Spectrophotometric Polyvinyl Alcohol Detection and Validation in Wastewater Streams: From Lab to Process Control

Academic Editor: Christos S. Akratos Received: 14 November 2025 Revised: 2 December 2025 Accepted: 4 December 2025 Published: 6 December 2025 Citation: Sturm, M.T.; Korzin, A.; Ronsse, P.; Kormelinck, K.G.; Myers, E.; Zernikel, O.; Schober, D.; Schuhen, K. Spectrophotometric Polyvinyl Alcohol Detection and Validation in Wastewater Streams: From Lab to Process Control. Water 2025,17, 3465. https://doi.org/10.3390/w17243465 Copyright: © 2025 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/ licenses/by/4.0/). Article Spectrophotometric Polyvinyl Alcohol Detection and Validation in Wastewater Streams: From Lab to Process Control Michael Toni Sturm 1 , Anika Korzin 1 , Pieter Ronsse 1 , Kaspar Groot Kormelinck 2 , Erika Myers 1 , Oleg Zernikel 1 , Dennis Schober 1and Katrin Schuhen 1,* 1Wasser 3.0 gGmbH, Neufeldstr. 17a-19a, 76187 Karlsruhe, Germany 2Van Remmen UV Technology, Hooglandweg 3a, 8131 TE Wijhe, The Netherlands *Correspondence: [email protected]; Tel.: +49-721-15-65-95-93 Abstract Polyvinyl alcohol (PVA) is increasingly encountered in wastewater, yet reliable quantification and effective removal remain challenging. A colorimetric method for PVA quantification was validated, demonstrating excellent linearity and recoveries of 100.6 ± 2.8%. Limits were established at a limit of detection (LOD) of 1.28 mg/L and a limit of quantification (LOQ) of 1.8 mg/L. Accuracy was influenced by the PVA type, with errors reaching up to 42% due to variations in molecular weight and degree of hydrolyzation affecting the color complex. Consequently, polymer-specific calibration is advised. Analytical precision required strict temperature control and exact reaction times, and potential matrix interferences in wastewater should be assessed prior to application. PVA removal was evaluated using an AOP process based on hydrogen peroxide (H 2 O 2 ) and UV-C irradiation. Increasing the H 2 O 2 /PVA ratio beyond 1:1 provided only marginal improvements, whereas increasing the UV-C dose was more impactful. A 1:1 H 2 O 2 /PVA ratio was sufficient even at PVA concentrations up to 5 g/L. Optimal UV-C doses were 7.5–12.5 kJ/m 2 ; higher doses yielded only marginal additional removal. The colorimetric method was suitable for laboratory trials. A pilot-scale treatment of industrial wastewater applied microplastic agglomeration with organosilanes followed by granular activated carbon (GAC) treatment, which reduced PVA from an average of 24.2 mg/L to 7.4 mg/L, achieving ~65% removal, while microplastic removal reached 99.1%. Keywords: polyvinyl alcohol; colorimetric detection; wastewater treatment; advanced oxidation process; microplastics; activated carbon 1. Introduction Polyvinyl alcohol (PVA) represents a group of water-soluble synthetic polymer (WSSP) widely used across industrial sectors—including textiles, paper production, and adhesives—as well as in a variety of household products such as laundry detergent pods and dishwashing tablets [ 1 ]. The global annual PVA production exceeds 650,000 tonnes, and due to its widespread consumption and diverse applications, substantial amounts of PVA are released into wastewater systems [ 2 ]. In 2018, PVA was identified as one of the most ubiquitous pollutants in wastewater, representing a significant and growing environmental challenge [3]. The microbial biodegradability of PVA is complex and determined partially by its molecular structure, in particular the degree of hydrolysis (DH) and the molecular weight Water 2025,17, 3465 https://doi.org/10.3390/w17243465 Water 2025,17, 3465 2 of 19 (MW) [ 4 ]. The DH has been found to impact PVA mineralization, whereby residual acetate groups (representing a lower DH) facilitate the initial penetration of water and the polymer’s breakdown into smaller chains. In general, a higher DH leads to reduced water solubility [ 4 ]. Some studies have found that PVA’s MW does not impact biodegradability, whereas other studies have found a high MW to inhibit degradation [ 3 , 5 ]. Overall, the highest degradation rates are found in PVA samples with a low MW and high DH, suggesting that the