Hybrid Biological Systems for Wastewater Treatment
Date
2018
Authors
D S, Manu
Journal Title
Journal ISSN
Volume Title
Publisher
National Institute of Technology Karnataka, Surathkal
Abstract
The current trend in sustainable development deals majorly with the
environmental management. There is a need for economically affordable, advanced
treatment methods for the proper treatment and management of domestic wastewater
containing excess nutrients (such as nitrogen and phosphorous) which otherwise may
lead to eutrophication. In the present study, the effect of carbon to nitrogen (C/N)
ratio, suspended biomass concentration (X), hydraulic retention time (HRT), and
dissolved oxygen (DO) on nutrients removal in a lab-scale activated sludge biofilm
(AS-biofilm) reactor was monitored. Based on various trials, it was seen that ASbiofilm reactor achieved good removal efficiencies with respect to COD-92%, NH4+-
N- 93%, TN- 86% and TP-52%. Further, in order to improve the quality of the treated
wastewater, photocatalysis by TiO2 was investigated as a post-treatment technology,
using solar and UV irradiations. The UV photocatalysis was found to be better than
solar photocatalysis during the comparative analysis. The maximum removal
efficiencies of COD, MPN and phosphorous at optimum conditions in the case of UV
and solar irradiations were 72%, 95%, 52% and 71%, 99%, 50% respectively.
Similarly, to enhance the performance of the system in terms of nitrogen and
phosphorous in addition to carbon removal integrated anaerobic/anoxic/oxic activated
sludge biofilm (A2O-AS-biofilm) reactor was designed and operated by varying
operating conditions such as C/N ratio, suspended biomass (X), HRT and DO. Based
on various trials, it was seen that the A2O-AS-biofilm reactor achieved good removal
efficiencies of COD-95.5%, TP-93.1%, NH4+-N-98% and TN-80% when the reactor
maintained C/N ratio - 4, suspended biomass (X) - 3 to 3.5 g/L, HRT-10hr, and DO -
1.5 to 2.5mg/L. Applicability of soft computing techniques viz, Adaptive Neuro
Fuzzy Inference System (ANFIS), Genetic Algorithm Adaptive Neuro Fuzzy
Inference System (GA-ANFIS) and Particle Swarm Optimization Adaptive Neuro
Fuzzy Inference System (PSO-ANFIS) to performance prediction of hybrid system
was studied. ANFIS was applied on real time WWTP of 43.5 MLD capacity. ANFIS
models showed better efficiency while modeling wastewater using multivariate
analysis. So in the current study, in order to improve the prediction ability of ANFIS,ii
hybrid models such as GA-ANFIS and PSO-ANFIS have been applied for the
prediction of effluent TN, COD and TP concentration yielded from a hybrid ASbiofilm reactor. From the results, both GA-ANFIS and PSO-ANFIS proved capable to
predict the effluent parameters of the reactor with varying operation conditions and
can be adopted for modeling the nonlinear data.
Description
Keywords
Department of Civil Engineering, AS-biofilm, Biomass, Carbon/nitrogen, GA-ANFIS, PSO-ANFIS