Extensive water and chemicals are used in the textile industry processes. Therefore, treatment of textile wastewater is vital to protect the environment, maintain the public health, and recover resources. However, due to poor operation and plant performance the partially treated textile wastewater was directly discharged to a nearby river. Thus, the aim of this study was to characterize the wastewater physicochemical properties and evaluate the performance of the textile factory-activated sludge process wastewater treatment plant (WWTP) in Bahir Dar, Ethiopia. In inlet and outlet of the WWTP, samples were collected for 6 months and analyzed on-site and in a laboratory for parameters including, dissolved oxygen, pH, temperature, total Kjeldhal nitrogen (TKN), chemical oxygen demand (COD), biochemical oxygen demand (BOD₅), total suspended solids (TSS), total nitrogen (TN), total phosphorous (TP), nitrite, nitrate, and metallic compounds. The TSS, BOD₅, COD, TP, nitrite, ammonia, and total chromium result were above the discharge limit with 73.2 mg/L, 48.45 mg/L, 144.08 mg/L, 7.9 mg/L, 1.36 mg/L, 1.96 mg/L, and 0.16 mg/L, respectively. Multiple regression models were developed for each overall, net moving average, and instantaneous effluent quality index (EQI). The predictor parameters BOD₅, TN, COD, TSS, and TP (R² = 0.995 to 1.000) estimated the net pollution loads of all predictors as 492.55 kg/day and 655.44 kg/day. Except TN, TKN, and NO₃, the remaining six performance parameters were violating the permissible limit daily. Furthermore, the overall plant efficiency was predicted as 38 % and 42 % for the moving average and instantaneous EQI, respectively. Our study concluded that the integrated regression models and EQI can easily estimate the plant efficiency and daily possible pollution load.

The challenge of selecting an appropriate wastewater treatment plant (WWTP) site is addressed in this study, using the case study of Bahir Dar City, Ethiopia. An innovative approach is proposed for selecting the WWTP site. Fifteen practically feasible alternatives were identified based on the geographical information system (GIS) based hydraulic design and considering the overall economy of the system. The three dimensions of sustainability were considered while evaluatingalternatives through incorporating economic, social, energy and environmental criteria in decision-making. The multiple attribute decision making (MADM) method was applied to prioritize the alternatives. Four scenarios representing the different perspectives of choices were used for weight elicitation. The results of the study show that the developed decisionmaking approach identified practically feasible alternatives. The framework and decision-making methodology developed in this study helped to facilitate the decision making by local government in a holistic view that incorporates environmental management in the city of Bahir Dar.

Textile factory water consumption could be optimized to minimize the generation of wastewater, reduce treatment costs, and promote resource recovery. However, downstream plant operation and management is a prime concern in the textile industry, particularly bringing treated wastewater effluent to an acceptable discharge limit. The aim of the study was to optimize key process control parameters to the observed operational challenges of existing processes and suggest an operational guide to the operators and decision makers to enhance the treatment performance in GPS-X. The formulated troubleshooting and decision support strategy, and the optimization results of waste-activated sludge in the primary and secondary clarifiers, was within the range of 15 ± 5 m³/d and 83 ± 7 m³/d, respectively, with a recycle-activated sludge flow of 150 ± 10 m³/d. The sludge retention time was 5 ± 1 d and 6.7 ± 0.5 d in the secondary and primary clarifiers, respectively. The addition of a carbon source in the form of molasses had a flow of 0.5 ± 0.05 m³/d, and the variation in the influent due to wastewater characteristics and rainfall was optimized to 600 ± 50 m³/d. The optimum air flow into the aeration tank was 550 ± 5 m³/hr and saved 91.5% of energy in the optimized process. Thus, the study is indispensable for the effective and efficient operation of the plant and serves as a good guide to the plant operators and decision makers for the best course of action.

Access to safe drinking water is a fundamental human need for health and well-being implemented globally by the United Nations under Sustainable Development Goal (SDG) 6. Storing drinking water is common in rural areas of Ethiopia due to off-premises water sources and intermittent piped water supply. However, this practice can lead to further contamination during collection, transport, and storage, posing a risk to public health. The objective of this study was to identify the determinant factors of drinking water quality at the point of use in the rural setting of northwestern Ethiopia, South Gondar zone. A questionnaire survey was conducted, and water samples from 720 households were collected during the wet and dry seasons. The determinant factors were identified using the multivariable logistic regression model. About 39.2% of the surveyed households had basic water supply services, 41.9% were using unimproved sources, and 8.3% were using surface water. Only 9.4% were using basic sanitation services, and 57.2% were practicing open defecation. Safe water storage was practiced by 84.3% of households, while only 2% engaged in household water treatment. About 14% of dry and 8% of wet season samples from the storage were free from fecal coliform bacteria. Furthermore, 52.9% of dry and 62.2% of wet season samples fell under the high microbial health risk category. The season of the year, the water source type, storage washing methods, and the socioeconomic status of the household were identified as key predictors of household drinking water fecal contamination using the multivariable logistic regression model. It was observed that the drinking water in households had a high load of fecal contamination, posing health risks to consumers. To tackle these problems, our study recommends that stakeholders should enhance access to improved water sources, implement source-level water treatment, increase access to improved sanitation facilities, advocate for safe household water management practices, and endorse household water treatment methods.

Extensive water and chemicals are used in the textile industry processes. Therefore, treatment of textile wastewater is vital to protect the environment, maintain the public health, and recover resources. However, due to inadequate quality data, inexperienced plant operators, and inconsistent measurements, a real-time prediction of effluent quality of a textile wastewater treatment plant is difficult. Thus, the aim of this study was to characterize the wastewater physicochemical properties and evaluate the performance of the textile factory wastewater treatment plant (WWTP) in Bahir Dar, Ethiopia. Inlet and outlet of the WWTP, samples were collected for six months and analyzed on-site and in a laboratory for parameters including, dissolved oxygen, pH, temperature, total Kjeldhal nitrogen (TKN), chemical oxygen demand (COD), biochemical oxygen demand (BOD₅), total suspended solids (TSS), total nitrogen (TN), total phosphorous (TP), nutrients, and metallic compounds. The TSS, BOD₅, COD, TP, nitrite, ammonia, and total chromium result were above the discharge limit with 73.2 mg/L, 48.45 mg/L, 144.08 mg/L, 7.9 mg/L, 1.36 mg/L, 1.96 mg/L, and 0.16 mg/L, respectively. Multiple regression models were developed for each overall, net moving average and instantaneous effluent quality index (EQI). The predictor parameters BOD₅, TN, COD, TSS, and TP (R² = 0.995 to 1.000) estimated the net pollution load as 492.55 kg/d and 655.44 kg/d. Except TN, TKN, and NO₃, the remaining six performance parameters were violating the permissible limit daily. Furthermore, the overall plant efficiency was predicted as 38 % and 42 % for the moving average and instantaneous EQI, respectively. Our study concluded that the integrated regression models and EQI can easily estimate the plant efficiency and daily possible pollution load.