Evaluation of the effluent concentrations of Karbala wastewater treatment plant using reliability analysis

Ruqayah Fadhil Atea; Riyadh Jasim Mohammed Al-Saadi; Jabbar H. Al-Baidhani; Waqed H. Hassan

doi:10.1515/eng-2024-0031

Article Open Access

Evaluation of the effluent concentrations of Karbala wastewater treatment plant using reliability analysis

Ruqayah Fadhil Atea , Riyadh Jasim Mohammed Al-Saadi , Jabbar H. Al-Baidhani and Waqed H. Hassan

Published/Copyright: June 26, 2024

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From the journal Open Engineering Volume 14 Issue 1

Abstract

The effective and consistent operation of wastewater treatment plant systems (WWTPs) is crucial for the sustainability of the environment and public health protection. The main objective of the present study is concentrated on assessing the reliability of the Karbala wastewater treatment plant’s (WWTP’s) performance. It investigates the plant’s efficiency through the weekly concentration values of three key water quality indicators, which are biochemical oxygen demand (BOD), total suspended solids (TSS), and chemical oxygen demand (COD) collected over 4 years of operation from 2020 to 2023. The methods employed were the coefficient of reliability (COR) method for plant performance in removing the effluent concentrations of 5-day biochemical oxygen demand, COD, and TSS. The analysis found that the COR values were generally close to 1 for all years, with the lowest value recorded at 0.71 in 2020, during the initial stabilization phase of the WWTP. The main finding was that the Karbala WWTP has been effective in pollutant removal. The present study is important because it supplies dependable data that wastewater treatment operators can use to assess their daily operations and gauge the success of biological treatment methods. It is worth noting that no study has been done on the reliability model for examining the quality of wastewater of the Karbala WWTP, and such a method of analysis is considered a new improvement for the evaluation of the plant to meet the Iraqi standards.

Keywords: reliability coefficient; the coefficient of variation; biochemical oxygen demand; wastewater treatment plant; Karbala

