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Article

Adaptable Process Design as a Key for Sustainability Upgrades in Wastewater Treatment: Comparative Study on the Removal of Micropollutants by Advanced Oxidation and Granular Activated Carbon Processing at a German Municipal Wastewater Treatment Plant

by
Michael Toni Sturm
1,2,
Erika Myers
1,
Dennis Schober
1,2,3,
Clara Thege
4,
Anika Korzin
1,2 and
Katrin Schuhen
1,*
1
Wasser 3.0 gGmbH, Neufeldstr. 17a–19a, 76187 Karlsruhe, Germany
2
abcr GmbH, Im Schlehert 10, 76187 Karlsruhe, Germany
3
Entsorgungs- und Wirtschaftsbetrieb Landau, Georg-Friedrich-Dentzel-Straße 1, 76829 Landau, Germany
4
Van Remmen UV Technology, Hooglandweg 3a, 8131 TE Wijhe, The Netherlands
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(18), 11605; https://doi.org/10.3390/su141811605
Submission received: 18 July 2022 / Revised: 31 August 2022 / Accepted: 9 September 2022 / Published: 15 September 2022
(This article belongs to the Section Sustainable Engineering and Science)
Browse Figures
Versions Notes

Abstract

:
Micropollutants have been increasingly detected at low concentrations in surface waters and may have harmful effects on humans, organisms, and the environment. As wastewater treatment plants are one of the main sources of micropollutants, conventional wastewater treatment methods and plants (mainly one to three cleaning stages) must be improved through an advanced (fourth) treatment stage. The optimal fourth treatment stage should be determined based not only on removal efficiencies but also on a holistic sustainability assessment that further considers the process’s adaptability, economic, environmental, and social parameters. The ability of a tertiary wastewater treatment plant to remove organic pollutants was investigated over four months using two different advanced treatment methods: (1) an advanced oxidation process (AOP) (using UV + H2O2) and (2) granular activated carbon (GAC). The resulting average micropollutant removal efficiencies were 76.4 ± 6.2% for AOP and 90.0 ± 4.6% for GAC. As the GAC became saturated, it showed a decreasing performance from 97.6% in week one to 80.7% in week 13, after 2184 bed volumes were processed. For the AOP, adjusting the UV and H2O2 doses results in higher removal efficiencies. With 40 ppm H2O2 and 10 kJ/m2 UV, a removal of 97.1% was achieved. Furthermore, the flexibility and adaptability of the AOP process to adjust to real-time water quality, along with a lower resource consumption and waste disposal, make it a more promising technology when comparing the sustainability aspects of the two methods.

Graphical Abstract

1. Introduction

It is estimated that approximately 50% of global wastewater is released into the environment without sufficient treatment, equivalent to 2 million tons of sewage, industrial, and agricultural waste [1,2]. This has significant negative impacts on aquatic ecosystems, such as the eutrophication and spread of de-oxygenated dead zones in oceans and seas, which already cover an estimated 245,000 km2 of marine ecosystems [1]. Runoffs from herbicides have also been shown to have extremely detrimental and toxic impacts on ecosystems, destroying 30 km2 of mangroves between 1999 and 2002 [1].
Proper water quality is essential for not only the environment but also society and economies, as it affects fisheries, the food chain, and drinking water resources. Thus, proper wastewater treatment is critical to ensure human health and wellbeing [1].
Climate change effects exacerbate water resource issues, impacting both the availability and quality of water. Additionally, wastewater and its treatment contribute to greenhouse gas (GHG) emissions, such as methane and nitrous oxide; these levels have increased by 50% and 25% from 1990 to 2020, respectively. This highlights the necessity for sustainable adaptations in wastewater treatment processes to reduce energy consumption and minimize climate related impacts [1].
Regarding circular economy and sustainability, wastewater should not be viewed purely as waste—it is also an important resource (Figure 1) [3,4]. If treated properly, the water can be reused for industrial purposes, irrigation, or for drinking water, which is essential in areas facing water scarcity [5,6,7]. The sewage sludge can be used to produce biogas and energy, and as it contains many nutrients, it can also be applied as a fertilizer [8]. Another important step of circular wastewater treatment is phosphorus recovery, as natural phosphorus resources are limited [9]. Recently, wastewater has also been used for the detection and tracking of SARS-CoV-2 and can be used as an effective early or preventative warning tool for novel pathogens [10]. Therefore, wastewater treatment is not only important for environmental protection but can also generate many additional social, ecological, and economic benefits and values.
The EU Urban Wastewater Treatment Directive outlines the requirements for the collection and treatment of wastewater for populations >2000 [11]. Currently, the EU regulates the levels of nitrogen/phosphorus (75% reduction in total nitrogen and phosphorus for wastewater treatment plants (WWTPs) serving a population >10,000 or discharging into sensitive areas), total suspended solids (TDS), and the chemical/biochemical oxygen demand in WWTP effluents; concentrations of micropollutants are not yet restricted in the legislation. As such, modern tertiary WWTPs can remove suspended solids, pathogens, and nutrients from wastewaters and protect aquatic ecosystems from their input but are not designed to effectively remove the majority of micropollutants present within the wastewater [12,13]. Thus, WWTP effluents are one of the main entry paths of organic micropollutants into the environment [14,15].
Micropollutants are synthetically produced trace and often persistent substances found in very low concentrations in the range of micro- to nanograms per liter [16]. Typical organic micropollutants are pharmaceutical residues, plant protection products, biocides, detergents, and other anthropogenic organic chemicals, including liquid polymers (Figure 2) [17]. Although they are typically detected at low concentrations in surface waters, they can have harmful effects on humans, organisms, the environment, and drinking water [18]. This includes degradation and transformation products of the original substances. The complexity of these organic micropollutant mixtures combined with long-term exposures makes it is difficult to perform representative ecotoxicological studies [19]. Therefore, their negative effects are not yet fully understood [18,19].
To avoid the release of organic micropollutants into the environment, modern WWTPs apply advanced treatment processes as a fourth treatment stage (Figure 3) [14,15,21]. The primary technologies feasible for large-scale applications are powder (PAC) or granular activated carbon (GAC), ozonation, and advanced oxidation processes (AOPs) [15,22,23]. Additionally, membrane technologies can be used [24]. However, due to the lack of legal regulations surrounding micropollutant levels, and additional disadvantages, such as high technical complexity, increased costs, maintenance needs, and increased energy consumption, the modernization of WWTPs is progressing slowly [25].
In Germany, a “trace substance strategy” is being developed to create legal thresholds for micropollutant concentrations; however, it is estimated that implementing a fourth cleaning stage for WWTPs will take 10–15 years following the introduction of such legal restrictions [12,16].
Ozonation, GAC, and AOPs have all been shown to sufficiently reduce the majority of micropollutants in wastewater effluents, but each technology has associated drawbacks, and the life cycle impacts of each should be investigated. Ozonation has been shown to efficiently degrade the majority of micropollutants through oxidation; however, the disinfection of wastewater requires high ozone doses resulting in the formation of harmful by-products, such as bromate, making an additional filtration step necessary [15,26,27]. GAC has a high specific surface area that enables the adsorption, and thus physical removal, of the majority of micropollutants from the wastewater effluent [15]. The overall efficiency of the process, however, is highly dependent upon the frequency of the GAC regeneration, contributing to economic and environmental impacts [15]. AOPs function at room temperature and pressure and are based on the in-situ generation of OH radicals [28]. A novel photochemical AOP approach, coupling UV light with H2O2 as an oxidant, has shown to be an effective way to eliminate micropollutants. However, the overall energy demands are higher than for the other two methods, and the remaining H2O2 must be removed, which may require an additional GAC filtration step [29]. The ability to reuse the H2O2 in the WWTP’s biological treatment step may be an option. Studies have shown that 5 mg/L residual H2O2 can improve dissolved organic carbon (DOC) removal by 28% but reduce microbial activity by 37%. Lower H2O2 concentrations of 0.25 mg/L have been shown to lower DOC removal by 10% with no impact on microbial activity [30]. Thus, the impacts on the biological treatment processes must be studied in further detail to determine whether introducing residual H2O2 into the biological treatment stage is an option to increase the circularity of the AOP process.
Sustainability 14 11605 g003 550
Figure 3. Overview of removal strategies for micropollutants in wastewater [31].
Figure 3. Overview of removal strategies for micropollutants in wastewater [31].
Sustainability 14 11605 g003
The applicability and adaptability of a fourth cleaning stage at various scales for pre-existing treatment plants must be considered [32]. The Life Cycle Assessment (LCA) methodology is often used to perform sustainability assessments, however, the full scope of wastewater treatments, such as economic and social aspects are often neglected [33]. Thus, to determine the most feasible method of micropollutant removal, a holistic sustainability assessment that investigates the micropollutant removal efficiency and factors such as energy and resource consumption and recovery, circular economy processes, social implications, and costs of construction and operation [32,34] must be performed.
This study evaluates the removal performance of organic micropollutants from a tertiary WWTP equipped with two pilot plants for micropollutant removal. The first pilot plant was equipped with GAC and the second uses an AOP combining UV light with H2O2. The long-term studies are evaluated on their removal performance over a period of four months in a comparative study design.

