Operational Regulation of Algal-Bacterial Granular Sludge for Nitrogen Removal Pathway Reconfiguration and N₂O...

Algal-bacterial granular sludge (ABGS) is a promising wastewater treatment technology that integrates algal-bacterial interactions within compact granules for enhanced nutrient removal. This study systematically regulated the C/N ratio, illumination, and aeration of ABGS cultivated under low hydraulic shear (0.5 cm s^-1) to elucidate nitrogen transformation pathway reconfiguration and its impacts on nitrous oxide (N₂O) production while evaluating the potential of biomass-associated nutrient retention. Operational regulation increased TN removal efficiency from 24.0% to 73.7% by progressively shifting nitrogen transformation from nitrification-dominated pathways toward enhanced algal-bacterial assimilation and simultaneous nitrification-denitrification (SND). Increasing the C/N ratio to 8 promoted nitrogen assimilation, whereas intensified illumination (from 12 h one-sided 10,000 lux to 24 h two-sided 10,000 lux) and reduced aeration (from 1 to 0.5 L min^-1) primarily stimulated SND while decreasing the relative contribution of microbial assimilation, indicating that improved nitrogen removal resulted from pathway reconfiguration rather than enhancement of a single pathway. Although microbial assimilation reduced nitrogen availability for the nitrification-denitrification process, it was not the sole mechanism responsible for N₂O mitigation. Instead, the reduction of N₂O emission factor to 0.10% (based on influent TN load) was associated with the redistribution of nitrogen transformation pathways and the increased SND-associated nitrogen removal. The enriched biomass also suggested potential for nutrient recovery, although further downstream processing and techno-economic evaluation are required. Nevertheless, the improved treatment performance and environmental benefits were achieved with additional carbon and energy inputs, highlighting the need for balancing operational benefits and resource consumption during future ABGS optimization.