1 Introduction

Reliability analysis greatly enhances the evaluation of design and performance in complex wastewater treatment plant (WWTP) systems. This important technique helps pinpoint design flaws, improvement opportunities, and potential risks associated with the facilities. In the field of engineering, the concepts of reliability and maintainability are still relatively new and developing. Several factors have propelled the advancement and evolution of these concepts, including the increased complexity of industrial systems, heightened awareness among reliability engineers, and the adherence to safety standards within various industries [1]. The analysis involves breaking down the system into multiple levels of disaggregation and assessing the availability and operational states of each component within the subsystems. Metrics like the plant operational effectiveness impact and the expected operational impact are used to measure the impact of inefficiencies on the overall system [2]. The researcher also mentioned that evaluating the feed water from wells in the Karbala desert aims to expand agricultural areas, thereby contributing to development and environmental improvement. Treated water from the Karbala WWTP can be utilized to replenish local wells if the plant demonstrates reliable and efficient pollutant removal capabilities, offering economic savings and promoting sustainability [3]. Climate change will significantly affect the quantity, timing, and intensity of precipitation, alongside increasing temperatures that will alter the hydrological cycle through changes in evapotranspiration, soil moisture, and overall precipitation patterns. Consequently, global precipitation distribution will become more uneven, with noticeable shifts in the duration of wet and dry seasons and potential reductions in rainfall in many regions worldwide. The report highlights that the primary factors contributing to the decreased availability and quality of groundwater due to climate change include reduced natural recharge and heightened demands on local and regional groundwater resources [4]. Additionally, predicting the scour depth around bridge piers under various field conditions is challenging due to the complex mechanisms involved. Key variables affecting these predictions include the pier width, attack angle, flow intensity, and water level. As a result, numerous prediction equations have been developed through traditional regression, leveraging field, and experimental data related to these factors [5]. Treating and reusing domestic wastewater has become essential for public health, environmental protection, prevention of water supply contamination, and the subsequent use of treated water in industries and agriculture. This necessity is driven by the increasing population and the dwindling availability of water resources [6]. It is crucial to ensure that residential wastewater is properly treated before it is reused in industrial and agricultural sectors, for the sake of public health, environmental preservation, and to prevent water supply contamination, especially given the reduction in available water sources and population growth [7]. Recently, the management of WWTPs has gained significant attention due to water shortages and contamination issues. Research on WWTP performance has been a focus globally. For example, a study by Al-Amery et al. assessed the performance of the wastewater treatment plant (WWTP) in Al-Samawah, Iraq, and discovered a decline in treatment efficiency. This was attributed to the lack of essential quality control systems, including oxygen measurement devices in the aeration tank, flow measuring devices at the plant's inlet, sludge volume index calculations, and settling tests in the secondary clarifiers [8]. Over the next 30 years, more than half of the global population is expected to face a freshwater crisis, posing significant sustainability issues due to water scarcity and pollution [9]. In addition, inadequate wastewater treatment can lead to severe environmental and social problems, such as water source contamination and the spread of diseases to humans and livestock. Consequently, enhancing the efficiency of contaminant removal, resource recovery, and wastewater reuse has become increasingly crucial [10]. The quality of water discharged from WWTPs significantly impacts the environment. The concept of reliability in this context can be defined as the ability of a system to perform its intended function consistently over time without failure. A more detailed measure of treatment plant performance might consider the percentage of time the effluent meets specific regulatory standards [11,12]. Utilizing reliability engineering principles allows for the assessment of the likelihood of adverse events occurring. Furthermore, ongoing research indicates that continuous discharge of untreated wastewater exacerbates water scarcity issues by polluting freshwater resources [13]. Thus, employing reliability-based analyses in the design and operation of wastewater treatment facilities is beneficial. Such analyses use data on the inflows and outflows of wastewater to estimate the probability of undesirable events. Given the variable nature of wastewater in terms of volume and quality, it is essential to set specific effluent thresholds for daily operational requirements. These thresholds should be based on the probability that they will be consistently met throughout the facility’s operational lifespan [14]. According to Metcalf and Eddy [11] and Kottegoda and Rosso [12], a WWTP is considered completely reliable if it adheres to environmental regulations without any violations of