2. Materials and Methods

2.1. Study Area

The study was performed in the tertiary WWTP Landau-Mörlheim. The capacity of the WWTP is 80,000 population equivalents. The treatment process includes a primary treatment using rakes and a fat separator, followed by a secondary biological treatment and the tertiary phosphate elimination. The catchment area includes households, industry, and agriculture, which mainly consists of viticulture. Additionally, 2 hospitals are in the catchment area [35].
The inflow ranges from 9000 to 40,000 m3/day depending on the weather conditions, with an average inflow of 13,000 m3/day. The hydraulic retention time is 24 h and the average sludge retention time is 12–14 days. The average COD (chemical oxygen demand) in the effluent is 20 mg/L, the nitrate 6.5 mg/L, ammonia <1 mg/L, and total phosphorus 0.3 mg/L. The average monthly energy consumption is 140,000 kWh; around 70% of this can be produced by a cogeneration unit using digester gas from the sludge.

2.2. Advanced Oxidation Process

The AOP Flex setup (Advanox™) was provided by Van Remmen UV Technology, Wijhe, Netherlands and combines the use of H2O2 supplied by Nouryon, Amsterdam, Netherlands, as an oxidant and photolytic degradation by UV. It is applicable for flow rates of 1–30 m3/h. It has four UV reactors (Advanox Focus 200) with single 600 W low-pressure UVC lamps. The control of the UVC dose and H2O2 dosing is automated. Based on the incoming water (flow rate and transmittance) the system will turn on or off lamps to match the UVC dose settings. The specific energy consumption depends on the required UVC dose, transmittance, and flow rate. During the tests, the flow rate was set to 6 m3/h, the UVC dose to 7.5 kJ/m2, and H2O2 to 30 ppm for a transmittance range of 60–72% T10. The system has an integrated cleaning functionality to remove fouling and scaling that builds up in the reactor. Citric acid is added to the system with an ejector and when the pH is brought to <3 the system is left to soak for 2 h. At the end of the soaking time, the system is flushed with water.

2.3. Granular Activated Carbon Technology

The GAC process was set up with a DynaSand® Carbon Filter by Nordic Water, Neuss, Germany, which was filled with AquaSorb™ 2000 by Jacobi Carbons, Premnitz, Germany. The DynaSand® Carbon Filter was filled with 1.1 m3 GAC. An air lift pump circulates the GAC in the filter, which prevents clogging and reduces the amount of water used for backwashing. The flow rate was set to 2 m3/h, resulting in a contact time of 1 h.

2.4. SAC Measurements

Continuous SAC (Spectral Absorption Coefficient 254) measurements were performed by UV 705 IQ SAC probes supplied by Xylem Analytics, Weilheim, Germany. The measurement range is 0.0–600.0 1/m, and the resolution is 0.1 1/m.
As the AOP effluent turned out to be harmful for the SAC probes due to the remaining H2O2, the SAC from AOP was measured using an Marchery-Nagel Nanocolor UV/VIS II by Marchery-Nagel, Düren, Germany.

