TY - JOUR
T1 - Contaminant Removal from Wastewater by Microalgal Photobioreactors and Modeling by Artificial Neural Network
AU - Mojiri, Amin
AU - Ozaki, Noriatsu
AU - Kazeroon, Reza Andasht
AU - Rezania, Shahabaldin
AU - Baharlooeian, Maedeh
AU - Vakili, Mohammadtaghi
AU - Farraji, Hossein
AU - Ohashi, Akiyoshi
AU - Kindaichi, Tomonori
AU - Zhou, John L.
N1 - Funding Information:
This study was funded by the JSPS KAKENHI (grant number 21H01465).
Publisher Copyright:
© 2022 by the authors.
PY - 2022/12
Y1 - 2022/12
N2 - The potential of microalgal photobioreactors in removing total ammonia nitrogen (TAN), chemical oxygen demand (COD), caffeine (CAF), and N,N-diethyl-m-toluamide (DEET) from synthetic wastewater was studied. Chlorella vulgaris achieved maximum removal of 62.2% TAN, 52.8% COD, 62.7% CAF, and 51.8% DEET. By mixing C. vulgaris with activated sludge, the photobioreactor showed better performance, removing 82.3% TAN, 67.7% COD, 85.7% CAF, and 73.3% DEET. Proteobacteria, Bacteroidetes, and Chloroflexi were identified as the dominant phyla in the activated sludge. The processes were then optimized by the artificial neural network (ANN). High R2 values (>0.99) and low mean squared errors demonstrated that ANN could optimize the reactors’ performance. The toxicity testing showed that high concentrations of contaminants (>10 mg/L) and long contact time (>48 h) reduced the chlorophyll and protein contents in microalgae. Overall, a green technology for wastewater treatment using microalgae and bacteria consortium has demonstrated its high potentials in sustainable management of water resources.
AB - The potential of microalgal photobioreactors in removing total ammonia nitrogen (TAN), chemical oxygen demand (COD), caffeine (CAF), and N,N-diethyl-m-toluamide (DEET) from synthetic wastewater was studied. Chlorella vulgaris achieved maximum removal of 62.2% TAN, 52.8% COD, 62.7% CAF, and 51.8% DEET. By mixing C. vulgaris with activated sludge, the photobioreactor showed better performance, removing 82.3% TAN, 67.7% COD, 85.7% CAF, and 73.3% DEET. Proteobacteria, Bacteroidetes, and Chloroflexi were identified as the dominant phyla in the activated sludge. The processes were then optimized by the artificial neural network (ANN). High R2 values (>0.99) and low mean squared errors demonstrated that ANN could optimize the reactors’ performance. The toxicity testing showed that high concentrations of contaminants (>10 mg/L) and long contact time (>48 h) reduced the chlorophyll and protein contents in microalgae. Overall, a green technology for wastewater treatment using microalgae and bacteria consortium has demonstrated its high potentials in sustainable management of water resources.
KW - bacteria
KW - caffeine
KW - DEET
KW - emerging contaminants
KW - microalgae
UR - http://www.scopus.com/inward/record.url?scp=85144604976&partnerID=8YFLogxK
U2 - 10.3390/w14244046
DO - 10.3390/w14244046
M3 - Article
AN - SCOPUS:85144604976
SN - 2073-4441
VL - 14
JO - Water (Switzerland)
JF - Water (Switzerland)
IS - 24
M1 - 4046
ER -