agents in forensic investigations. Rather than relying on novel instrumentation, this work provides the first literature-driven, experimentally validated workflow for broad-spectrum, nontargeted LC-MS detection. This strategy, widely applicable across environmental and forensic applications, is a valuable resource for harmonization, spectral library growth, and automated annotation. Moreover, the compiled reference database of chromatographic conditions serves as a unique tool for method development in the community.
SN - 2470-1343
ER -