2.5. Sampling Process, Sample Preparation, and Target Analytics

The samples from the effluent of the third cleaning stage and the effluents of the AOP and GAC were taken weekly. For a qualified sample, 6 subsamples were taken every 10 min over 1 h. In the sampling process, the offset time (20 min for AOP and 1 h for GAC) needs to be considered. A sample from the WWTP influent was taken once every two weeks, 24 h before taking the sample of the effluent of the third cleaning stage. The samples were filled into sample vessels and frozen until transported to the external analytics laboratory.
To remove the remaining hydrogen peroxide from the AOP sample, 300 µL of catalase (AB139273, abcr GmbH, Karlsruhe, Germany) was added to a 600 mL sample before freezing it. Therefore, a blank value measured using the same amount of catalase in demineralized water was subtracted from the measured TOC content.
The following micropollutants were analyzed according to DIN standards by Limbach Analytics GmbH, Labor Mannheim, Germany (Table 1). The selection is based on the recommendations of the Competence Center for Trace Substances in Baden-Württemberg Germany [36].
To obtain the mean removals, the removal for each measurement day and each substance was calculated and averaged over the time of the trials.
For statistical analysis, a paired, two-sided t-test was performed. Homogeneity of variance and normality was checked using residuals versus fits- and QQ-plots. The significance levels are p = 0.05 (*); p = 0.01 (**); p = 0.001 (***).

3. Results

3.1. Removal of Organic Micropllutants in a Tertiary Treatment Process

Organic micropollutants were detected in the influent of the tertiary cleaning stage of WWTP in Landau from 0.72 ± 0.17 µg/L for carbamazepine to 14.00 ± 3.02 µg/L for ibuprofen. The mean total concentration of micropollutants was 3.97 ± 0.72 µg/L (Figure 4). The deviations are caused by temporal differences in the inputs as well as rain events that dilute the wastewater, thereby reducing the organic micropollutant concentrations [37,38].
All organic micropollutants were also detected in the effluent of the WWTP’s tertiary clarifier. Benzotriazole had the highest value with 5.11 ± 1.08 µg/L, while sulfamethoxazole showed the lowest value with 0.27 ± 0.13 µg/L. The average concentration of organic micropollutants in the effluent is 1.87 ± 0.84 µg/L. Compared with the reference literature, the measured values are in a typical range for WWTPs [18,39,40].
Looking at the measured removals of the micropollutants compared with the influent of the WWTP (Figure 5), the WWTP plant effectively removes ibuprofen with an average removal of 97.8 ± 0.8%. Concentrations of sulfamethoxazole (56.9 ± 12.9%), 4- and 5-methylbenzotriazole (46.5 ± 13.2%), and benzotriazole (38.5 ± 9.9%) are all reduced during the wastewater treatment process. The remaining organic micropollutants showed no significant removal. The average removal of all organic micropollutants is 21.7 ± 2.8%. As ibuprofen is the only micropollutant removed effectively, this data clearly highlights the necessity of an advanced wastewater treatment process.
It was found that both the micropollutant characteristics (e.g., hydrophobicity, biodegradability, and volatility) and treatment conditions of the WWTP processes (e.g., micropollutants present and pH and temperature of wastewater) influence the removal rates of the various compounds [39,41,42]. Moreover, every WWTP has their own microbial community which strongly affects the biodegradation of organic micropollutants [41,43]. Compared with the reference literature, the removals of ibuprofen, sulfamethoxazole, and 4- and 5-methylbenzotriazole in this study are comparably high, while the removals of candesartan, carbamazepine, diclofenac, hydrochlorothiazide, irbesartan, and metoprolol are comparably low. Other studies have shown that these organic micropollutants are typically degraded between 10–30%, depending on the respective substance, but there was no significant reduction in these compounds within this study [39,40].
Looking at the mean concentration of micropollutants (Figure 4), almost 50% are removed, but the average removal of all organic micropollutants accounts for only 21.7 ± 2.8% (Figure 5). This is due to the higher concentrations of well-degradable substances, such as ibuprofen, that have a stronger influence on the mean. The method applied in this study, calculating the removal for each substance as a percentage before taking the mean, leads to normalization of the data and removes this effect, as all organic trace substances are weighted equally.
It must be considered that the choice of the measured organic micropollutants also affects the total removal performance [39]. If more well-degradable organic micropollutants are used within the study, the average removal increases. If more poorly degradable organic micropollutants are selected, the average removal decreases.
It is notable that some of the calculated mean reductions of candesartan, diclofenac, carbamazepine, and irbesartan are negative, as the measured concentrations in the effluent were higher than in the influent. This is due to uncertainties in the sampling process. First, the 24 h residence time of the water in the WWTP (see Section 2.5) is an estimation, which can vary depending on the amount of water being processed [44]. Additional deviations result from the water being well mixed during the water treatment process, resulting in the effluent sample being more homogenized than the influent sample [44].

3.2. Comparison of the Removal Efficiencies of Organic Micropllutants by GAC and AOP

The AOP and the GAC effluents show a significant reduction in the micropollutant concentrations (Figure 6). In the AOP, the measured concentrations range from 0.85 ± 0.36 µg/L for 4- and 5-methylbenzotriazole to 0.05 ± 0.05 µg/L for diclofenac. The GAC effluent shows the highest concentration for candesartan with 1.13 ± 0.50 µg/L, while metoprolol and ibuprofen are no longer detectable using a detection limit of 0.02 µg/L. The average concentration of all organic micropollutants is 0.31 ± 0.08 µg/L for the AOP and 0.20 ± 0.16 µg/L for the GAC.
The removal of the organic micropollutants from the WWTP effluent compared with the influent of the fourth cleaning stage provides a more conclusive comparison of the AOP and GAC (Figure 7 and Figure 8). With an average removal of 90.0 ± 4.6%, the GAC performs 13.1 ± 6.4% better than the AOP with 76.4 ± 6.2% when using 30 ppm H2O2 together with a 7.5 kJ/m2 UV dose. The GAC achieves the targeted removal of over 80% for 8 of the 10 measured organic micropollutants, while the AOP has a removal > 80% for only three organic micropollutants: diclofenac, 4- and 5-methylbenzotriazole and benzotriazole (with 7.5 kJ/m2 UV dose and 30 ppm H2O2).
The removal comparisons (Figure 8) show that the AOP and GAC have a similar removal performance for diclofenac and irbesartan. The only substance removed more efficiently by the AOP is candesartan, as it is well-degradable by photolysis and oxidation [45,46]. The GAC removes the remaining seven substances (carbamazepine, hydrochlorothiazide, ibuprofen, metoprolol, sulfamethoxazole, 4- and 5-methylbenzotriazole, and benzotriazole) more efficiently.
Comparing our data with other studies, Yang et al., 2011 found that GAC could remove diclofenac almost completely and carbamazepine up to 75%; our study found higher removal efficiencies of 93% and 99%, respectively [47]. GAC efficiency is affected by the quality of the wastewater and varies according to the used GAC. Important factors are regeneration frequency, pore shape and size, pore-size distribution, and the surface charge of the compounds [13,48].
UV + H2O2 has been reported by Kim et al., 2009 to have a 90% removal efficiency for 39 of 41 compounds studied using a dose of 3.5–9.2 kJ/m2 and an H2O2 concentration as low as 5 mg/L. Organics (TOC, COD, etc.) present in the water may affect the UV transmittance, and thus the effectiveness of any UV-based removal process [49]. The reactor design is also essential for the removal performance [50,51].
Ozonation is another commonly applied advanced treatment method and has also been shown to significantly remove the majority of micropollutants to >80%. One of the main drawbacks is that it leads to the formation of potentially harmful by-products that need to be removed in an additional filtration step. Higher ozone doses are reported to increase the removal of the aforementioned compounds, but also result in higher costs and a higher risk of forming toxic by-products such as bromate [15,52]. Östman et al., 2019 found that overall, ozone was not found to be as effective at removing pharmaceuticals as GAC [48].
Another important group of micropollutants entering the environment through wastewaters are poly- and perfluoroalkyl substances (PFAS) [53]. These are particularly problematic due to their poor degradability and the resulting accumulation in the environment. While GAC can remove these from water effectively via adsorption, advanced oxidation processes, such as ozone, have been proven to be ineffective due to PFAS’s slow degradation and defluorination rates [54,55,56,57,58].