initial depolymerization to short chains is a critical step for microbial uptake and subsequent breakdown [6,7]. Conventional wastewater treatment plants (WWTPs) are generally ineffective at achieving complete PVA removal. Studies have found that approximately 76.7% of PVA remains undegraded after conventional treatment, with the majority discharged into the environment via sewage sludge (61%) and the aqueous effluent (15.7%) [ 7 ]. Although PVA is often considered a biodegradable polymer, it only degrades slowly and under very specific conditions that are rarely met in the environment or within WWTPs [ 7 , 8 ]. The biodegradability of wastewater is commonly evaluated using biodegradability indices (BIs), such as the ratio between its five-day biochemical oxygen demand (BOD5) to chemical oxygen demand (COD). A BOD5/COD ≥ 0.5 indicates the wastewater is biodegradable; however, PVA has a ratio of only 0.11. Consequently, PVA largely passes through WWTPs unaltered, leading to its accumulation in aquatic ecosystems [3]. Although studies have found the oral toxicity of PVA to be low, indirect ecological risks arise from its environmental persistence and fate through various pathways [ 3 , 9 ]. In particular, PVA can contribute to foam formation in low water volumes, inhibiting oxygen transfer and potentially inducing hypoxic conditions by impeding gas exchange at the water surface [ 10 , 11 ]. Furthermore, due to its hydrophilic nature, PVA may adsorb hazardous substances such as heavy metals or organic contaminants, thereby facilitating their bioaccumulation and transfer through aquatic food webs [10,11]. Therefore, effective wastewater management requires monitoring of PVA contamination levels and treatment performance [ 12 ]. Without accurate data, environmental risks and potential ecotoxicological impacts cannot be properly assessed [ 10 ]. In addition, the efficiency of removal technologies must be systematically controlled and quantified [5]. Given PVA’s persistence and potential adverse environmental impacts, it is critical to understand and identify effective removal technologies available for implementation at WWTPs. Common strategies include advanced oxidation processes (AOPs), membrane filtration, and improved biological treatments, each with associated pros and challenges related to efficiency, cost, and complexity, thereby influencing their feasibility for large-scale adoption. AOPs in particular are increasingly recognized as sustainable treatment technologies for degrading organic contaminants in wastewater. Among these, the UV/H 2 O 2 process stands out as a particularly effective approach for PVA degradation, particularly as a pretreatment prior to biological processes, primarily due to its utilization of easily accessible reagents, operation under ambient conditions without the need for elevated temperature or pressure, and its advantage of not producing sludge or secondary waste streams that require subsequent treatment [3]. Previous studies have found an interaction between the H 2 O 2 dosage and the influent PVA concentration in relation to the PVA degradation, with an optimal H 2 O 2 -to-PVA mass ratio of 1:1 and PVA removal efficiencies of up to 98% [ 13 – 15 ]. However, many AOPs have so far only been investigated and applied at the laboratory scale. The degradation efficiency of PVA can vary considerably depending on the wastewater characteristics and operational conditions in real-world applications, and until now, UV/H 2 O 2 has been found to be more economically feasible for improving biological degradability (BOD/COD ratio) rather Water 2025,17, 3465 3 of 19 than achieving complete TOC removal [ 16 ]. In the first step, PVA chains are oxidized and split, while complete oxidative degradation ultimately leads to complete mineralization of PVA [17]. PVA removal through adsorption to silica oxides has also shown potential, with polymer size and hydrolysis percentage leading to subtle differences in patterns of adsorption [ 18 ]. Previous studies on the absorption of PVA on Fuller’s earth exhibited the formation of hydrogen bonds between the OH groups of PVA and aluminols, silanols, and carboxylate ions of the organic matter in