Cooking oils and fat waste collection infrastructure planning: a regional-level outline

Among the current trends in waste management and circular economy is the involvement of new fractions of waste for sorting and collection. One of them is fats and cooking oils, especially those coming from households. Now, the nascent fat waste recycling becomes promoted as regulations and waste recovery targets have been set in the European Union. The traditional manner of discarding household fat waste usually causes sewage problems. However, utilisation of this waste brings the potential for contributing to the energy supply and material recovery. This research presents a mathematical model for the optimal location of fat waste bins and containers in the given municipalities. The container network should comprise as few containers as possible, while the walking distance for the citizens towards the container is as short as possible. The objective of the proposed optimisation model is to minimise the total number of collection points (infrastructure cost). The collection points represent the citizens' addresses in a municipality. The average walking distance towards a container is a novel feature in the model, which is pertinent to waste fractions with low production per person. Cluster analysis describes the variability between municipalities, and further, it is possible to use regression analysis to model the number of containers for any municipality or region. The proposed general decision support tool estimates the total cost and number of bins needed for any region or a country. The region from the Czech Republic, which was used as a study area, revealed the requirement for 609 containers, with only EUR 30,000 of investment cost. There are around 950 inhabitants assigned to a single collection point on average. [GRAPHICS] .

Keywords

Cooking oil and fat waste, Waste infrastructure planning, Waste bin and container, Network design

Citation

Clean Technologies and Environmental Policy. 2022, vol. 24, issue 1, p. 109-123.
https://doi.org/10.1007/s10098-021-02087-y

Document type

Peer-reviewed

Document version

Accepted version

Language of document

en

Document licence

(C) SPRINGER