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INTRODUCTION

Municipal waste management is a distinct component within waste management, playing a significant role in various economic sectors for resource use [Mininni et al. 2015; Zhao 2018; Geng et al. 2020; Halecki et al. 2021; Kalenik et al. 2023]. Municipal waste management extends beyond mere waste collection and processing [Młyński et al. 2016]. It includes strategic planning, oversight, and the adoption of innovative technological solutions [Yakamercan et al. 2021; Swolkień et al. 2021; Sionkowski et al. 2023]. The legal regulations of the European Union concerning the collection and treatment of municipal wastewater are specifically outlined in the Council Directive of 21 May 1991 regarding the treatment of municipal wastewater (91/271/EEC) [Dyrektywa]. This directive pertains to the collection, treatment, and discharge of municipal wastewater, as well as the treatment and discharge of wastewater from agri-food industry facilities. The purpose of these provisions is to safeguard the aquatic environment against the adverse impacts of these discharges. The increase in sewage sludge in terms of its dry mass is a result of the growing level of population connected to sewage systems in Poland and the construction of highly efficient wastewater treatment plants [Państwowe Gospodarstwo Wodne 2018].

To accurately evaluate the properties of sewage sludge, it is essential to ascertain its technological and rheological characteristics, chemical composition, concentration of organic substances in dry mass, calorific value, mineral content, and hydration level [Ignatowicz 2017; Latosińska et al. 2021; Zhang et al. 2022; Ferrentino et al., 2023]. Municipal sewage sludge is characterised by its high organic and nitrogen compound content, low levels of toxic organic substances, high hydration, variable trace element concentrations (Potentially Toxic Elements), and diverse sanitary risk [Karwowska, Dąbrowska 2017; Tytła 2019]. Additionally, it shows adsorption properties [Rozada et al. 2008]. Consequently, it exhibits a spectrum of chemical, physical, fertilising, sanitary, and technological properties [Halecki et al. 2016; Hušek et al. 2022]. Therefore, in the production technology process, the processing stage is pivotal [Wang et al. 2019]. The techniques utilise in this stage, encompassing dewatering, thickening, stabilisation, drying, and incineration, are employed to alter the physicochemical composition of the sludge, thereby facilitating volume reduction. This process prepares the sludge for subsequent stages, which may involve recovery or disposal [Neyens, Baeyens 2003; Raheem et al., 2018; Ronda et al. 2023]. The approach to handling sludge may vary among different treatment plants, depending on their size and budget constraints [Mao et al. 2022]. Typically, larger facilities implement more extensive technological processes and a wider array of thermal utilization methods [Siddiqui et al. 2023]. The technological process for creating sewage sludge, designed to optimally remove pollutants from wastewater, encompasses biological and chemical processes with support from mechanical processing [Cárdenas-Talero et al. 2022; Fan et al. 2023]. This study aimed to showcase the assessment of heavy metals in raw, treated wastewater and sewage sludge from the selected WWTP.

METHODS
Research area

The Nowy Sącz wastewater treatment plant is a modern facility dedicated to treating sewage from municipal sources. It operates with a system where sewage is conveyed to the plant through 1400 mm diameter pipes and then pumped into the treatment equipment using Archimedes pumps. The treatment process includes several stages:

Removal of larger debris: At the initial treatment stage, there is a device that captures larger debris and contaminants from the incoming sewage.

Sand traps: Following the initial debris removal, the sewage proceeds to sand traps, where sand is separated and removed from the wastewater.

Grease traps: In this stage, fats and oils are eliminated from the sewage. The collected fats are stored in a specialised facility and are later directed to fermentation chambers for further processing.

Preliminary fermentation: Sewage also undergoes preliminary fermentation in two primary settling tanks.

Nitrogen and phosphorus removal: Throughout the treatment process, the sewage is purified of nitrogen and phosphorus compounds, which are common pollutants in wastewater.

Clean water output: The end result of the treatment process is clean water that is free from unpleasant odors and pollutants. This treated water is released into the local river, ensuring the protection of the environment.

