The importance of polysaccharides in the affinity of natural organic matter affinity for mackinawite, FeS: A chemometrics approach

Very little is known about the affinity of natural organic matter (NOM) for reduced iron species such as mackinawite (FeS) in the anoxic layers of marine sediments. In this study, equilibrium partition coefficients (Kd) for three types of NOM (soil extract, corn leaf extract and plankton extract) on FeS were determined through batch sorption experiments. Models were then built via multiple linear regression (MLR) and partial least squares regression (PLSR) in order to predict sorption Kd’s based on the chemical characteristics of the NOM as determined by ATR-FTIR. Investigation of the PLSR regression coefficients indicates that functional groups characteristic of polysaccharides are the greatest positive predictors of NOM sorption onto FeS at marine sediment porewater pH. This conclusion was independently verified by analyses of NOM FTIR spectra pre- and post-sorption. PLSR outperformed MLR with a lower root mean square error of prediction (RMSEP) of 53.4 L/kg compared to 64.0 L/kg. To our knowledge, this research presents a novel machine-learning approach to the quantitative modelling of NOM sorption to minerals found in anoxic marine environments.