Optimization of Greenhouse Gas Accounting Methods for Wastewater Treatment Plants in East Chinese Regions: A Comparative Analysis of IPCC and Group Standards Based on 49 Plants in Shandong Province

Abstract

In order to achieve China’s carbon neutrality target by 2060, accurate carbon accounting for wastewater treatment plants (WWTPs) is imperative. This study takes Shandong Province as the research object, through large-scale empirical analysis, research method differences, and the annual operation data of 49 sewage treatment plants, for the first time to realize the systematic comparison of multiple methods on the provincial scale. The main findings show a 19.7% reduction in calculated emissions from Standard for Carbon Emission Reduction Assessment of Urban WWTPs (T/CUWA 50055-2023, GS 2023) compared to Intergovernmental Panel on Climate Change (IPCC 2019), thanks to its inclusion of CO₂ from fossil sources (5.0% of total emissions) and optimized CH₄/N₂O emission factors. Indirect emissions accounted for 56.8% of total emissions, with electricity consumption (43.3%) and chemical use (13.5%) being the main contributors. Carbon sources (27.6%) and phosphorus removal agents (15.2%) were the most important chemical-related emissions. The scale effect of indirect emissions is significant. It was found that there was a large difference in emission factors (such as a 236.9% difference in carbon source factors), and optimization strategies were proposed: preferentially using low-emission carbon sources (methanol reduced emissions by 77.6% compared with sodium acetate) and developing alternative carbon sources.

1. Introduction

Global warming, exacerbated by the rising concentrations of greenhouse gases (GHG) [1], has severely impacted natural ecosystems and the human living environment, becoming a significant challenge currently faced by all of humanity. The Paris Agreement, an international climate agreement adopted at the 21st United Nations Climate Change Conference in December 2015, aims to control greenhouse gas emissions and address climate change through global cooperation to keep the global average temperature increase within 2 °C above the pre-industrial level and strive to limit the increase to within 1.5 °C. We aim to peak global greenhouse gas emissions as soon as possible and achieve carbon neutrality in the second half of this century. Wastewater treatment plants (WWTPs) can reduce the concentration of water pollutants, improve water quality, and improve water ecosystems [2,3,4,5,6]. The president of the International Water Association emphasized that the carbon footprint originating from urban water supply systems and wastewater treatment facilities constitutes 3% to 8% of the world’s total carbon emissions [7]. China, as the economy with the highest total global carbon emissions over the past decade (contributing 28.8% of global carbon emissions from 2005 to 2020) [8,9], has seen explosive growth in its wastewater treatment industry, with an average annual growth rate in treatment capacity of 6.3% and a 217% increase in the number of WWTPs [10,11]. WWTPs have become a significant source of carbon emissions [12,13,14,15,16,17,18,19], with China’s WWTPs contributing 1–3% to the nation’s total carbon emissions [20,21,22]. Therefore, comprehensive collection of relevant basic data and precise quantification of carbon emissions and carbon emission intensity from WWTPs are essential for formulating pollution reduction and carbon emission reduction policies under the “dual carbon” goals. This study aims to construct an optimized accounting framework suitable for the regional characteristics of China by comparing the Intergovernmental Panel on Climate Change (IPCC) guidelines with domestic group standards.

2. Materials and Methods

2.1. Shandong Province’s WWTPs

Targeting Shandong Province as the research subject, this study selected the complete operational data of 49 wastewater treatment plants (WWTPs) in 15 prefecture-level cities for the year 2022. The total capacity of these plants is 2.214 million m³/d, accounting for 14.8% of the province’s total wastewater treatment capacity. The sample’s representativeness was confirmed using the Kolmogorov–Smirnov test (p-value greater than 0.05, indicating that the sample conforms to the overall distribution of the province). Basic information of the sample WWTPs (such as process type, design capacity, etc.) is detailed in Table S1. Influent and effluent water quality indicators, electricity consumption per ton of water, and sludge production are presented in Table S2, while chemical dosing information is provided in Table S3.

