Prediction of dissolved organic carbon concentrations in inland waters using optical proxies of aromaticity

The chemical structures of dissolved organic compounds in natural waters, including the degree of aromaticity, affect their physical, chemical, and biological properties and ultimately the fate of carbon in aquatic systems and during water treatment. Herein, a new fluorescence-based aromaticity index named ARIX is shown to link the composition of aquatic dissolved organic matter to its aromaticity across diverse aquatic systems in both bulk DOM and extracts. ARIX predicts SUVA, a widely used proxy of aromaticity, more accurately than prevailing optical indices. It also predicts the percentage of polycyclic aromatic and polyphenolic molecular formulas determined by FT-ICR MS and the ratio of “humic substances” to “building blocks” fractions determined by LC-OCD, indicating it is additionally a proxy of DOM molecular weight. In waterbodies exhibiting decoupling between DOC and absorbance linked to biogeochemical processing, DOC concentrations are accurately predicted using a multilinear m..., The data were compiled from published datasets cited in the manuscript and listed in the references. Fluorescence indices (ARIX, FIX, HIX, BIX) were calculated from fluorescence EEMs using the pickpeaks function in the drEEM toolbox available at https://dreem.openfluor.org/, which implements algorithms according to the cited references.  Absorption coefficients were calculated by multiplying the measured absorbance by 2.303 and dividing by the cuvette pathlength in m. Spectral slopes were calculated according to the cited references.
, , # Data from: Prediction of dissolved organic carbon concentrations in inland waters using optical proxies of aromaticity

[https://doi.org/10.5061/dryad.x69p8czt8](https://doi.org/10.5061/dryad.x69p8czt8)

## Description of the data and file structure

These data consist of measurements performed on dissolved organic matter samples collected in natural aquatic systems or at water treatment plants. They represent a subset of datasets established by researchers who are cited in the manuscript and listed in the references tab of the excel file.

### Files and variables

#### File: Murphy_ARIX_archive.csv

**Description:** 

#### **Variables**

| Abbreviation | Description | Unit of measurement |
| :------------- | :----------------------------------------------------- | :------------------ |
| Dataset | Name of dataset | - |
| Geo\_Loc | Country /site code ...,