TY - JOUR
T1 - SARS-CoV-2 removal by mix matrix membrane
T2 - A novel application of artificial neural network based simulation in MATLAB for evaluating wastewater reuse risks
AU - Zahmatkesh, Sasan
AU - Rezakhani, Yousof
AU - Chofreh, Abdoulmohammad Gholamzadeh
AU - Karimian, Melika
AU - Wang, Chongqing
AU - Ghodrati, Iman
AU - Hasan, Mudassir
AU - Sillanpaa, Mika
AU - Panchal, Hitesh
AU - Khan, Ramsha
N1 - Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2023/1
Y1 - 2023/1
N2 - The COVID-19 outbreak led to the discovery of SARS-CoV-2 in sewage; thus, wastewater treatment plants (WWTPs) could have the virus in their effluent. However, whether SARS-CoV-2 is eradicated by sewage treatment is virtually unknown. Specifically, the objectives of this study include (i) determining whether a mixed matrixed membrane (MMM) is able to remove SARS-CoV-2 (polycarbonate (PC)-hydrous manganese oxide (HMO) and PC-silver nanoparticles (Ag-NP)), (ii) comparing filtration performance among different secondary treatment processes, and (iii) evaluating whether artificial neural networks (ANNs) can be employed as performance indicators to reduce SARS-CoV-2 in the treatment of sewage. At Shariati Hospital in Mashhad, Iran, secondary treatment effluent during the outbreak of COVID-19 was collected from a WWTP. There were two PC-Ag-NP and PC-HMO processes at the WWTP targeted. RT-qPCR was employed to detect the presence of SARS-CoV-2 in sewage fractions. For the purposes of determining SARS-CoV-2 prevalence rates in the treated effluent, 10 L of effluent specimens were collected in middle-risk and low-risk treatment MMMs. For PC-HMO, the log reduction value (LRV) for SARS-CoV-2 was 1.3–1 log10 for moderate risk and 0.96–1 log10 for low risk, whereas for PC-Ag-NP, the LRV was 0.99–1.3 log10 for moderate risk and 0.94–0.98 log10 for low risk. MMMs demonstrated the most robust absorption performance during the sampling period, with the least significant LRV recorded in PC-Ag-NP and PC-HMO at 0.94 log10 and 0.96 log10, respectively.
AB - The COVID-19 outbreak led to the discovery of SARS-CoV-2 in sewage; thus, wastewater treatment plants (WWTPs) could have the virus in their effluent. However, whether SARS-CoV-2 is eradicated by sewage treatment is virtually unknown. Specifically, the objectives of this study include (i) determining whether a mixed matrixed membrane (MMM) is able to remove SARS-CoV-2 (polycarbonate (PC)-hydrous manganese oxide (HMO) and PC-silver nanoparticles (Ag-NP)), (ii) comparing filtration performance among different secondary treatment processes, and (iii) evaluating whether artificial neural networks (ANNs) can be employed as performance indicators to reduce SARS-CoV-2 in the treatment of sewage. At Shariati Hospital in Mashhad, Iran, secondary treatment effluent during the outbreak of COVID-19 was collected from a WWTP. There were two PC-Ag-NP and PC-HMO processes at the WWTP targeted. RT-qPCR was employed to detect the presence of SARS-CoV-2 in sewage fractions. For the purposes of determining SARS-CoV-2 prevalence rates in the treated effluent, 10 L of effluent specimens were collected in middle-risk and low-risk treatment MMMs. For PC-HMO, the log reduction value (LRV) for SARS-CoV-2 was 1.3–1 log10 for moderate risk and 0.96–1 log10 for low risk, whereas for PC-Ag-NP, the LRV was 0.99–1.3 log10 for moderate risk and 0.94–0.98 log10 for low risk. MMMs demonstrated the most robust absorption performance during the sampling period, with the least significant LRV recorded in PC-Ag-NP and PC-HMO at 0.94 log10 and 0.96 log10, respectively.
KW - Artificial neural network
KW - Mix matrix membrane
KW - SARS-CoV-2
KW - Wastewater treatment
UR - http://www.scopus.com/inward/record.url?scp=85140272890&partnerID=8YFLogxK
U2 - 10.1016/j.chemosphere.2022.136837
DO - 10.1016/j.chemosphere.2022.136837
M3 - Article
C2 - 36252897
AN - SCOPUS:85140272890
SN - 0045-6535
VL - 310
JO - Chemosphere
JF - Chemosphere
M1 - 136837
ER -