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Article

Optimising Chemical Treatment of Dairy Wastewater for Sustainable Protection of Karst Ecosystems

by
Aleksandar Šobot
1,*,
Sergej Gričar
2,3 and
Diana Bilić-Šobot
4
1
Faculty of Economics and Informatics, University of Novo Mesto, Na Loko 2, 8000 Novo mesto, Slovenia
2
Faculty of Business and Management Sciences, University of Novo Mesto, Na Loko 2, 8000 Novo mesto, Slovenia
3
Faculty of Tourism and Hospitality Management, University of Rijeka, 51410 Opatija, Croatia
4
Pivka Perutninarstvo d.d., Kal 1, 6257 Pivka, Slovenia
*
Author to whom correspondence should be addressed.
Sustainability 2025, 17(23), 10556; https://doi.org/10.3390/su172310556
Submission received: 13 October 2025 / Revised: 2 November 2025 / Accepted: 7 November 2025 / Published: 25 November 2025
(This article belongs to the Special Issue Sustainable Solutions for Wastewater Treatment: Innovations and Applications)
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Versions Notes

Abstract

Slovenia is among the few countries where the olm, Proteus anguinus, is found, with its habitat largely coinciding with Natura 2000 sites. In these regions, various agricultural and food-processing activities, including the dairy industry, have developed. Krepko, a dairy facility, is situated directly within the olm’s habitat. Current legislation prohibits the direct discharge of dairy wastewater into the environment and mandates prior treatment. This study examined the primary treatment phase, specifically the chemical processing steps of neutralisation, coagulation, and flocculation. Field jar tests, pH measurements, and laboratory analyses of chemical oxygen demand (COD) were employed to assess the effectiveness of various chemicals. The findings indicate that sodium hydroxide with higher molarity enables faster and more stable neutralization, while polyaluminum coagulants and acidic flocculants are more effective than traditional reagents in reducing COD. The optimised chemical treatment process substantially reduced the organic load of wastewater and, consequently, the potential impacts on karst habitats. The improved treatment system represents a significant advancement in reducing pressure on karst water resources and protecting the habitat of the olm, thereby contributing to the achievement of the United Nations Sustainable Development Goals, particularly SDG 6 (Clean Water and Sanitation), SDG 12 (Responsible Consumption and Production), and SDG 15 (Life on Land).

1. Introduction

Managing industrial wastewater is a critical challenge for global environmental sustainability, especially in sectors with high organic waste, such as the dairy industry. Proper treatment is crucial for meeting regulatory requirements and safeguarding aquatic ecosystems and groundwater in the long term. In Slovenia, the dairy company Krepko has committed to environmental responsibility by constantly enhancing production efficiency and wastewater treatment practices aligned with sustainable development principles. Its location in the karst region, home to the endangered and highly sensitive Proteus anguinus, highlights the importance of using advanced, eco-friendly treatment technologies.
From a policy standpoint, European Union (EU) laws such as the Water Framework Directive 2000/60/EC [1] and the Habitats Directive 92/43/EEC [2], along with Slovenian environmental standards, mandate that wastewater from the food-processing industry must be treated before discharge. These legal regulations support the United Nations Sustainable Development Goals (SDGs), especially SDG 6 (Clean Water and Sanitation), SDG 12 (Responsible Consumption and Production), and SDG 15 (Life on Land). Together, they emphasise the importance of clean water, sustainable industrial practices, and biodiversity conservation.
Scientifically, the chemical phase of wastewater treatment, including neutralization, coagulation, and flocculation—is crucial for the concentration of lowering organic materials and stabilizing the hydrogen ion concentration (pH) of hydrogen ions (H) before biological processes. Nonetheless, the success of these steps relies significantly on choosing the right chemical reagents and their amounts. Despite advances in technology, there remains limited empirical evidence on how to optimally combine neutralisers, coagulants, and flocculants to boost process efficiency while safeguarding sensitive karst ecosystems.
The research question is: How can optimised chemical treatment of dairy wastewater enhance process efficiency while protecting karst habitats and aligning with the Sustainable Development Goals?
The objectives are to (i) assess how effective various chemicals are in neutralisation, coagulation, and flocculation processes; (ii) find the best reagent combination that ensures sustainable results; and (iii) evaluate how these efforts improve water quality and protect habitats within the SDG framework.

2. Literature Review and Research Hypotheses

2.1. Literature Review

The EU, through the Habitats Directive (92/43/EEC) and the Birds Directive (2009/147/EC), established the Natura 2000 network to protect the most critical habitats and species [3]. Slovenia has included 355 sites in this network, with karst systems playing a crucial role due to the high rock permeability, rapid underground flow, and limited self-purification capacity [4,5]. For these reasons, karst aquifers are incredibly vulnerable to pollution, as contaminants from the surface can quickly reach groundwater with minimal alteration [6]. Among the species susceptible to changes in water quality is the olm (Proteus anguinus), a critical bioindicator of karst underground ecosystems [7,8].
The olm, endemic to the Dinaric karst, requires extremely stable physicochemical conditions. Optimal habitat parameters include temperatures between 8 and 12 °C, neutral to slightly acidic pH values (6.5–7.5), and dissolved oxygen concentrations above 7 mg/L (≈90% saturation) [9]. These values are typical of pristine karst aquifers in southwestern Slovenia, such as the Postojna and Planina Cave systems, where groundwater remains cold, oxygen-rich, and chemically stable year-round. Long-term monitoring, however, indicates gradual changes in certain parameters. For example, the authors’ in situ measurements show that pH occasionally drops below 6.3, while dissolved oxygen levels decrease to 6 mg/L or lower, particularly during periods of increased organic load. At the same time, nitrate concentrations exceeding 10 mg/L have been recorded. Relevant studies [10,11] report the influence of anthropogenic and environmental changes and the associated changes in environmental parameters important to the habitat of Proteus anguinus.
Such deviations from optimal conditions pose a serious threat to Proteus anguinus, whose metabolism, feeding activity, and reproduction depend on constant environmental parameters. Even minor pH reductions can increase metal solubility and toxicity, while lower oxygen levels impair respiration through external gills and skin. Prolonged exposure to organic and chemical pollutants leads to habitat degradation, loss of food sources, and population decline, making the species an early warning indicator of groundwater contamination. Maintaining the natural range of these parameters is therefore essential not only for the conservation of Proteus anguinus but also for the overall ecological integrity of karst aquifers.
The greatest pressures on the quality of karst waters are caused by agriculture, hospitality and tourism [12], and the food-processing industry, particularly the dairy sector [13]. Dairy wastewater contains high concentrations of organic substances, such as proteins, fats, and lactose, as well as nitrogen and phosphorus compounds and various detergents and disinfectants [14,15]. Such effluents increase chemical and biochemical oxygen demand, lower dissolved oxygen concentrations, alter pH, and can lead to eutrophication [16,17]. Due to karst characteristics, these impacts are not confined to local areas but spread through underground networks, threatening entire ecosystems [18].
Adequate wastewater treatment is therefore crucial for protecting karst habitats. In the initial treatment phase, chemical processing—including neutralisation, coagulation, and flocculation—is decisive [19,20]. Neutralisation ensures an appropriate pH within the range of 6.5–7.5, coagulation destabilises particles and enables their removal, while flocculation binds them into larger aggregates that settle and are eliminated [21,22]. Together, these processes reduce organic load, decrease COD, and improve water quality. Their efficiency strongly depends on the selection of chemicals, their composition, concentration, and application conditions [23]. Therefore, several combinations were tested in this study to determine the most effective, economically viable, and environmentally acceptable solutions.

