Issue 5, 2022

Implications of sample treatment on characterization of riverine dissolved organic matter

Abstract

High-resolution mass spectrometry techniques are widely used in the environmental sciences to characterize natural organic matter and, when utilizing these instruments, researchers must make multiple decisions regarding sample pre-treatment and the instrument ionization mode. To identify how these choices alter organic matter characterization and resulting conclusions, we analyzed a collection of 17 riverine samples from East River, CO (USA) under four PPL-based Solid Phase Extraction (SPE) treatment and electrospray ionization polarity (e.g., positive and negative) combinations: SPE (+), SPE (−), non-SPE (−), and non-SPE (+). The greatest number of formula assignments were achieved with SPE-treated samples due to the removal of compounds that could interfere with ionization. Furthermore, the SPE (−) treatment captured the most formulas across the widest chemical compound diversity. In addition to a reduced number of assigned formulas, the non-SPE datasets resulted in altered thermodynamic interpretations that could cascade into incomplete assumptions about the availability of organic matter pools for heterotrophic microbial respiration. Thus, we infer that the SPE (−) treatment is the best single method for characterizing environmental organic matter pools unless the focus is on lipid-like compounds, in which case we recommend a combination of SPE (−) and SPE (+) to adequately characterize these molecules.

Graphical abstract: Implications of sample treatment on characterization of riverine dissolved organic matter

Supplementary files

Article information

Article type
Paper
Submitted
01 Febr. 2022
Accepted
28 Marts 2022
First published
04 Apr. 2022
This article is Open Access
Creative Commons BY license

Environ. Sci.: Processes Impacts, 2022,24, 773-782

Implications of sample treatment on characterization of riverine dissolved organic matter

A. R. Nelson, J. Toyoda, R. K. Chu, N. Tolić, V. A. Garayburu-Caruso, C. M. Saup, L. Renteria, J. R. Wells, J. C. Stegen, M. J. Wilkins and R. E. Danczak, Environ. Sci.: Processes Impacts, 2022, 24, 773 DOI: 10.1039/D2EM00044J

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