discharge standards. The mathematical reliability of a treatment facility is achieved when there are no failures in process performance, such as violations of discharge requirements. Research, particularly since the studies focusing on trickling filters and activated sludge processes by Niku et al. [15] and [16], respectively, shows limited exploration into the reliability of activated sludge treatment technologies. To date, no quantitative studies specifically using activated sludge treatment technologies to assess the reliability of WWTPs have been found in the literature. Snehalatha et al. [17] modified a WWTP model’s water and sludge lines by adjusting aeration intensity and sludge flow rates to enhance performance. Their research aimed to manage the biomass of activated sludge and the levels of dissolved oxygen. The study examined the effects of altering air introduction and sludge flow speeds within a WWTP on both the quality of the treated water and the overall system efficiency. Although operational costs increased, these modifications resulted in cleaner wastewater and enhanced system reliability. Simultaneous control over water and sludge lines improved the quality of the treated water by 9.3% and raised operational costs by 1%. The system’s efficiency in reducing ammonia, solid waste, and chemical contaminants improved by 33.4, 9, and 12.2%, respectively. In a study by Kurek et al., the reliability of pollution removal at the Minsk Mazowiecki WWTP was evaluated using the Weibull probability model. The plant demonstrated high average removal rates, with 5-day biochemical oxygen demand (BOD5), CODCr, and TSS elimination percentages at 99.1, 96.3, and 98.9%, respectively, over the course of the study [18]. The Weibull distribution revealed that the median reliability for BOD5 removal was 69, which translates to achieving an outflow BOD5 concentration of 4 mgO₂ dm⁻³ for 245 days annually. Similarly, the reliability for COD removal stood at 62 in median terms, corresponding to an outflow concentration of 32.9 mgO₂ dm⁻³. The analysis showed that the empirical data for BOD5, COD, and TSS removal closely followed the Weibull distribution, with respective probabilities of 69, 62, and 94. Shabangu et al. utilized the Weighted Average System Reliability Index (WASRI) to evaluate and prioritize maintenance tasks at water treatment facilities based on both system reliability and cost-effectiveness [19]. The maintenance activities are assessed by comparing the ratio of marginal benefits, represented by improvements in WASRI, to costs. These improvements in WASRI are calculated based on a linear model that correlates the benefits from maintenance labor to reductions in the rate of component failures. This methodology enables a structured approach to enhancing the reliability of water treatment systems while considering economic efficiency. Jóźwiakowska and Bugajski explored the influence of air temperature in southwestern Poland on the effectiveness of a hybrid wetland wastewater treatment system in removing pollutants [20]. The research involved analyzing the water quality before and after treatment in both vertical and horizontal wetlands following initial mechanical processing in a settling tank. Key pollutants such as BOD5, COD, total suspended particles, total nitrogen, and total phosphorus were monitored to determine the system’s performance. The results indicated that air temperatures, which never fell below freezing, did not significantly impact the pollutant removal efficiency. The hybrid wetland system in this region successfully maintained reliable and efficient pollutant reduction throughout the year, keeping contaminant levels within acceptable standards. This method demonstrates a robust approach to wastewater treatment in southern Poland’s climate, aiding operators in optimizing maintenance schedules to enhance system reliability and cost efficiency. Gopal and Panchal [21] conducted an analytical examination of the curd unit’s operational efficacy within a dairy processing facility. They employed the Triangular Membership Function to facilitate the fuzzification process of data pertaining to reliability and risk. This methodological approach was aimed at enhancing the precision of outcomes that are contingent upon performance metrics. In their 2023 investigation, Al-Baijat and Alzgool [22] embarked on an extensive empirical analysis aimed at integrating wastewater from olive oil mills and saline solutions into concrete formulations to assess effects on torsional resistance, flexural stress, shear, and compressive strength. The primary finding of their inquiry highlighted that the inclusion of brine wastewater at an optimal concentration of 10% significantly enhanced the torsional capacity of the concrete specimens, achieving a strength of 5.46 MPa. Ahmad et al. [23] undertook a qualitative inquiry aimed at examining the efficacy of the triple layered business model canvas strategy in fostering environmental advancements within the Indonesian fashion sector. The study underscores the imperative for a financially viable and ecologically sustainable business approach, given the sector’s notable impact on environmental degradation, with its operations responsible for approximately 20% of the world’s wastewater output. In 2023, Javan et al. [24] carried out a research analysis focused on the effects of climatic alterations on agricultural and touristic activities in the Ardabil region. The findings from their study revealed a notable decrease in precipitation by 38%, predominantly during the autumnal period, accompanied by potential shifts in both the timing and intensity of rainfall events.

