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dc.contributor.authorGressi, Rigum
dc.date.accessioned2012-06-04T01:05:22Z
dc.date.available2012-06-04T01:05:22Z
dc.date.issued2011-04
dc.identifier.urihttp://dspace.unimap.edu.my/123456789/19600
dc.descriptionAccess is limited to UniMAP community.en_US
dc.description.abstractGross pollutant traps (GPTs) is a structural controlled device used as an early pretreatment for water especially in open channel. GPTs detained rubbish such as leaf, plastics, polystyrene, paper and sediment to reduce water pollution before it entering the main river. It is usually construct in an open channel with flow from several sources, and end to the outlet which is the river. The objective of this study is to characterize the pollutant traps in the GPTs accordingly and to monitor the water quality of water before and after the GPTs. From the observation and finding, an improved GPTs design is proposed. The method applied during this study are including weighing the rubbish, and sediment collected, water quality monitoring and laboratory analysis and designing a better GPTs system. There are five parameters involve in water quality sampling and analysis which are pH, DO, BOD, COD, SS and AN. This study is carried out at two point of GPTs in Kangar. Based on result obtain, it can be conclude that the pollutant traps can be characterize into five major group ; vegetative, plastics, paper, materials and sediment, with vegetative has the higher amount trapped in the GPTs system. Highest removal efficiency of SS in water quality in GPTs Point 2 show that the GPTs system can be an effective method to reduce water pollution if the maintenance of the GPTs system carried out properly. A Rubbish Trap is designed based on GPTs design criteria on MASMA for better performance.en_US
dc.language.isoenen_US
dc.publisherUniversiti Malaysia Perlis (UniMAP)en_US
dc.subjectGross pollutant traps (GPTs)en_US
dc.subjectWater qualityen_US
dc.subjectWater pollution treatmenten_US
dc.subjectRiver pollutionen_US
dc.subjectPerlis - Pollutantsen_US
dc.titleCharacteristic of gross pollutants and evaluation of gross pollutant traps (GPTs) in Perlisen_US
dc.typeLearning Objecten_US
dc.contributor.advisorMd Hadli Abu Hassanen_US
dc.publisher.departmentSchool of Environmental Engineeringen_US


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