Optical Detection of Dissolved Solids in Water Samples

Nida Nasir, Omer Al Bashier, Ahmed Ali Murad, Mahmoud Al Ahmad

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)

Abstract

This work investigates the use of optical methods for the detection of dissolved solids in water. In this spectrophotometry, we used high-intensity Xenon light within the wavelength range of 640-1010 nm, to measure the transmittance of water samples. Several water samples of groundwater and medical wastewater collected from different locations under different set of conditions have been used. For all the tested samples, the transmittance was measured and the relations between the parameters such as salinity, pH and total dissolved solids (T.D.S.) concentration were developed. By considering the average of digital counts by the spectrophotometer, the concentration of dissolved solids in water samples is evaluated and the quantitative analysis is done based on the transmittance of the samples in the near infrared region.

Original languageEnglish
Title of host publication2018 IEEE 5th International Conference on Engineering Technologies and Applied Sciences, ICETAS 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
ISBN (Electronic)9781538679661
DOIs
Publication statusPublished - Jul 2 2018
Event5th IEEE International Conference on Engineering Technologies and Applied Sciences, ICETAS 2018 - Bangkok, Thailand
Duration: Nov 22 2018Nov 23 2018

Publication series

Name2018 IEEE 5th International Conference on Engineering Technologies and Applied Sciences, ICETAS 2018

Conference

Conference5th IEEE International Conference on Engineering Technologies and Applied Sciences, ICETAS 2018
Country/TerritoryThailand
CityBangkok
Period11/22/1811/23/18

Keywords

  • Ground Water
  • Medical Waste Water
  • NIR Spectrophotometry
  • Transmittance

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Computer Science Applications
  • Computer Vision and Pattern Recognition
  • Information Systems
  • Electrical and Electronic Engineering
  • Mechanical Engineering
  • Education

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