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Title:	Solid waste management sub-models for sustainable regional development : case studies of Langkawi (Malaysia) and Mashhad (Iran)
Authors:	Elmira Shamshiry (P49248)
Supervisor:	Mazlin. Bin Mokhtar, Prof.
Keywords:	Sustainable regional development Case studies Sustainable development -- Malaysia -- Langkawi -- Case studies
Issue Date:	8-Apr-2013
Description:	This research investigated components of an integrated solid waste management approach in Langkawi (Malaysia) and Mashhad (Iran), in moving towards sustainable regional development. It is focused on collection and transportation of solid waste as part of integrated solid waste management approach with environmental and economical issues to protect the Langkawi island as Geopark for future generation and Mashhad city as the second largest city for pilgrimage in the world. This research has been undertaken to develop solid waste management sub-models within an integrated context. The main objective was to enhance optimization of solid waste management via forecasting of solid waste generation in Langkawi Island (Malaysia) and Mashhad city (Iran). It also investigated one of the important aspects of solid waste management, that is, the incinerator in Langkawi. The use of incinerator is one of the best integrated management alternatives in Langkawi Island that can be useful particularly to Langkawi Geopark. This can reduce the high cost to transfer the solid waste to main land by ship. An improved statistical sub-model for cost reduction on collection and transportation of solid waste has also been developed. The role of law and governance has also been examined. The establishment of systematic program for general education and awareness with environmental friendly technology can enhance environmental preservation and return on investment to the national economy by building the cultural of 3Rs (reduction- reuse-recycle). The research has used both primary and secondary data to investigate the challenges associated with solid waste management in the study areas. Moreover, the study found that growing population, booming tourism industry, expansion of industrial activities and changing consumption patterns are the main factors of solid waste generation in the study areas. The sub-model of Artificial Neural Network (ANN) and Response Surface Model (RSM) were developed using selected variables (amount of solid waste generation, types and numbers of trucks, consumption fuel, number of personnel and number of tourist in collection and transportation) to optimize and predict solid waste collection and transportation costs in Langkawi and Mashhad; the peak time effect on generation of solid waste is identified by sensitive analysis, after selection of the best function for training and testing, optimize the hidden layer number through applying the genetic algorithm, the R2 values bigger than or equal 0.9. The result showed a cost reduction by RSM of more than 10.64% in Langkawi and 13.66% in Mashhad. The use of higher number of variables in this research can enrich literature on the use of ANN and RSM sub-models in solid waste management to enhance policy making procedures, especially in financial and environmental aspects. The finding found the need for proactive and stronger institutional support by the planning authorities for solid waste management plans in the study areas. Therefore, several policy recommendations have been proposed for the consideration of government agencies, private sector, activists, non-government and community-based organizations in the study areas.,Ph.D
Pages:	362
Call Number:	TD194.6.S533 2013
Publisher:	UKM, Bangi
Appears in Collections:	Institute for Environment and Development / Institut Alam Sekitar dan Pembangunan (LESTARI)

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