Self-sufficiency in energy: The treatment plant is self-sufficient in terms of energy production. It generates its own power to operate the equipment, which is an environmentally friendly and sustainable practice.

Comprehensive testing: The facility conducts comprehensive testing both before and after the treatment process. This includes monitoring the content of heavy metals and microbiological indicators to ensure the quality and safety of the treated water.

Each year, the treatment plant processes roughly nine million cubic meters of raw sewage. The facility was introduced to residents in 1996. In 2005, after modernisation, the Nowy Sącz sewage treatment plant became self-sufficient, generating its own energy for a more effective facility. The average RLM of raw sewage is 147,806.

Data handling and statistical analysis

The Nowy Sącz wastewater treatment plant is noted for being one of the most advanced facilities of its kind in Poland. It is equipped with an accredited laboratory that ensures the high quality of water and wastewater analysis, further emphasising its commitment to environmental protection and public health. The analysis of dehydrated sludge intended for composting involved the assessment of various critical parameters. The data from the years 2004 to 2015 was originally obtained from the WWTP in response to a request for examination the quality of wastewater before and after treatment, as well as the quality of sewage sludge. Our goal was to statistically analyze the data obtained. We conducted an analysis of heavy metals, including zinc (Zn), lead (Pb), cadmium (Cd), copper (Cu), chromium (Cr), and nickel (Ni) in untreated and treated wastewater to assess the presence of potentially harmful heavy metals in the wastewater and sewage sludge. The sewage sludge samples were collected following the PN-EN ISO 5667-13:2004P standard. Furthermore, we investigated two additional elements: manganese (Mn) and mercury (Hg). Manganese (Mn) data were only available for wastewater, while mercury (Hg) data were only available for sewage sludge.

We used data concerning heavy metal content of raw sewage, treated sewage and sludge from measurements taken in the Nowy Sącz waste water treatment. The analysis included measurements conducted between 2004 and 2015. To assess the efficiency of wastewater treatment in eliminating heavy metals, we conducted a comparative analysis of the concentration of each examined element in both untreated and treated wastewater using repeated measures ANOVA. Additionally, we introduced an independent variable – the quarter of the year during which the measurements were conducted. The next step involved verifying whether the sludge generated during the treatment process met the legal requirements regarding the permissible concentration of heavy metals. For this purpose, we utilised a one-sample t-test with respect to a constant reference value. The reference value represented the permissible standard for the concentration of a specific metal in sludge originating from municipal wastewater. In cases where data were missing, the cases for wastewater were excluded in pairs. Missing data occurred because the measurement was not made out – for example, due to technical failure. To describe the relations between investigated elements in wastewater and sewage sludge we performed principal component analysis (PCA), a linear unconstrained ordination method using logarithmic data.

The ANOVA and one sample t-test were performed using Statistica 13. The PCA analysis was conducted in Canoco 4.5.

RESULTS

The treated wastewater exhibited a diminished concentration of heavy metals compared to untreated wastewater and lower manganese and nickel content compared to raw wastewater, while for chromium, cadmium, and lead content, no statistically significant difference was observed (Table 1, Fig. 1). The heavy metal content in sludge met the standards for all the examined metals (Table 2 Fig. 2).

The results of the repeated measures, analysis of variance. “R1” represents the wastewater treatment effect, and “quarter” refers to the quarter of the year. Significant effects are bolded. Following symbols denote: df – degrees of freedom, F – F-statistic, p – p-value