2.2. Research Path and Hypotheses Development

The objectives of the research were to analyse the efficiency of different chemicals in the neutralisation, coagulation, and flocculation of dairy wastewater, to compare the achieved results in terms of pH regulation and COD reduction, and to assess the contribution of optimised procedures to improved water quality and, indirectly, to the protection of karst habitats. The following hypotheses were formulated: (a) chemicals with higher molarity enable faster and more efficient neutralisation; (b) polyaluminum coagulants and acidic flocculants are more effective in reducing COD than traditional chemicals; (c) an optimised chemical treatment process significantly reduces the load on karst waters and contributes to habitat protection.
The dairy industry produces large quantities of wastewater containing fats, proteins, lactose, detergents, and cleaning agents. For this reason, appropriate pretreatment is necessary, where neutralisation, coagulation, and flocculation play a crucial role [24,25]. The first treatment step is often neutralisation, since the pH of dairy wastewater fluctuates between acidic and alkaline values, which can affect the efficiency of subsequent processes. In industrial practice, sodium hydroxide of different concentrations is commonly used. At a 50% concentration, the effect is faster and smaller quantities of reagent are required, but handling is more demanding due to its higher causticity and greater risk to workers [26]. Conversely, 30% Sodium hydroxide (NaOH) is safer to use, allows more controlled pH adjustment, and reduces the risk of oversaturation and rapid neutralisation, but requires larger volumes of chemicals to achieve the same effect [27].
After neutralisation, coagulation occurs, which is essential for removing colloidal particles, fats, and proteins. Aluminium salts are most commonly used, though there are significant differences among formulations. Aluminium chloride (30–40%) is a traditional coagulant that effectively destabilises colloids but is sensitive to pH fluctuations and may result in elevated aluminium concentrations in treated water [28]. An alternative is polyaluminum chloride (PAC), which is more stable, functions over a wider pH range, and produces larger, denser flocs [29]. This improves sedimentation and reduces chemical consumption [30]. Studies have shown that PAC achieves higher efficiency in phosphorus and turbidity removal compared to classical aluminium chloride, while generating less sludge [31].
The final stage is flocculation, where destabilised particles aggregate into larger agglomerates. In the tests, two organic flocculants based on sulfamic and adipic acids were used at concentrations of 2.5% and 10%. Lower concentrations allow slower floc formation, suitable for wastewater with lower turbidity. In comparison, higher concentrations lead to faster, more intense aggregation, which is advantageous for highly loaded waters but may result in greater sludge volume [32,33]. Citric acid was added as a synergist because it enhances cation binding and increases floc stability, thereby improving the removal of organic matter and nutrients [34]. Research indicates that combining sulfamic or adipic acid with citric acid increases removal efficiency by more than 15% compared to using individual reagents [35].
Figure 1 depicts two process tanks, integral components of the chemical wastewater treatment system used in the dairy industry. Raw wastewater enters the lower tank at the upper right side for initial treatment.
A neutralising agent is introduced via a white inlet pipe, initiating the neutralisation process, which is continuously monitored and regulated by an automatic pH meter. Subsequently, the neutralised water flows to the second compartment of the same tank on the lower left side, where a coagulant is added through a white pipe to facilitate coagulation. The upper circular tank represents the subsequent treatment stage, receiving neutralised and coagulated wastewater. In this compartment, a flocculant is added to promote flocculation, leading to the formation and separation of flocs from the treated water. The resulting flocs or sludge are discharged into a sludge tank. At the same time, the clarified water is directed to secondary (biological) and tertiary (disinfection) treatment stages before being discharged into the environment. The process diagram is shown in Figure 2.

3. Materials and Methods

This section describes the materials, equipment, and analytical methods employed to assess the efficiency of chemical processes in dairy wastewater treatment. The approach was developed to ensure accuracy, reproducibility, and applicability to real industrial settings within sustainable water management practices. The chosen reagents and instruments represent standard industrial procedures, enabling direct comparison of different chemical solutions tested under controlled laboratory conditions.

3.1. Materials

The study analysed various chemicals for neutralisation, coagulation, and flocculation, forming the core of the chemical phase in wastewater treatment. This opened the way for more efficient and sustainable wastewater management practices, addressing the urgent need for improved environmental solutions.
For neutralisation, sodium hydroxide (NaOH) of different concentrations (50% and 30%) from two manufacturers was tested: Sotoplus 50% (Sotom d.o.o., Ljubljana, Slovenia) and Chemie NPK 30% (Chemie NPK d.o.o., Komenda, Slovenia). For coagulation, two reagents of different compositions were used: Kemiklar (Sotom d.o.o., Slovenia)—aluminium chloride (30–40%), and VTA Combiflock (VTA d.o.o., Rottenbach, Austria)—aluminium chloride with polyaluminum hydroxychloride (52–65%). For flocculation, two preparations based on sulfamic and adipic acids at different concentrations were tested: Acefloc (Sotom d.o.o., Slovenia), containing 2.5%, and VTA F98 (VTA d.o.o., Austria), containing 10% with added citric acid.