The primary objective of this study was to conduct an exhaustive reliability analysis of the WWTP in Karbala, with a specific focus on its ability to effectively remove critical pollutants such as BOD5, COD, and TSS. The purpose was to identify and resolve significant performance challenges, while enhancing our understanding of the plant’s reliability, compliance with regulatory norms, and potential areas for improvement. This research involved a thorough evaluation of the plant’s operational reliability and adherence to regulatory standards, which are crucial for recognizing and comprehending the obstacles it faces. The insights gained from this study are intended to enhance the plant’s overall functionality, ensure more effective wastewater treatment, and contribute to environmental protection.

2 Materials and methods

2.1 Karbala WWTP

This study was conducted at the Karbala WWTP, located approximately 100 km south of Baghdad at coordinates 32.525590°N and 44.074909°E. The facility uses traditional activated sludge technology and an A2/O system for nutrient removal, as detailed in Table 1. The Karbala WWTP is designed with five distinct treatment stages depicted in Figure 1. The preliminary treatment, the first stage, includes coarse and fine screens alongside a grit and oil removal chamber. The second stage features primary treatment through primary sedimentation basins. The third stage involves secondary treatment focused on nutrient removal using an anaerobic, anoxic, oxic, and final clarifier tank. The fourth stage achieves tertiary treatment via chemical disinfection in the chlorination tank. Lastly, the fifth stage pertains to sludge treatment, incorporating drying beds, an anaerobic digester, a mechanical thickener, and a gravity thickener.

Table 1

Features of WWTP in Karbala: collected data were taken from the administrative staff of the plant

Parameter	Value
Flowrate	60,000 m³/day
Volume of anaerobic reactor	8,736 m³
Volume of anoxic reactor	14,112 m³
Volume of aeration reactor	54,054 m³
Surface area for primary sedimentation	3,216 m²
Surface area for final clarifier	6,432 m²
Volume of anaerobic digester	13,600 m³
Surface area for gravity thickener	400 m²
Surface area for mechanical thickener	60 m²
Volume chlorination tank	3,000 m³
Surface area for drying bed	50,000 m²
Dissolved oxygen	2–3 mg/L
Mixed liquor suspended solids	2,000–4,000
Solids loading rate (SLR)	3.6 kg mlss/m² h
Hydraulic loading rate (HLR)	15.5 m³/m² day
Waste activated sludge (WAS)	3,000–4,000 m³/day
Return activated sludge (RAS)	50,000–60,000 m³/day
Food to microorganism ratio (F/M)	0.16
Internal recirculation (IR)	3
Sludge Volume Index (SVI)	85 mL/g

Figure 1

Photo of Karbala WWTP.

2.2 Data collection and analysis

Monthly data on pollutant concentrations, including BOD5, COD, and TSS in the effluent from the Karbala WWTP, were collected over 4 years to assess the facility’s reliability. Weekly testing of each pollutant was carried out throughout the year from January to December. Table 2 presents the average pollutant parameter concentrations of both influent and effluent wastewater at the Karbala WWTP across these 4 years.

Table 2

Characteristics of influent and effluent wastewater for Karbala WWTP: collected data were taken from the administrative staff of the plant

Parameter	Inlet (mg/l)	Outlet (mg/l)	Iraqi standards
BOD5	250	21	100
COD	115	11	40
TSS	140	12	60

2.3 WWTP reliability assessment

The reliability of a WWTP hinges on understanding the dynamics of its processes. It is essential that the plant is designed to release treated effluent while ensuring that specific effluent quality indicators stay below a set threshold for discharge quality. Due to the variability in the volume and quality of incoming water, a probabilistic analysis method was used to define these thresholds. This approach essentially helps in determining the average level of a parameter where a minimum standard must be met. Such a method has been recommended and previously used, as noted in works by Crites and Tchobanoglous [25] and Metcalf and Eddy [11]. Additionally, this method has been referenced or applied by numerous researchers over the past 25 years, including Etnier et al. [26], and Gupta and Shrivastava [27]. A treatment process is considered to have failed when the discharged water does not comply with the set standards. To quantify such failures, a simple equation (Equation (1)) was formulated as illustrated in a study of Niku et al. [16]

(1) F = C e > C s ,

where F is the failure, C _e is the selected treated effluent quality parameter concentration, and C _s represents the concentration requirement for selected treated effluent quality parameters as determined by regulatory standards. Technically, the core idea of reliability is defined as the “probability of success” or “probability of adequate performance.” This is measured by the proportion of time that the concentration of selected treated effluent quality parameters meets these standards, as outlined by Niku et al. [15]

(2) R = 1 − P ( F ) ,

where R is the reliability, P(F) is the probability of failure.

