Application of multivariate statistical techniques in the evaluation of large-scale water treatment plants in Baghdad.

Nisreen Y. Mohammed; KHALID ADEL ABDULRAZZAQ

doi:http://dx.doi.org/10.1088/1757-899X/1105/1/012109

Details

Publication Date

Tue Jun 01 2021

Journal Name

Https://www.researchgate.net/journal/iop-conference-series-materials-science-and-engineering-1757-899x

Volume

1105

DOI

http://dx.doi.org/10.1088/1757-899X/1105/1/012109

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Application of multivariate statistical techniques in the evaluation of large-scale water treatment plants in Baghdad.

Multivariate statistical

Techniques

Evaluation

Large-scale

Water treatment plants

Baghdad.

Nisreen Y. Mohammed

KHALID ADEL ABDULRAZZAQ

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AbstractThis paper aims to evaluate large-scale water treatment plants’ performance and demonstrate that it can produce high-level effluent water. Raw water and treated water parameters of a large monitoring databank from 2016 to 2019, from eight water treatment plants located at different parts in Baghdad city, were analyzed using nonparametric and multivariate statistical tools such as principal component analysis (PCA) and hierarchical cluster analysis (HCA). The plants are Al-Karkh, Sharq-Dijlah, Al-Wathba, Al-Qadisiya Al-Karama, Al-Dora, Al-Rasheed, Al-Wehda. PCA extracted six factors as the most significant water quality parameters that can be used to evaluate the variation in drinking water quality and responsible for 73.389% of the variance in the data set. Based on this selection criterion, the most significant water quality parameters that can be used to evaluate the variation in drinking water quality parameters are the mineral-related parameters (e.g., Ca+2, Mg+2, salinity, hardness), the nutrient parameters (i.e., dissolved nitrate and nitrite and orthophosphate), and a physical parameter. HCA analysis was able to group water treatment plants with similar raw water and treated water quality based on the water quality data from eight WTPs into three clusters.

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Journal Name

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Cr2O3

Thin Films

Optical Properties

Spray Pyrolysis

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Sami Salman

Nadir Fadhil

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Purpose

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Design/methodology/approach

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Zainab Thamer

Ehab M

Mohammad J

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Convolutional Neural Network (C.N.N.)

Deep learning (D.L.)

Musculoskeletal (M.S.K.)

Knee

Meniscus

Tear

Area Under the Curve (A.U.C.)

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