Locating and quantifying CH4 sources within a wastewater treatment plant based on mobile measurements

Abstract. Wastewater treatment plants (WWTPs) are substantial contributors to greenhouse gas (GHG) emission because of the high production of methane (CH4) and nitrous oxide (N2O). A typical WWTP complex contains multiple functional areas that are potential sources for GHG emissions. Accurately quantifying GHG emissions from these sources is challenging due to the inaccuracy of emission data, the ambiguity of emission sources, and the absence of monitoring standards. Locating and quantifying WWTPs emission sources in combination with measurement-based GHG emission quantification methods are crucial for evaluating and improving traditional emission inventories. In this study, CH4 mobile measurements were conducted within a WWTP complex in the summer and winter of 2023. We utilized a multi-source Gaussian plume model combined with the genetic algorithm inversion framework, designed to locate major sources within the plant and quantify the corresponding CH4 emission fluxes. We identified 12 main point sources in the plant and estimated plant-scale CH4 emission fluxes of 603.33 ± 152.66 t a-1 for the summer and 418.95 ± 187.59 t a-1 for the winter. The predominant sources of CH4 emissions were the screen and primary clarifier, contributing 55 % and 67 % to the total emissions in summer and winter, respectively. The comparison against traditional emission inventories revealed that the CH4 emission fluxes in the summer were 2.8 times greater than the inventory estimates, and in the winter, emissions were twice the inventory values. Our flux inversion method achieved a good agreement between simulations and observations (correlation > 0.6 and a root mean square error (RMSE) < 0.7 mg m-3). This study demonstrated that mobile measurements, combined with the multi-source Gaussian plume inversion framework, are a powerful tool to locate and quantify GHG sources in a complex site, with the potential for further refinement to accommodate different types of factories and gas species.