Spatio-temporal characterization of a complete algal bloom event using fluorescence spectroscopy in tandem with conventional physico-chemical methods

Abstract

An increase in the frequency and geographic distribution of algal and cyanobacterial blooms has been observed over the last two decades, threatening marine and freshwater ecosystems. In situ fluorometers have been proposed for their potential to provide early warning of bloom development through the analysis of fluorescence signatures of the water. Despite the potential of the technology, there has been no in-depth analysis studying the fluorescence and 3-D excitation emission matrixes (EEMs) in a waterbody experiencing an algal bloom with intensive monitoring. Furthermore, the correlations between the EEMs and other physical and chemical parameters of blooms have not been elucidated till date. The Milford Gathering Pond in Geary County, KS experiences annual algal blooms that cause public access closures and affects the Kansas Department of Wildlife, Parks, and Tourism (KDWPT) fish hatchery. An algal bloom at the pond was intensively monitored from April 2021 to November 2021. Various water quality parameters such as pH, turbidity, orthophosphate, total filtered nitrogen, and total filtered carbon were tracked, and the 3-D fluorescence EEM spectroscopy was analyzed. Water quality parameters confirmed bloom development and proliferation through an observed logarithmic change in turbidity, increase in pH above 9, and decrease in orthophosphate. EEM intensity changes were traced through both visual peak identification and with Parallel Factor Analysis (PARAFAC). Two peaks were identified visually: Peak C and Peak T. PARAFAC identified three fluorescence components with compound peaks. Component 1 had Peak A and Peak C1, component 2 had Peak A and Peak C2, and Component 3 had Peak T1 and Peak T2. Peaks A and C represent humic-like compounds and Peak T represents tryptophan like compounds. The visually identified T peak and PARAFAC component C3 representing tryptophan-like fluorescence were shown to be the best predictor of algal bloom severity and progression with high correlations to pH, turbidity, and orthophosphate. In addition, the tryptophan-like fluorescence showed an increase in intensity before the onset of the bloom event, signaled by the jump in turbidity. This suggests that tryptophan-like fluorescence can be used as a predictive indicator of bloom proliferation. The findings show promise for a proactive and realistic algal monitoring tool which can be used by regulators and scientists alike for greater societal and environmental well-being.