Applying the Wastewater Quality Index for Assessing the Effluent Quality of Recently Upgraded Meet Abo El-koum Wastewater Treatment Plant

The wastewater quality index (WWQI) can be defined as a single value, which reflects the overall wastewater quality related to its input constituent parameters. The major objective of the present study was to investigate the suitability of the effluent quality from Meet Abo El-koum wastewater treatment plant in Egypt for safe disposal based on the wastewater quality index approach. Moreover, statistical analysis was applied to develop a simple model using multiple linear regression (MLR) for accurate prediction of WWQI depending on different wastewater quality parameters. The results indicate good quality of the treated wastewater for safe disposal in general. Moreover, it is apparent that about 17% of the WWQI values reached excellent quality referring to the classification of the WWQI levels. For greater simplicity, a relationship between BOD5 and COD was deduced using linear regression, so that the results of the BOD5 analyses that appear after five days can be skipped. This approximation can be used to calculate WWQI on a specific day given the results of the treated wastewater analyses on that day.


INTRODUCTION
Water quality index (WQI) provides a single dimensionless value that indicates the overall water quality under specified conditions of time and location depending on various water quality parameters. In most cases, WQI is applied to assess the quality of water resources and potability of the treated water (Praus, 2019; Phadatare and Gawande, 2016; Tsakiris, 2016; Tyagi et al., 2013;WHO, 2018). The idea of WQI was pioneered by Horton (1965) and developed by Brown et al. (1970) to be a decision-making tool for planners, stakeholders in addition to the governmental authorities and agencies to facilitate smart management of the water quality issues ( Libânio and Lopes, 2009). This concept of WQI is applied to wastewater and the quality of the wastewater may be determined based on the wastewater quality index (WWQI). The wastewater quality index can be defined as a single value, which reflects the overall wastewater quality related to its input constituent parameters (Chmielowski et Oni and Fasakin (2016) applied Weighted Arithmetic WAWQIM to assess potability of the surface and groundwater in Nigeria. In addition, Yogendra and Puttaiah (2008) applied WAWQIM to assess the appropriateness of an urban water body in Shimoga Town, Karnataka. These researchers concluded that WAWQIM is an influential approach that guarantees the suitability of water for human consumption in the case of freshwater bodies. Furthermore, Phadatare and Gawande (2016) informed that the WAWQIM method is beneficial globally for evaluating, monitoring and impact studies for different water bodies.
Ibrahim (2019) applied WAWQIM for evaluating the suitability of effluent quality of a wastewater treatment plant (WWTP) in Jordan for the irrigation purpose. The treated wastewater quality was categorized to be suitable for different types of agricultural crops based on the estimated WWQI. Moreover, Jamshidzadeh and Barzi (2020) merged twenty-three wastewater parameters to develop WWQI for assessing the effluent quality of Isfahan North WWTP. Therefore, WWQI is a useful tool for researchers and decision-makers to monitor and assess the wastewater quality. It is also helpful for the public to understand the treated wastewater quality for any purpose (Jamshidzadeh and Barzi, 2020; Praus, 2019; Ibrahim, 2019). The major objective of the present study was to investigate the suitability of the effluent quality from a newly upgraded wastewater treatment plant in Egypt for safe disposal based on the wastewater quality index approach.

Study area
A recently upgraded WWTP shown in Figure 1 receives 10,000 m 3 /d of municipal wastewater. The WWTP was implemented in Meet Abo El-koum village, El-Menoufya Governorate (about 65 km from Cairo, Egypt). The WWTP had been previously operating with an extended aeration system with a capacity of 4,600 m 3 /d, and it was newly developed to accommodate 10,000 m 3 /d of wastewater. The upgrading involved regular installation of surface turbine aerators on the aeration tanks and construction of primary sedimentation tanks.

The analyses results of treated wastewater
The treated effluent wastewater characteristics were collected and statistically analyzed as denoted in Table 1. The parameters and the equipment utilized in the laboratory tests are represented in Table 2 (1) where: q n = quality rating of n th water quality parameter, and W n = unit weight of n th water quality parameter The following equation was applied for estimating the quality rating (q n ) where: V n = estimated value of n th water quality parameter, V id = ideal value for n th parameter (i.e. for pH, V id = 7.0, and V id = zero for the other parameters), and S n = standard permissible value of n th water quality parameter The unit weight (W n ) was calculated using the following equation: where: S n = standard permissible value of n th water quality parameter, and K= constant of proportionality. It was calculated using the following equation: When applying this WQI concept to wastewater, the wastewater quality can be determined based on the WWQI. Rating of WWQI and corresponding grade of the treated wastewater are displayed in Table 3.

WWQI during the study period
Comparing the results of the treated wastewater quality analyses shown in Table 4 with the limit of the effluent treated wastewater presented in Table 1 revealed that the treated wastewater quality conforms to the international standards of secondary treated wastewater (WHO, 2018, Metcalf and Eddy, 2003). Furthermore, WWQI was calculated using WAWQIM for each month during the study period as shown in Table 4.
The monthly WWQI values ranged between 21.4 and 40.5 with an average value of 31.63 through the study period, which indicates good

Model development for predicting WWQI
Multiple linear regression (MLR) model was applied as a statistical tool for the prediction of WWQI depending on the recorded treated wastewater quality parameters (Vijayan et al., 2016). The output data from the analysis of variance (ANOVA) model are shown in Table 5, whereas coefficients and statistical results from the MLR model are represented in Table ( WWQI was considered a dependent variable, while the parameters of wastewater quality were independent variables in MLR confirmed by Rsquared value of 0.994. Therefore, MLR is a simple, direct, and very accurate model for assessing the effluent quality of the Meet Abo El-koum wastewater treatment plant. The estimated WWQI using WAWQIM and the predicted WWQI using MLR model were outlined as shown in Figure 2, in relationship with the study period (from October 2019 till September 2020). The close values of estimated and predicted wastewater quality indices are very noticeable. Hence, the predicted WWQI using the MLR model is valid for assessing the quality of treated wastewater in Meet Abo El-koum WWTP, given the values of treated wastewater characteristics. For greater simplicity, a relationship between BOD 5 and COD can be deduced using linear regression as shown in Figure 3, so that  the results of the BOD 5 analyses that appear after five days can be skipped. This approximation can be used to calculate WWQI on a specific day given the results of the treated wastewater analyses on that day. With reference to Figure 3, the relationship between BOD 5 and COD can be expressed by using the following equation: By substitution into equation (5)

CONCLUSIONS
The wastewater quality index can be defined as a single value, which reflects the overall wastewater quality related to its input constituent parameters. The monthly WWQI values ranged between 21.4 and 40.5 with an average value of 31.63 through the study period, which indicates good quality of the treated wastewater for safe disposal in general. Moreover, it is apparent that about 17% of the WWQI values recorded excellent quality referring to the classification of WWQI levels. On the other hand, MLR is a simple, direct, and very accurate model for assessing the effluent quality of the Meet Abo El-koum wastewater treatment plant. For greater simplicity, a relationship between BOD 5 and COD was deduced using linear regression, so that the results of the BOD 5 analyses that appear after five days can be skipped. This approximation can be used to calculate WWQI on a specific day given the results of the treated wastewater analyses on that day.