%T Central Composite Design (CCD) applied for statistical optimization of glucose and sucrose binary carbon mixture in enhancing the denitrification process
%I Springer Verlag
%V 7
%A J.-W. Lim
%A H.-G. Beh
%A D.L.C. Ching
%A Y.-C. Ho
%A L. Baloo
%A M.J.K. Bashir
%A S.-K. Wee
%P 3719-3727
%K Carbon; Denitrification; Mixtures; Nitrogen; Nitrogen removal; Regression analysis; Sugar (sucrose), Activated sludge; Carbon mixtures; Carbon source; Carbon-to-nitrogen ratio; Central composite designs; Denitrification process; N removal; Optimisations; Statistical optimization; Sucrose mixtures, Glucose, activated sludge; carbon; denitrification; experimental design; glucose; nitrate; nitrogen; optimization; sucrose
%X The present study provides an insight into the optimization of a glucose and sucrose mixture to enhance the denitrification process. Central Composite Design was applied to design the batch experiments with the factors of glucose and sucrose measured as carbon-to-nitrogen (C:N) ratio each and the response of percentage removal of nitrate�nitrogen (NO3 ��N). Results showed that the polynomial regression model of NO3 ��N removal had been successfully derived, capable of describing the interactive relationships of glucose and sucrose mixture that influenced the denitrification process. Furthermore, the presence of glucose was noticed to have more consequential effect on NO3 ��N removal as opposed to sucrose. The optimum carbon sources mixture to achieve complete removal of NO3 ��N required lesser glucose (C:N ratio of 1.0:1.0) than sucrose (C:N ratio of 2.4:1.0). At the optimum glucose and sucrose mixture, the activated sludge showed faster acclimation towards glucose used to perform the denitrification process. Later upon the acclimation with sucrose, the glucose uptake rate by the activated sludge abated. Therefore, it is vital to optimize the added carbon sources mixture to ensure the rapid and complete removal of NO3 ��N via the denitrification process. © 2016, The Author(s).
%O cited By 10
%L scholars8150
%J Applied Water Science
%D 2017
%N 7
%R 10.1007/s13201-016-0518-9