Removal of Hg and Cu from raw gold-mine tailings by microalgae- and bacteria-augmented microbial fuel cells: Effects of bio-augmentation, diurnal cycling and operational faults

Artisanal gold-mining tailings carry dissolved mercury, copper and lead at concentrations requiring treatment before discharge. Bench-scale microbial fuel cells (MFCs) offer passive treatment of such streams, but exhibit operational variability that obscures whether removal is biologically driven. This study applies an integrated diagnostic framework to two bench-scale systems treating tailings from two artisanal gold-mining districts in Ecuador. System 1 evaluated Micractinium inermum bio-augmentation, while System 2 compared Psychrobacter alimentarius- and Trichococcus patagoniensis-dominated anodic consortia. The framework combines paired time-series statistical modeling, an adaptive percentile-floor change-point detector, equivalent-circuit modeling, and baseline-corrected XRD/FTIR spectroscopy. In System 1, treatment reduced mercury from 0.042 to 0.0027-0.0148 mg L^-1 and copper from 2.79 to 0.130-1.837 mg L^-1. Against the applicable discharge limits, copper complied in six of eight reactor--phase combinations, whereas mercury exceeded its limit throughout, identifying it as the limiting contaminant. Removal was governed by system-level physicochemical processes rather than algal-specific biocatalysis, with the non-algal control matching or exceeding the augmented reactors. Paired per-day testing showed that algal bio-augmentation conferred no voltage advantage under stable operation (+0.17%) but a +27.54% gain under diurnal perturbation, periodicity analysis attributed these shifts to the 24-h chamber photoperiod. An adaptive change-point detector distinguished recoverable excursions from terminal structural collapse in both systems, and equivalent-circuit fitting attributed System 2 consortium power difference to internal resistance and open-circuit voltage. The framework separates biological treatment effects from mechanical failure, supporting automated health monitoring in bio-electrochemical wastewater treatment.