Exploring the impact of hyper-quantity on the performance to access GHG emission in a full-scale A 2 O+MBR process: From predictions to implementation

Abstract

Abstract It was different to reduce the greenhouse gas (GHG) emission intensity of the wastewater treatment industry in China, owing to a lack of research and demonstration experience. This study aims to predict hyper-quantity functional performance, and provide a guidance for its real operation to assess the GHG emission in a full-scale anaerobic-anoxic-oxic membrane bioreactor (A2O + MBR) process in Beijing. The emulated result illustrated that ASM model offers broad applicability to predict functional performance during hyper-quantity operational periods. The running results show that the GHG emission intensity decreased from 1.31 CO2e/m3 to 1.24 CO2e/m3, representing a 5.3% decline in 2022, despite the total annual GHG emissions increased by 42.69% compared to the levels in 2018. Further, the GHG emission intensity of CH4, N2O, electricity consumption and chemical agent consumption decreased by 7.4%, 7.1%, 4.9% and 12.5%, respectively. The proportion of CH4, N2O, electricity and chemical agent consumption accounted for 20.38%, 31.89%, 47.67% and 0.06% of the total GHG emissions, showing minimal changes compared to those in 2018. Overall, this research provides valuable insights to policy-makers regarding water and carbon issue, assisting them in identifying to find low-risk and cost-effective solutions to reduce climate change impact.