3.2. Methods

3.2.1. Instruments for pH Analysis

For field measurements of wastewater pH and temperature, portable measuring instruments were used, ensuring high accuracy, repeatability, and traceability of results. The purpose of using such instruments was to obtain reliable data on the efficiency of neutralisation processes and their impact on wastewater quality under real conditions.
Two internationally recognised instruments were employed:
  • Multi 3620 IDS (WTW, Weilheim, Germany) (Figure 3)—a multiparameter instrument designed for simultaneous measurement of various physico-chemical parameters, with pH and temperature being key to this study. The system enables the use of digital sensors (IDS—Intelligent Digital Sensors), providing automatic recognition, internal calibration, and data storage, thereby reducing measurement errors and ensuring easy traceability of procedures.
  • ProfiLine pH 3310 (WTW, Germany) (Figure 4)—a portable pH meter used as a control instrument for verifying the accuracy and repeatability of measurements. It is equipped with a robust electrode suitable for field measurements in demanding environments and an internal data logging system.
Both instruments were calibrated prior to measurements using multipoint calibration (standard buffers pH 4 and 7), in accordance with manufacturer instructions and applicable standards. During measurements, values were regularly checked with control standards, ensuring methodological accuracy and comparability of results. By employing two independent instruments, greater reliability and robustness of data were achieved, as results were compared and validated through cross-validation. This approach enabled a detailed assessment of wastewater neutralisation efficiency and contributed to the scientific and technical soundness of the study.

3.2.2. Jar Tests

The jar test was the central laboratory method for evaluating the efficiency of coagulants, flocculants, and other auxiliary chemicals used in wastewater treatment. The method simulates real conditions of coagulation and flocculation processes, allowing optimisation of operational parameters such as chemical dosage, reagent combinations, mixing time, and mixing intensity. This enables the desired purification effect, reduces chemical consumption, and improves process stability [36].
The jar test procedure was carried out in several successive phases, in accordance with standard methodological recommendations:
  • Preparation of wastewater samples—samples were homogenised and, if necessary, pretreated by basic laboratory procedures to remove coarse solids, ensuring comparable initial conditions. Wastewater from the Krepko dairy is directed into the treatment plant tank, where it is combined with other water collected on the same day. The treatment process initiates once the tank reaches a volume of 60 m3. This procedure ensures homogenization of the water and stabilization of the COD levels.
  • Preparation of chemical solutions—coagulants and flocculants were prepared according to manufacturer instructions and experimental design requirements.
  • Chemical dosing—prepared solutions were added to individual wastewater samples.
  • Mixing—rapid mixing was first applied to achieve even dispersal of coagulants, followed by slow mixing to promote the formation of stable flocs.
  • Sedimentation and reaction time—after mixing, samples were left to stand for at least 30 min to allow complete reactions and settling of flocculated structures.
  • Efficiency evaluation—process efficiency was assessed visually (floc formation and size, sedimentation rate, and amount of sediment formed).
For the experiments, a four-position portable jar test apparatus (A&F Machine Products, 120 VAC, Nova-Tech International, Inc., Kingwood, TX, USA) (Figure 5) was used, enabling simultaneous treatment of multiple samples under different experimental conditions. This allowed direct comparison of water response to various dosages and combinations of chemicals.
Additional control tests were performed using a magnetic stirrer with heating (Serie MR 3001, IKA-Werke GmbH & Co. KG, Staufen im Breisgau, Germany) (Figure 6) and a digital five-position IKA RO magnetic stirrer (IKA-Werke GmbH & Co. KG, Staufen im Breisgau, Germany) without heating, ensuring the repeatability of experimental conditions and the validation of results.
Thus, the jar test served as a key tool for experimentally determining optimal operating conditions and for understanding interactions among different chemical agents in the wastewater treatment process.

3.2.3. Laboratory Analysis of Chemical Oxygen Demand

To evaluate the efficiency of different chemical combinations in wastewater treatment, a detailed laboratory analysis of COD was conducted, as this parameter is one of the most commonly used indicators of organic load. The method is based on the oxidation of organic and inorganic reductants in the sample with a potent oxidising agent, and the result expresses the amount of oxygen (mg O2/L) required to degrade the present compounds.
In this study, a 30-day continuous sampling period was used, during which both raw wastewater and chemically treated water were analysed. This approach enabled comprehensive monitoring of wastewater composition variability, thereby providing a more realistic assessment of the effectiveness of the applied reagents.
For COD determination, Nanocolor cuvette tests (Macherey-Nagel) were employed. These allow standardised and reproducible sample preparation in hermetically sealed cuvettes, reducing the risk of contamination and handling errors. Analyses were carried out using photometric measuring devices Vario Mini and PF-12 Plus, designed for precise concentration determination by spectral photometry. Instrument calibration was regularly verified using standard solutions, in line with methodological guidelines.
Special attention was given to the comparative analysis of results across different chemical combinations (coagulants, flocculants, neutralisers), enabling evaluation of their efficiency under various experimental conditions. The results were statistically processed to ensure validity and reliability, with potential anomalies identified and assessed.
Consideration of the specific composition of raw wastewater (e.g., variations in organic content, pH, and the presence of inorganic pollutants) further enhanced the credibility and robustness of the analysis, enabling a realistic assessment of how individual chemical combinations perform in practice (Figure 7).
Thus, laboratory COD analysis served as a key indicator for evaluating optimal chemical treatment, providing both quantitative comparisons of reagent efficiency and an assessment of their potential to reduce organic loads in wastewater (Figure 8).