3.3. Temporal Variations of Removal Performance

When evaluating the advanced treatment processes, it is important to not only look at the overall mean removal values but also at the temporal variations in their long-term performance. Figure 9 shows the mean trace substance removal and mean trace substance concentrations over the 13 weeks in which the experiments were performed.
The organic micropollutant levels in the wastewater entering the WWTP show temporal variations mainly caused by rainfall events that dilute the incoming wastewater [37,38]. The mean concentration of the organic micropollutants ranges from 1.40–2.43 µg/L. Seasonal variations can occur depending on the weather or industries, such as viticulture, which is widespread in the catchment area of the WWTP. The mean concentration of organic micropollutants varies between 0.11–0.66 µg/L for the AOP effluent and 0.10–0.32 for the GAC effluent.
Looking at the development of the mean organic micropollutant removal over time, there is a clear decreasing trend for the GAC. During the first week of operation, it removed 97.6% of the organic micropollutants. After 7 weeks, the removal was already reduced to 91.1%, and after 13 weeks, the removal accounted for only 80.7%. This is due to the limited sorption capacity of the GAC as it reaches equilibrium with the wastewater. With a flow rate of 2 m3/h, the amount of processed water was 336 m3, or 168 bed volumes per week. Over 13 weeks, a total of 4368 m3 or 2184 bed volumes were processed. To improve the removal performance, the GAC needs to be exchanged.
Previous studies show that decreased removal performance over the processed bed volumes depends on the type of GAC used [59]. A study performed by Benstöm (2017) [59] tested five different GACs for their long-time performance. The highest performing GAC could remove diclofenac efficiently (<80%) for 28.108 bed volumes, while the worst performing GAC was only able to process 8.869 bed volumes. For sulfamethoxazole, the GAC with the best performance processed 7.172 bed volumes before the removal dropped below 80%, while the least efficient GAC only processed 2.498 bed volumes before the removal fell below 80%.
The AOP showed temporal variations of the removal efficiencies, ranging from 66.4% to 91.2%, a difference of 24.8%. The AOP was cleaned internally using the automated cleaning process with citric acid before 25 February 2022, when the maximum removal of 91.2% was reached. Other factors affecting the removal performance could be temporal variations in the wastewater, such as the type and amount of organic species present, differences in transmittance, or the composition of organic micropollutants [50,60].
Due to these fluctuations, it is important to have the possibility to control the treatment process parameters. As the targeted analytics for organic micropollutants are time-consuming and expensive, TOC and SAC have been commonly suggested as potential non-target sum parameters that can be used for a simple and continuous control of the functionality of the fourth cleaning stage [61,62]. During the continuous operation of the AOP and GAC processes, for every organic micropollutant sample taken, the associated TOC and SAC were also analyzed. Figure S1 shows the results for the correlation of the reduction in TOC, SAC, and the mean concentrations of the organic micropollutants.
Looking at the Pearson correlation coefficient (r) and coefficient of determination (R2), we could not see any statistically significant correlations. The highest values were an r of 0.76 and R2 of 0.57 for the correlation between the TOC removal and organic micropollutant removal in the GAC. No correlations were found between the SAC and TOC removals.
The TOC and SAC are non-selective sum parameters that are influenced by a variety of substances in the water; thus, they are also strongly influenced by temporal variations of the water composition (e.g., dilution by rain and agricultural inputs) and various substances that are not targeted by organic micropollutant analytics (e.g., KomS) [36]. Furthermore, we investigated only a small range of organic micropollutant removal performance, from 80.2% to 97.6% for GAC and 66.4% to 91.1% for the AOP. Based on the results of this study, the sum parameters SAC and TOC were not selective enough and not reliable indicators of the amount of organic micropollutants present in the sample. They are therefore not suitable parameters for process control in the desired measuring range.

3.4. Dose–Response Testing of the AOP Process

The hydrogen peroxide dose and amount of UV light were varied to investigate their impact on the AOP’s removal of organic micropollutants. In total, 40 ppm H2O2 with 10 kJ/m2 UV light led to the best removal performance of 97.1%. Comparable results were achieved with 30 ppm H2O2 and 7.5 kJ/m2 UV light and 20 ppm H2O2 and 10 kJ/m2 UV light with removals of 94.3% and 94.0%, respectively (Figure 10). This shows that the H2O2 and UV doses can compensate for each other, and the most economically optimal settings can be chosen according to the H2O2 and energy costs [51,60].
A high H2O2 dose of 40 ppm and a low dose of 5 kJ/m2 UV light achieved an average removal of 81.6% and was less efficient than the previously mentioned settings. The lowest removal of 75.7% resulted from the combination of 20 ppm H2O2 and 5 kJ/m2 UV light, which also had the lowest energy and H2O2 consumptions. This demonstrates that the ability of UV light to compensate for a lower H2O2 is limited.
These results reveal that the AOP process is adaptable and can be adjusted according to the targeted removal efficiencies and energy or H2O2 prices. The UV and H2O2 levels can also be adapted to different pollution levels (e.g., caused by seasonal variations) in the WWTP to maintain a consistent removal efficiency despite varying micropollutant loads [60].

