A simple method to isolate fluorescence spectra from small dissolved organic matter datasets

Dissolved organic matter (DOM) is a complex pool of compounds with key role in the global carbon cycle. To understand its natural and engineered systems, efficient approaches are necessary for tracking DOM quality quantity. Fluorescence spectroscopy combined parallel factor analysis (PARAFAC) very widely used to identify quantify different fractions as proxies source, concentration biogeochemical processing. A major limitation PARAFAC approach requirement large data set containing many variable samples which vary independently. This severely curtails possibilities study fluorescence composition behavior small or unique datasets. Herein, we present simple inexpensive experimental procedure that makes it possible mathematically decompose dataset only highly-correlated fluorescent fractions. The approach, uses widely-available commercial extraction sorbents previously established protocols expand original inject missing chemical variability, can be implemented at low cost. demonstration shows how robust six-component model extracted from even river-water five bulk samples. Widespread adoption analyzing datasets needed confirm suspected ubiquity certain create shared inventory ubiquitous components. Such an could greatly simplify improve use tool investigate processing diverse water sources.