3.3. Data Collection, Processing, and Presentation

The collected experimental data were systematically organised, processed, and presented in tables, enabling clear, transparent presentation of results and their subsequent interpretation. Such an approach was essential for comparative analysis and for ensuring traceability of procedures when evaluating the effectiveness of applied chemicals in wastewater treatment processes.
In addition to the introductory presentation of results, descriptive statistics were performed, including key parameters (arithmetic mean, standard deviation, minimum, maximum, and quartiles). Statistical significance/differences were determined using the t-test. This approach provided a more in-depth assessment of variability among samples and offered a stronger basis for comparing reagent efficiency.
The first table presented the pH neutralisation values obtained from experiments with different neutralisers. Based on these results, the most effective neutralising agent was identified and subsequently used in the subsequent phases of laboratory tests.
The results of coagulation and flocculation were presented in two separate tables. These compared the effects of different commercially available products, focusing on parameters such as floc size and stability, sedimentation rate, and final clarity of the supernatant water. On this basis, the most effective coagulants and flocculants suitable for further use were selected.
In the third table, a direct comparison of two flocculants was carried out to confirm the optimal preparation. The results clearly indicated which reagent performed best in terms of both flocculation rate and aggregate stability.
Additional chemical combinations were evaluated for their impact on COD over 30 days. During this interval, influent COD levels fluctuated in response to daily production activities, including the processing of cheese, butter, kefir, and milk. The minimum recorded influent COD values ranged from 801 to 900 mg per liter, while the maximum values ranged from 1401 to 1500 mg per liter. Water treatment and purification processes were conducted on-site and completed within the same day, with required measurements performed in the facility’s laboratory on the day of treatment.
This long-term approach provided a more realistic assessment of treatment efficiency and reduced the influence of short-term fluctuations in wastewater composition. The fourth table presented a comparison of COD results between previously used and newly tested chemicals.
Based on the complete dataset and descriptive statistical analysis, comments and discussion were prepared, linking the results to primary empirical findings and placing them in the context of secondary scientific sources and professional literature.

4. Results

The experimental results provide a detailed overview of the effectiveness of the various chemical reagents used for neutralisation, coagulation, and flocculation of dairy wastewater. The findings are organised sequentially based on the main treatment stages, accompanied by descriptive statistics, comparative analyses, and interpretive commentary to identify the most effective combinations and their environmental significance.

4.1. Neutralisation

Neutralisation presented in Table 1 is a key stage in dairy wastewater treatment, as pH stabilisation directly affects the efficiency of subsequent processes, particularly coagulation, flocculation, and biological treatment.
Explanation of Table 1. The time interval ranges from 0 to 10 min. Sample 1 is Sotoplus 50%, Sample 2 is Chemie NPK 30%. The pH value is shown from the initial state of raw water (3.5) throughout the entire course of the reaction. The target value is pH 7, representing the key goal guiding the process. Both samples used the same raw water, with equal amounts of neutraliser added to adjust the pH. Mixing was performed identically for both samples. For NaOH neutralisation, only two commercial concentrations (30% and 50%) are available on the Slovenian market. All tests employed control pairs, and no statistically significant differences were observed. Consequently, further comparisons focused on two representative and economically rational cases to determine the optimal variant. Table 2 presents the descriptive statistics.
Table 2 data indicate that both neutralisers reached the target pH of 7.0, but they differed in stabilisation speed and consistency. Sotoplus 50% neutralised more quickly and showed more stable results than Chemie NPK 30%, suggesting it is more efficient and better suited for industrial use. Therefore, Table 3 presents a comparative analysis between the two samples.
The results (Table 3) did not show statistically significant differences (p = 0.59), but they indicate that Sotoplus 50% achieved faster and more stable neutralisation. The average pH value for this sample (6.13) was closer to the optimal range for subsequent processes (6.5–7.5), with neutral pH reached within two minutes and then stably maintained until the end of measurements (Table 2). By contrast, Chemie NPK 30% achieved a lower average (5.65) and required four minutes to stabilise at neutral pH. The standard deviation for NPK (1.55) was slightly higher than for Sotoplus (1.46), indicating greater fluctuations between measurements and, consequently, lower process stability. Such instability in real treatment plants can lead to more challenging process control and increased chemical consumption to achieve the desired pH. It is also noteworthy that Sotoplus provided a smoother pH increase, ensuring a seamless transition into the optimal range for coagulant and flocculant efficiency. This confirms that the choice of neutraliser is directly linked not only to speed but also to the overall effectiveness of subsequent treatment stages.
Overall, these results suggest that Sotoplus 50% represents a more reliable solution for rapid system stabilisation. In comparison, the use of Chemie NPK 30% requires more time and introduces greater variability, which could pose challenges in industrial plants with high, fluctuating loads.

4.2. Coagulation and Flocculation

The coagulation and flocculation stage is crucial for lowering turbidity and organic content in dairy wastewater by facilitating the aggregation and removal of colloidal particles. This section discusses experimental results that compare various combinations of neutralisers, coagulants, and flocculants, highlighting their impact on reaction time, floc quality, and overall process efficiency.
Explanation of Table 4. The time interval ranges from 0 to 10 min. Four samples were tested with high precision. Each sample contained the same volume of wastewater (800 ML), the same amount of neutraliser (80 ML), coagulant (40 ML), and flocculant (20 ML). It is important to emphasise that the pH value was 7, a key parameter in our experiment. The temperature remained constant (20 °C). Table 5 presents the descriptive statistics for flocculation.
Table 5 highlights significant differences in flocculation efficiency across the reagent combinations tested. Samples with the VTA coagulant and flocculant exhibited higher average values, suggesting faster floc formation and more stable aggregation than formulations that use only Sotom chemicals. Therefore, the comparison between samples is presented in Table 6.
The results in Table 4 and Table 5 clearly demonstrate statistical differences between reagent combinations. The most effective was Sample 2, which, with the highest mean (2.18), achieved rapid flocculation improvement: already by the third minute it reached a “good” rating, and by the fifth minute the maximum “excellent” rating. The standard deviation (1.08) confirms that the process was relatively stable throughout the test.
Sample 3 (mean 1.18) and Sample 4 (0.82) exhibited slower responses, achieving only intermediate values, which indicates limited efficiency of their reagent combinations. Interestingly, toward the end of the test, both reached a “good” rating, meaning that with extended mixing time, they can achieve satisfactory flocculation, albeit with lower kinetic efficiency.
The weakest was Sample 1 (mean 0.55), which mostly remained at the “initial” stage. The low mean and standard deviation (0.52) confirm that this reagent combination was insufficient for effective destabilisation of colloidal particles and formation of stable flocs. It is also notable that Sample 2 showed much more consistent progress, while Samples 3 and 4 produced more scattered results. This reflects the greater process stability of the optimised reagent combination.
The results of pairwise comparisons (Table 6) showed statistically significant differences between some groups. The lowest mean value was observed in Sample 1 (M = 0.55, SD = 0.52), while Sample 2 had the highest mean (M = 2.18, SD = 1.08). The pairwise t-test showed a highly significant difference between Sample 1 and Sample 2 (p = 0.0007) and between Sample 1 and Sample 3 (p = 0.0299). Further significant differences were found between Sample 2 and Sample 3 (p = 0.0234) and between Sample 2 and Sample 4 (p = 0.0049). Differences between Sample 1 and Sample 4, and between Sample 3 and Sample 4, were not statistically significant (p > 0.05).