the Fuller’s earth [ 19 ]. Adsorption onto the silanol groups of silica gels has also been described in previous PVA removal studies [ 20 ]. A similar mechanism may thus potentially bind PVA to the silanol groups of hybrid silicas, incorporating it into the formed agglomerates. An organosilane-based agglomeration method originally designed for microplastic (MP) removal together with granular activated carbon (GAC), may therefore have potential for PVA removal. Effective process control and environmental management necessitate consistent and reliable monitoring. PVA is typically monitored in wastewater using analytical techniques such as spectrophotometry, High-Performance Liquid Chromatography (HPLC), and total organic carbon (TOC) analysis. For routine PVA monitoring, spectrophotometry (colorimetric method), is typically used, as it is simple, non-destructive, inexpensive, and can detect PVA at low concentrations. This method involves the interaction of PVA and an iodine-borate solution, which forms a blue-colored complex. By measuring the absorbance of this color at a specific wavelength, the amount of PVA can be quantified. However, this requires frequent calibration, and false positives may result from interfering starches or sugars if present in the solution [21]. The objective of this study was to develop and evaluate a photometric method for the detection of polyvinyl alcohol (PVA) in aqueous systems. The method was first tested and validated under controlled laboratory conditions to assess its accuracy and reliability. Following this evaluation, the method was applied in laboratory-scale experiments investigating PVA removal using advanced oxidation processes (AOPs) with stock solutions prepared in demineralized water. This preliminary study was intended to enable later attempts to remove PVA from wastewater and simultaneously test the applicability of the measurement method as a case study. In addition, the applicability of the photometric method was examined in a pilot-scale treatment system. This system employed organosilane-based agglomeration, originally designed for microplastic (MP) removal, in combination with granular activated carbon (GAC). The pilot study aimed to explore whether this treatment approach could also contribute to PVA removal. Overall, the study sought to (i) establish a robust analytical tool for monitoring PVA concentrations, (ii) apply the method to assess removal efficiencies in laboratory-scale AOP experiments, and (iii) evaluate its suitability for monitoring PVA removal in pilotscale treatment processes that combine organosilane-based agglomeration and adsorption (Figure 1). Water 2025,17, 3465 4 of 19 Figure 1. Overview of PVA detection method validation and application in different technology environments. 2. Materials and Methods 2.1. PVA Analytics The method is based on the work of Procházková et al. 2013, with optimized reaction times and reaction process for more reliable results [ 21 ]. It was adapted for the analysis of known and unknown water-soluble polymers and PVA [22,23]. 2.1.1. Equipment and Chemicals Spectrophotometric measurements were conducted using a Nanocolor UV/VIS II spectrophotometer (Macherey-Nagel, Düren, Germany) with a wavelength range of 190–1100 nm . Sample preparation involved a Heidolph Hei-Tec magnetic stirrer with an integrated hotplate and pt1000 temperature sensor (100–1400 rpm) (Heidolph Scientific Products GmbH, Schwabach, Germany). Measurements were performed using 10 mm Rotilabo ® single-use polystyrene cuvettes (Makro type, 4.0 mL volume, dual optical windows, Carl Roth, Karlsruhe, Germany). Analytical-grade chemicals were sourced from abcr GmbH (Karlsruhe, Germany). Lugol’s solution (CAS 12298-68-9) containing 25 g/L potassium iodide and 12.7 g/L iodine was used as the chromogenic reagent. Boric acid (CAS 10043-35-3) was prepared at a concentration of 40 g/L. WSSP solutions were freshly prepared daily. The PVA standard was Mowiol ® 28-99 (CAS 9002-89-5) with a molecular weight of approximately 145,000 Da unless stated otherwise. 