Multivariate Statistical Techniques to Identify the Source of Pollution and Assessment of Surface Water Quality

Principal component analysis (CPA) and multiple liner regression (MLR) analysis was applied on the data for 14 physico-chemical parameters of surface waters from Tunggak River adjacent to the Gebeng Industrial Estate, Pahang, Malaysia during February 2012 – January 2013 with the objective of identif...

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Main Authors:	Islam, Mir Sujaul, Hossain, Mohamed Amjed, Nasly, Mohamed Ali
Format:	Article
Language:	English
Published:	National Institute of Ecology 2013
Subjects:	TA Engineering (General). Civil engineering (General) TD Environmental technology. Sanitary engineering
Online Access:	http://umpir.ump.edu.my/id/eprint/11998/ http://umpir.ump.edu.my/id/eprint/11998/ http://umpir.ump.edu.my/id/eprint/11998/1/Multivariate%20Statistical%20Techniques%20to%20Identify%20the%20Source%20of%20Pollution%20and%20Assessment%20of%20Surface%20Water%20Quality.PDF

id	ump-11998
recordtype	eprints
spelling	ump-119982018-09-28T02:37:25Z http://umpir.ump.edu.my/id/eprint/11998/ Multivariate Statistical Techniques to Identify the Source of Pollution and Assessment of Surface Water Quality Islam, Mir Sujaul Hossain, Mohamed Amjed Nasly, Mohamed Ali TA Engineering (General). Civil engineering (General) TD Environmental technology. Sanitary engineering Principal component analysis (CPA) and multiple liner regression (MLR) analysis was applied on the data for 14 physico-chemical parameters of surface waters from Tunggak River adjacent to the Gebeng Industrial Estate, Pahang, Malaysia during February 2012 – January 2013 with the objective of identifying sources of pollution and their contribution to the variation in water quality. Physico-chemical parameters were determined for a period of 12 months by following standard methods of analysis. Results reveled that most of the parameters including BOD, COD, conductivity, NH4-N and phosphorus were in concentrations greater than the national standard of Malaysia. PCA was applied to identify the source and MLR analysis was done to determine their contribution. PCA yielded five VFs; which extracted 74.72% of total variance that established its validation. Results showed that, surface water quality was strongly influenced by ionic groups of salts, soil erosion and agricultural runoff, organic and nutrient pollutions from domestic wastewater, industrial sewage and wastewater treatment plants. Vicinity of industrial parks resulted in low DO concentration all over the basin. MLR showed the contribution of every variable to be highly significant (p<0.01). National Institute of Ecology 2013 Article NonPeerReviewed application/pdf en cc_by_nc_nd http://umpir.ump.edu.my/id/eprint/11998/1/Multivariate%20Statistical%20Techniques%20to%20Identify%20the%20Source%20of%20Pollution%20and%20Assessment%20of%20Surface%20Water%20Quality.PDF Islam, Mir Sujaul and Hossain, Mohamed Amjed and Nasly, Mohamed Ali (2013) Multivariate Statistical Techniques to Identify the Source of Pollution and Assessment of Surface Water Quality. International Journal of Ecology and Environmental Sciences, 39 (3). pp. 187-193. ISSN 2320-5199 http://www.nieindia.org/Journal/index.php/ijees/article/view/234
repository_type	Digital Repository
institution_category	Local University
institution	Universiti Malaysia Pahang
building	UMP Institutional Repository
collection	Online Access
language	English
topic	TA Engineering (General). Civil engineering (General) TD Environmental technology. Sanitary engineering
spellingShingle	TA Engineering (General). Civil engineering (General) TD Environmental technology. Sanitary engineering Islam, Mir Sujaul Hossain, Mohamed Amjed Nasly, Mohamed Ali Multivariate Statistical Techniques to Identify the Source of Pollution and Assessment of Surface Water Quality
description	Principal component analysis (CPA) and multiple liner regression (MLR) analysis was applied on the data for 14 physico-chemical parameters of surface waters from Tunggak River adjacent to the Gebeng Industrial Estate, Pahang, Malaysia during February 2012 – January 2013 with the objective of identifying sources of pollution and their contribution to the variation in water quality. Physico-chemical parameters were determined for a period of 12 months by following standard methods of analysis. Results reveled that most of the parameters including BOD, COD, conductivity, NH4-N and phosphorus were in concentrations greater than the national standard of Malaysia. PCA was applied to identify the source and MLR analysis was done to determine their contribution. PCA yielded five VFs; which extracted 74.72% of total variance that established its validation. Results showed that, surface water quality was strongly influenced by ionic groups of salts, soil erosion and agricultural runoff, organic and nutrient pollutions from domestic wastewater, industrial sewage and wastewater treatment plants. Vicinity of industrial parks resulted in low DO concentration all over the basin. MLR showed the contribution of every variable to be highly significant (p<0.01).
format	Article
author	Islam, Mir Sujaul Hossain, Mohamed Amjed Nasly, Mohamed Ali
author_facet	Islam, Mir Sujaul Hossain, Mohamed Amjed Nasly, Mohamed Ali
author_sort	Islam, Mir Sujaul
title	Multivariate Statistical Techniques to Identify the Source of Pollution and Assessment of Surface Water Quality
title_short	Multivariate Statistical Techniques to Identify the Source of Pollution and Assessment of Surface Water Quality
title_full	Multivariate Statistical Techniques to Identify the Source of Pollution and Assessment of Surface Water Quality
title_fullStr	Multivariate Statistical Techniques to Identify the Source of Pollution and Assessment of Surface Water Quality
title_full_unstemmed	Multivariate Statistical Techniques to Identify the Source of Pollution and Assessment of Surface Water Quality
title_sort	multivariate statistical techniques to identify the source of pollution and assessment of surface water quality
publisher	National Institute of Ecology
publishDate	2013
url	http://umpir.ump.edu.my/id/eprint/11998/ http://umpir.ump.edu.my/id/eprint/11998/ http://umpir.ump.edu.my/id/eprint/11998/1/Multivariate%20Statistical%20Techniques%20to%20Identify%20the%20Source%20of%20Pollution%20and%20Assessment%20of%20Surface%20Water%20Quality.PDF
first_indexed	2023-09-18T22:13:09Z
last_indexed	2023-09-18T22:13:09Z
_version_	1777415161428049920

Multivariate Statistical Techniques to Identify the Source of Pollution and Assessment of Surface Water Quality

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