Graywater turbidity removal by coagulation/ flocculation/ decantation us-ing response surface methodology
International Journal of Development Research
Graywater turbidity removal by coagulation/ flocculation/ decantation us-ing response surface methodology
Received 25th April, 2022 Received in revised form 29th May, 2022 Accepted 24th June, 2022 Published online 25th July, 2022
Copyright © 2022, Mayk Ernando Brito de Barros Miranda et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
The gray waters from washing machines are the ones that show the easiest treatment due to their physical, chemical, and microbiological characteristics. This study characterized the samples of gray water generated in a laundry in Palmas-TO and applied the coagulation/ flocculation/ decantation test, analyzing the removal of turbidity to determine the statistical model that represents the efficiency of the adopted process. Bench tests were carried out simulating a gray water treatment process: coagulation, flocculation, sedimentation, and filtration in a sand filter using the Jar-Test equipment with the use of aluminum sulfate coagulant, and the factorial plans were also made: fractional factorial design (FFD) and central rotational composite design (CRCD). For the characterization of the samples, the following results were obtained: pH (9.2), temperature (25ºC), turbidity (112uT), COD (200 mg / L), and alkalinity (241 mg / L). In the DFF process, turbidity responses between 7.8 uT and 28.1 uT are observed, and according to the Pareto graph, the greatest effects on the sample's turbidity result were the coagulant dosage variables (9.45) and sedimentation time (-10.70). In the CRCD process, the turbidity result between 5.2 and 26.1 uT was obtained through a regression model and according to the Pareto graph, the two variables X1 Dosage (mg / L) and X2 Sedimentation Time (min) showed considerable significance for the response. Through the analysis of variance, the R² coefficient reached by the regression was 0.9641, showing a good fit of the model. The results determined the statistical model that represents the removal of gray water turbidity through the coagulation/flocculation/decantation process.