4. Discussion

4.1. Removal of Organic Micropllutants in a Tertiary Treatment Process

The results investigating the removal performance of organic micropollutants at the tertiary WWTP in Landau i.d. Pfalz clearly show that there are big differences between the degradability of the studied micropollutants, mainly driven by their biodegradability and sorption to sludge. For the 10 measured organic micropollutants, we received an average removal performance of 21.7 ± 2.8%. Ibuprofen was the only micropollutant with a high removal efficiency (well degraded), while we saw no degradation at all for 6 of the 10 tested organic micropollutants.
This shows that the tertiary wastewater treatment does not sufficiently remove organic micropollutants, in agreement with various other studies [63,64]. WWTPs are important point entry paths for micropollutants into the environment and should be upgraded with a fourth (advanced) cleaning stage. There are many discussions within science, politics, and society on the drawbacks and costs of the technologies applied in fourth cleaning stages, thus the implementation of policies and modernization of WWTPs is progressing slowly [26].

4.2. Comparing the Removal of Organic Micropllutants by GAC and AOP

Considering the average micropollutant removal efficiencies over 13 weeks, the GAC process seems to be the more efficient choice. However, this is just a snapshot averaged over a short sampling period. To properly evaluate and compare these methods, it is important to also consider the temporal variations and adaptability of the processes (e.g., the UV and H2O2 doses can be adjusted to obtain higher removal efficiencies).
As shown in the results in Section 3.3, the amount of micropollutants in the effluent of the third cleaning stage with respect to the influent of the fourth cleaning stage shows temporal variations. There are also differences in micropollutant concentrations between WWTPs depending on their catchment area and cleaning performance [18]. When evaluating the removal performance of advanced wastewater treatment processes, usually only the removal efficiencies are considered. For example, German authorities recommend an organic micropollutant removal over 80%, but it is also important to consider the contamination level of the wastewater and the volume of water being treated [16]. When removing a lower proportion of micropollutants from highly contaminated water, the positive impact on the environment can be higher than removing a higher proportion from a small amount of contaminated water. The amount of wastewater treated needs to be considered when looking at the total mass of micropollutants released into the environment.
Here, we see an advantage of the AOP process over the GAC. The AOP is adaptable depending on the desired removal performance, as shown in Section 3.4. Thus, it can be adjusted with low effort according to changing contamination scenarios or changing regulations and thresholds for micropollutant removal. The dose–response testing of the AOP process confirmed this adaptability and could also show that, depending on the costs and/or environmental impact, energy (UV dose) and H2O2 can compensate one another. This can be used to make the process more energy- and cost-efficient and minimize environmental impacts.
The GAC process is limited to the specific properties of the GAC material and the contact time with the water and is therefore less adaptable [59]. Another disadvantage of the GAC is the declining removal performance with the amount of treated wastewater, which can only be increased again by exchanging the GAC. Thus, we rate the AOP as the process that is more controllable and adaptable to different scenarios.

