With the growing environmental awareness of society, the implementation of environmentally friendly alternatives and thoughtful strategies is no longer a choice, but a necessity. Evaluating everyday activities has become a must. This is particularly relevant when discussing water resources management [1]. Wastewater treatment plants play an essential role in municipalities as they facilitate water reuse and recycling. Overall, they help maintain a safe level of pollutants released into the environment. However, like every industrial plant, they require energy and chemical compounds to operate and inevitably release emission into the atmosphere [2].

Even though the treatment technology principle of the Wastewater Treatment Plant (WWTP) has been known for more than 50 years, recent advances in instrumentation, chemical analysis, and online monitoring are paving new path for research and process optimisation [3]. However, these improvements are far from straightforward; the complex and variable nature of the incoming water makes wastewater treatment plants challenging subjects of study [4]. Influent characteristics may change depending on the season, human activities, and population growth. Moreover, understanding of the water-energy nexus in the traditionally compartmentalised wastewater treatment industry is key to developing an efficient, cost-effective and sustainable process [5].

Technological advancements are leading to the implementation of on-line monitoring and control systems in the wastewater treatment industry. Nowadays, integrated systems allow for overcoming traditional static water management by not only providing real-time monitoring and control but also by storing data that can be further utilised for network-wide distribution and create new variables correlations [6]. Certainly, the connection of devices into the network needs to be backed up by a system that can be manually operated and complemented with offline samplings to guarantee performance and avoid disruptions in the operation of the wastewater treatment plant, all while maintaining the compliance with pollutant levels contained in the water prior to releasing it into the environment [4]. Therefore, the availability of this data smoothens plant operation by facilitating the decision-making thanks to the integration of the traditional water quality standards (total solids, total nutrients, pH, oil products, particle size, metal concentration) with key process parameters (mass balance, mixing, residence time, energy demands) [6], and addresses new monitoring needs such as multidirectional communication between sensors and continuous retrofit [7]. Additionally, more sophisticated analytical methods and new concerns are paving the way for integrating new water quality variables based on the control of emerging pollutants such as phthalates, Bisphenol A, and pharmaceuticals [8].

While chemical treatments are beginning to be replaced by membrane technology, the chemical segment of the global wastewater treatment industry accounted for $46.2 billion in 2022 [9]. Chemical treatment processes are divided into chemical precipitation, neutralisation, adsorption, disinfection and ion exchange [10]. In this context, pH neutralisers, anti-foaming agents, coagulant and flocculants are the main types of chemicals used in the wastewater treatment process [11]. pH neutralisation is added to the process to prevent undesirable chemical reactions that can occur due to the mixing between the wastewater effluent and other sub-process streams [11]. Neutralisation is particularly important to meet the regulatory specification of water discharge into lakes or rivers [12]. Anti-foaming agents, on the other hand, can be seen as process adjuvant since their presence maintains operational efficiency and reduces process costs by limiting deposits inside storage tanks and processing vessels. In this way, bacterial growth is limited while ensuring worker safety [13]. This study shifts its focus to the examination of chemicals that intervene in the coagulation/flocculation process and affect the separation process between the suspended particles and water.

Coagulation, the first step of the process, involves colloidal destabilisation, followed by the initiation of flocculation when destabilised particles begin to propagate and agglomerate. The mechanisms of destabilisation are related to the nature of the coagulant employed [14]. This article does not cover the optimisation of coagulant amount. Instead, it focuses on the screening of cationic polymers used in the flocculation process. The wastewater treatment plant chosen for evaluated the proposed methodologies, adds ferrous sulphate for secondary clarification at a rate of 30 g/m³. All the samples studied contained this concentration of coagulant before conducting the flocculation studies. It is well known that in presence of cationic polymer, particle destabilisation is achieved by the charge neutralisation mechanism, but interparticle bridging also plays a significant role. In simple terms, flocculation by polymer bridging occurs when the active polymer attaches to a free surface particle. When the particles attach, the distance between them reduces, thereby increasing the frequency of collision. Therefore, in the presence of higher concentration of “active” particles the probabilities of creating these bonds increases [15].