2.2. Data Sources

The data comes from 49 sewage treatment plants in 15 prefecture-level cities in Shandong province up to 2022. These data cover a range of key parameters, including the design capacity of the WWTPs, core treatment processes, number of operational days per year, average daily treated water volume, influent and effluent chemical oxygen demand (COD), biochemical oxygen demand (BOD), total nitrogen, electricity consumption for production, and the dosage and effective content of various chemicals (including coagulants, flocculants, disinfectants, and carbon sources). In addition, parameters such as the organic content in sludge, wet sludge production, and the water content of sludge were also collected.

2.3. Accounting Method

Greenhouse gas emissions from wastewater treatment plants (WWTPs) can be divided into two categories: direct and indirect. Direct emissions include dinitrogen monoxide (N₂O), methane (CH₄), and carbon dioxide (CO₂) produced during the treatment process, whereas indirect emissions arise from the carbon footprint linked to electricity usage, heating, and chemical consumption [23,24].

For the aforementioned emission sources, the main methods for the accounting of greenhouse gas emissions currently include the measurement method, the modeling method, the carbon footprint method, and the emission factor method, each with its applicable scope and limitations [25].

(1)

Measurement Method: This method obtains direct emission data through on-site air sampling and continuous monitoring, which offers high precision. However, it is limited by instrument sensitivity and maintenance costs, making it unsuitable to apply on a large scale.

(2)

Modeling Method: Based on biodynamic models that simulate microbial metabolic processes, this method can quantify the generation of GHG in specific processes. Nevertheless, the model parameters (such as nitrification/denitrification rates) require calibration with localized data, and the universality of this method is relatively poor.

(3)

Carbon Footprint Method: Using a life cycle assessment framework, this method accounts for both emissions throughout the entire process of WWTP construction, operation, and demolition. Although it can provide a basis for systemic emission reduction, it faces data availability issues during the construction phase, limiting its application scope.

(4)

Emission Factor Method: This method estimates carbon emissions by combining the activity level (such as electricity consumption) with the corresponding emission factor (such as CH₄/kgCOD). It has the advantages of being easy to operate and applicable to regional assessments and is widely used for provincial-scale evaluations. However, the regional heterogeneity of emission factors (such as differences in processes and management levels) may lead to calculation deviations, necessitating dynamic corrections with local data.

Currently, the greenhouse gas accounting system based on the emission factor method mainly includes the following three guiding documents:

(1)

IPCC 2019 Revised Edition: This is applicable for national-level carbon emission accounting. The accounting targets focus on the direct emissions of CO₂, CH₄, and N₂O.

(2)

Technical Specification for Low-Carbon Operation Evaluation of WWTPs (T/CAEPI 49-2022 [26]): This document is targeted at the operation stage of WWTPs. It can directly calculate the emissions of CH₄ and N₂O, along with indirect emissions like those from electricity and chemical consumption (calculated in CO₂ equivalents), providing a quantitative basis for low-carbon operation.

(3)

Standard for Carbon Emission Reduction Assessment of Urban WWTPs (T/CUWA 50055-2023) [27]: This document is based on a life cycle perspective, covering all stages from construction to operation and decommissioning. In addition to accounting for the emissions of fossil-derived CO₂, CH₄, and N₂O during the operation stage, it also integrates calculation methods for the emission reduction thanks to low-carbon technologies such as heat pumps, photovoltaic applications, and sludge anaerobic fermentation.

Provincial carbon emission management is a crucial link in mitigating global climate change. However, existing studies have rarely systematically compared the applicability of different accounting methods, especially empirical analyses based on the actual operational data of multiple plants over the past three years, which are still a blank area. As the third-largest economy in China (with a GDP of 921 billion yuan in 2023), Shandong Province has a sewage treatment scale of 14.931 million m³/d, and its carbon emission characteristics hold significant reference value for the entire country. Nevertheless, most existing literature focuses on theoretical models or single-case studies, lacking a provincial-scale systematic assessment based on actual production data. This research, based on the complete operational data of 49 WWTPs in Shandong Province for the year 2022, constructs a multi-method comparison framework using the IPCC 2019, GS 2022, and GS 2023 methods. It analyzes the differences in accounting and identifies key influencing factors (such as process type and scale effects), ultimately proposing an optimized carbon accounting path that matches regional characteristics to fill the dual gap in methodology and empirical research. The details of the accounting system for this study can be found in the Supplementary Materials.

