Quantitative analysis of carbon emissions and material flow of a full-scale wastewater treatment plant with AAO process

• Anaerobic tank was identified as the primary direct emission source in AAO process. • Strong correlations were found between N 2 O, CH 4 emissions and influent pollutants. • Machine learning optimization achieved 30% carbon reduction and 33% cost savings. • Material flow analysis quantified the removal of COD, TN, and TP in each unit. • Multi-algae system was proposed for carbon reduction and nutrient recovery. Given the increasing attention in achieving carbon neutrality, carbon emissions and material flow are critical for the sustainability of wastewater treatment plants (WWTPs). This research firstly integrated carbon emission accounting, material flow analysis (MFA), and machine learning-based optimization to characterize a full-scale WWTP with the anaerobic-anoxic-oxic process. It was found that the annual carbon emission intensity was 0.734±0.069 kgCO 2 ·m -3 , with direct and indirect emissions contributing 36.8% and 63.2%, respectively. Notably, the anaerobic tank was identified as the primary source of direct emissions from nitrous oxide and methane production, while the aerobic tank was the largest contributor of indirect emissions, accounting for about 40% of the total electricity consumption. Additionally, nitrogen and organic load had a significant impact on direct emissions, while the poly aluminum chloride dosage had the largest effect on chemical consumption-related carbon emissions (r=0.853, p