Advanced Quantification of Fugitive Methane Emissions in Wastewater Treatment Plants

Introduction
Greenhouse gas (GHG) emissions, such as carbon dioxide (CO2) and methane (CH4), represent a major contributor to climate change with significant environmental implications (Gautam et al., 2021). These emissions are produced from different anthropogenic activities, including wastewater treatment plants (WWTPs) (Varon et al., 2021). CH4 emissions are particularly critical due to its high global warming potential. In WWTPs, CH4 is generated during the biological processes that involve breaking down the organic matter during anaerobic digestion (Elsayed et al., 2024). A key challenge facing methane quantification in WWTPs is its fugitive nature. While leakage from anaerobic digesters can be a key hotspot, there might be additional unexpected sources of CH4 emissions that may contribute to the overall emissions from these WWTPs. As these emissions can be episodic and location-specific, multi-level sensing is essential for capturing the temporal and spatial emission patterns and variabilities from these different sources. Therefore, the use of advanced sensing technologies, such as ground and drone-mounted sensors, has been gaining greater attention during recent years. These technologies generally assist in more precise and continuous monitoring, allowing for effective detection of fugitive methane emissions and identification of the hotspots.

Objectives
The main objectives of the current study are to: (1) demonstrate the employment of multi-level sensing techniques to monitor the fugitive methane emissions from WWTPs using ground sensors, drone, and Optical Gas Imaging (OGI) camera; (2) identify the hotspots of methane emissions within the wastewater treatment facility based on the deployed sensing techniques; and (3) determine the suitability and applicability of each sensing technique in detecting and quantifying methane emissions from the WWTP.

Methods
In the current study, sixteen ground sensors were installed in a Canadian WWTP with typical configuration to continuously monitor the fugitive methane from the treatment processes for more than five months. In addition, drone and OGI sensing campaigns were carried out to determine detailed insights about the methane emissions from different treatment processes. During the campaign, the drone was flown to isolate each treatment process through creating flight paths upwind and downwind each process and building. The drone featured a quantification sensor (i.e., open-path laser spectrometer (OPLS)) that can detect methane levels as low as 10 parts per billion (ppb). Moreover, a hand-held OGI camera was used to access the areas that cannot be assessed using the drone including the indoor spaces and chambers.

Results
Based on the drone and OGI campaigns, the anaerobic digesters, gas burner facility, and sludge handling facilities yielded high emissions that ranged from 2 to about 20 kg-CH4/hr based on wind characteristics. For example, the anaerobic digesters had an emission rate of approximately 9 kg-CH4/hr. (Fig. 1a). Interestingly, additional hotspots for methane emissions were identified during the campaigns. For example, the primary treatment process emitted approximately 8 kg-CH4/hr. More surprisingly, it was observed that there were some methane emissions around the aeration tanks where the methane emission rate was approximately 4 kg-CH4/hr/tank. (Fig. 1b).

A major limitation in drone-based measurements is its dependence on wind conditions. In cases where very slow winds or inconsistent/turbulence in wind directions, drones' measurements become invalid and inaccurate. In such a case, the use of OGI camera was more reliable which underscores the value of the adopted multi-level sensing approach. As shown in Fig. 2, a major hotspot in sludge holding tanks with more than 5 kg-CH4/hr was observed by the OGI camera, while multiple drone attempts failed due to the very slow wind conditions.

Using the ground sensors, it was observed that there are multiple hotspots for methane emissions within the WWTP. For example, the average methane concentration over the observation period ranged from 7.0 to 11.0 ppm for the sensors surrounding the aeration tanks (Fig. 3), indicating high methane emissions which agrees with the observations of the OPLS drone (Fig. 1b). The on-going research focuses on converting the time-series of methane concentrations into emissions which can assist in better correlation with the other sensing techniques (e.g., OGI camera).

Conclusions
The results of this study showed different methane hotspots near the primary tanks, aeration basins, sludge processing, and anaerobic digestion units. This encompasses both anticipated and unexpected emissions sources which can enhance our understanding about the sources of fugitive methane emissions in WWTPs. The advantages of the aerial drone, coupled with the OGI camera, allowed for rapid and comprehensive coverage of the facility, providing accurate spatial emission data. The ground sensors generally can underscore the variability of methane emissions and emphasize the importance of continuous monitoring to capture short-term spikes and long-term trends with high affordability compared to other sensing techniques. Ultimately, employing different sensing techniques can enhance our understanding about the methane emissions from WWTPs and assist in recommending effective emission mitigation strategies in the operation and management of these systems.