2.1.2. Preparation of Standard Solution To prepare the standard solution, 1 g of PVA was added to a 1 L volumetric flask. Approximately 800 mL of VE water was introduced, followed by a magnetic stirring fish. The mixture was heated to 90 ◦ C while stirring at 300 rpm and maintained at this temperature for 15 min to ensure complete dissolution. The solution was then cooled in a refrigerator until it reached room temperature (21 ◦ C). After removing the stirring fish, the solution was diluted to exactly 1 L with VE water. A series of standard dilutions was subsequently prepared to span the desired measurement range. The concentration chosen for the calibration curve were 0, 10, 20, 35, 50, 100, 200, 300, 400, and 500 mg/L. To construct the calibration curve, the series of standard solutions was prepared following the standardized sample preparation protocol. Water 2025,17, 3465 5 of 19 2.1.3. Standard Protocol for Polyvinyl Alcohol Quantification in Water Each sample was prepared by adding 2.4 mL of sample to a test tube, followed by 9 mL of boric acid solution (40 g/L) and gentle shaking. Subsequently, 1.8 mL of Lugol’s solution (25 g/L KI + 12.7 g/L I 2 ) was added and mixed. After exactly 30 min, 3 mL of the reaction mixture was transferred into a cuvette for spectrophotometric analysis and measured at λmax. If a sample exhibited an absorbance value greater than 3, it was diluted appropriately and remeasured. 2.1.4. Determination of Optimal Measurement Wavelength (λmax) To determine the optimal measurement wavelength, three standard solutions were selected to represent low (A = 0–1), medium (A = 1–2), and high (A = 2–3) absorbance levels. For the standards, Mowiol®28-99 was used at concentrations of 50 mg/L, 100 mg/L, and 200 mg/L. For other water-soluble synthetic polymers (WSSPs), preliminary measurements might be necessary to find a suitable concentration. A reagent blank was prepared using deionized water. The samples and blanks were prepared following the standardized sample preparation protocol (Section 2.1.3). 2.1.5. Quality Assurance Measures The described color reaction, which forms a dark-blue to deep-green complex, is influenced by various factors. It is therefore important that each step is carried out precisely and that all factors are consistent across analyses. Temperature directly influences the reaction kinetics and must be kept constant in all measurements. All substances and solutions must also be stored at this temperature or brought to the temperature before the experiments [ 21 ]. The color complex undergoes a constant reaction and thus changes its intensity depending on the reaction time; therefore, measuring times must be followed exactly. Before preparing WSSP stock solutions, check whether they are heat-sensitive or undergo chemical transformation when heated [ 24 , 25 ]. Care must be taken to ensure that the reagents used are accurately weighed and that the chemical supplier is reliable, as the reaction is strongly influenced by their concentration. In UV-VIS spectrometry, an absorbance of 3 (or the maximum measurable absorbance of the used UV-VIS spectrometer) should not be exceeded; otherwise, the linear measurement range will be exceeded, distorting the calibration curve [ 26 ]. All equipment and containers used were thoroughly cleaned and composed of glass or other non-water-soluble materials to prevent contamination. 2.2. Lab-Scale Optimization of PVA Removal with an AOP (UV/H2O2) UV-C illumination was performed in a standardized collimated beam apparatus according to biodosimetric testing protocols described in NEN [NEN-EN 14897+A1] and Ö [ÖNORM M 5873-1 20010301] norms for UV biodosimetric testing (Figure 2). The CB apparatus contains two 75 W low-pressure UV lamps, operated singly or in pairs, a UV-C sensor with a wide-angle diffuser, calibrated for 200–310 nm, a stirring motor for homogeneous mixing, an adjustable lamp-sample distance, and 8.7 cm plastic Petri dishes (for 50 mL sample volume). Lamp stability is validated by measuring UV-C output until stabilized with a variance < 2%/15 min, then the Petri factor (light distribution over the Petri dish) is measured with the same calibrated sensor to be 0.95 (<5% variance) over the illumination surface. With these factors included, the applied UV-C dose can be precise to a variability of <1%, which is significantly