Not Every Utility is Equal: How Operational Patterns, Influent Characteristics, and Compliance Limits Shape Fugitive GHG Emission Variability in Wastewater Treatment Plants

Introduction Amid the accelerating impacts of climate change, the urgent need to reduce greenhouse gas (GHG) emissions is more critical than ever, yielding commitments from developing countries aimed at achieving net-zero emissions by 2050. While energy sector decarbonization is underway, less attention has been given to direct GHG emissions from essential infrastructure. To this end, the wastewater sector alone contributes approximately 5% of global non-CO2‚ GHG emissions, largely in the form of methane (CH) and nitrous oxide (N2O), which have global warming potentials of 28 and 298 times higher than CO2, respectively [1]. As a prerequisite to mitigation, there has been growing academic and industrial interest in the quantification of the direct, or scope 1, emissions from wastewater treatment plants (WWTPs) -- emissions generated through bioprocesses [2]. The standard method for estimating emissions relies on the current Intergovernmental Panel on Climate Change (IPCC) guidelines, which use a simplified global emission factor (EF). However, this approach lacks the granularity required to capture the actual dynamics of GHG emissions from WWTPs [3]. Recent studies document substantial discrepancies, with observed CH emissions reaching up to 100 times the IPCC's estimated EF [4], and N2O emissions varying over six orders of magnitude [5]. These findings underscore the critical need for site-specific investigations to better understand emissions behavior, identify the factors driving variability, and pinpoint the specific sources contributing to these emissions. Therefore, in this research, we present findings from an ongoing Canadian project monitoring greenhouse gas (GHG) emissions from three full-scale wastewater treatment plants (WWTPs) across Canada. Our multi-level approach combines various advanced measurement techniques, including gas/liquid sensors, optical gas imaging, drone-based sensing, aircraft imaging, and satellite imaging. While previous studies have largely examined emissions variability in relation to treatment technology [5] and plant's size [4], this research attempts to link plant's GHG emissions with influent characteristics, compliance limits, and operational patterns. Treatment plant description and measurements campaign The Canadian wastewater treatment plant featured in this study operates with a typical treatment configuration. The plant comprises primary treatment, followed by the activated sludge (AS) process and, finally, disinfection. Given that there are no nitrogen compliance requirements, the AS process does not incorporate anaerobic and anoxic zones. Secondary sludge undergoes thickening, which is then combined with primary sludge for anaerobic digestion. The digested sludge is subsequently dewatered, and the centrate is returned to the AS process. To enhance settling efficiency, thickened waste activated sludge (TWAS) is mixed with primary sludge (PS) before digestion. To monitor nitrous oxide, two Unisense® sensors were used and located strategically to capture possible variation across the aeration tank. Methane (CH) emissions are quantified using 16 ground-based sensors, complemented by a 3-day intensive measurement campaign employing drone-based and optical gas imaging techniques. Results and discussion For over six months, liquid N2O concentrations were monitored at two locations in the aeration basin: the first and third quarters. As illustrated in Figure 1, median daily N2O emissions were recorded at 2.22 KgN-N2O/day and 2.91 KgN-N2O/day, with only occasional instances exceeding 10 KgN-N2O/day. This corresponds to an N2O emission factor (EF) of 0.005±0.0012 kg N2O-N per kg TN which is substantially lower than the IPCC EF of 0.016 kg N2O-N per kg. This can be referred to the limited nitrogen removal in the plant, Figure 1. This is because the plant does not have ammonia or total nitrogen compliance limit. While prior studies reported higher N2O emissions with incomplete nitrification [6], the present plant was operated at sludge age (3.34±0.65 day) close to the washout of nitrifying biomass which resulted in lower EF. Results of the methane emissions quantification are shown in Figure 2. The average methane emissions from the plant equal to 1293±807 kgCH4/day. This is equivalent to 3.5-4% of gCH4/m3 treated and 2.9-3.1% of the influent COD load. These values are relatively high but are within the typical range reported in literature [4]. Yet, emissions distribution within the plant is interesting. As seen in Figure 2, the highest contributors to methane emissions are the aeration tanks and primary clarifiers which combined contributed to almost 60% of total plant's methane emissions, whereas Digesters and gas burners contributed only 25% of such emissions. The low emissions from the digesters were confirmed by the handheld OGI camera which indicated no detected leakage either from covers or structural cracks. The high emissions from aeration tanks can be referred to several potential reasons. One possible reason can be unideal aeration and mixing, given that coarse bubble aeration is used to do both. This is supported by the low DO levels observed at the first quarter of the tank (below 0.5 mg/L). Another potential source is the centrate return after digesters which can contain high dissolved methane concentrations. Similar observation were reported in prior studies [7]. The high emissions from the primary clarifiers can be potentially explained by (i) high methane concentrations in the received influent, (ii) high TSS concentrations in the influent, (iii) the return of the TWAS and associated high sludge blankets in the primary sludge. The resulting total daily GHG emissions of the plant are estimated to be equivalent to 43.57 metric tonne of CO2. Interestingly, as shown in Figure 3, methane constituted more than 80% of the plant's emission. This is opposing the typical results in the literature where N2O contributes to more than 50% of plant's GHG emissions [3,8]. This is due to (i) compliance limits that do not mandate ammonia removal, (ii) operational decisions such as centrate return, operating at short sludge age washing out nitrifiers, TWAS return, and (iii) received influent that contained high dissolved methane concentrations and high TSS concentrations. Conclusion In conclusion, this study highlights how influent characteristics, operational patterns, and compliance limits can influence GHG emissions from wastewater treatment plant processes. Methane accounted for over 80% of the total emissions, contrasting with typical findings where Nâ‚‚O dominates. These findings emphasize the need for site-specific GHG monitoring and targeted mitigation strategies in wastewater treatment.