Abstract. Modern fluorescence spectroscopy methods, including excitation-emission matrix (EEMs) spectra parsed using parallel factor analysis (PARAFAC) statistical approaches, are widely used to characterize dissolved organic matter (DOM) pools. The effect of soluble reduced iron, Fe(II), on EEM spectra can be significant, but is difficult to quantitatively assign. In this study, we examine the effects of Fe(II) on the EEM spectra of groundwater samples from an anaerobic deltaic aquifer containing up to 300 mg/L Fe(II), located a few kilometers from the ocean, adjacent to the Fraser River in Richmond, British Columbia, Canada. We added varying quantities of Fe(II) into groundwater samples to evaluate Fe(II)-DOM interactions. Both the overall fluorescence intensity and the intensity of the primary peak, a humic-like substance at excitation/emission wavelengths 239/441–450 nm (Peak A), decreased by approximately 60 % as Fe(II) concentration increased from 1 to 306 mg/L. Furthermore, the quenching effect was non-linear and proportionally stronger at Fe(II) concentrations below 100 mg/L. This non-linear relationship suggests a static quenching mechanism. In addition, DOM fluorescence indices are substantially influenced by the Fe(II) concentration. With increasing Fe(II), the fluorescence index (FI) tends to shift to a more microbial-derived origin, and both the humidification index (HIX) and freshness index (FrI) indicate more freshly produced DOM. Nevertheless, the 13-component PARAFAC model showed that the component distribution was relatively insensitive to Fe(II) concentration, and thus, PARAFAC may be a reliable method for obtaining information about the DOM composition and its redox status in Fe(II)-rich waters. By characterizing the impacts of up to 300 mg/L Fe(II) on EEMs using groundwater from an aquifer which contains similar Fe(II) concentrations, we advance previous works which characterized impacts of lower Fe(II) concentrations (less than 2 mg/L) on EEMs.
AN ALGORITHM FOR THE SOLUTION OF PARAFAC MODEL AND ANALYSIS OF THE DATA BY THE INTERNATIONAL RICE ADAPTATION EXPERIMENTS
