A multilevel Bayesian framework for predicting municipal waste generation rates.

Prediction of waste production is an essential part of the design and planning of waste management systems. The quality and applicability of such predictions depend heavily on model assumptions and the structure of the collected data. Ordinarily, municipal waste generation data are organized in hierarchical structures with municipal or county levels, and multilevel models can be used to generalize linear regression by directly incorporating the structure into the model. However, small amounts of data can limit the applicability of multilevel models and provide biased estimates. To cope with this problem, Bayesian estimation is often recommended as an alternative to frequentist estimation, such as least squares or maximum likelihood estimation. This paper proposes a multilevel framework under a Bayesian approach to model municipal waste generation with hierarchical data structures. Using a real-world dataset of municipal waste generation in Denmark, the predictive accuracy of multilevel models is compared to aggregated and disaggregated Bayesian models using socio-economic external variables. Results show that Bayesian multilevel models outperform the other models in prediction accuracy, based on the leave-one-out information criterion. A comparison of the Bayesian approach with its frequentist alternative shows that the Bayesian model is more conservative in coefficient estimation, with estimates shrinking to the grand mean and broader credible intervals, in contrast with narrower confidence intervals produced by the frequentist models.

A comparison of the transport requirements of different curbside waste collection systems in Denmark.

With an increased focus on recycling, local authorities need to adapt their systems for curbside collection of household waste to accommodate an increased degree of sorting of waste types. Therefore, it is essential to study the transport aspects of waste collection. In this paper, we analyze the driving requirements for curbside collection of household waste for different systems in the context of Denmark. We consider a Collect, then sort system, as opposed to two Sort, then collect systems using single and multi-compartment vehicles, and compare the systems among themselves, and to the collection for incineration system. Our approach consists of solving the underlying capacitated arc routing problems of each system, and comparing the transport requirements in terms of driven distance and number of routes across systems. Our findings show that an increased degree of sorting is synonymous with a significant increase in the driven distance and the number of routes. Moreover, we find that the sort, then collect by multi-compartment vehicles system outperforms the others in terms of driven distance, and that the sort, then collect by single compartment vehicles system outperforms the others in terms of number of routes. We found that three cost drivers affect the overall results: the change in the size of the vehicle, the compression factor inside the vehicles' compartments, and the packing of the vehicles' compartments.