By substituting Equation (1) into Equation (2), the value of R becomes

(3) R = 1 − P ( C e > C S ) .

The likelihood of issues occurring in a water treatment process is greatly influenced by the amount of a specific substance in the water being treated. A mathematical formula, representing this distribution rule, can be applied to calculate how long a particular concentration level has surpassed a given threshold in past occurrences. Assuming the process conditions and control variables stay the same, this formula can be used to predict the future performance of a WWTP [18]. By using Equation (4), it is possible to determine the threshold (mx) for a specific average component found in treated wastewater quality

(4) m x = COR × C S ,

where m _x is the the average amount of a substance; rules for the desired level of a specific component in treated wastewater and COR is the reliability coefficient.

According to Niku et al. [15], the following mathematical model should be used to process the coefficient of reliability (COR):

(5) COR = ( C v x 2 + 1 ) 1 2 × e { − z 1 − α [ ln ( C v x 2 + 1 ) ] 1 / 2 } ,

where Cv x is the coefficient of variation, which assesses the variability among a set of numbers by dividing the standard deviation by the mean. It is utilized here to measure the variability of a particular water quality parameter’s concentration. Z 1 − α represents the standardized normal variate, a numerical value typically found in statistical tables that indicates the probability that a certain value will not exceed a defined limit at a given confidence level (1−α). α represents the significance level, which determines the threshold for statistical significance in hypothesis testing.

The performance reliability of the Karbala WWTP was evaluated using the theoretical concepts described above, together with the recorded concentration values of selected pollutants such as BOD5, COD, and TSS in the treated wastewater.

3 Results and discussion

3.1 Statistical analysis of effluent wastewater

The reliability model devised by Niku et al., which employs a lognormal distribution, was developed to model data for the Karbala Selected Treated Water Quality Laboratory (WWTP). The initial step involves identifying the actual probability distribution laws for this setting. Consequently, the quality of effluents discharged by the WWTP has been analyzed using three commonly used parameters for WWTP discharges: BOD5, COD, and TSS.

Karbala WWTP for the year 2022 collected data taken from the administrative staff of the plant.

The normalization of treated effluent from the Karbala WWTP was carried out following methodologies suggested by Helsel and Hirsch [28], D’Agostino et al. [29], D’Agostino and Stephens [30], and Pearson et al. [31]. The asymmetry of distribution, measured by the standard skewness, gauges the divergence of values from symmetry. A skewness value close to zero typically indicates a distribution skewed to the right and suggests positive symmetry when the distribution curve appears balanced. The kurtosis coefficient, which describes the degree of curvature or flatness of a distribution, generally nears three in a normal distribution. By examining histograms and probability density functions for each concentration, variations linked to specific factors are identified and quantified, enhancing the assessment of wastewater treatment quality. Illustrations of historical data and probability distribution functions (PDFs) for concentrations of BOD5, COD, and TSS in 2022 from the Karbala City WWTP are presented in Figures 2–4. These figures show a slight rightward shift in the data, consistent with the standard deviations noted in Table 3. Statistical analysis was performed using the Statistics and Machine Learning Toolbox V.R2019A. Probabilistic analysis of effluent parameters for BOD5, COD, and TSS is depicted in Figures 5–7 and analyzed using MATLAB 19. The distributions for all effluent pollutant parameters (BOD5, COD, and TSS) in both the classical activated sludge and sequencing batch reactor systems at the Karbala WWTP exhibit a lognormal distribution, which is frequently used in wastewater treatment research as referenced by sources including Oliveira and Von Sperling [32], Charles et al. [33], Bugajski et al. [34], and Górka [35].

Figure 2

Histogram and PDF of effluent BOD5 concentration of Karbala WWTP (2022).

Figure 3

Histogram and PDF exhibit the concentration of COD in the effluent from the Karbala WWTP (2022).

