Projecting Solid Waste Arisings: the Case of Domestic Waste of Hong Kong SAR
Waste projection informs waste policy making and is an indispensable process in waste management planning. However, not only is valid waste projections difficult to make, their reliability is also difficult to prove. Between the two major methodological approaches in forecasting MSW generation, the time-series approach uses past data and their distribution to determine future waste trends. The factor model on the other hand explains and predicts waste arisings with explanatory variables such as socio-economic factors of the waste generators. This latter approach not just aims at making predictions on waste quantities, it also aims at unveiling hypothetical causal relationships between factors for the prediction of waste arisings. Thus, it is more sophisticated and intellectually sound. In this paper, results of previous waste projection studies conducted by the Hong Kongs environmental authority on domestic waste growth are verified against actual waste data for determining the accuracy of these predictions. It is then followed by the use of another factor-model based technique, autoregression, to forecast domestic waste growth for Hong Kong SAR. While the use of multiple factor autoregression model appears to rectify the over-estimation tendency of classical linear regression model, a number of empirical constraints which are also typical of other factor-model based techniques are encountered.
municipal solid waste waste projection classical linear regression autoregression factor models time series models
Chung Shan Shan
Croucher Institute for Environmental Sciences, Department of BiologyHong Kong Baptist University, Kowloon Tong, Hong Kong.
国际会议
The 3rd International Conference on Waste Management and Technology(第三届固体废物管理与技术国际研讨会)
北京
英文
129-138
2008-11-05（万方平台首次上网日期，不代表论文的发表时间）