The boundaries of this study’s accounting are confined to the internal operations of the wastewater treatment plant, covering processes such as preliminary treatment, biological treatment, advanced treatment, disinfection, and in-plant sludge dewatering. Off-site pipeline networks and the final disposal of sludge are excluded from the accounting scope. For specific details on the accounting boundary division, refer to

Table 1. Accounting boundaries and applicability of different accounting standards.

Accounting Items	IPCC 2019	GS 2022	GS 2023
Pretreatment	√	√	√
Biological Treatment	√	√	√
In-Plant Sludge Dewatering	√	√	√
Off-Site Pipeline Networks	×	×	×
Chemical Consumption	× (refer to GS 2023)	√	√
Biogenic CO2	×	×	×
Fossil-Derived CO2	×	×	√
Off-Site Sludge Disposal	×	×	×
Applicability	Internationally applicable	Operation phase	Full life cycle

Note: “√” indicates that this part of the accounting method is included in the method, while “×” indicates that this part of the accounting method is not included in the method.

. During the wastewater treatment process, CO₂ emissions are mainly generated from the oxidation and decomposition of organic matter. Based on their sources, CO₂ emissions can be classified into biogenic and fossil-derived categories. Since biogenic CO₂ has a negligible impact on global warming [28], this study only includes fossil-derived CO₂ in the accounting, and biogenic CO₂ is not counted.

In China, there is currently no unified national standard for carbon emission accounting in the sewage treatment industry. At present, relevant work is mainly guided by industry group standards. This study adopts the following standards and guidelines for the accounting of greenhouse gas emissions from WWTPs: the “Technical Specification for Low-Carbon Operation Evaluation of Sewage Treatment Plant” (GS 2022) released by the China Environmental Protection Industry Association on 6 June 2022and the “Carbon Emission Reduction Assessment Standard for Municipal Wastewater Treatment Plants” (T/CUWA 50055-2023) (GS 2023) released by the China Urban Water Association on 21 December 2023. Leveraging the three aforementioned methods, this research computed and contrasted the greenhouse gas emissions of 49 WWTPs located in Shandong Province. These emissions consist of the direct releases of CH₄, N₂O, and CO₂, along with the indirect emissions stemming from electricity utilization and chemical consumption. The specific accounting results are shown in Tables S4, S5, and S6, respectively.

To ensure the consistency of the accounting scope and results, this study has standardized the parameters for the calculation of indirect emissions as follows:

(1)

Electricity Consumption: All three accounting methods use the latest 2021 China electricity carbon dioxide emission factor published to calculate the indirect emissions related to electricity consumption, ensuring consistency in the accounting of indirect emissions from electricity use.

(2)

Chemical Consumption: T/CAEPI 49-2022 and T/CUWA 50055-2023 use the chemical emission factors provided in their respective appendices for calculation. Specifically, T/CAEPI 49-2022 uses Table S9, and T/CUWA 50055-2023 uses Table S4 in Supplementary Materials. Since IPCC 2019 does not provide accounting parameters related to chemicals, the method for calculating indirect emissions from chemical consumption uniformly adopts the chemical emission factor method from T/CUWA 50055-2023.

3. Results and Discussion

3.1. Direct Carbon Emissions Assessed by Three Different Methods

3.1.1. Comparison of N₂O Emission Calculations

The annual direct N₂O emissions from 49 WWTPs in 2022 calculated using the IPCC 2019, T/CAEPI 49-2022, and T/CUWA 50055-2023 methods were 601,287.0 kg, 468,870.9 kg, and 293,044.3 kg, respectively (Figure 1a). Among them, the N₂O emission calculated using the IPCC 2019 method was the highest, while that calculated using the T/CUWA 50055-2023 method was the lowest.

N₂O emissions from wastewater treatment plants (WWTPs) primarily stem from incomplete nitrification and denitrification during the biological removal of nitrogen [1]. This occurrence is closely linked to the concentration of total nitrogen in the effluent. The IPCC 2019 method only considers TN in the influent and does not take into account the amount of total nitrogen (TN) removed, resulting in an overestimated value. In contrast, T/CAEPI 49-2022 and T/CUWA 50055-2023 consider the TN removal, yielding more accurate results. The N₂O emission factors in T/CAEPI 49-2022 and T/CUWA 50055-2023 display a substantial disparity. The former is 0.016 kgN₂O-N/kgN, while the latter is 0.01 kgN₂O-N/kgN, causing the results of T/CUWA 50055-2023 to be significantly lower than those of T/CAEPI 49-2022.

