Deciphering natural and anthropogenic sources in estuarine sediment organic matter using multi-spectroscopic...

Identifying the sources of sedimentary organic matter (OM) is essential for understanding pollution dynamics and guiding effective management in estuarine environments. This study proposes a novel and transferable source tracking framework that integrates Fourier transform infrared (FTIR) and fluorescence spectroscopy with a principal component analysis-absolute principal component score-multiple linear regression (PCA-APCS-MLR) receptor model to apportion OM sources in surface sediments across four South Korean estuaries with contrasting land use. Five new infrared-based indices (IRIs), developed from diagnostic FTIR absorbance features of water-extractable organic matter (WEOM), were designed to capture source-specific functional group compositions linked to terrestrial, synthetic, and petroleum-derived OM. The robustness of the IRIs was evaluated through a two-tier validation approach. First, ultrahigh-resolution mass spectrometry of representative sediment extracts revealed strong and consistent correlations between each IRI and specific molecular compound classes, confirming the chemical relevance of the indices. Second, the source contribution estimates derived from the PCA-APCS-MLR model were externally validated using long-term bottom water quality datasets. These comparisons demonstrated coherence between modeled OM source profiles and independently measured indicators of nutrient enrichment and anthropogenic influence in bottom waters. The proposed IRIs, when coupled with fluorescence-based indicators, improved the discrimination among OM sources and enhanced model performance, capturing >85 % of the compositional variance in all sites. This integrated framework offers a cost-effective, spectroscopically driven alternative to high end molecular tools and is well suited for routine source tracking in estuarine systems impacted by diverse anthropogenic pressures.