4.3. Flocculation

Flocculation (Table 7) is the final and crucial step in the chemical treatment of dairy wastewater, where destabilised particles form larger, settleable flocs. This section shows the results of comparative tests with various flocculants, emphasising reaction behaviour, floc stability, and their impact on overall treatment effectiveness.
Explanation of Table 7. The time interval ranged from 0 to 10 min. Sample 1 used the VTA F98 flocculant, and Sample 2 the Sotom flocculant. Both samples were treated with the same wastewater, the same amount of VTA F98 coagulant (Table 8), and the same amount of Sotom flocculant. Temperature and electromagnetic mixing were kept constant.
The statistical summary in Table 8 clearly shows differences in flocculation performance between the two reagents. VTA F98 has a higher mean value and a wider reaction range, indicating it is more efficient and agglomerates faster than the Sotom flocculant. Therefore, the comparative analysis of samples is shown in Table 9.
The results in Table 8 and Table 9 clearly demonstrate that Sample 1 (VTA F98) was substantially more effective than Sample 2 (Sotom Acefloc). The mean for VTA F98 (2.18) was nearly twice that of Sotom (1.18), reflecting faster and more stable flocculation kinetics. Within three minutes, VTA F98 reached the “good” level and progressed to “excellent” by the fifth minute, maintaining this level until the end of the test. The standard deviation (1.08) indicates moderate variability but with a clear trend toward stabilisation.
The Sotom sample showed slower dynamics. Its mean (1.18) and lower quartiles confirm that it remained mostly at the “initial” stage, only reaching “good” at the 10th minute. The lower standard deviation (0.75) indicates that the weaker response was consistent, with slight improvement in the early stages. The binary variable (0.82) indicates that a positive reaction occurred in more than 80% of measurements, although there are significant differences in dynamics between the two flocculants. VTA F98 enabled rapid system stabilisation, while Sotom required more time to achieve a satisfactory effect.
The pairwise comparisons (Table 9) showed that Sample 1 (VTA F98) differed significantly from Sample 2 (Sotom) (p = 0.0214), and highly significantly from the binary Reaction variable (p = 0.0018). The difference between Sample 2 (Sotom) and the Reaction variable was not statistically significant (p = 0.1801).

4.4. Chemical Oxygen Demand (COD)

The COD phase (Table 10) is a crucial step in chemical treatment of dairy wastewater, as it directly affects the effectiveness of suspended and colloidal particle removal. This section compares various reagent combinations, emphasising their effects on floc formation, process stability, and overall treatment effectiveness.
Explanation of Table 10. The table shows the input values of raw wastewater and the output values of treated water using old chemicals (neutraliser—Chemie NPK, coagulant—Sotom, flocculant—Sotom) and new chemicals (neutraliser—Sotom, coagulant—VTA, flocculant—VTA). The study spanned 30 days and identified seven distinct variations, each corresponding to a different sample.
Table 11 clearly shows a steady reduction in COD across all treatment scenarios, validating the role of chemical intervention in lowering the organic load of dairy wastewater. The comparison between traditional and optimised reagents reveals a noticeable improvement in treatment efficiency, indicating progress in technology and environmental sustainability aligned with development goals.
The analysis reveals a clear trend of COD reduction in both treatment processes, with new chemicals proving more effective. The average COD of raw wastewater was approximately 1150 mg/L, reduced to 850 mg/L with old chemicals and to 750 mg/L with new chemicals. This means the new reagents reduced the load by an additional 100 mg/L compared to the old ones.
The standard deviation was the same (216 mg/L) across all groups, reflecting similar data dispersion and indicating that improvements were not due to random variation but to systematic differences between chemical combinations. Notably, the new chemicals achieved better results across all COD ranges: in raw water with an initial COD of around 900 mg/L, they reduced COD to below 500 mg/L, closer to legally permissible limits. At higher initial concentrations (>1200 mg/L), efficiency was also greater, with COD reduced by about one whole class interval.
The pairwise comparison results (Table 12) showed that COD concentrations in raw wastewater were significantly higher than in treatment with old chemicals (p = 0.0233) and considerably higher than in treatment with new chemicals (p = 0.0047). The differences between old and new chemicals were not statistically significant (p = 0.4034). These findings lay the groundwork for a more in-depth analysis of how chemical selection, treatment effectiveness, and environmental sustainability interconnect, as explored in the upcoming discussion section.

5. Discussion

The discussion analyses the experimental results in relation to prior research and regulatory standards, highlighting how optimised chemical treatment impacts process efficiency and environmental safety. The findings are assessed regarding their role in promoting sustainable wastewater management, aligning with the SDGs, and protecting delicate karst ecosystems inhabited by Proteus anguinus.