Further calculations of N₂O emissions per unit mass of total nitrogen removed by different treatment processes using the IPCC 2019 method are shown in Figure 1b. The results indicate that the UCT process has the highest N₂O emissions per unit of total nitrogen removed, while the anaerobic-anoxic-oxic (AAO), anaerobic-oxic (AO), and oxidation ditch process (OD) processes have relatively lower emissions. This suggests that the choice of nitrogen removal process is crucial for controlling N₂O emissions. Although the IPCC 2019 method can reflect the differences in emissions among different processes, its overall tendency to overestimate N₂O emissions needs to be noted.

3.1.2. Comparison of CH₄ Emission Calculations Using Different Methods

The annual CH₄ emissions from 49 WWTPs in Shandong Province in 2022 were calculated using three methods, with the results being 1,082,451.6 kg, 113,716.9 kg, and 1,050,117.8 kg, respectively (Figure 2a). It can be seen that the results of the IPCC 2019 and T/CUWA 50055-2023 methods are very close, and both are nearly 10 times the result of the T/CAEPI 49-2022 method.

The differences in the CH₄ emission factor and correction factor values are the main reasons for the deviation of the results. In the IPCC method, the CH₄ emission factor is 0.6, and the correction factor is 0.03; in T/CAEPI 49-2022, the CH₄ correction factor is 0.003, and the CH₄ emission factor for the anaerobic process degrading unit COD is 0.25 kgCH₄/kgCOD. Its low correction factor results in a low CH₄ emission. In contrast, the CH₄ correction factors in the IPCC 2019 method and T/CUWA 50055-2023 are higher. T/CUWA 50055-2023 recommends a CH₄ emission factor of 0.004 to 0.0075 kgCH₄/kgCOD, and in this study, the value is taken as 0.00575 kgCH₄/kgCOD. It also considers the CH₄ emissions from the pump station and sand settling tank, which improves the accuracy of the calculation. Therefore, the result of T/CUWA 50055-2023 is close to that of IPCC 2019 but slightly lower.

There are flaws in the IPCC 2019 method for calculating methane emissions. The calculation method of its methane emission factor relies on restricted literature data. It fails to comprehensively take into account the BOD₅ removed in the form of sludge. As a consequence, there is a lack of consistency between the CH₄ emission factor and the emission calculation formula.

3.1.3. Calculation of Fossil-Derived CO₂ Emissions Using T/CUWA 50055-2023

In 2022, the fossil-derived CO₂ emissions of 49 WWTPs in Shandong Province were computed in accordance with the guidelines of T/CUWA 50055-2023. These emissions were composed of two primary components: carbon emissions from fossil-derived mineralization and fossil-derived CO₂ stemming from the mineralization of external carbon sources. The carbon emissions from fossil-derived mineralization attained 7046.44 tCO₂, with an emission intensity of 0.0114 kgCO₂/m³. The mineralization of external carbon sources resulted in carbon emissions of 6967.18 tCO₂, with an emission intensity of 0.0112 kgCO₂-eq per cubic meter. Overall, fossil-derived CO₂ emissions totaled 14,013.62 tCO₂, with an emission intensity of 0.0226 kgCO₂-eq per cubic meter. Although fossil-derived CO₂ accounted for only 5.0% of the total carbon emissions from WWTPs, its inclusion in carbon emission assessments is crucial. Therefore, it should be incorporated into the accounting framework. Research has indicated that the share of fossil-derived CO₂ emissions in Italian WWTPs varies between 16% and 26% [29].

Currently, the IPCC guidelines and T/CAEPI 49-2022 do not include fossil-derived CO₂ in their accounting. On the one hand, this is because the boundary between biogenic carbon and fossil carbon is blurred, and there is uncertainty in distinguishing between them during accounting. On the other hand, the existing accounting standards do not definitely stipulate whether to include fossil-derived CO₂, which may result in an underestimation of the carbon footprint of WWTPs and weaken the reference value of the accounting results for policy-making and the optimization of emission reduction measures.

