Textile wastewater treatment plant performance assessment using time-function based effluent quality index and multiple regression models

Abstract

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.