The rapid accumulation of plastics in the environment has created the need for methods that allow to identify synthetic organic matter (SyOM) in sample matrices dominated by natural organic matter (NOM). We investigated the molecular composition of mixtures of peat with several key synthetic polymers –polyethylene (PE), polypropylene (PP), polyethylene terephthalate (PET), polystyrene (PS) and polyvinyl chloride (PVC)– using pyrolysis-GC-MS (Py-GC-MS) and thermally assisted hydrolysis and methylation (THM-GC-MS), to determine the capacities of these analytical tools to identify and quantify SyOM accumulation in organic-rich sample matrix without prior elimination of the NOM. The detection limit of Py-GC-MS depends mainly on the pyrolysis yield (signal intensity per unit of mass; PS > PE > PP > PET > PVC) and the specificity of the markers in the NOM matrix (PS > PET > PP > PVC > PE). Py-GC-MS allowed the identification of PET at a concentration of 0.002%, PS at 0.01%, PP at 0.1%, PE at 0.2% and PVC at 2%. Quantification was more problematic, as most markers showed inconsistent trends with SyOM concentration. THM-GC-MS yielded similar results, albeit the products of PP and PE could be more easily distinguished from NOM products because of the protection of the NOM’s fatty acids from decarboxylation, and because THM-GC-MS minimizes PET decarboxylation, enabling the use of the dimethyl terephthalate marker (detection limits: 0.02% for PE, PP and PET, 0.1% for PS and 0.2% for PVC). High-throughput analytical pyrolysis approaches have a clear potential to identify SyOM, but quantification requires NOM removal. In addition, we raise awareness of co-pyrolysis effects in simultaneous NOM-SyOM analysis, such as the influence of HCl formed during pyrolysis of PVC, which inhibits the intramolecular reorganization during cellulose pyrolysis and thus mitigates formation of the key product levoglucosan, and the effect of NOM on the balance between monomer, dimer and trimer products of PS. This study significantly advances on the analysis of widespread plastics polymers in NOM-rich environmental samples by pyrolysis and identify pitfalls in data interpretation.
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