5.1. Neutralisation

Our results clearly showed that Sotoplus 50% (NaOH), due to its higher molarity, acted faster and more stably, whereas Chemie NPK 30% exhibited a slower transition and greater variability. This difference is not only kinetic but also has practical implications: faster neutralisation ensures more stable plant operation, reduces the risk of pH fluctuations, and consequently decreases coagulant and flocculant consumption.
Reaching the neutral pH range (6.5–7.5) is critical for multiple reasons. On the one hand, it allows optimal performance of aluminium- and iron-based coagulants, which, at lower pH values, form insoluble hydroxide complexes with reduced adsorption capacity [37]. On the other hand, stable pH reduces the solubility of metals and other toxic substances, which is essential for environmental protection and regulatory compliance [38]. Our findings are consistent with those of Amuda and Amoo [20], who showed that NaOH, as a neutraliser, provides a rapid transition into a stable range, enhancing subsequent treatment efficiency in the food-processing industry. Similarly, Kumar and Kumari [38] reported that the speed of reaching optimal pH directly affects coagulation efficiency and reduces the need for additional chemical dosing. Al-Qodah et al. [39] also emphasise the importance of concentrated alkaline reagents in dynamic systems, such as dairy treatment plants, where rapid load fluctuations require flexible, robust neutralisation processes.
It is also essential to highlight the environmental aspect—rapid pH stabilisation reduces the risk of acidic or alkaline discharges into natural watercourses [40]. In karst systems, where self-purification capacity is low, even small pH changes can have a pronounced negative impact on aquatic ecosystems and sensitive species such as Proteus anguinus.
Therefore, these results confirm not only the higher process efficiency of Sotoplus 50% but also its potential advantage in the long-term protection of sensitive environments. Based on the results, we can confirm hypothesis (a): the use of concentrated neutralisers such as Sotoplus 50% ensures a faster and more stable transition to the neutral range, thereby enabling more efficient subsequent treatment stages compared to traditional preparations.

5.2. Coagulation and Flocculation

The results confirm that the combination of the Sotom neutraliser with the VTA coagulant and flocculant is the most effective for coagulation and flocculation. Its efficiency is reflected in the rapid destabilisation of colloidal particles, the formation of larger aggregates, and the achievement of optimal settleability. The slower response of Samples 3 and 4 shows the intermediate efficiency of partial combinations, while the exclusive use of Sotom chemicals (Sample 1) proved insufficient.
These findings are consistent with those of Loloei et al. [30] and Miranda et al. [32], which demonstrate that polyaluminum coagulants (PACl) form larger, more stable flocs and reduce final turbidity compared to traditional aluminium salts. Similarly, Kuzin et al. [35] confirm that effective coagulation significantly reduces colour, organic load, and bacteria in dairy wastewater.
The practical importance of these results lies in the time component: rapid and stable coagulation enables more efficient subsequent treatment phases, reduces chemical consumption, and increases process reliability. In real plants, this means a lower risk of system overload and reduced operating costs.
The environmental dimension is even more critical: faster and more stable flocculation ensures better removal of suspended and colloidal particles, leading to lower COD values and reduced risk of anaerobic processes in karst aquifers [41]. These aquifers are highly vulnerable to pollution due to their low self-purification capacity. Consequently, the results are crucial for the long-term protection of subterranean ecosystems and sensitive species such as Proteus anguinus.
Based on these results, we can confirm hypothesis (b): polyaluminum coagulants in combination with suitable flocculants significantly improve the efficiency of coagulation and flocculation processes and therefore represent a better choice than traditional reagents.

5.3. Flocculation

The results confirm that the VTA F98 flocculant is more effective compared to Sotom Acefloc. The chemical composition of VTA F98, which includes a higher proportion of organic acids and citric acid additives, enhances the binding of colloidal particles, leading to more compact, settleable flocs. These are easier to remove and ensure lower residual turbidity in the treated wastewater.
Sotom products enabled some initial destabilisation but formed smaller, less stable aggregates, as evidenced by slower process dynamics. Our findings are consistent with the literature. Miranda et al. [32] and Wolf et al. [42] confirm that organic acid additives and improved polymer structures increase flocculation efficiency. Similarly, Girich et al. [43] and Kalaitzidou et al. [44] emphasise that electrostatic interactions between polymer molecules and colloidal particles are decisive in the formation of stable aggregates. The higher cationic activity of VTA F98 flocculant clearly enabled faster destabilisation of the system.
The practical significance is twofold. On the one hand, better and faster flocculation reduces coagulant consumption and shortens treatment time, which is crucial in industrial facilities. On the other hand, it directly contributes to lowering COD in treated water. In karst aquifers, where oxygen is a limited resource, COD reduction can mean the difference between a stable ecosystem and the onset of anaerobic conditions. This is particularly important for protecting sensitive subterranean species such as Proteus anguinus, which have narrow ecological tolerance.
Based on the obtained results, we can confirm hypothesis (b), that VTA acidic flocculants with organic acid additives are more effective in reducing COD and ensuring more stable flocculation than traditional Sotom products.

5.4. Chemical Oxygen Demand (COD)

Discussion:
The results clearly confirm that the optimised chemical combination (Sotom neutraliser + VTA coagulant + VTA flocculant) is more effective than the traditional combination (Chemie NPK + Sotom coagulant + Sotom flocculant). The main reasons for improved efficiency are multifaceted.
First, faster, more stable neutralisation with stronger sodium hydroxide (Sotom NaOH) ensures optimal conditions for subsequent coagulation and flocculation. Stabilisation of pH is crucial, since many coagulants operate within a narrow pH range, with aluminium salts being particularly sensitive to fluctuations [22].
Second, the use of VTA polyaluminum coagulant enables more efficient destabilisation of colloidal particles than traditional aluminium-based agents. The polymeric structure enhances particle bridging, leading to larger, more compact flocs [45]. In addition, polyaluminum coagulants are known to produce less sludge, reducing sludge management costs and improving the sustainability of the treatment process.
Third, the VTA F98 flocculant, with the addition of citric acid, promotes the formation of larger and more stable flocs. Citric acid acts as a synergist by complexing metal ions, thereby enabling stronger interactions between the flocculant polymer chains and suspended particles [46]. The result is faster sedimentation, better removal of suspended solids, and further reductions in COD.
Our findings are consistent with existing research. Kuzin et al. [35] showed that the use of advanced polyaluminum coagulants in the dairy industry leads to significant reductions in colour, turbidity, and microbial load. Amuda and Amoo [20] highlighted that the proper combination of coagulants and flocculants is key to achieving over 80% reduction in COD. Similarly, Miranda et al. [32] emphasised that organic acid additives, such as citric acid, enhance flocculation efficiency by increasing polymer binding capacity.
The environmental significance of these results is considerable. Even a COD reduction of 100 mg/L beyond that achieved with old chemicals substantially lowers the likelihood of anaerobic conditions developing in wastewater. This increases dissolved oxygen availability in natural water bodies and reduces the risk of eutrophication.
In karst aquifers, which are especially vulnerable due to rapid percolation of polluted water and limited self-purification capacity, this is crucial for preventing ecosystem degradation. Lower COD directly reduces the risk of endangering sensitive subterranean organisms such as Proteus anguinus, whose survival depends on stable water quality with low organic load.
Our results, therefore, confirm that the optimised chemical combination not only improves treatment efficiency but also carries significant environmental implications. Based on these results, we can confirm hypothesis (c), that optimised chemical combinations substantially reduce the organic load of wastewater compared to traditional reagents. In the long term, this contributes to protecting karst aquatic ecosystems and to greater sustainability of the dairy industry, as improved treatment reduces environmental impact and ensures compliance with EU environmental legislation.

