Enhanced electrocoagulation process for natural organic matter removal from surface drinking water sources: coagulant dose control & organic matter characteristics

Abstract

In this study, an enhanced electro-coagulation (En-EC) technique is described for removal of natural dissolved organic matter (DOM) from surface drinking water sources. Assessment of the En-EC technique included investigating the impacts of operational factors on DOM removal efficiency, DOM characteristic variations, and energy consumption (C_E). DOM removal efficiencies by En-EC were compared with removals by enhanced chemical coagulation (EnC) along with residual metal levels. The removal of DOM was assessed by tracking the % reduction (R%) of dissolved organic carbon (DOC) and its surrogate parameters (i.e. UV absorbance at 254 nm (A₂₅₄), colour, fluorophore DOM fluorescence signal (fDOM_s)) following the En-EC process. Experiments were conducted using samples collected from three surface drinking water sources, i.e., Murray River, Myponga River and Middle River located in South Australia, Australia. An electrocoagulation cell was assembled and equipped with capability for measuring consumed C_E and electrical charge (Q). The impacts of process parameters (i.e. I_EC, the process pH [pH_EC], and the aluminium coagulant dose [Al_EC]) on the R% and C_E were also studied. The DOM characteristic variations following the process were studied using UV-vis spectroscopy, fluorescence excitation–emission (ex/em) (matrix) spectroscopy and high performance size exclusion chromatography equipped with UV and fluorescence ex/em spectrophotometer detectors. An optimum pH_EC of 6 was obtained experimentally for the En-Ec process. A comparable DOM removal efficiency was observed for either Al_EC in En-EC or alum in EnC. A maximum % A₂₅₄ removal of 74% to 92% was observed for the studied water sources, depending on the DOM characteristics. A comparable DOM removal performance was observed for En-EC and EnC. This was a basis for adopting a previously developed decision support system for alum dosing in the EnC process, for Al_EC dosing control in the En-EC process.