Polyacrylamides (PAM) are commonly employed in water treatment processes. Despite their widespread use, there is not an established standard method to determine their traces in water [16]. Detection of polyacrylamides in solution requires complex sample preparation to ensure detection levels, and in some cases, reproducibility cannot be ensured. So far, the incorporation of a fluorescence marker appears to be the most suitable technique to ensure accuracy and reproducibility by adding a fluorescence tag, the ions coming from the functional groups of the polymer will be selectively enhanced, and detection can be achieved. For example, in patent US6514617B1 [17] a tagging material obtained from the combination of one fluorophore dye and one semi-conducting luminesce nanoparticle allows the identification of polymer via spectrofluorometer. A similar approach to detect and control the dosage of polymers was proposed in the patent US20010018503A1 [18], where the fluorescence tag is derived from a water-in-oil emulsion tag that is later incorporated into the polymer. Swift et al. [19] proposed the use of interpolymer complexation to monitor the polymer concentration of PAM. The advantage of this method is that interpolymer complexation can be easily achieved by mixing polymers. The inter-polymerisation occurs thanks to the structure similarity between the PAM and the polymer complex; in this case, poly (acrylic acid-co-acenaphthylene). It is also possible that the required amounts of the fluorescence tag to be added are low, which directly implies an economically viable alternative. According to the guidelines for drinking-water quality [20], the maximum polyacrylamide concentration in water is 1 mg/L, while the monomer concentration should not exceed 0.5 µg/L (i.e., 0.05% of the monomer content of residual monomer in polymer). To summarize, avoiding excessive amounts of polymer constitutes the most efficient alternative to limit the potential detrimental effect that the degradation of this polymer can have on the environment. The optimisation of the concentration of polyacrylamides was one of the drivers of the current study.

Recognising the critical relationship between water and energy is key to achieving sustainable resource management [5]. Wastewater treatment is a highly energy-consuming process [21] to propose cost reduction by more efficiently controlling electricity demands. The optimisation of these demands needs to ensure continuous operation by guaranteeing process performance [22]. In this context, the use of Energy Storage Systems (EES) has been recognised as an viable option to provide an optimal balance between energy supply and demand, while improving net carbon emissions [23]. In practice, the role of the EES is to store energy and use it whenever and wherever needed [23]. For instance, when the energy supply exceeds demand, it can be beneficial to store the energy and then utilize that energy when the scenario is reversed [23]. This approach can help eradicate problems associated with peak load and other power supply disturbances [23]. Clearly, storage systems allow for integration and flexible handling of market demands. The suitability of a specific storage system involves evaluating several factors, such as application type, application period, maintainability demands, reduction of the performance after charge-discharge cycles, efficiency and capital cost [24]. Another important factor when implementing a sustainable approach is to include the circularity approach. Therefore, the decommissioning and removal of chemicals contained in the batteries is playing a crucial role in technology selection [25] the need for new recycling approaches is currently experiencing significant development [26].

Given the importance of integrating chemical and energy approaches to optimize the operation of the wastewater treatment plant, this study identifies a significant gap in the current practices. The primary objective is to explore alternatives that enable the implementation of a more cost-efficient water treatment process. This exploration is grounded in a real-world case study: a wastewater treatment plant located in Turku, Finland. The detrimental effects of excessive polymer presence in the ecosystem and the high energy consumption of a water treatment plant are key considerations.

The first part of this study is dedicated to reducing the amount of polymer used in the secondary clarification step. This is achieved by enhancing the understanding of the impact of the flocculant and residence time on the kinetic profiles of the secondary clarification unit. The second part of this study evaluates the potential for cost reduction and operational flexibility that can be achieved by implementing an energy storage system. Specifically, the installation of a grid-scale battery is proposed. This guarantees the continuous operation of the plant by capitalising on fluctuating electricity prices in the market.

In essence, this study introduces two novel approaches aimed at optimising the operation of wastewater treatment plants. The first approach focuses on determining the optimal amount of polymer required for plant operation. This is achieved by monitoring parameters such as zeta potential, particle size evolution, turbidity, and metal ion concentration using Inductively Coupled Plasma Optical Emission Spectroscopy (ICP-OES). The goal is to ensure the expected safety and quality attributes of the treated water. The second approach proposes the use of a grid-scale battery to reduce electricity costs associated with plant operation. This method not only guarantees the continuous operation of the plant but also significantly reduces energy costs. These methodologies, when implemented, could lead to more efficient and cost-effective wastewater treatment processes. The following sections provide a detailed discussion of these approaches and their potential impact on wastewater treatment.