6. Conclusions

This research demonstrated that optimising the chemical phase in dairy wastewater treatment significantly enhances purification efficiency. This aligns with the broader goals of sustainable water management, industrial responsibility, and ecosystem conservation as outlined by the UN SDGs. By aligning technical performance with environmental regulations such as the EU Water Framework Directive, the study provides a practical route to sustainable industry compliance. The improved treatment method not only reduces the concentration of organic pollutants in sensitive karst regions but also helps preserve habitats vital for species such as Proteus anguinus.
The study confirmed that chemical treatment of dairy wastewater is an essential step in reducing its impact on karst aquifers, which, due to their high permeability and limited self-purification capacity, are among the most vulnerable aquatic ecosystems. Optimisation of chemical selection proved to be a key factor in achieving high process efficiency. Neutralisation with higher-molarity sodium hydroxide enabled rapid stabilisation of pH; polyaluminum hydroxychloride (VTA) outperformed traditional aluminium chloride as a coagulant, while the use of flocculant F98 in combination with citric acid improved floc formation and, consequently, more efficient removal of organic load. As a result, significantly lower COD values were achieved, confirming that the optimised combination of chemicals (higher-molarity NaOH, VTA coagulant, and F98 flocculant) represents a more effective and environmentally friendly approach to treating dairy wastewater. This approach not only improves the quality of treated water but also reduces long-term pressure on karst habitats and contributes to the conservation of Proteus anguinus, a sensitive bioindicator of the state of subterranean aquatic ecosystems.
Despite the improvements achieved, open questions remain regarding the effects of production variability, seasonal changes, and potential interactions between chemicals on treatment efficiency, as well as the ecotoxicological consequences for subterranean communities. Future research will need to incorporate holistic approaches that balance high treatment efficiency with environmental safety and economic sustainability. Only through such an interdisciplinary orientation will it be possible to develop long-term sustainable technologies for the protection of karst water resources, which represent invaluable natural capital and, at the same time, the habitat of numerous endemic species.
From a scientific and engineering perspective, this research enhances knowledge of how optimised chemical processes can improve the efficiency and dependability of industrial wastewater treatment systems. The results offer a practical framework for expanding sustainable treatment methods to other industries with similar effluent profiles. Future studies should aim to incorporate these optimised methods with advanced sensor technologies, automation, and life-cycle assessments to better support their environmental and economic sustainability.

Author Contributions

Conceptualization, A.Š. and D.B.-Š.; methodology, A.Š.; software, A.Š.; validation, A.Š. and D.B.-Š.; formal analysis, A.Š. and D.B.-Š.; investigation, A.Š.; resources, A.Š. and D.B.-Š.; data curation, A.Š.; writing—original draft preparation, A.Š., D.B.-Š., and S.G.; writing—review and editing, A.Š., D.B.-Š., and S.G.; visualisation, S.G.; supervision, D.B.-Š.; project administration, D.B.-Š.; funding acquisition, A.Š., and D.B.-Š. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the public call Problem-Based Learning of Students in the Work Environment: Economy, Non-Economy and the Non-Profit Sector in the Local/Regional Environment 2024–2027 of the Ministry of Higher Education, Science and Innovation of the Republic of Slovenia.

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

This research was conducted under the protocol of Krepko, a company specializing in production, trade, and services, located at Laze 22a, 1370 Logatec, Slovenia; therefore, the data are available only upon request to the corresponding author.

Conflicts of Interest

Diana Bilić-Šobot is employed by Pivka perutninarstvo d.d. The remaining authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest.