4.3. Sustainable Process Analysis

In the past, engineering and process designs often focused on economic and technical dimensions, with environmental and social aspects considered as constraints or limited to their monetary benefits or setbacks. However, with increasing anthropogenic environmental impacts, there is a shift to sustainable process design and enhancement, whereby economic, environmental, and social dimensions are considered at all stages of the process design, from early planning to end of life. This leads to long-term economic benefits, reduced environmental impacts, and increased social development [65].
Determining the most feasible fourth treatment process for micropollutant removal requires a holistic sustainability assessment that addresses the full spectrum of environmental, health, social, and economic impacts, including the micropollutant removal efficiency (and associated effluent water quality), energy and resource consumption and recovery, circular economy processes, social implications, and costs of construction, operation, and disposal (Figure 11) [32,34]. The applicability and adaptability of a fourth treatment stage at various scales for pre-existing treatment plants must also be considered along with the potential and flexibility for sustainability and process improvements [32].
Life Cycle Assessments (LCAs) are a commonly used and standardized sustainability assessment method that take a cradle-to-grave approach to determine potential environmental impacts. Numerous LCA studies have been performed to facilitate the design, operation, and control strategies of WWTPs by evaluating the construction of the plant, influx of fuels, energy, chemicals, effluent chemistry, the waste disposal, and end-of-life decommissioning impacts (Figure 12). Most of the environmental impacts for WWTPs stem from the electricity consumption (primarily for pumping and aeration) and the quality of the WWTP effluent [33,67,68].
More recently, LCAs have been performed to assess the environmental impacts of advanced (fourth) treatment technologies. However, there are methodological constraints and limitations, particularly in how the impact of the effluent water quality is assessed. Typically, removal efficiencies are not considered, and the net impacts vary significantly depending on the amount of micropollutants included in the LCA along with the characterization of their (eco)toxicities, for which data is often lacking or inconsistent [67,68]. Therefore, a more comprehensive approach that includes both the potential environmental impacts alongside the removal benefits should be introduced.
As a result, numerous LCA studies performed on advanced treatment options for WWTPs indicate that the overall regional environmental impacts associated with increased energy and chemical consumptions may outweigh the benefits of increased water quality locally [69,71]. As the extent of the harm induced by micropollutants is not fully quantified, this poses additional complications when assessing and weighing the sustainability impacts and implementing legislation that restricts micropollutant concentrations in WWTP effluents [72,73]. However, improving LCAs to provide a flexible and adaptable basis from which different pollution and removal scenarios can be assessed would provide stakeholders and decision makers with useful insight into the impacts and benefits of various treatment technologies and the ability to both plan and adjust according to different technological, financial, and environmental conditions [67,68].
In Europe, the most commonly used advanced treatment processes are ozonation and GAC; the AOP is a relatively modern approach [74]. For GAC, the primary contributors to the environmental impact are the production of GAC (41% of total impacts) and end-of-life scenarios (26%) [73]. A large majority of GAC is generated from brown or black coal; thus, the impacts can be reduced by utilizing material such as regenerated GAC, coconut shells, or organic waste [63]. Significant research is being conducted on how to use various organic waste materials to generate GAC more sustainably. Recent research also shows the application of innovative adsorbents such as aerogels can be an effective replacement for GAC in the future, but these are not yet available on large scale [75,76,77]. Once GAC is “full” (the longevity of the GAC material depends on multiple factors, including the WWTP effluent quality and the specific material properties), it must be regenerated or disposed of, typically via incineration. Improving the regeneration and disposal methods would reduce the overall environmental impacts.
The primary impacts of the AOP (UV + H2O2) stem from the H2O2 production (50%); the disposal requirements of any excess H2O2 must be considered, and the potential to re-use H2O2 within the secondary treatment stage to improve the biological treatment process is being assessed. Research is also being conducted on alternative production methods for H2O2 to reduce the energy consumption and environmental impacts. Additionally, UV technology is continuously improved to make it more energy efficient [50,51]. Currently, the AOP is not often implemented at a large-scale due to concerns of technical feasibility and cost. However, the flexibility to adjust the H2O2 and UV dosing according to the real-time water quality in the AOP, along with the significant potential to improve the overall sustainability, makes it an appealing option to minimize losses and makes it a promising treatment option if renewable energy sources are used.
Ozonation requires that ozone be generated on site, which is highly energy-intensive; it has been found to have a 25% higher impact than GAC, with electricity contributing 71% to its total impact [78]. However, it must be noted that the majority of LCAs on ozonation do not include the additional filtration required to remove toxic by-products that are generated during treatment, such as bromate [52].
An initial qualitative comparison of AOP and GAC is shown in Table 2 based on cost and energy estimates for a system with a flow rate of 400 m3/h. For the AOP, 65% transmittance with 7.5 kJ/m2 and 30 ppm H2O2 is assumed; for the GAC, estimates are based on an in-flow system using 12 filters with a total of 180 m3 of granular activated carbon. The CAPEX for AOP ranges from EUR 270,000 to EUR 820,000 depending on the transmittance range, as this influences the amount of Advanox reactors required. The CAPEX for GAC is approximately EUR 560,000, with most costs stemming from the machinery and GAC filters. The AOP has a higher OPEX (0.185 EUR/m3) compared with GAC (0.04 EUR/m3) due to the H2O2 costs and electricity demands. However, these costs may be offset by using renewable energy sources [52].
As electricity is a main factor in the environmental impact of all processes, utilizing renewable energy sources and considering circular processes such as sludge for biogas production can greatly reduce both the costs and the total toxicity influences and make advanced treatment processes more economically feasible [69]. The current energy consumption for the tertiary wastewater treatment at Landau is approximately 0.30 kWh/m3, with approximately 65% of this being generated on-site.
The AOP can be adjusted to select the most optimal setting regarding energy consumption, while still ensuring sufficient organic micropollutant removal. The amount of energy used for the AOP dosing scenarios can be seen in Table 3. The lowest energy consumption is obtained from 20 ppm H2O2 with 5 kJ/m2 UV; however, results show that this set-up was not capable of sufficiently removing micropollutants. Assuming 65% transmittance, the ideal UV dosing is therefore 7.5 kJ/m2 with 30 ppm H2O2. This obtains a removal efficiency of 76.4 ± 6.2% and a lower energy consumption than the combination of 10 kJ/m2 UV together with 20 ppm H2O2, resulting in an increased energy consumption at the WWTP of 0.41 kWh/m3. For a full sustainability analysis and comparison, the energy required to produce the H2O2 should also be considered.
The energy requirements of a GAC system when placed in-flow are relatively low (5 W/m3), which is necessary for the compressed air to circulate and flush the GAC (Table 2). However, when comparing the GAC and AOP processes, the electricity and resources required for the production and activation of the GAC must be considered. It is estimated that the production of GAC for a system with a 400 m3/h flow rate (roughly equivalent to that of the WWTP in Landau) would require 180 m3 of activated carbon that needs to be replaced every 2–4 years. Assuming that 1 kg of activated carbon is produced from 3 kg of coal, with an electricity consumption of 1.6 kWh per kg of fresh GAC, this would require 132.5 MWh to be produced, excluding the associated energy and GHG emissions from the mining and transportation processes [79]. Unlike the electricity required for the AOP process, the material extraction and production/regeneration of the GAC cannot be offset by renewable energy sources. Novel methods and materials to produce activated carbon are currently being researched and should be considered in the sustainability and adaptability of GAC. Furthermore, a full life-cycle assessment of both the AOP and GAC processes that considers the extraction, production, and transport of materials, alongside the operating and disposal parameters, is necessary for a full sustainability comparison of the two methods.
Ghimire et al. (2021) investigated potential scenarios for incorporating circular economy and energy sustainability into existing WWTPs that would make them either self-sufficient or energy-positive [32]. Both improving the resource efficiency of the WWTP through enhanced carbon capture and the integration of anaerobic wastewater treatment schemes (e.g., bioelectrochemical systems such as microbial fuel cells) show potential, but further research needs to be conducted to address the numerous associated economic and technical challenges.
Switzerland, the first country to implement legal regulations on micropollutant levels in WWTP effluents, acknowledges in its Swiss National Strategy that for the successful implementation of an advanced treatment stage it must have a solid technical and scientific basis, there must be broad societal and political acceptance, and it must be technically and economically feasible, manageable, pragmatic, and adaptable over time—all important factors of a holistic sustainable approach [18].
However, even after legislation on micropollutant concentrations is realized, it can take up to 20 years to upgrade all WWTPs. Establishing restrictions on micropollutant levels that are more attainable in the short term, e.g., >60% removal, would set the development in motion and allow for the technology to be improved over time to make higher micropollutant removal efficiencies more economically and technologically feasible. This is particularly useful for the AOP system, where higher doses are capable of higher removal efficiencies, but the broader environmental implications and costs may currently outweigh the benefits from an LCA perspective. For example, an additional advanced treatment stage results in a 5–30% increase in energy consumption (increasing Switzerland’s total national energy consumption by 0.1%), but the excess energy is planned to be compensated for by increased WWTP energy efficiency along with renewable energy production [18].
A fourth cleaning stage increases the overall cost of the wastewater treatment. Referring to the case of Switzerland, the average cost for standard wastewater treatment is 0.07 CHF/m3 of wastewater; with an additional treatment stage, the annual costs increase by approximately 6%. However, reports in the media brought awareness to the topic of pharmaceuticals in water resources, raising public concern. As a result, when public consultations were performed on the proposed Swiss water ordinance that would address micropollutant concentrations in water, there was an overall agreement on the necessity to reduce micropollutant levels, despite the increased costs [18]. This highlights the importance of involving the public when attempting to implement new legislation.
An appropriate and holistic strategy is required to incorporate sustainable and effective infrastructure for micropollutant removal into existing WWTPs. If a long-term strategy is in place, that includes a broad assessment of sustainability impacts, planning, and financing, the cost increase may be minimal [18]. However, a strategy should also address future mitigation measures regarding the ongoing release of micropollutants.