Figure 4

Histogram and PDF of effluent TSS concentration. Karbala WWTP (2022).

Table 3

Statistic parameters of effluent BOD5, COD, and TSS concentrations

	BOD 5 (mg/l)	COD (mg/l)	TSS (mg/l)
Average	11.308	20.096	11.673
Standard deviation	1.5535	1.4587	1.6535
Coeff. of variation	0.137382	0.072586	0.14165
Minimum	9.0	17	8
Maximum	16.0	24	16
Range	7.0	7	8
Std. skewness	0.744	0.36774	0.40105
Std. kurtosis	3.31	3.1121	3.4519

Figure 5

Lognormal probability plot with curve offset at 5% significance level of the Kolmogorov-Smirnov (K-S) test of effluent BOD5 concentration of Karbala WWTP (2022).

Figure 6

Lognormal probability plot with curve offset at 5% significance level of the K–S test of effluent COD concentration of Karbala WWTP (2022).

Figure 7

Lognormal probability plot with curve offset at 5% significance level of the K–S test of effluent TSS concentration of Karbala WWTP (2022).

3.2 COR calculation

Helsel and Hirsch [28] used Equation (5) to compute the COR values by assigning arbitrary Cv values across various confidence intervals (1 − α), as detailed in Table 4. This finding aligns with another study, which also assigned random Cv values to determine COR values at specific confidence levels (1 − α). This study observed that with an increase in Cv values at the same confidence level, the COR values decreased, and conversely, at a constant Cv value, the COR decreased as the confidence level increased, as illustrated in Figure 8.

Table 4

COR for the different values of Cv and high-reliability levels [28]

Reliability level (%)	C v
Reliability level (%)	0	0.2	0.4	0.6	0.8	1.0	1.2	1.4	1.6	1.8	2.0
90	1.00	0.79	0.66	0.57	0.52	0.49	0.47	0.45	0.45	0.44	0.44
95	1.00	0.74	0.57	0.47	0.40	0.36	0.33	0.31	0.30	0.29	0.28
99	1.00	0.64	0.44	0.32	0.25	0.20	0.17	0.15	0.14	0.13	0.12

Figure 8

Variation of the COR with the Cv for different reliability levels [28].

The Cv and COR values for concentrations of BOD5, COD, and TSS in the effluent wastewater from the Karbala WWTP were calculated across 90, 95, and 99% confidence intervals for the period from 2020 to 2023. Figure 9 illustrates an inverse relationship between the COR and Cv for BOD5 concentrations at a 95% confidence interval during the specified period. A similar inverse relationship between COR and Cv was also observed for COD and TSS concentrations at 90 and 99% confidence intervals for the same timeframe. This finding corroborates the earlier research conducted by Oliveira and Sperling in 2008.

Figure 9

Variation of COR with Cv for 95% reliability level for the concentrations of BOD5 for the period (2020–2023).

Table 5 presents the Cv, COR, and mx values for concentrations of BOD5, COD, and TSS in the effluent wastewater from the Karbala WWTP at a 95% confidence interval over the studied period. The data indicate that most Cv values for the effluent concentrations are below 1. Lower Cv values correspond to higher COR values and an increase in the average concentration of the effluent, maintaining a consistent reliability level of 95%. The highest COR values were generally observed across all considered parameters (BOD5, COD, and TSS). Operational limits (mx) for monitoring specific effluent quality parameters are established using the theoretical framework, with Equation (4) applied to determine these limits. The values for the variable Cs, drawn from Iraqi standards, are set as follows: Cs BOD5 = 40 mg/l, Cs TSS = 60 mg/l, and Cs COD = 100 mg/l. The results displayed in Table 5 for the mx calculations via Equation (4) along with COR values suggest an improvement in the performance of the Karbala WWTP from 2020 to 2023, reflecting effective management practices in controlling and monitoring the quality at the plant and efforts to enhance its overall performance.