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Figure 1. Chemical Wastewater Treatment Process in the Dairy Industry Krepko.
Figure 1. Chemical Wastewater Treatment Process in the Dairy Industry Krepko.
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Figure 2. Flow diagram of the chemical phase of water treatment.
Figure 2. Flow diagram of the chemical phase of water treatment.
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Figure 3. pH measuring device No. Multi 3620 IDS.
Figure 3. pH measuring device No. Multi 3620 IDS.
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Figure 4. pH control device No. ProfiLine pH 3310.
Figure 4. pH control device No. ProfiLine pH 3310.
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Figure 5. A&F Machine Products.
Figure 5. A&F Machine Products.
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Figure 6. Magnetic stirrers with heating (Serie MR 3001) and a digital five-position IKA RO magnetic stirrer without heating.
Figure 6. Magnetic stirrers with heating (Serie MR 3001) and a digital five-position IKA RO magnetic stirrer without heating.
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Figure 7. Sample preparation device Vario Mini.
Figure 7. Sample preparation device Vario Mini.
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Figure 8. Sample value meter device PF-12 Plus.
Figure 8. Sample value meter device PF-12 Plus.
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Table 1. Neutralisation of pH values using different neutralisers.
Table 1. Neutralisation of pH values using different neutralisers.
Duration (min)Sample 1 (Sotoplus 50%)Sample 2 (Chemie NPK 30%)Reaction
03.53.5No
15.34.1Yes
27.05.5Yes
37.06.8Yes
47.07.0Yes
5–107.07.0Yes
Table 2. Descriptive statistics for flocculation.
Table 2. Descriptive statistics for flocculation.
SampleMeanStd. Dev.Minimum25%Median75%Maximump-Value
Sotoplus 50%6.131.463.505.727.007.007.00
Chemie NPK 30%5.651.553.504.456.156.957.000.59
Table 3. Comparison between samples using t-test (p-values).
Table 3. Comparison between samples using t-test (p-values).
Pairwise Comparisont-Valuep-Value
Sotoplus 50%—Chemie NPK 30%0.550.59
Table 4. Time course of coagulation and flocculation.
Table 4. Time course of coagulation and flocculation.
Time (min)Sample 1:
Sotom—Neutraliser, Sotom—Coagulant, Sotom—Flocculant		Sample 2:
Sotom—Neutraliser, VTA—Coagulant, VTA—Flocculant		Sample 3:
Sotom—Neutraliser, VTA—Coagulant, Sotom—Flocculant		Sample 4:
Sotom—Neutraliser, VTA—Coagulant, Sotom—Flocculant		Reaction
0NoNoNoNoNo
1NoInitialNoNoNo/Yes
2NoInitialInitialNoNo/Yes
3NoGoodInitialNoNo/Yes
4NoGoodInitialInitialYes
5InitialExcellentInitialInitialYes
10InitialExcellentGoodGoodYes
Table 5. Descriptive statistics for flocculation.
Table 5. Descriptive statistics for flocculation.
SampleMeanStd. Dev.Minimum25%Median75%Maximum
Sample 10.550.520.000.001.001.001.00
Sample 22.181.080.001.503.003.003.00
Sample 31.180.750.001.001.002.002.00
Sample 40.820.750.000.001.001.002.00
Table 6. Comparison between samples using t-test (p-values).
Table 6. Comparison between samples using t-test (p-values).
Pairwise Comparisont-Valuep-Value
Sample 1–Sample 2−4.300.0007 ***
Sample 1–Sample 3−2.360.0299 *
Sample 1–Sample 4−1.090.2891
Sample 2–Sample 32.470.0234 *
Sample 2–Sample 43.320.0049 ***
Sample 3–Sample 41.210.2410
* p < 0.05 (statistically significant), *** p < 0.001 (extremely significant).
Table 7. Flocculation with different flocculants.
Table 7. Flocculation with different flocculants.
Duration (Min)Sample 1 (VTA)Sample 2 (Sotom)Reaction
0NoNoNo
3GoodInitialYes
5ExcellentInitialYes
10ExcellentGoodYes
Table 8. Descriptive statistics for flocculation.
Table 8. Descriptive statistics for flocculation.
SampleMeanStd. Dev.Minimum25%Median75%Maximum
Sample 1 (VTA F98)2.181.080.001.503.003.003.00
Sample 2 (Sotom)1.180.750.001.001.002.002.00
Reaction (binary)0.820.400.001.001.001.001.00
Table 9. Comparison between samples using t-test (p-values).
Table 9. Comparison between samples using t-test (p-values).
Pairwise Comparisont-Valuep-Value
Sample 1 (VTA F98)–Sample 2 (Sotom)2.520.0214 **
Sample 1 (VTA F98)–Reaction (binary)3.920.0018 ***
Sample 2 (Sotom)–Reaction (binary)1.400.1801
**—p < 0.01 (highly significant), ***—p < 0.001 (extremely significant).
Table 10. Chemical Oxygen Demand.
Table 10. Chemical Oxygen Demand.
DayRaw WastewaterTreated Wastewater—
Old Chemicals		Treated Wastewater—
New Chemicals
g/L O2 CODg/L O2 CODg/L O2 COD
2, 8, 15, 23, 300.801–0.9000.501–0.6000.401–0.500
1, 4, 9, 17, 22, 290.901–1.0000.601–0.7000.501–0.600
3, 10, 24, 271.001–1.1000.701–0.8000.601–0.700
5, 11, 141.101–1.2000.801–0.9000.701–0.800
12, 13, 161.201–1.3000.901–1.0000.801–0.900
6, 7, 20, 251.301–1.4001.001–1.1000.901–1.000
18, 19, 21, 261.401–1.5001.101–1.2001.001–1.100
Table 11. Descriptive statistics for COD in mg/L O2.
Table 11. Descriptive statistics for COD in mg/L O2.
Statistical IndicatorCOD of Raw WastewaterCOD—Old ChemicalsCOD—New Chemicals
Number of samples7.007.007.00
Mean1150.50850.50750.50
Standard deviation216.02216.02216.02
Minimum850.50550.50450.50
25th percentile1000.50700.50600.50
Median1150.50850.50750.50
75th percentile1300.501000.50900.50
Maximum1450.501150.501050.50
Table 12. Comparison between samples using t-test (p-values).
Table 12. Comparison between samples using t-test (p-values).
Pairwise Comparisont-Valuep-Value
COD raw wastewater–COD old chemicals2.600.0233 **
COD raw wastewater–COD new chemicals3.460.0047 ***
COD old chemicals–COD new chemicals0.870.4034
**—p < 0.01 (highly significant),***—p < 0.001 (extremely significant).
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Šobot, A.; Gričar, S.; Bilić-Šobot, D. Optimising Chemical Treatment of Dairy Wastewater for Sustainable Protection of Karst Ecosystems. Sustainability 2025, 17, 10556. https://doi.org/10.3390/su172310556

AMA Style

Šobot A, Gričar S, Bilić-Šobot D. Optimising Chemical Treatment of Dairy Wastewater for Sustainable Protection of Karst Ecosystems. Sustainability. 2025; 17(23):10556. https://doi.org/10.3390/su172310556

Chicago/Turabian Style

Šobot, Aleksandar, Sergej Gričar, and Diana Bilić-Šobot. 2025. "Optimising Chemical Treatment of Dairy Wastewater for Sustainable Protection of Karst Ecosystems" Sustainability 17, no. 23: 10556. https://doi.org/10.3390/su172310556

APA Style

Šobot, A., Gričar, S., & Bilić-Šobot, D. (2025). Optimising Chemical Treatment of Dairy Wastewater for Sustainable Protection of Karst Ecosystems. Sustainability, 17(23), 10556. https://doi.org/10.3390/su172310556

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