5. Conclusions

Of the 10 analyzed micropollutants at the tertiary WWTP in Landau, only ibuprofen was effectively removed. The removal efficiencies of two advanced (4th) cleaning stages, AOP (UV + H2O2) and GAC, were investigated in a comparative study design. The AOP and GAC removed an average of 76% and 90% of the micropollutants, respectively. Dose–response testing for the AOP showed that the removal efficiency can be improved by adjusting the H2O2 and UV dosing. A removal of 97.1% was reached applying 40 ppm H2O2 and 10 kJ/m2 UV. As the GAC became saturated, it showed a decreasing removal efficiency. In week one, a removal of 97.6% was measured, while in week 13, after 2184 bed volumes were processed, a removal of 80.7% was measured. The flexibility and adaptability of the AOP process according to real-time water quality parameters, along with its modular design and potential to re-use the hydrogen peroxide in the secondary water treatment stage, makes it a promising technology for a sustainability upgrade of wastewater treatment processes. However, the impacts of H2O2 manufacturing and more sustainable options for this process still need to be considered. The GAC removal efficiency varies according to GAC properties and declines substantially over time as it becomes saturated. The GAC disposal, generation, and regeneration makes it a potentially less sustainable alternative due to high resource and energy consumption. The ability to use organic waste for GAC generation would reduce the environmental impacts. The sustainability of both processes can be improved by considering a circular economy approach that would enable higher resource re-use and renewable energy sources (Table 2).

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/su141811605/s1, Figure S1: Linear correlation of for the calculated reductions for SAC, TOC, and mean organic micropollutant (OMP) during the AOP and GAC process. r = Pearson correlation coefficient, R2 = coefficient of determination.

Author Contributions

Conceptualization M.T.S., E.M. and K.S.; methodology, M.T.S., C.T., D.S. and A.K.; software, C.T. and D.S.; validation, M.T.S. and K.S.; formal analysis, M.T.S.; investigation, M.T.S. and K.S.; resources, C.T., D.S. and A.K.; data M.T.S., C.T. and K.S.; writing—original draft preparation, M.T.S. and E.M.; writing—E.M. and K.S.; visualization E.M. and K.S.; supervision, K.S.; project administration K.S. All authors have read and agreed to the published version of the manuscript.

Funding

This study was part of a funding of the Ministry of Climate Protection, Environment, Energy and Mobility Rhineland-Palatinate/GERMANY (identification number: 4-3660).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

The data presented in this study are available in the current manuscript, raw data are available on request from the corresponding author.

Acknowledgments

Wasser 3.0 gGmbH is a non-profit company with strong focus on responsible research, education, and communication. The enterprise abcr GmbH (Website abcr GmbH Deutschland. Available online: http://www.abcr.de (accessed on 8 September 2022)) from Karlsruhe (Germany), EW Landau (Germany), Van Remmen (Netherlands). and Nouryon (Sweden) are directly involved in the project as an industrial partner. The authors acknowledge special support from Ton van Remmen and Thomas Greschik (Nouryon) and thank them for the fruitful discussion about the AOP processing and micropollutants removal.

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

CSfourth cleaning stage
AOPadvanced oxidation process
GACgranular activated carbon
GHGGreenhouse gas
LCALife Cycle Assessments
n.s.not significant
PFASpoly- and perfluoroalkyl substances
SACspectra absorption coefficient at 254 nm
TOCtotal organic carbon
UVultraviolet light
WWTPwastewater treatment plant