lower than the dose effects measurable in the Water 2025,17, 3465 6 of 19 analysis of target compounds or biology. A total of 50 mL of the sample are used in the CB apparatus, and the results are sent to an external laboratory for analysis (Figure 3). Figure 2. Schematic of collimated beam (CB) apparatus. Figure 3. Schematic of CB testing. Based on [ 14 , 15 ] and previous experiments, a first set of exploratory settings for UV-CAOP destruction was defined to be tested and further elaborated in subsequent research. The initial tests included varying UV-C-doses between 2500 and 25,000 J/m 2 , PVA-H 2 O 2 ratios of 1:1, 1:5, and 1:10, PVA concentrations between 250 mg/L and 5000 mg/L, testing a direct photolysis effect whereby no H 2 O 2 is added, and testing the direct oxidation effect in the absence of UV-C. Water 2025,17, 3465 7 of 19 Samples were taken in 100 mL brown glass bottles and stored and shipped frozen until analysis. 2.3. Removal of PVA and Microplastics via Pilot-Scale GAC and OrganosilaneInduced Agglomeration The pilot plant is a mobile wastewater treatment unit, which targets the simultaneous removal of high loads of MPs and PVA by agglomeration–fixation in combination with GAC. The wastewater originates from a plastic packaging industry and is shipped in two 1 m3IBC containers to the pilot plant. Wasser 3.0 PE-X ® is based on the “Clump & Skim” process for filter-free removal of MPs from water. The technology utilizes hybrid silica gels—silicon-based chemicals with various reactive groups. Water is placed in a reactor with a stirrer, creating a vortex. After adding abcr eco Wasser 3.0 PE-X ® industrial wastewater (AB930006, abcr GmbH, Karlsruhe, Germany), agglomeration–fixation and partial PVA aggregation take place. The purified wastewater and the agglomerates formed are discharged (separation unit) and separated from each other. The purified wastewater then flows from the filtrate tank into the fixed-bed reactor with modified activated carbon (GAC) for ten minutes. The base material is Jacobi, model: AquaSorb™2000, grain size: 8 × 16 mesh. It was filled with 175 L or 77 kg of GAC. The removal efficiency of the MP is monitored using Wasser 3.0’s standardized MP detection method by applying a novel fluorescent dye (abcr eco Wasser 3.0 detect mix MP-1, AB930015, abcr GmbH, Karlsruhe, Germany), which has been described in detail in Sturm et al. 2024 [27]. Samples were taken in 0.5 L brown glass bottles and stored cooled until analysis. Sampling was conducted at the inlet, after the belt filter, and in the GAC effluent during operation. 2.4. WSSP or PVA Removal Efficiency To calculate the efficiency of removing a PVA or WSSP from a sample, the absorbance of the sample before and after the removal process is measured. As the ratio of absorbance to concentration is linear, halving the concentration also halves the absorbance. Instead of absorbance, the measured concentration can also be used in this calculation. The concentration in mg/L can be calculated by inputting the data in the calibration curve. The formula for this is as follows: Removal efficiency (%) = Aoriginal sample −Aafter removal Aoriginal sample !×100 If the exact concentration is to be measured, the identity of the WSSP must first be known. A calibration curve can then be created with this WSSP. 3. Results and Discussion 3.1. Validation of the Detection Method 3.1.1. Calibration Curve, Detection Limits, and Recovery Rates A linear calibration curve (Figures 4and 5) for PVA was obtained and described by the regression equation c(PVA) = 207.5 × A + 1, where c is expressed in mg/L and A denotes the measured absorbance signal. The calibration exhibited excellent linearity across the investigated concentration range, as evidenced by a correlation coefficient of r = 0.999 and a coefficient of determination of R 2 = 0.998. The calculated limit of detection (LOD) is 1.28 mg/L and the limit of quantification (LOQ) 1.80 mg/L, determined according to the signal-to-noise approach (S/N = 3 for LOD and S/N = 10 for LOQ). These parameters Water 2025,17, 3465 8 of 19 confirm the reliability of the analytical procedure, ensuring its suitability for the quantitative determination of