ASSESSMENT OF SURFACE WATER QUALITY IN A MALAYSIAN PORT VIA MULTIVARIATE STATISTICAL ANALYSIS
Abstract
Maritime transport has become an important method of comprehensive connectivity for imports and exports for major centers of economic activity all over the world. However, transport and port activities have grown without addressing their pollution impact on the environment. Marine water samples in a port in Malaysia were collected to find the similarities and differences in the physicochemical aspect. The principal component analysis concluded that 87.0% of the variance was explained by the four components at high tide, each accounted for 33.6% (physicochemical), 26.9% (correlation between pH and organic matter), 14.1% (trace metals), and 12.4% of the total variance (the concentration of Copper). Then, 94.5% of the total variance of the five components contributed 37.9% (turbidity, pH, organic parameters, and suspended solids), 19.6% (parameter Zn), 17.4% (parameter Ni), 11.7% (average of organic pollutants) and 7.7% of the total variance (DO and physical factors associated with TSS), each at low tide have been identified. Hierarchical cluster analysis grouped eight sampling stations into four clusters of similar water quality characteristics at both tides. Therefore, water quality monitoring and the control of untreated metal and organic waste discharge into marine waters are indispensable.
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Diane, B., Thomas, P., Gina M.S., Todd, R.C., Gail, R.F., Julie, M. & Bella, T. (2004). Harboring Pollution. Strategies to Clean Up U.S Ports. NRDC.
Ford, R. G., Natalie, A. S. & Rowan, G. C. (2008). Using Historical Oil Spill Data to Predict Seabird Mortality from Small oil Spills. University of Rochester School of Medicine and Dentistry, USA.
Gulgundi, M. S. & Shetty, A. (2018). Groundwater quality assessment of urban Bengaluru using multivariate statistical techniques. Appl Water Sci, 8, 43.
Gupta, A.K., Gupta, S.K. & Rashmi, S.P. (2005). Statistical analysis of coastal water quality for a port and harbour region in India. Environmental Monitoring and Assessment, 102, 179 – 200.
Hulsey & Ludivina., (2012). Marine Pollution. New Delhi: World Technologies.
IMO and Sustainable Development International Maritime Organization (2020) GloMEEP and IAPH. Port Emissions Toolkit Guide No. 1: Assessment of port emissions. GloMEEP Project Coordination Unit and International Association of Ports and Harbors (IAPH), Lewes, East Sussex. 2018.
ITOPF., (2011). Effects of oil pollution on the marine environment.
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Kamaruddin, S. A., Rusli, H. H., Abd.Aziz, K. N. & Roslani, M. A. (2020). Characteristics and Distribution of Microplastics in Surface Sediment ff Selat Pulau Tuba, Langkawi, Kedah. Malaysian Journal of Sustainable Environment, 7(2), 139 – 160. https://doi.org/10.24191/myse.v7i2.10269
Kamaruddin, S. A., Abd Aziz, K. N., Roslani, M. A., Tajam, J., Zaınolabdın, S. N., & Mohd Razman, N. F. (2018). Mapping of Salinity Level using Spline Interpolation Techniques over the Water of Sungai Merbok, Kedah. Malaysian Journal of Sustainable Environment, 5(2), 114. https://doi.org/10.24191/myse.v5i2.5620
Kazi, T.; Arain, M.; Jamali, M.; Jalbani, N.; Afridi, H.; Sarfraz, R.; Baig, J. & Shah, A.Q. (2009). Assessment of water quality of polluted lake using multivariate statistical techniques: A case study. Ecotoxicol. Environ. Saf. 72, 301–309.
Li, T., Li, S., Liang, C., Bush, R. T., Xiong, L. & Jiang, Y. (2018). A comparative assessment of Australia’s Lower Lakes water quality under extreme drought and post-drought conditions using multivariate statistical techniques. J Clean Prod, 190, 1-11.
Liu, C. W., Lin, K. H. & Kuo, Y. M. (2003). Application of factor analysis in the assessment of groundwater quality in blackfoot disease in Taiwan. The Science of the Total Environment, 313, 77–89.
Machiwal, D. & Singh, P. K. (2015). Understanding factors influencing groundwater levels in hard-rock aquifer systems by using multivariate statistical techniques. Environmental Earth Sciences 74(7), 5639–5652.
Masoud, A.A. (2013). Spatio temporal evaluation of the groundwater quality in Kafr Al-Zayat District, Egypt. Hydrological Processes 27(20), 2987–3002.
Masoud, N. & Amir, G. (2016). Groundwater quality analysis using multivariate statistical techniques (case study: Fars province, Iran). Environ Monit Assess, 188, 419.
Réhman, S., Hussain, Z., Zafar, S., Ullah, H., Badshah, S., Ahmad, S., Saleem, J. & Jinnah, F. (2018). Assessment of Ground Water Quality of Dera Ismail Khan, Pakistan, Using Multivariate Statistical Approach. Sci Technol Soc, 37, 173-183.
Said, A., Stevens, D.K. & Sehlke, G. 2004. An innovative index for evaluating water quality in streams. Environmental Management, 34(3), 406-414.
Smith, J.M. (2004). Water quality trends in the Blackwater River Watershed Canaan Valley, West Virginia. West Virginia University. Master of Science Theses. 8- 80.
SoE (State of the Environment Advisory Council), 1996. ‘Australia State of the Environment 1996’. Department of Environment Sport and Territories, Canberra.
Su, S., Zhi, J., Lou, L., Huang, F., Chen, X. & Wu, J. (2011). Spatio-temporal patterns and source apportionment of pollution in Qiantang River (China) using neural-based modeling and multivariate statistical techniques. Phys. Chem. Earth 36, 379–386.
Wu, Z.Z., Che, Z.W., Wang, Y.S., Dong, J.D. & Wu, M.L. (2015). Identification of surface water quality along the Coast of Sanya, South China Sea. PLoS ONE 10(4), e0123515. https://doi/10.1371/journal.pone.0123515
Published
2022-08-31
How to Cite
ABDOL JANI, Wan Nur Fazlina et al.
ASSESSMENT OF SURFACE WATER QUALITY IN A MALAYSIAN PORT VIA MULTIVARIATE STATISTICAL ANALYSIS.
Malaysian Journal of Sustainable Environment, [S.l.], v. 9, n. 2, p. 257-278, aug. 2022.
ISSN 0128-326X.
Available at: <https://myjms.mohe.gov.my/index.php/myse/article/view/18838>. Date accessed: 03 oct. 2023.
doi: https://doi.org/10.24191/myse.v9i2.18838.
Section
Articles