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Figure 1. Direct effect of sustainable wastewater treatment [1,2,3].
Figure 1. Direct effect of sustainable wastewater treatment [1,2,3].
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Figure 2. Important sources of micropollutants in water resources. Adapted from Kokkinos et al. (2020) [16,20].
Figure 2. Important sources of micropollutants in water resources. Adapted from Kokkinos et al. (2020) [16,20].
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Figure 4. Means of the measured organic micropollutants in the effluent of the third cleaning stage of the WWTP. For statistical analysis, a paired, two-sided t-test was performed (ns: p > 0.05; ** p < 0.01; *** p < 0.001).
Figure 4. Means of the measured organic micropollutants in the effluent of the third cleaning stage of the WWTP. For statistical analysis, a paired, two-sided t-test was performed (ns: p > 0.05; ** p < 0.01; *** p < 0.001).
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Figure 5. Means of the removals of the organic micropollutants and total organic carbon (TOC) from the influent of the WWTP (WWTP) to the effluent of the third cleaning stage of the WWTP.
Figure 5. Means of the removals of the organic micropollutants and total organic carbon (TOC) from the influent of the WWTP (WWTP) to the effluent of the third cleaning stage of the WWTP.
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Figure 6. Organic micropollutants in the effluent of the third cleaning stage of the WWTP (influent of the fourth cleaning stage (4 CS)) and effluents of the AOP and GAC. For statistical analysis, a paired, two-sided t-test was performed (ns: p > 0.05; ** p < 0.01; *** p < 0.001).
Figure 6. Organic micropollutants in the effluent of the third cleaning stage of the WWTP (influent of the fourth cleaning stage (4 CS)) and effluents of the AOP and GAC. For statistical analysis, a paired, two-sided t-test was performed (ns: p > 0.05; ** p < 0.01; *** p < 0.001).
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Figure 7. Means of the removals of the organic micropollutants and total organic carbon (TOC) from the effluent of the third cleaning stage of the WWTP (influent of the fourth cleaning stage (4 CS)) and the effluent of the AOP vs. effluent of GAC. For statistical analysis, a paired, two-sided t-test was performed (ns: p > 0.05; ** p < 0.01; *** p < 0.001).
Figure 7. Means of the removals of the organic micropollutants and total organic carbon (TOC) from the effluent of the third cleaning stage of the WWTP (influent of the fourth cleaning stage (4 CS)) and the effluent of the AOP vs. effluent of GAC. For statistical analysis, a paired, two-sided t-test was performed (ns: p > 0.05; ** p < 0.01; *** p < 0.001).
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Figure 8. Differences between AOP and GAC for organic micropollutants removals and total organic carbon (TOC). Positive values indicate a better removal with AOP; negative values indicate a better removal by GAC.
Figure 8. Differences between AOP and GAC for organic micropollutants removals and total organic carbon (TOC). Positive values indicate a better removal with AOP; negative values indicate a better removal by GAC.
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Figure 9. Mean values over time for organic micropollutants in the influent of the 4th cleaning stage, the effluent of the AOP and GAC (top), and their removal in the AOP and GAC (bottom).
Figure 9. Mean values over time for organic micropollutants in the influent of the 4th cleaning stage, the effluent of the AOP and GAC (top), and their removal in the AOP and GAC (bottom).
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Figure 10. Removal of micropollutants from WWTP effluent (third cleaning stage) with AOP and different doses of H2O2 and UV light.
Figure 10. Removal of micropollutants from WWTP effluent (third cleaning stage) with AOP and different doses of H2O2 and UV light.
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Figure 11. Overview on technical, ecological, social and economic levers for a sustainable process design [66].
Figure 11. Overview on technical, ecological, social and economic levers for a sustainable process design [66].
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Figure 12. Example of LCA framework for an advanced wastewater treatment process. Adapted from [33,69,70].
Figure 12. Example of LCA framework for an advanced wastewater treatment process. Adapted from [33,69,70].
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Table
Table 1. Analytical methods used to analyze the water samples.
Table 1. Analytical methods used to analyze the water samples.
ParameterTest Procedure
pHDIN 38404-C 4: 1976-12
Electrical conductivity (at 25 °C)DIN EN 27888-C 8: 1993-11
TOCDIN EN ISO 10523-C 5: 2012-04
CandesartanLAM-MLC.M.0051: 2015-08 *
CarbamazepineLAM-MLC.M.0051: 2015-08 *
DiclofenacLAM-MLC.M.0051: 2015-08 *
HydrochlorothiazideLAM-MLC.M.0051: 2015-08 *
IbuprofenLAM-MLC.M.0051: 2015-08 *
IrbesartanLAM-MLC.M.0051: 2015-08 *
MetoprololLAM-MLC.M.0051: 2015-08 *
SulfamethoxazoleLAM-MLC.M.0051: 2015-08 *
BenzotriazoleLAM-MLC.M.0051: 2015-08 *
Sum of 4- and 5-methylbenzotriazoleLAM-MLC.M.0051: 2015-08 *
* In-house standard by Limbach Analytics GmbH, oriented on DIN 38407-47:2017-07.
Table
Table 2. Initial qualitative comparison of AOP and GAC based on preliminary energy and cost estimates for a system processing 400 m3/h over 15 years. The GAC is assumed to be constructed in-flow (therefore energy demands are primarily resulting from the compressor used for GAC cleaning). OPEX costs consider the maintenance and repair costs, including replacement of CAPEX part. Green indicates a high performance, whereas yellow indicates a baseline performance (adapted from de Boer et al., 2022 [52]).
Table 2. Initial qualitative comparison of AOP and GAC based on preliminary energy and cost estimates for a system processing 400 m3/h over 15 years. The GAC is assumed to be constructed in-flow (therefore energy demands are primarily resulting from the compressor used for GAC cleaning). OPEX costs consider the maintenance and repair costs, including replacement of CAPEX part. Green indicates a high performance, whereas yellow indicates a baseline performance (adapted from de Boer et al., 2022 [52]).
AOPGAC
Micropollutant removal efficiency
Energy demand
Adaptability
Waste amount
CAPEX
OPEX
Energy for reagent
(H2O2 or activated carbon production)
Table
Table 3. Energy requirements and costs of the AOP system according to various H2O2 and UV doses for one year assuming 100% running time at a flow rate of 417 m3/h and 65% transmittance.
Table 3. Energy requirements and costs of the AOP system according to various H2O2 and UV doses for one year assuming 100% running time at a flow rate of 417 m3/h and 65% transmittance.
H2O2 (ppm)203040
UV (kJ/m2)5107.55
H2O2 (kg/m3)0.020.020.030.04
H2O2 (EUR/m3)€ 0.015€ 0.015€ 0.022€ 0.029
Energy kWh/m30.270.540.410.27
Energy (EUR/m3)€ 0.08€ 0.16€ 0.12€ 0.08
Total Energy for AOP for 1 year (MWh/year)98619731498986
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Sturm, M.T.; Myers, E.; Schober, D.; Thege, C.; Korzin, A.; Schuhen, K. Adaptable Process Design as a Key for Sustainability Upgrades in Wastewater Treatment: Comparative Study on the Removal of Micropollutants by Advanced Oxidation and Granular Activated Carbon Processing at a German Municipal Wastewater Treatment Plant. Sustainability 2022, 14, 11605. https://doi.org/10.3390/su141811605

AMA Style

Sturm MT, Myers E, Schober D, Thege C, Korzin A, Schuhen K. Adaptable Process Design as a Key for Sustainability Upgrades in Wastewater Treatment: Comparative Study on the Removal of Micropollutants by Advanced Oxidation and Granular Activated Carbon Processing at a German Municipal Wastewater Treatment Plant. Sustainability. 2022; 14(18):11605. https://doi.org/10.3390/su141811605

Chicago/Turabian Style

Sturm, Michael Toni, Erika Myers, Dennis Schober, Clara Thege, Anika Korzin, and Katrin Schuhen. 2022. "Adaptable Process Design as a Key for Sustainability Upgrades in Wastewater Treatment: Comparative Study on the Removal of Micropollutants by Advanced Oxidation and Granular Activated Carbon Processing at a German Municipal Wastewater Treatment Plant" Sustainability 14, no. 18: 11605. https://doi.org/10.3390/su141811605

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