In addition, the lower emission factors in T/CUWA 50055-2023 are more in line with the actual emission levels of N₂O and CH₄, and it also takes into account the emissions of fossil-derived CO₂. Although fixed emission factors cannot reflect the differences in emissions between different processes, the precision and applicability of the accounting can be improved by updating and refining the process emission factors. In addition, incorporating fossil-derived CO₂ enables a more all-encompassing evaluation of the TC emissions in WWTPs. It furnishes a scientific foundation for formulating carbon emission reduction policies and optimizing management strategies. As a result, this approach becomes the favored choice for current direct carbon emission accounting.

3.2. Indirect Carbon Emissions Assessed Using Three Different Methods

3.2.1. Comparison of Chemical Carbon Emission Calculation Results Using T/CAEPI 49-2022 and T/CUWA 50055-2023

The addition of chemical agents increases indirect carbon emissions [30,31,32]. In the process of wastewater treatment, phosphorus-removing agents need to be added for deep phosphorus removal, flocculants are required for sludge dewatering, disinfectants must be added before the treated water is discharged, and when the influent carbon source does not meet the denitrification requirements, carbon sources also need to be added. The carbon emissions generated during the production and use of chemicals are usually estimated by emission factors. However, due to the different emission factors used in different accounting systems, the results show notable discrepancies.

The chemical carbon emissions calculated using T/CAEPI 49-2022 were 42,651.58 tCO₂-eq, with a carbon emission intensity of 0.0688 kgCO₂-eq/m³, accounting for 15.32% of the total greenhouse gas emissions. In contrast, the chemical carbon emissions calculated using T/CUWA 50055-2023 were 37,862.65 tCO₂-eq, with a carbon emission intensity of 0.0611 kgCO₂-eq/m³, accounting for 13.51% of the total greenhouse gas emissions. There is a certain difference between the results obtained from these two sets of standards. The main reason is that T/CUWA 50055-2023 remodeled the chemicals based on the ecoinvent database according to the literature tracing of the wrong chemicals, reconstructed the chemical emission factors, and the recommended values are more in line with the actual situation, resulting in lower calculation results.

Upon further analysis, it was discovered that the carbon-emission contributions of diverse chemical types vary significantly. The dosages and carbon-emission contributions of chemicals in 49 wastewater treatment plants were categorized and tallied (For details, see Figure 3). The findings indicated that the chemical with the most substantial carbon-emission contribution was the carbon source, which accounted for 27.6%. Next was the phosphorus-removing agent, representing 15.2% of the TC emission contribution. The three chemicals with the highest carbon emissions were glucose, PAC, and sodium hypochlorite, among which the carbon emissions of glucose were nearly twice that of PAC. Due to the widespread problems of aging, damage, and misconnection in China’s sewage collection network, serious rainwater and sewage overflow pollution, and low sewage collection rate, the influent carbon/nitrogen ratio is generally insufficient, which significantly increases the dosage of carbon sources. Chenxi Pang [33] and others found in their study that the annual carbon emissions generated by the addition of sodium acetate in Gaobeidian WWTPs in Beijing accounted for 2.63% of the TC emissions of the plant. Among various carbon sources, the emission factor of sodium acetate is the highest (2.90), while that of methanol is the lowest (0.65), indicating significant differences in the impact of different carbon sources on carbon emissions. Therefore, it is recommended to prioritize the usage of carbon sources with lower emission factors (such as methanol or glucose), reduce the use of sodium acetate, or develop alternative carbon sources (such as high BOD wastewater, kitchen wastewater, etc.). A plausible alternative is the use of wastewater. Feng Hongbo [34] used tofu wastewater as a carbon source for a sewage plant with a scale of 20,000 m³/d and found that the carbon-substitution effect was significant. It reduced 337.9 tCO₂-eq, accounting for about 15.8% of the total emissions of the sewage plant, and saved 7–10% of the total operating costs. The carbon emissions of chemical phosphorus-removing agents should not be ignored. Optimizing the biological phosphorus-removing process is an available way to reduce the dosage of PAC. For example, by controlling the dissolved oxygen in the anaerobic section to create good phosphorus-releasing conditions for polyphosphate-accumulating organisms, the biological phosphorus-removing effect can be maximized, and the usage of chemical phosphorus-removing agents can be reduced.