Table 5

Cv, COR, and mx values for the concentrations of BOD5, COD, and TSS in the effluent wastewater of Karbala WWTP for a 95% confidence interval for the period from 2020 to 2023

		2020	2021	2022	2023
BOD 5 (mg/l)	C _V	0.22	0.20	0.13	0.05
	COR	0.71	0.73	0.80	0.91
	m _x = COR × C _s	28.4	29.2	32.0	36.4
COD (mg/l)	C _V	0.15	0.13	0.07	0.06
	COR	0.78	0.81	0.88	0.90
	m _x = COR × C _s	78.0	81.0	88.0	90.0
TSS (mg/l)	C _V	0.18	0.17	0.14	0.09
	COR	0.74	0.75	0.80	0.86
	m _x = COR × C _s	44.4	45.0	48.0	51.6

Emphasizing reliability, the operation of the Karbala WWTP should be maintained at a high quality, ensuring that the average concentration of pollutants in the effluent wastewater remains below the regulatory limits to uphold the plant’s high reliability. It is strongly advised that efforts to enhance and develop the plant’s performance continue.

The findings of the study provide critical insights into operational deficiencies and areas prone to failures within the plant, underscoring the immediate need for strategic improvements. These results are pivotal as they offer specific recommendations that assist plant staff in enhancing operational protocols, refining maintenance approaches, and ultimately, boosting the overall functionality of the facility. Such measures are crucial not only for improving the efficacy of wastewater treatment but also for minimizing environmental impacts and adhering to environmental protection and regulatory standards. Implementing these improvements is essential for resolving persistent issues and achieving superior operational performance.

4 Conclusions

This research was carried out to evaluate the performance reliability of the Karbala WWTP and to provide essential data that plant operators can use to gauge reliability levels, enhance biological treatment processes, and guide the quality improvement of wastewater for future plant enhancements. The study findings reveal that the concentrations of pollutant parameters in the effluent wastewater (BOD5, COD, and TSS) at the Karbala WWTP follow a lognormal distribution. The results concerning the reliability coefficient (COR) and the average pollutant concentrations (mx) indicate that the performance of the Karbala WWTP has improved over time from 2020 to 2023. This improvement highlights the effective management of the plant in terms of quality control and monitoring, as well as ongoing efforts to boost overall performance. It is crucial to continue optimal operations at the Karbala WWTP to ensure that the average concentrations of pollutants in the discharged wastewater remain below set limits, thereby maintaining the plant’s reliability and efficiency at a commendable level. The significance of this study lies in its provision of reliable data that can be used by wastewater treatment facility staff to evaluate day-to-day reliability and understand the effectiveness of biological treatment processes. This evaluation considers the quality of the effluent, which assists in developing rational, efficient, and feasible discharge standards.

Acknowledgements

Special thanks to the Karbala Water and Sewage Directorate/Karbala WWTP Department for providing the database used in this study.

Funding information: Authors state no funding involved.
Author contributions: All authors have accepted responsibility for the entire content of this manuscript and consented to its submission to the journal, reviewed all the results, and approved the final version of the manuscript. RJMA-S and JHA-B developed a plan for their research, determining the required data and analysis techniques, while RFA collected and processed the data, analyzing it and presenting the results using tables and figures. Following this, RJMA-S, JHA-B, and WHH discussed the findings and reached appropriate conclusions. RFA prepared the manuscript with contributions from all co-authors.
Conflict of interest: Authors state no conflict of interest.
Data availability statement: The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Received: 2024-01-22

Revised: 2024-04-15

Accepted: 2024-04-20

Published Online: 2024-06-26

This work is licensed under the Creative Commons Attribution 4.0 International License.

Articles in the same Issue

https://doi.org/10.1515/eng-2024-0031

Keywords for this article

reliability coefficient; the coefficient of variation; biochemical oxygen demand; wastewater treatment plant; Karbala

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