Effect df F p
Zn (N = 138) Intercept 1 948.19 <0.001
Quarter 3 1.23 0.302
Error 133 - -
R1 1 7.07 0.009
R1*Quarter 3 4.32 0.006
Error 133 - -
Pb (N = 123) Intercept 1 708.47 <0.001
Quarter 3 1.88 0.138
Error 118 - -
R1 1 2.09 0.151
R1*Quarter 3 0.19 0.905
Error 118 - -
Cd (N = 88) Intercept 1 411.53 <0.001
Quarter 3 0.96 0.414
Error 83 - -
R1 1 2.78 0.099
R1*Quarter 3 1.87 0.141
Error 83 - -
Cu (N = 137) Intercept 1 969.36 <0.001
Quarter 3 0.26 0.857
Error 132 - -
R1 1 14.19 <0.001
R1*Quarter 3 0.10 0.960
Error 132 - -
Cr (N = 121) Intercept 1 707.04 <0.001
Quarter 3 0.34 0.794
Error 116 - -
R1 1 1.80 0.183
R1*Quarter 3 2.18 0.095
Error 116 - -
Ni (N = 125) Intercept 1 635.60 <0.001
Quarter 3 1.48 0.222
Error 120 - -
R1 1 17.16 <0.001
R1*Quarter 3 0.47 0.707
Error 120 - -
Mn (N = 138) Intercept 1 1600.64 <0.001
Quarter 3 0.16 0.923
Error 133 - -
R1 1 61.15 <0.001
R1*Quarter 3 1.28 0.285
Error 133 - -

Figure 1.

The heavy metal content in raw and treated wastewater. The means with 95% confidence intervals. Grey bars represent raw wastewater and white bars represent treated wastewater

Compliance with the heavy metal content standard in sewage sludge originating from municipal wastewater treatment. Results of the one-sample t-test relative to a constant reference value – the norm. N denotes sample size. SE denotes Standard error, t indicates t-statistic, and p indicates p-value

Mean [mg/l] SE Reference value [mg/l] N t p
Zn 1,148.97 42.39 2,500 70 31.87 <0.001
Pb 68.86 3.90 750 70 174.48 <0.001
Cd 4.06 1.45 20 70 11.03 <<.001
Cu 170.82 7.95 1,100 70 104.35 <0.001
Cr 81.46 11.37 500 70 36.82 <0.001
Ni 34.12 2.33 300 70 113.89 <0.001
Hg 0.98 0.06 16 70 261.84 <0.001

Figure 2.

The heavy metal content in sewage sludge from municipal wastewater treatment. The means with 95% confidence intervals. If the upper limit of the confidence interval is below the value of the standard, it means that the standard is met, if the confidence interval overlaps the value of the standard, it means that the standard is not met, but the metal content is close to the standard, in the situation when the lower limit of the confidence interval is above the value of the standard, it means that the metal content significantly exceeds the standard. The upper bound of the confidence interval falls below the standard (red line), indicating that the metal content in the sludge is statistically significantly lower than the maximum permissible content

The results obtained through Principal Component Analysis (PCA) indicated the general effectiveness of the wastewater treatment process when considering the collective presence of all heavy metals (Fig. 3a). The treated wastewater exhibited a diminished concentration of heavy metals compared to untreated/raw wastewater (Fig. 3a). The first ordination axis elucidated 93.5% of the variability in heavy metal content within the wastewater. With the exception of cadmium, the majority of elements demonstrated a significant positive correlation with the first PCA axis, registering scores surpassing 0.5. These findings signified a robust positive correlation among all elements. Specifically, zinc (Zn), copper (Cu), and manganese (Mn) were associated to the first axis with scores of 0.999, 0.797, and 0.741, respectively, disclosing the highest concentrations of these metals in wastewater. In the context of sewage sludge, the initial PCA axis explicated 57.8% of the variation, while the second ordination axis clarified an additional 21.2% of the variability in metal content. All elements exhibited correlations with the first axis, yielding scores exceeding 0.5. Notably, chromium (Cr), nickel (Ni), and copper (Cu) displayed the highest scores: 0.891, 0.823, and 0.711, respectively. This suggests that these metals predominantly contributed to the differentiation in the heavy metal composition of sewage sludge (Fig. 3b). Cadmium (Cd) exhibited a correlation with the second PCA axis, registering score of 0.603 (Fig. 3b).

Figure 3.

