Advancing greenhouse gas emission factors for municipal wastewater treatment plants in China

Estimations of greenhouse gas (GHG) emissions from municipal wastewater treatment plants (MWTPs) remain significant uncertainties in China owing to a lack of reliable emission factors (EFs). This study developed a framework to obtain multi-level (technology, province, and nation) GHG EFs of MWTPs using a database containing 3107 MWTPs in China and published site-specific monitoring data. Results show that GHG EFs of different technologies range widely from 180.0 to 615.7 g CO2-eq/t wastewater, and significant differences are also observed among different provinces in China (190.5-600.3 g CO2-eq/t wastewater), which are generally lower than the previous estimates. It confirms the importance of more detailed technology classification and considering the technological disparity of different provinces in refining GHG estimations of MWTPs. To test the feasibility of the developed EFs, we compared GHG emissions from MWTPs based on multi-level EFs at different spatial and temporal scales. Similar estimation results imply that selecting corresponding EF depending on the availability of activity data would simplify GHG estimations of MWTPs without sacrificing much accuracy. This study contributes a set of well-developed EFs to improve the estimates of GHG emissions from MWTPs, and also offers a method to develop GHG EFs for other sectors.

Automated summary

This study developed a framework to obtain multi-level greenhouse gas (GHG) emission factors (EFs) of municipal wastewater treatment plants (MWTPs) in China. The results showed significant differences in GHG EFs among different technologies and provinces, highlighting the importance of detailed technology classification and considering regional disparities. The study also tested the feasibility of the developed EFs and found similar estimation results, suggesting that selecting the appropriate EF based on activity data availability could simplify GHG estimations without sacrificing accuracy.