Projecting municipal solid waste: The case of Hong Kong SAR

Research output: Contribution to journalJournal articlepeer-review

60 Citations (Scopus)
60 Downloads (Pure)


Waste projection informs waste policy making and is an indispensable process in waste management planning. 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 study, results of previous waste projections conducted by Hong Kong's environmental authority on domestic, commercial and industrial waste growth are verified against actual waste data for determining the accuracy of these predictions. In addition, using the MSW data from 1979 to 2007 as the reference paths, two autoregression models, a factor-model based technique, were developed to simulate commercial, industrial and domestic waste disposal for the period 2008-2036 for Hong Kong SAR. While the use of multiple factor autoregression model appears to have rectified the overestimation tendency of classical linear regression model, a number of empirical and data constraints which are also typical of other factor-model based techniques are encountered.

Original languageEnglish
Pages (from-to)759-768
Number of pages10
JournalResources, Conservation and Recycling
Issue number11
Early online date22 Dec 2009
Publication statusPublished - Sept 2010

Scopus Subject Areas

  • Waste Management and Disposal
  • Economics and Econometrics

User-Defined Keywords

  • Municipal solid waste
  • Waste projection
  • Classical linear regression
  • Autoregression
  • Factor models
  • Time series models


Dive into the research topics of 'Projecting municipal solid waste: The case of Hong Kong SAR'. Together they form a unique fingerprint.

Cite this