Evidence Hub

Meta-Analysis of Optical Surrogates for the Characterization of Dissolved Organic Matter

Korak JA, McKay G

Environmental science & technology, 2024

762 participants · 59 citations

Abstract

High Resolution Image Download MS PowerPoint Slide Optical surrogates, derived from absorbance and fluorescence spectra, are widely used to infer dissolved organic matter (DOM) composition (molecular weight, aromaticity) and genesis (autochthonous vs allochthonous). Despite the broad adoption of optical surrogates, several limitations exist, such as context- and sample-specific factors. These limitations create uncertainty about how compositional interpretations based on optical surrogates are generalized across contexts, specifically if there is duplicative or contradictory information in those interpretations. To explore these limitations, we performed a meta-analysis of optical surrogates for DOM from diverse sources, both from natural systems and after water treatment processes ( n = 762). Prior to analysis, data were screened using a newly developed, standardized methodology that applies systematic quality control criteria before reporting surrogates. There was substantial overlap in surrogate values from natural and treated samples, suggesting that the gradients governing the surrogate variability can be generated in both contexts. This overlap provides justification for using optical surrogates originally developed in the context of natural systems to describe DOM changes in engineered systems, although the interpretations may change. Absorbance-based surrogates that describe the amount of spectral tailing (e.g., E2:E3 and S 275–295 ) had a high frequency of strong…

How strong is the evidence?

Evidence Hub reads this as a meta-analysis. Its evidence level is 1 of 5 (Highest · pooled evidence). Pooled evidence from several studies sits at the top of the evidence pyramid. Reported size: 762 participants or records.

How the five levels of evidence work. The level is assigned automatically from the abstract and can be wrong, so check the paper.

Read the paper

Related studies

Go deeper in Evidence Hub

Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.

Open this study Sign up free