Login / Signup

Optimization of treating phenol from wastewater through the TiO2-catalyzed advanced oxidation process and response surface methodology.

Camila Oliveira GuimarãesAlexandre Boscaro FrançaGisella Rossana Lamas SamanamudEduardo Prado BastonRenata Carolina Zanetti LofranoCarla Cristina Almeida LouresLuzia Lima Rezende NavesFabiano Luiz Naves
Published in: Environmental monitoring and assessment (2019)
The use of dispersed catalysts in aqueous medium inside reactors in advanced oxidative processes is common among researchers. However, due to the difficult separation of these species after treatment, in many cases, the treatment process is unfeasible. In this context, the main target of the work was the evaluation of degradation of the phenolic solution by ozonation titanium dioxide (TiO2/P25), supported on zeolite spheres. The process was investigated through the response surface methodology (RSM) and optimized by the generalized reduced gradient (GRG) algorithm. The effects of various operating parameters including pH, power ozone (O3) generation, flow rate, and treatment time were investigated, using as a response to removal of chemical oxygen demand (COD). It was made in optimum conditions the ratio of biochemical oxygen demand (BOD)/chemical oxygen demand to check the increasing biodegradability, aiming ozonation as preliminary treatment, with the possibility of subsequent biological treatments. There was an increase in this ratio from 0.17 to 0.50 in 48 min, which would facilitate the use of the subsequent biological process. The proposed model showed good fit to the experimental data with R2 and R2adj correlation coefficients of 0.9964 and 0.9932, respectively.
Keyphrases
  • machine learning
  • deep learning
  • nitric oxide
  • air pollution
  • atomic force microscopy
  • particulate matter
  • wastewater treatment
  • room temperature
  • neural network