Figure 7a illustrates the influence of time on the evolution of the peak thickness after addition of the polymer solution at different concentrations, obtained from the sample “20/02/2023”: In contrast, Figure 7b displays the time evolution of the peak thickness for the different data set. As observed, the peak thickness of the water sample collected on 20/02/2023 differs by several orders of magnitude compared to the other two data sets. Nevertheless, the stability plateau of the analysed samples (with and without polymer addition) is typically achieved after 100 seconds of analysis.

Figure 7.

Time evolution of the peak thickness: a) obtained at different polymer concentration for the sample “20/02/2023” (a); of the raw water collected at different dates (b)

Therefore, to comprehend the influence of the polymer concentration on the speed of the flocculation, the variation of the peak thickness as a function of time for the initial times was calculated (Figure 8). Integrating the information shown in Figure 7b and Figure 8, the lowest particle migration rate of the sample set corresponds to about 10 mm of peak thickness, which can be achieved at 0.861 mg/mL of polymer. Conversely, the sample set that exhibits a peak thickness stability plateau at 64 mm required 1.322 mg/mL of polymer. Considering this last particle migration rate, less than 0.1 mm/s can be attained using only 0.114 mg/mL of polymer for the data set with initial low peak thickness. Based on the general characteristics of the water samples (Table 1), the only difference between those samples is the inflow volume. The inflow volume of the sample “20/02/2023” was 62% lower compared to the other two samples. Moreover, when examining the weather conditions on those days [34], it can be observed that the increasing of the inflow volume was due to rain, as shown in Figure 9 (9a represents 30/01/2023 and 9b stands for 20/02/2023). In theory, due to the rain the input water was cleaner, and this justifies why for the samples of 30/01/2023 and 25/01/2023 (gray and blue respectively in Figure 7b) less amount of polymer is required than for 20/02/2023, even if the initial suspended particles concentration is similar.

Figure 8.

Evolution of the particle migration during the initial times of sedimentation as a function of the polymer concentration, obtained from different raw water samples

Figure 9.

Past weather in Turku, Finland during two days when samples were collected: 30/01/2023 (a) and 20/02/2023 (b) [34]

Figure 10 depicts the evolution of the zeta potential as a function of the polymer concentration for the different data sets. It is noteworthy that the zeta potential reaches the isoelectric point at similar concentration of polymer, regardless of the data set studied. Flocculation between the impurities and the polymer particles can be initiated by one or simultaneous mechanisms, namely charge neutralisation, polymer bridging, and polymer-particle surface complex formation [35]. At lower concentration of polymer in the solution (up to 0.114 mg/mL), the dominant mechanism is the charge neutralisation, given the available cationic charges provided by the block structure of the polymer are high and sufficient to achieve the neutralisation of the negative charges of the wastewater. Subsequently, as the zeta potential value increases, impurities-polymer particles reach a new stabilisation stage and polymer bridging becomes the dominant mechanism.

Figure 10.

Evolution of the zeta potential as a function of the polymer concentration obtained from different raw water samples

Figure 11a presents the evolution of the particle size represented in terms of size class and frequency volume compatibility, while Figure 11b displays the measured particle sizes. As observed, the evolution of the particle size progresses in a stepwise manner. In the absence of flocculant, the mean particle size is 190 µm.

Figure 11.

Evolution of the size classes (a) and particle size as a function of the polymer concentration (b)

When the concentration of polymer is around 0.114 mg/mL, two populations of mean particle size of 210 µm and 1630 µm can be identified. After 0.364 mg/mL, one population with a mean particle size of 450 µm dominates until the concentration is increased to 1.321 mg/mL, achieving particle size higher than 760 µm. Correlating this data with the zeta potential, insights about the stability of the system can be gained. It can therefore be stated that for concentration below 0.114 mg/mL, the system is in transition, evidenced by the zeta potential close to 0 mV and by the presence of two populations. Then, after increasing the concentration up to 0.364 mg/mL, the system attains another stability state by reaching zeta potential values of about 10 mV. The maximum stability occurs around 0.861 mg/mL, which appears to be the best concentration for promoting the flocculation mechanism. At this point, the flocs are large enough to promote the phase separation in the clarification unit and stable enough to be processed.

