Beyond One-Size-Fits-All: How Operational Patterns and Compliance Limits Shape Fugitive GHG Emission Variability in Wastewater Treatment Plants

Introduction:
Amid the accelerating impacts of climate change, the urgent need to mitigate greenhouse gas (GHG) emissions is more critical than ever, yielding commitments from developed countries aimed at achieving net-zero emissions by 2050. Wastewater treatment plants (WWTPs), a major source of direct emissions, contributes approximately 5% of global non-CO2 GHG emissions, largely in the form of methane (CH4) and nitrous oxide (N2O)[1]. Thus, there has been growing academic and industrial interest in the quantification of the direct, or Scope 1, emissions from WWTPs [2]. The standard method for estimating GHG emissions relies on the current 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]. To better quantify GHG emissions, prior studies have focused on investigating GHG emissions in relation to adopted technologies, received wastewater flows, and/or treatment level [4,5].

Therefore, the current study leverages a multi-level GHG quantification framework to demonstrate how operational patterns, compliance limits, and influent characteristics not only influence the total emissions but also their profile and distribution within the plant. This work is part of an ongoing NSERC project monitoring GHG emissions from Canadian WWTPs in which a multi-level approach is utilized combining various advanced measurement techniques, including gas/liquid sensors, optical gas imaging (OGI), drone-based sensing, aircraft imaging, and satellite imaging.

Methods:
The Canadian wastewater treatment plant featured in this study operates with a typical activated sludge treatment configuration. To monitor nitrous oxide, two Unisense® sensors were strategically installed to capture possible variation across the aeration tank. Methane (CH4) emissions were quantified using 16 ground-based sensors, complemented by a 3-day intensive measurement campaign employing drone-based and OGI techniques.

Results and discussion:
For over six months, liquid N2O concentrations were monitored at two locations in the aeration basin. The system typically is operated as a step-feed, with primary effluent entering the bioreactor through eight gates distributed along the aeration tank and regulated via gate openings. During the study, the reactor was tested under various modes; for example, Figure 1 shows the N2O emissions during typical operation with standard gate settings. Median daily N2O emissions were recorded at only 2.91 KgN-N2O/day, with occasional spikes exceeding 10 KgN-N2O/day. This corresponds to an N2O emission factor (EF) of 0.005 ± 0.0012 kg N2</Sub>O-N per kg TN, significantly lower than the IPCC EF of 0.016 kg N2O-N per kg TN [6]. This reduced EF can be attributed to the plant's compliance limits, which do not require nitrogen removal. Accordingly, the reactor operated near nitrifier washout conditions, with an average SRT of 3.4 days and median ammonia removal of less than 25% (Figure 1). It is worth noting that while non-BNR activated sludge systems typically exhibit higher emissions [5], the lower emissions observed in this plant can be attributed to operation at a washout SRT.

The average methane emissions from the plant were quantified at 1385 ± 871 kgCH4/day. This corresponds to 3.9—4.4 gCH4/m3 of treated wastewater and 3.2—3.5% of the influent COD load. These values are relatively high but fall within the typical range reported in the literature [4]. The distribution of methane emissions across the plant revealed unexpected insights. As shown in Figure 2, the aeration tanks and primary clarifiers were the largest contributors, accounting for approximately 60% of the total methane emissions. In contrast, digesters and gas burners combined contributed only 25%. The use of a handheld OGI camera proved instrumental in diagnosing emission sources and quantifying emissions from locations where drone-based measurements were unreliable due to adverse wind conditions. The handheld camera confirmed low emissions from the digesters, with no detectable leaks from covers or structural cracks. However, leaks detected in the dewatering building contributed approximately 6% of the plant's total methane emissions.

The resulting total daily GHG emissions of the plant are estimated to be equivalent to 47.727 metric tonnes of CO2. Interestingly, as shown in Figure 3, methane constituted more than 80% of the plant's emissions. This finding contrasts with typical literature reports, where N2O often accounts for more than 50% of plant GHG emissions [3,7]. This divergence can be attributed to (i) compliance limits that do not require ammonia removal, (ii) operational practices such as TWAS return and operation at a short sludge age, which promotes nitrifier washout, and (iii) the received influent, which contained elevated dissolved methane and high TSS concentrations.

Conclusion:
This study demonstrates how influent characteristics, operational patterns, and compliance limits shape GHG emissions in WWTPs. Methane contributed over 80% of total emissions, with aeration tanks and primary clarifiers identified as major sources-contrasting with typical findings where N2O predominates. These results highlight the importance of site-specific GHG monitoring and tailored mitigation strategies for effective emissions reduction in wastewater treatment.