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High-throughput characterization of sediment organic matter by pyrolysis–gas chromatography/mass spectrometry and multivariate curve resolution: A promising analytical tool in (paleo)limnology
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•Multivariate curve resolution is suitable for processing Py–GC/MS data from sediment.•GC/MS was optimized for accurate spectra deconvolution and peak integration by MCR.•Py at 450°C produces more specific biomarkers than 650°C when analyzing mass <mg.•>200 chemical fingerprints of the common OM classes was identified with RSD <15%.•OM sources and degradation can be investigated with this new high-throughput method.
Molecular-level chemical information about organic matter (OM) in sediments helps to establish the sources of OM and the prevalent degradation/diagenetic processes, both essential for understanding the cycling of carbon (C) and of the elements associated with OM (toxic trace metals and nutrients) in lake ecosystems. Ideally, analytical methods for characterizing OM should allow high sample throughput, consume small amounts of sample and yield relevant chemical information, which are essential for multidisciplinary, high-temporal resolution and/or large spatial scale investigations. We have developed a high-throughput analytical method based on pyrolysis–gas chromatography/mass spectrometry and automated data processing to characterize sedimentary OM in sediments. Our method consumes 200μg of freeze-dried and ground sediment sample. Pyrolysis was performed at 450°C, which was found to avoid degradation of specific biomarkers (e.g., lignin compounds, fresh carbohydrates/cellulose) compared to 650°C, which is in the range of temperatures commonly applied for environmental samples. The optimization was conducted using the top ten sediment samples of an annually resolved sediment record (containing 16–18% and 1.3–1.9% of total carbon and nitrogen, respectively). Several hundred pyrolytic compound peaks were detected of which over 200 were identified, which represent different classes of organic compounds (i.e., n-alkanes, n-alkenes, 2-ketones, carboxylic acids, carbohydrates, proteins, other N compounds, (methoxy)phenols, (poly)aromatics, chlorophyll and steroids/hopanoids). Technical reproducibility measured as relative standard deviation of the identified peaks in triplicate analyses was 5.5±4.3%, with 90% of the RSD values within 10% and 98% within 15%. Finally, a multivariate calibration model was calculated between the pyrolytic degradation compounds and the sediment depth (i.e., sediment age), which is a function of degradation processes and changes in OM source type. This allowed validation of the Py–GC/MS dataset against fundamental processes involved in OM cycling in aquatic ecosystems.