The addition of chemicals has an important impact on the indirect carbon emissions of WWTPs and is an indispensable part of greenhouse gas accounting. Although the existing standards provide some reference values for the emission factors of chemicals, there is a lack of unified regulations at the global or national level, resulting in a lack of consistency in the results of different regions and accounting methods. This uncertainty is particularly prominent in the carbon emission accounting of WWTPs, especially because there are many types of chemicals and complex production processes. Selection of emission factors largely depends on data availability and local conditions. Although T/CUWA 50055-2023 has updated the chemical emission factors, it still does not cover all types of chemicals, such as sodium bisulfate, which ranked fourth in chemical carbon emissions in this study, liquid oxygen, a common disinfectant raw material, and ferrous sulfate, a common phosphorus-removing agent. At present, the accounting of chemical carbon emissions still relies on limited data sets and lacks detailed data to support the production process and use links of chemicals. In the future, it is particularly important to formulate a unified standard for chemical emission factors, especially for chemicals with high total carbon emissions, such as carbon sources and phosphorus-removing agents. Further refining the emission factors will help improve the accuracy and consistency of the results.

3.2.2. Carbon Emissions from the Energy Consumption of the 49 WWTPs

The annual carbon emissions from the electricity consumption of the 49 WWTPs amount to 121,371.72 tCO₂-eq/a, accounting for 41.6% (T/CAEPI 49-2022) and 43.3% (T/CUWA 50055-2023) of the TC emissions. The electricity-related carbon emission intensity is 0.196 kgCO₂-eq/m³. Reducing the electricity consumption of WWTPs is a direct and effective measure to decrease carbon emissions [35].

3.3. The Impact of Various Emission Intensities on the Total Emission Intensity

The SPSS software v23 was used to conduct a KW test, and a significance difference analysis of carbon emission intensity was performed on the N₂O, CH₄, chemicals, electricity, and the total greenhouse gas (Table S7). The carbon emission intensity of WWTPs is mainly affected by the indirect carbon emission intensity (r = 0.9724), with a very high correlation with the electricity carbon emission intensity (r = 0.9118) and a relatively low correlation with the direct carbon emission intensity. Reducing electricity consumption is a key way to control carbon emissions.

As shown in Figure 4, further statistics on the actual electricity consumption distribution of the 49 WWTPs in 2022 showed that the electricity consumption of the biological treatment process accounted for the highest proportion, 65.8%, followed by the influent lift pump system at 18.8%, the advanced treatment system (such as filter beds, high-efficiency sedimentation tanks, etc.) at 9.5%, and the sludge dewatering and disinfection system (such as UV, ozone) had the lowest electricity consumption. This indicates that the electricity consumption of WWTPs is concentrated in the biochemical treatment and lift pump system, which are the core sources of electricity-related carbon emission intensity.

To reduce the electricity consumption of WWTPs and lower the indirect carbon emission intensity, the operation and management can be optimized in the following aspects: improving the operational efficiency of influent lift pumps, optimizing equipment selection and operating parameters; optimizing the aeration system of the biological treatment process, such as using intelligent aeration or intermittent aeration; replacing inefficient equipment, such as replacing low-efficiency blowers with high-efficiency magnetic levitation blowers; and, for wastewater treatment plants with a low load rate, installing frequency converters on mixers and pushers.

3.4. The Impact of Different Influencing Factors on Carbon Emissions in Wastewater Treatment

Comparing the three carbon accounting methods, T/CUWA 50055-2023 has a more comprehensive calculation scope, considers more factors, and has a richer variety of chemical carbon emission factors, making it more suitable for the carbon emission accounting of Chinese WWTPs. The subsequent analysis adopts the calculation results of T/CUWA 50055-2023.

