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Surface water quality status and prediction during movement control operation order under COVID-19 pandemic: Case studies in Malaysia.
Najah, A; Teo, F Y; Chow, M F; Huang, Y F; Latif, S D; Abdullah, S; Ismail, M; El-Shafie, A.
  • Najah A; Institute of Energy Infrastructure (IEI), Universiti Tenaga Nasional (UNITEN), 43000 Kajang, Selangor Darul Ehsan Malaysia.
  • Teo FY; Faculty of Science and Engineering, University of Nottingham Malaysia, 43500 Semenyih, Selangor Malaysia.
  • Chow MF; Institute of Sustainable Energy (ISE), Universiti Tenaga Nasional (UNITEN), 43000 Kajang, Selangor Malaysia.
  • Huang YF; Department of Civil Engineering, Lee Kong Chian Faculty of Engineering and Science, Universiti Tunku Abdul Rahman, Kajang, Selangor Malaysia.
  • Latif SD; Department of Civil Engineering, College of Engineering, Universiti Tenaga Nasional (UNITEN), 43000 Kajang, Selangor Malaysia.
  • Abdullah S; Air Quality and Environment Research Group, Faculty of Ocean Engineering Technology and Informatics, Universiti Malaysia Terengganu, 21030 Kuala Nerus, Terengganu Malaysia.
  • Ismail M; Faculty of Science and Marine Environment, Universiti Malaysia Terengganu, 21030 Kuala Nerus, Terengganu Malaysia.
  • El-Shafie A; Institute of Tropical Biodiversity and Sustainable Development, Universiti Malaysia Terengganu, 21030 Kuala Nerus, Malaysia.
Int J Environ Sci Technol (Tehran) ; 18(4): 1009-1018, 2021.
Article in English | MEDLINE | ID: covidwho-1070970
ABSTRACT
Global concerns have been observed due to the outbreak and lockdown causal-based COVID-19, and hence, a global pandemic was announced by the World Health Organization (WHO) in January 2020. The Movement Control Order (MCO) in Malaysia acts to moderate the spread of COVID-19 through the enacted measures. Furthermore, massive industrial, agricultural activities and human encroachment were significantly reduced following the MCO guidelines. In this study, first, a reconnaissance survey was carried out on the effects of MCO on the health conditions of two urban rivers (i.e., Rivers of Klang and Penang) in Malaysia. Secondly, the effect of MCO lockdown on the water quality index (WQI) of a lake (Putrajaya Lake) in Malaysia is considered in this study. Finally, four machine learning algorithms have been investigated to predict WQI and the class in Putrajaya Lake. The main observations based on the analysis showed that noticeable enhancements of varying degrees in the WQI had occurred in the two investigated rivers. With regard to Putrajaya Lake, there is a significant increase in the WQI Class I, from 24% in February 2020 to 94% during the MCO month of March 2020. For WQI prediction, Multi-layer Perceptron (MLP) outperformed other models in predicting the changes in the index with a high level of accuracy. For sensitivity analysis results, it is shown that NH3-N and COD play vital rule and contributing significantly to predicting the class of WQI, followed by BOD, while the remaining three parameters (i.e. pH, DO, and TSS) exhibit a low level of importance.
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Full text: Available Collection: International databases Database: MEDLINE Type of study: Case report / Observational study / Prognostic study Language: English Journal: Int J Environ Sci Technol (Tehran) Year: 2021 Document Type: Article

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Full text: Available Collection: International databases Database: MEDLINE Type of study: Case report / Observational study / Prognostic study Language: English Journal: Int J Environ Sci Technol (Tehran) Year: 2021 Document Type: Article