PCA analysis results. Ordination diagrams showing the first and second ordination axes: (a) for wastewater, (b) sewage sludge. For diagram (a), circles represent raw wastewater and squares represent treated wastewater

DISCUSSION

Metallurgical processes, chemical processing, electronics manufacturing, and various other industrial sectors can introduce heavy metals into wastewater (Śliz & Bugajski, 2022). Traditionally, heavy metals have received significant attention and are regulated by directives like the Sewage Sludge Directive (86/278/EEC). Research emphasizes the emerging risks to both human health and ecosystems posed by new contaminants in sewage sludge, including toxic trace elements, nanoparticles, and various chemical and biological agents (Fijalkowski et al. 2017). While sewage sludge offers soil benefits, it often contains heavy metals. A recent study in Poland assessed the risk of heavy metal contamination, highlighting the importance of controlling metal mobility for sludge viability (Kowalik et al. 2021).

For our study, analyzing all the results of statistical tests collectively, it can be observed that the wastewater treatment process, especially concerning zinc and copper, is sufficiently effective, as suggested by the PCA analysis results. However, the results of the variance analysis for repetitive measurements indicated that, probably periodically, the purification process is disrupted and highly inefficient. This is significant as it impacts the assessment of the treatment plant's long-term effectiveness, resulting in unsatisfactory outcomes. In the case of zinc, a significant R1*Quarter interaction indicates temporal variations in wastewater treatment efficiency. However, this interaction is difficult to interpret in detail.

In similar wastewater treatment plants the heavy metal concentrations in both the sludge and water samples were, by and large, at low levels, but notably, Cd levels were elevated in effluents and surface waters. Regrettably, all treatment facilities struggled with Cu and Zn removal, which remained inadequate [Agoro et al. 2020]. Another study investigated heavy metal pollution hazards in sewage sludge from four wastewater treatment plants in Nanchang City, China. The research uncovered high total metal contents, particularly Cd and Ni, indicating significant ecological risks based on potential risk indexes. Cd contamination emerged as a primary concern [Ting et al. 2017].

The heavy metal content in both raw and treated wastewater is presented in Figure 1. In a national survey covering 107 municipal sewage treatment plants in China, decreasing levels of Cd, Cr, Cu, Hg, Ni, Pb, and Zn were observed due to stricter industrial waste regulations. However, concentrations of Cd, Cr, Cu, Ni, and Zn still exceeded disposal limits [Yang et al. 2014].

For efficient extraction of copper from purified wastewater, the use of specialised treatment methodologies and technologies is crucial. This includes techniques such as iron chelation, coagulation, or electrocoagulation. Simultaneously, consistent monitoring of water quality parameters and compliance with strict environmental regulations remains essential [Arbabi & Golshani, 2016]. The removal of zinc from wastewater can be done by various methods, tailored to the specific needs of the wastewater treatment process [Zwain et al., 2014]. In our study, we highlight that a dedicated technological approach for zinc removal was not effectively implemented. Additionally, we suggest that membrane filtration did not perform satisfactorily in this technological treatment process of wastewater.

Zinc ions can be removed by adjusting the pH of the wastewater, leading to the formation of insoluble zinc hydroxides that can be separated from the water. Furthermore, one method entails substituting zinc ions in wastewater with other ions, such as sodium or hydrogen ions, using an exchange resin. Once saturated, the resin can be regenerated for further use or disposed of properly [Bezzina et al., 2019]. Another technique involves using electrodes to produce coagulating agents, resulting in the creation of zinc hydroxide flocs that can be easily extracted [Shaker et al., 2023].

Our findings indicate that neither zinc nor copper were effectively treated in the technological process under study. We recommend applying novel methods to enhance zinc removal and improve copper removal from wastewater. Moreover, some of the methods involve the use of adsorbents such as activated carbon, zeolites, and bentonite for zinc removal from treated wastewater [Kozera-Sucharda 2020].

