title: Forecasting of municipal solid waste quantity in a developing country using multivariate grey models.
abstract: In order to plan, manage and use municipal solid waste (MSW) in a sustainable way, accurate forecasting of MSW generation and composition plays a key role. It is difficult to carry out the reliable estimates using the existing models due to the limited data available in the developing countries. This study aims to forecast MSW collected in Thailand with prediction interval in long term period by using the optimized multivariate grey model which is the mathematical approach. For multivariate models, the representative factors of residential and commercial sectors affecting waste collected are identified, classified and quantified based on statistics and mathematics of grey system theory. Results show that GMC (1, 5), the grey model with convolution integral, is the most accurate with the least error of 1.16% MAPE. MSW collected would increase 1.40% per year from 43,435-44,994 tonnes per day in 2013 to 55,177-56,735 tonnes per day in 2030. This model also illustrates that population density is the most important factor affecting MSW collected, followed by urbanization, proportion employment and household size, respectively. These mean that the representative factors of commercial sector may affect more MSW collected than that of residential sector. Results can help decision makers to develop the measures and policies of waste management in long term period.
authors.affiliation: Energy Field of Study, School of Environment, Resources and Development, Asian Institute of Technology, P.O. Box 4, KlongLuang, Pathumthani 12120, Thailand. Electronic address: rotchana.in@gmail.com.
authors.forename: Rotchana
authors.initials: R
authors.lastname: Intharathirat
authors.affiliation: Energy Field of Study, School of Environment, Resources and Development, Asian Institute of Technology, P.O. Box 4, KlongLuang, Pathumthani 12120, Thailand. Electronic address: salam@ait.ac.th.
authors.forename: P
authors.initials: P
authors.lastname: Abdul Salam
authors.affiliation: Energy Field of Study, School of Environment, Resources and Development, Asian Institute of Technology, P.O. Box 4, KlongLuang, Pathumthani 12120, Thailand. Electronic address: kumar@ait.ac.th.
authors.forename: S
authors.initials: S
authors.lastname: Kumar
authors.affiliation: School of Tourism Development, Maejo University, Chiangmai, Thailand. Electronic address: akarapong_un@hotmail.com.
authors.forename: Akarapong
authors.initials: A
authors.lastname: Untong
mesh_terms: D003906:Developing Countries; D005544:Forecasting; D008962:Models, Theoretical; D015999:Multivariate Analysis; D062611:Solid Waste / Q000032:analysis*; D013785:Thailand; D018505:Waste Management
chemical_list: D062611:Solid Waste
keywords: Forecasting; Grey model; Influencing factors; MSW; Thailand