Undoubtedly, the kinetic of sedimentation needs to be understood by considering the contribution of one population at a time. In this sense, one population will record a specific sedimentation speed and its general contribution to the total sedimentation of the system will depend on the concentration of the suspended impurities particles and how they interact with the polymer particles. Figure 12 demonstrates the impact of the storage time on the kinetics of sedimentation. In absence of agitation, the aggregates are partially sedimented and even if the impurities particles are not “strongly” attached among them, the polymer bridging mechanism is favoured under those conditions. Therefore, a lower polymer concentration is required to achieve optimal flocculation conditions. As expected, the residence time and turbulence are key parameters on the flocculation formation mechanism. Nevertheless, increasing the residence time implies not only a reduction of the production time, but also a surplus in the inflow volume, increasing the risk of overload. Adapting the system’s residence time at a slower pace during low-inflow periods can therefore further reduce the need for polymer use and may slightly reduce electricity consumption in pumps by demanding lower internal flow.

Figure 12.

Influence of storage time on the evolution of the peak thickness obtained at the same initial polymer concentration

Up this point and in agreement with the literature [36], the predominant mechanisms of the flocculation of the wastewater using cationic polyacrylamide are the charge neutralisation and the interaction between polymer and impurities via polymer bridging. Based on the two minimum found in the flocculation rate, charge neutralisation takes place at concentration around 0.114 mg/mL, while the polymer bridging takes place at 1.321 mg/mL. Indeed, the system is evolving, therefore re-conformation process is continuously occurring, so the competition between the mechanism can be dependent on the particle size, nature, and even related to the storage of the sample.

Figure 13 demonstrates the influence of the concentration of polymer on the ion’s removal. For this study, the concentration of phosphorus, sodium and sulphur were measured. The concentration of phosphorus, nitrogen and sulphur [36] are of interest due to the potential eutrophication effect that the chemical modification [37] of those ions can have on the environment [38]. Here, notable differences were observed in the phosphorus concentration, and as illustrated in Figure 13, 0.030 mg/mL of polymer is sufficient to lower the concentration of phosphorus from 5.525 mg/mL to 0.308 mg/mL. The initial sulphur charge was already under the detection limit of the ICP-OES measurement, i.e., 3 mg/100 g; and the concentration of sodium varied between 2.0 mg/100 g and 1.2 mg/100 g. Given that a portion of this study was conducted during wintertime and cities tend to use road salt to prevent the road icing, information about the concentration of sodium is also valuable. In fact, a higher concentration of sodium might affect not only on the permeability of the soils, but also the reduction of oxygen content in the receiving waterbody [7].

Figure 13.

Evolution of the contaminant’s concentration in presence of polymer.

From the battery’s perspective, the total capital investment (CAPEX) required for the battery’s installation is 169 million € over an expected operational lifetime of 20 years. This figure takes into account a 2% interest rate, a 1.1 USD/€ exchange rate, and battery costs as projected for 2025 from [39]. The lifetime benefit of operating the battery (considering 2022 for electricity market price variations) for Scenario 1 is estimated at 106.9 million € in energy savings, while for Scenario 2, the calculation yields 73.8 million € in revenue from electricity sales. Thus, under the current assumptions, the battery is not a profitable venture, as the benefits in both cases fall below the investment level. However, the battery offers additional benefits that are not economically measurable, such as system resiliency and back up, as well as grid stability. Moreover, several of the assumed factors used for the economic calculations are susceptible to variations that could make the battery profitable, such as different battery technology, different interest rates, an accelerated technology learning curve, and specifically for Scenario 2, a lower fixed-price agreement. The results of the financial calculations are presented in Table 2.

As shown in Table 2, and under the presented assumptions, different benefits are obtained from the battery operation modes as described in Scenarios 1 and 2. Although the battery dimensions, and thus investment, are equal for Scenario 1 and 2, the benefits manifest in different forms and at different values. For Scenario 1, there is no trade of electricity back to the grid, so the entirety of the benefit comprises electricity cost savings when comparing the electricity paid to the hourly electricity market price that would otherwise be paid. In contrast, Scenario 2 yields in the form of revenue, by selling electricity back to the grid at the times where profit could be made, as the difference between the fixed price and market electricity price. Since the capital investment of 169 M€ is higher than the benefits that could be obtained by either scenario, the installation of such a system is not economically viable but it can be justified in the current international context that Finland is facing.