According to the calculation of T/CUWA 50055-2023, the total carbon emissions of 49 WWTPs in Shandong Province in 2022 were 280,308.040 tCO₂-eq/a, of which the direct emissions were 121,073.7 tCO₂-eq/a, accounting for 43.2%. The indirect emissions were 159,234.4 tCO₂-eq/a, accounting for 56.8%, with an emission intensity of 0.452 kgCO₂-eq/m³. This intensity is higher than that of Shenzhen [36] (0.30 kgCO₂-eq/m³) and Shanghai [21] (0.29 kgCO₂-eq/m³), indicating that there is still room for optimization in terms of process level, energy consumption, and management of WWTPs in Shandong Province. The differences in the accounting results are also related to some factors, including the level of regional economic development, the scale of WWTPs, and the quality of influent water [37].

Due to the differences in production conditions, technical levels, and process flows of WWTPs, the selection of emission factors may lead to uncertainties in the estimation results. WWTPs can obtain more accurate CH₄ and N₂O emission factors through actual measurement or model simulation to improve the accuracy of the accounting.

3.4.1. The Impact of Treatment Processes on Carbon Emissions

A depiction was conducted on the total carbon emissions and emission intensity of different processes in 49 wastewater treatment plants in Shandong Province in 2022 (Figure 5). The AAO process contributes the most to carbon emissions. Among the 49 wastewater treatment plants, 36 adopted the AAO process, but the average emission intensity of the AAO process was 0.425 kgCO₂-eq/m³, which was lower than that of other processes. The emission intensity of the oxidation ditch process was the highest, boasting an average value of 0.697 kgCO₂-eq/m³. This figure was markedly greater than that of the AAO process and nearly approached the 0.79 kgCO₂-eq/m³ value reported for the MBR process in Shenzhen’s WWTPs [36]. The higher carbon emissions from the oxidation ditch process are attributed to the lack of a clear boundary between the aerobic and anoxic zones within the oxidation ditch and the fact that the oxidation ditch operates in a completely mixed flow pattern. The anoxic conditions required for denitrification are not sufficient, leading to incomplete denitrification and the production of more N₂O. Additionally, poor control of anaerobic conditions may affect the phosphorus-releasing effect of polyphosphate-accumulating organisms, increasing the dosage of phosphorus-removing agents.

3.4.2. The Influence of Scale upon Carbon Emissions

Figure 6 presents the carbon emission intensity of wastewater treatment plants at various scales. Among wastewater treatment plants of different scales, no substantial difference was observed in direct emission intensity. In contrast, the indirect emission intensity steadily declined as the scale increased, which was in line with the research findings of Cardoso et al. [38,39,40]. The results showed that the emission intensity of small-scale WWTPs with a scale of ≤20 km³/d was the highest, at 0.467 kgCO₂-eq/m³. The main reason was the low equipment efficiency and high indirect emissions. The electricity-related carbon emission intensity was 0.258 kgCO₂-eq/m³, which was higher than the average electricity intensity of the 49 WWTPs (0.196 kgCO₂-eq/m³), revealing that there was significant room for energy efficiency optimization in other small-scale WWTPs and the facilities. The carbon emission intensity of large-scale WWTPs with a scale of ≥100 km³/d was relatively high (0.499 kgCO₂-eq/m³). The main reason was that the influent COD and TN concentrations of some large plants were significantly higher than the average values.

3.4.3. The Impact of Influent Load Rate on Carbon Emissions

Figure 7 depicts the carbon emission intensity of wastewater treatment plants having different load rates. The findings indicate that as the influent load rate rises, the emission intensity gradually diminishes. The emission intensity of WWTPs with a load rate of ≤60% stands at 0.640 kgCO₂-eq/m³. In contrast, the emission intensity of WWTPs with a load rate exceeding 100% is the lowest [39], at 0.390 kgCO₂-eq/m³. It is analyzed that high-load operation can improve equipment utilization efficiency and reduce the energy consumption and chemical dosage required per unit of treated water. At low load rates, the treatment equipment and facilities also need to be fully operational, and the number of equipment started is almost the same as that at high load, resulting in low operational efficiency and high electricity consumption per ton of water treated.

3.4.4. The Impact of Influent Water Quality and Emission Standards on Carbon Emissions

No notable correlation was found between the influent COD and TN and the indirect carbon emission intensity. However, a significant positive relationship was observed with the direct emission intensity. At lower influent COD and TN levels, the direct emission intensity remained relatively low. On the contrary, as influent COD and TN increased, so did the direct emission intensity. A higher influent COD supplied more degradable organic matter, favoring methane production, while a higher TN led to increased N₂O emissions during nitrification and denitrification processes, both contributing to the rise in direct emission intensity. When the influent COD was below 100 mg/L and TN was 20–30 mg/L, the total emission intensity was the lowest. Appropriately controlling the influent water quality can effectively reduce the direct emission intensity, but the impact of increased carbon sources needs to be considered.

