Challenges in carbon footprint evaluations of state-of-the-art municipal wastewater resource recovery facilities

Analyzing the variation of greenhouse gas emissions from typical municipal wastewater treatment plants in Beijing during 2007-2021

With the proposal of dual carbon goals and stringent effluent standards, the path of mitigating greenhouse gas (GHG) emissions from wastewater treatment plants (WWTPs) has gained significant research attention. Here, we evaluate the impact of season, elevated standards, operating parameters, and using clean energy on GHG emissions from 8 typical WWTPs in Beijing based on 180 monthly monitoring data. Coupled with the increasing demand for wastewater treatment and 77% more chemical oxygen demand being removed in 2017, total GHG emissions from 5 WWTPs increased by 89% compared to the status quo in 2007, and after energy structure reform total GHG emissions decreased by 17% in 2021. Scenario analysis reveals that energy recovery and clean energy utilization provide 64% and 48% mitigation potential by 2050, respectively. We argue stricter effluent standard leads to GHG emissions growth in WWTPs; meanwhile, process optimization, proper temperature and targeted policies at WWTPs can reduce GHG emissions.

Critical evaluation of different mass transfer equations to model N2O emissions from water resource recovery facilities with diffuse aeration

N2O measurements by liquid sensors in aerated tanks are an input to gas-liquid mass-transfer models for the prediction of N2O off-gas emissions. The prediction of N2O emissions from Water Resource Recovery Facilities (WRRFs) was evaluated by three different mass-transfer models using Benchmark Simulation Model 1 (BSM1) as a reference model. Inappropriate selection of mass-transfer model may result in miscalculation of carbon footprints based on soluble N2O online measurements. The film theory considers a constant mass-transfer expression, while more complex models suggest that emissions are affected by the aeration type, efficiency, and tank design characteristics. The differences among model predictions were 10-16% at dissolved oxygen (DO) concentration of 0.6 g/m3, when biological N2O production was the highest, while the flux of N2O was 20.0-24 kg N2O-N/d. At lower DO, the nitrification rate was low, while at DO higher than 2 g/m3, the N2O production was reduced leading to higher rates of complete nitrification and a flux of 5 kg N2O-N/d. The differences increased to 14-26% in deeper tanks, due to the pressure assumed in the tanks. The predicted emissions are also affected by the aeration efficiency when KLaN2O depends on the airflow instead of the KLaO2. Increasing the nitrogen loading rate under DO concentration of 0.50-0.65 g/m3 increased the differences in predictions by 10-20% in both alpha 0.6 and 1.2. A sensitivity analysis indicated that the selection of different mass-transfer models did not affect the selection of biochemical parameters for N2O model calibration.