Recognising the critical relationship between water and energy is key to achieving sustainable resource management. Wastewater treatment, being a highly energy-consuming process, offers a significant opportunity for optimisation. This study identifies a significant gap in the current practices, despite the well-established nature of typical wastewater treatment processes that have been in use for decades. Even the most state-of-the-art facilities present potential for improvement. This study introduces two innovative approaches aimed at optimising the operation of wastewater treatment plants. These approaches are applied to a real-world case study: a wastewater treatment plant in Turku, Finland.

The first strategy is centred on the optimisation of polymer usage during the secondary clarification phase. Implementation of this methodology could potentially lead to an enhancement in the efficiency of wastewater treatment processes. The second strategy proposes the incorporation of a grid-scale battery to mitigate electricity costs. This approach not only ensures uninterrupted operation of the plant but also significantly curtails energy expenditures. Collectively, these strategies contribute to the advancement of operational efficiency and cost-effectiveness in wastewater treatment plants.

Optimising the use of polymer in wastewater treatment is a multifaceted process. To comprehend the primary mechanisms influencing the flocculation of impurities using polymer, it is advantageous to combine zeta potential measurement with particle migration using turbidity measurements. The optimal amount of polymer can then be modulated based on various factors. A key finding of this study is that a polymer concentration of merely 0.030 mg/mL can significantly reduce the phosphorus concentration from 5.525 mg/mL to 0.308 mg/mL. This reduction plays a crucial role in mitigating the potential eutrophication effect on the environment.

The choice of flocculation mechanism − charge neutralisation using high cationic polymer or polymer bridging using a long chain polymer − depends on the specific objective. Charge neutralisation is preferred when the goal is to reduce polymer concentration, while polymer bridging is favoured for achieving larger and more stable flocs. Factors such as mixing, and shear can influence the competition between these mechanisms by altering particle collision. The storage time also plays a significant role in the kinetics of sedimentation and flocculation formation. By adapting the system’s residence time at a slower pace during low-inflow periods, the need for polymer use can be further reduced. This adaptation may also slightly decrease electricity consumption in pumps by demanding lower internal flow.

The proposed grid-scale battery system, while not presenting an economic benefit under the current assumptions analysed, offers additional benefits beyond those of an economic nature. For instance, the presence of a grid-scale battery at the WWTP facility ensures uninterrupted operation of the plant during extended periods of power disruptions. Depending on the battery’s lifetime point, the Depth of Discharge (DoD) allowed in the event of an extended power interruption, and the current state of charge, the battery could power the WWTP for over 30 hours on a full charge. If non-essential systems are further disconnected (e.g., the geothermal heat pump), the battery could power the WWTP for over 7 days, maintaining its essential operation even in cases of extended power outages.

Although power outages are extremely rare in the region where the WWTP is located, the potential need for backup power could be justified in the current international context. Up until February of 2022, Finland, along with several other EU countries, had a significant energy dependency to Russia, a dependency that was bilaterally severed shortly after the invasion of Ukraine. In the following year, preparation notices for potential power outages became common in Finland, and electricity prices soared. Therefore, the consideration of backup systems for infrastructure services has now become pertinent.

In conclusion, this study underscores the potential for significant advancements in wastewater treatment processes. By optimising the use of polymer in the secondary clarification step and proposing the use of a grid-scale battery to reduce electricity costs, it has been introduced innovative approaches that could lead to more efficient and cost-effective operations. While these strategies may not present immediate economic benefits under current assumptions, they offer additional advantages such as ensuring uninterrupted operation of the plant during power disruptions and contributing to system resiliency and grid stability. Furthermore, the study highlights the importance of considering external factors such as geopolitical context and weather conditions in operational decision-making. As the field continues to evolve, further research is warranted to explore other potential areas of optimisation and to validate these findings in other real-world contexts. Ultimately, the goal is to contribute to sustainable resource management and to the resilience of wastewater treatment infrastructure in the face of changing environmental and socio-economic conditions.

We acknowledge Tuomi Jouko from Turun Seudun Puhdistamo for his insightful discussion and for providing the water samples and some data used in this study. We also extend our gratitude to Luis Bezerra from Åbo Akademi for his invaluable support with the ICP-OES analysis.