In Table 2 and Figure 2, our study presented data regarding heavy metal content in sewage sludge from municipal treatment. The data were represented as means with 95% confidence intervals. Notably, the upper boundary of the confidence interval fell below the predefined standard, demonstrating a statistically significant reduction in the metal content within the sludge, ensuring it fell well below the maximum allowable concentration. Another study in southern Poland examined heavy metal concentrations and chemical forms in sewage sludge from two municipal wastewater treatment plants. Zinc (Zn) and copper (Cu) were the most abundant metals, while cadmium (Cd) and mercury (Hg) had the lowest concentrations. The dominant forms of these metals were immobilised, with oxidizable and residual forms being prevalent. The results indicated minimal metal migration from the sludge into the environment, and variations in metal speciation were attributed to differences in wastewater composition and biological treatment processes [Tytła et al. 2016]. In a multi-year study (2010–2014) at the Jasło WTP, daily sewage volume variations were analyzed. The average daily inflow was 13,045 m3, with the highest admissions in March, May, June. The facility was often hydraulically underloaded [Młyński et al. 2016]. Older water supply and sewage systems were often made from materials containing heavy metals, such as Zn in pipes or other metals in various infrastructure elements. When water flowed through these pipes, it could lead to the release of these metals into drinking water.

Sewage sludge materials produced through pyrolysis and chemical activation effectively adsorbed metals, with chemical activation (AS) demonstrating higher capacity. The preferred adsorption order was Hg(II) > Pb(II) > Cu(II) > Cr(III), with adsorption being pH-dependent. These materials hold promise for treating metal-polluted effluents [Rozada et al. 2008].

Derived from household waste and generated during biological treatment processes, sewage sludge improved agricultural soil and rehabilitated reclaimed lands, thanks to its nutrient-rich organic matter. Multivariate analysis in the study revealed no heavy metal toxicity risks, emphasising the importance of thoughtful consideration and understanding local variations in sludge composition. Previous research disclosed the average concentrations of various heavy metals in sewage sludge. Analyses, including Pearson's correlation and PCA, pinpointed traffic emissions and the manufacturing industry as the primary sources of lead (Pb) and cadmium (Cd) pollution, while agricultural discharges were responsible for arsenic (As) and chromium (Cr) contamination [Zhang et al. 2020].

CONCLUSION

Our study had a central focus on evaluating the efficiency of wastewater treatment in eliminating heavy metals. Our analysis unveiled noteworthy discrepancies in metal concentrations between treated and untreated wastewater. Although certain metals conformed to established legal standards, persistent challenges were identified, notably in the effective removal of copper and zinc. Research underlined the presence of substantial environmental risks, primarily concerning cadmium contamination in sewage sludge. In the case of sewage pipes, if zinc is released, it can affect the wastewater treatment process. Higher concentrations of Zn can hinder sewage treatment processes and impact the efficiency of pollutant removal. The variance analysis for repetitive measurements indicates periodic disruptions in the purification process, leading to inefficiency. This has significant implications for the long-term effectiveness assessment of the treatment plant, resulting in unsatisfactory outcomes. To achieve efficient copper extraction from purified wastewater, the adoption of specialised treatment methodologies such as iron chelation, coagulation, or electrocoagulation is essential. Continuous monitoring of water quality parameters and adherence to stringent environmental regulations are crucial. Our findings highlight that both zinc and copper were not effectively treated in the studied technological process, suggesting the need for novel methods to enhance zinc removal and improve copper removal. These methods may involve the use of adsorbents such as activated carbon, zeolites, and bentonite for zinc removal from treated wastewater. Therefore, it is essential to monitor the condition of the water supply and sewage infrastructure and to modernize or replace old pipes and elements containing heavy metals. Preventing the release of heavy metals is of paramount importance for ensuring a safe and efficient water and sewage infrastructure. Our investigation into metal speciation further illuminated distinctions between untreated and treated wastewater.

eISSN:
2353-8589
Język:
Angielski
Częstotliwość wydawania:
4 razy w roku
Dziedziny czasopisma:
Life Sciences, Ecology