PVA for concentration ranges from 1.8 to 500 mg/L. In comparison, Procházková et al. 2013 found an LOD of 0.5 mg/L and LOQ of 1.7 mg/L for a calibration ranging from 5 to 100 mg/L Mowiol 28-99 [ 21 ]. Pritchard and Akintola 1971 could reach an LOD of 0.4 mg/L with a calibration curve ranging from 0 to 4 mg/L [28]. Figure 4. Depiction of the colorimetric reaction process for PVA concentrations ranging from left 0 to right 500 mg/L, according to the calibration curve. With increasing concentrations the color shifts from yellow over green to blue. The design of the calibration curve by the respective selection of standards causes high concentrations to disproportionately influence the curve. Looking at the respective recovery rates, the detection of low concentrations is reliable (Table 1). The recovery rate for 10 mg/L is 108.2 ± 9.9%, and for 20 mg/L it is 100.3 ± 2.3%. Thus, if focusing on PVA concentrations in the range of 10 mg/L or lower, a new calibration curve with concentrations adapted to the desired rage is recommended. Table 1. Measured recovery rates of different Mowiol ® 28-99 standards. The measurements were performed in triplicates. n.d. = not determined. c PVA Standard [mg/L] c PVA Measured [mg/L] Recovery Rate [%] 0 1 ±0.1 n.d. 10 10.8 ±1 108.2 ±9.9 20 20.1 ±0.5 100.3 ±2.3 35 35.1 ±0.9 100.2 ±2.4 50 49.3 ±1.2 98.6 ±2.5 100 98.2 ±3.1 98.2 ±3.1 200 200.7 ±7.4 100.3 ±3.7 300 299.9 ±12.3 100 ±4.1 400 398.8 ±11.7 99.7 ±2.9 500 501.1 ±15.8 100.2 ±3.2 Average 100.6 ±2.8 Water 2025,17, 3465 9 of 19 The average recovery rate of 100.6 ± 2.8% demonstrates the high accuracy and precision of the analytical method. It should be noted, however, that the calibration was performed in demineralized water, which limits the ability to assess the method’s robustness in different waters or wastewaters. The most relevant interfering factors in colorimetric measurements include turbidity or discoloration of the sample and chemical interference. For example, salts, oxidizing agents, and fluctuating pH values can influence the measurement results [ 21 , 29 ]. Turbid samples must always be filtered before analysis [ 21 ]. Starch has been identified as an important interfering substance in the iodine-containing reagents used here. This high precision and linearity of the calibration curve was reached by extensive preliminary tests. Quality assurance measures, including maintaining a constant temperature and accurate reaction time, are crucial factors in the colorimetric reaction process. Mixing the samples and color reagents with higher volumes in the mixing vessels instead of directly in the cuvettes also contributes to improved accuracy. In preliminary tests, there were also problems with inaccurate and inconsistent concentrations of chemicals for the color reaction from certain suppliers; thus, a reliable chemical supplier is essential for reliable longer-term test series. Figure 5. Calibration curve for PVA detection using Mowiol ® 28-99 standards in demineralized water with concentrations ranging from 10 to 500 mg/L. Three blanks and three repetitions per concentrations were measured. 3.1.2. Comparison of PVAs with Different Molecular Weights and Hydrolyzation PVAs can have various molecular weights and degrees of hybridization. As in environmental samples and in industrial wastewater, PVAs can be present in mixtures. Also, it is not always known which specific PVA is contained in the water sample. Therefore, the influence of molecular weight (Mw) and degree of hydrolyzation on the colorimetric quantification process was investigated. Results are displayed in Table 2and Figure 6. Water 2025,17, 3465 16 of 19 PVA-containing wastewaters showed a removal of 90% [ 43 ]. For biological degradation of PVA in textile wastewater, a removal of 42% is documented [ 16 ]. An anaerobic degradation reactor could remove 83.6 to 87.5% PVA in two days. As the MP removal performance was already evaluated in previous studies, MP was only quantified in test runs 3 and 8. MP contamination was reduced by 99.1% from an average of 829 mio. MP/L to 6.2 mio MP/L. The previous study found a reduction of 99.1% from 673 ± 183 mio MP/L to 5.8 ± 2.8 mio MP/L over a testing period of 5 weeks or 25 days, which aligns with the current results. In summary, the presented detection method can be used for process control in the demonstrated wastewater treatment process using organosilane-based MP agglomeration and GAC treatment. It provided important insights into possible overdosing of the agglomeration reagent and on the removal performance of the GAC, which showed the beginning of saturation in the two test runs, expressed in decreasing removal performance and the need for replacement. 