Statistics regarding the influent water quality of the 49 WWTPs revealed that the average value of COD stood at 217.3 mg/L. The average BOD was 78.5 mg/L, and the average TN measured 34.95 mg/L. The BOD/TN ratio was calculated as 2.25, falling below the minimum of 3.0, which is essential for the denitrification process. Due to the insufficient carbon source, 43 out of the 49 WWTPs needed to add carbon sources, accounting for as high as 87.8%, which significantly increased the chemical carbon emission intensity. In addition, the stricter the emission standard, the higher the indirect emission intensity (Figure 8). This trend was consistent with the research conclusion of Jiemiao Ma and others [15,21,41,42]. It was analyzed that the strict emission standards required wastewater treatment plants to reduce the effluent COD, BOD, and ammonia nitrogen concentrations, which not only required higher aeration volumes and more chemicals but also increased the amount of sludge produced and the consumption of electricity.

4. Conclusions

This study constructed the first provincial-level multi-standard carbon emission assessment framework for WWTPs in China. By systematically comparing the IPCC 2019, T/CAEPI 49-2022, and T/CUWA 50055-2023 accounting methods, and based on the actual operation data of 49 WWTPs in Shandong Province for the whole year of 2022, the study revealed the differential impacts of different accounting systems on greenhouse gas assessment results and proposed carbon accounting optimization strategies suitable for the Chinese sewage treatment industry.

(1)

Methodological innovation and standard adaptability

The study constructed the first provincial-level multi-dimensional accounting framework that integrates international guidelines with domestic standards, breaking through the spatial applicability limitations of traditional single-method approaches. It was found that T/CUWA 50055-2023, by including fossil-derived CO₂ (contributing 5.0%) and optimizing emission factors (CH₄: 0.00575 kg/kgCOD, N₂O: 0.01 kg/kgN, with CH₄ and N₂O emission factors reduced by 23.3% and 37.5%, respectively), resulted in a 19.6% decrease in calculated emissions compared to IPCC 2019 (Δ = 68,576 tCO₂-eq, p = 0.002 < 0.01), making it more in line with the actual operating characteristics of Chinese WWTPs. It is recommended to prioritize the use of the T/CUWA 50055-2023 method. This study achieved dynamic traceability analysis of chemical carbon emission factors, quantifying the emission contribution differences in key chemicals such as glucose (3.1% of total emissions), PAC (1.6%), and sodium hypochlorite (1.3%), revealing the shortcomings of the chemical emission factor database in existing standards.

(2)

Key emission characteristics and driving mechanisms

Indirect emissions dominated the total greenhouse gas emissions (56.8%), with electricity consumption (43.3%) and chemical consumption (13.5%) being the core sources of contribution. Carbon sources (27.6% of chemical emissions) and phosphorus-removing agents (15.2%) constituted the main targets for emission reduction. Using low-emission-factor carbon sources (such as replacing sodium acetate with methanol) could reduce carbon emissions by 77.6%.

The scale effect showed a non-linear characteristic: small-scale plants with a capacity of ≤20,000 m³/d, due to low equipment efficiency, had an indirect emission intensity (0.258 kgCO₂-eq/m³) that was 23.4% higher than the average carbon emission intensity of the 49 WWTPs. Large-scale plants with a capacity of ≥100,000 m³/d, on the other hand, did not show a scale effect due to fluctuations in influent load. Based on marginal abatement cost analysis, replacing sodium acetate with methanol could reduce carbon-source-related emissions by 77.6% (Δ = 2.25 kgCO₂-eq/kg carbon source). It is recommended to formulate the “Technical Guidelines for the Selection of Low-Carbon Chemicals” and accompany it with carbon-credit incentive policies.

This study provided a theoretical basis and practical paradigm for establishing a precise carbon accounting system for the Chinese WWTPs and has important reference value for promoting the green transformation of the industry under the “dual-carbon” goals.