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

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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.

KHALID ADEL

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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.

Publication Date

Thu Jun 01 2023

Journal Name

Iraqi Journal Of Physics

D-Shaped Photonic Crystal Fiber Toxic Metal Ions (Arsenic) Sensor Based on Surface Plasmon Resonance

Surface Plasmon Resonance

Optical Fiber Sensor

Toxic Metal Ions in Water

Photonic Crystal Fiber

D-shaped PCF

Ghufran Mohammed

Soudad

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In this work, a Photonic Crystal Fiber (PCF) sensor based on the Surface Plasmon Resonance (SPR) technology was proposed. A thin layer of gold (Au) was deposited on a D-shaped Photonic Crystal Fiber (PCF), which was coated with plasmonic chemically stable gold material with a thickness of 40nm. The performance parameters like sensitivity including wavelength sensitivity and amplitude sensitivity and resolution were evaluated by simulation using COMSOL software. The proposed sensor was created by using the finite element approach, it is numerically examined. The results show that the surface of D-shaped Photonic Crystal Fiber coated with Au behaves as a sensor to detect the refractive index (IR) of toxic metal ions. The impacts of the str

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