4. Conclusions A straightforward colorimetric method was employed for the quantification of PVA. The technique demonstrated excellent linearity and yielded recovery rates of 100.6 ± 2.8%. The limit of detection (LOD) and limit of quantification (LOQ) were determined to be 1.28 mg/L and 1.8 mg/L, respectively. Calibration accuracy is influenced by the specific polymer used. For unknown polymers, error rates may reach up to 42%, primarily due to variations in molecular weight and degree of hydrolyzation influencing the color complex. It is advisable to apply polymer-specific calibration to ensure accurate detection. For accurate results, it is of high importance to have controlled temperatures and exact reaction times for the analytical procedure. Prior to application in wastewater analysis, potential interfering substances should be assessed and controlled. The efficiency of PVA removal using H 2 O 2 and UV-C irradiation was evaluated. Increasing the H 2 O 2 /PVA ratio beyond 1:1 resulted in only marginal improvements in removal efficiency, whereas increasing the UV-C dose proved more effective. A ratio of H 2 O 2 /PVA at 1:1 was sufficient for treatment, even at high PVA concentrations of up to 5 g/L. Optimal UV-C doses ranged between 7.5 and 12.5 kJ/m 2 , further increases in UV-C dose only marginally enhanced the removal performance. The colorimetric detection method was found to be suitable for laboratory-scale trials of PVA removal. However, it should be noted that PVA fragments containing fewer than 12 vinyl alcohol residues cannot be detected using this method. A pilot plant setup combining MP agglomeration and PVA removal with organosilanebased agglomeration followed by GAC achieved a reduction in PVA concentration from an average of 24.2 mg/L to 7.4 mg/L, corresponding to a removal efficiency of approximately 65%. Simultaneously, microplastic removal reached 99.1%. The PVA detection method was well applicable for process control, and filtration was necessary for turbid samples. The colorimetric detection method enabled monitoring of agglomeration reagent dosing and facilitated control of GAC saturation levels during operation. Author Contributions: Conceptualization, A.K., P.R., D.S., K.G.K. and K.S.; methodology, A.K., P.R., M.T.S., K.G.K. and K.S.; validation, M.T.S. and K.S.; formal analysis, A.K., P.R., M.T.S., K.G.K. and K.S.; investigation, P.R., A.K. and O.Z.; resources, K.S.; data curation, M.T.S., P.R. and K.S.; writing—original draft preparation, M.T.S., E.M. and K.S.; writing—review and editing, A.K., M.T.S., E.M. and K.S.; visualization, E.M. and M.T.S.; supervision, K.S.; project administration, K.S.; funding acquisition, K.S. All authors have read and agreed to the published version of the manuscript. Water 2025,17, 3465 17 of 19 Funding: The authors gratefully acknowledge the financial support of the Horizon Mission project UPSTREAM (GA 101112877), co-funded by the European Union and the UK Research and Innovation. This publication reflects the views only of the author, and the European Commission cannot be held responsible for any use that may be made of the information contained therein. Data Availability Statement: The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author. Acknowledgments: The authors thank abcr GmbH, Karlsruhe, Germany, for their project-related support and the discussion of the results. Conflicts of Interest: Authors Michael Toni Sturm, Anika Korzin, Pieter Ronsse, Erika Myers, Oleg Zernikel, Dennis Schober and Katrin Schuhen were employed by the company Wasser 3.0 gGmbH. Author Kaspar Groot Kormelinck was employed by the company Van Remmen UV Technology. 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