- Title
- Spatial modelling of municipal waste generation: Deriving property lot estimates with limited data
- Creator
- Madden, Ben; Florin, Nick; Mohr, Steve; Giurco, Damien
- Relation
- Resources, Conservation and Recycling Vol. 168, Issue May 2021, no. 105442
- Publisher Link
- http://dx.doi.org/10.1016/j.resconrec.2021.105442
- Publisher
- Elsevier
- Resource Type
- journal article
- Date
- 2021
- Description
- Given recent circular economy policy and waste minimisation targets, there is a significant opportunity to fundamentally change the way waste is managed in Australia, and re-focus waste management to promote resource recovery and efficiency. Detailed data on household waste generation can assist decision makers in targeting waste minimisation incentives, improving resource recovery and circularity, identifying specific technology and infrastructure gaps and informing future development. Unfortunately, high-resolution spatial estimates of waste generation at the property lot scale is typically unavailable. This study presents a novel spatial model developed to estimate waste generation data at the property lot level. Utilising census data at multiple spatial scales and council waste generation data, we apply our model to estimate quantities of residual waste, dry recyclables and garden waste generated for more than 1,200,000 property lots in the Sydney metropolitan area, Australia. Results show the spatial distribution of estimated household waste generation, achieving a high degree of accuracy when compared to validation data. To illustrate the application of our results in the context of identifying ideal areas for waste processing facilities, we analyse the spatial distribution of available garden waste arising from property lots. An area of intense garden waste generation was identified, indicating a supply area of approximately 13km in northern Sydney that can support a facility of approximately 20,000t throughput a year. Our analytical approach presented is novel, and has practical application for locating waste processing facilities; analysing efficient kerbside waste collection services; and in informing data driven urban waste management strategies.
- Subject
- urban waste management; spatial disaggregation; GIS; data analytics; microsimulation; SDG 11; SDG 12; Sustainable Development Goals
- Identifier
- http://hdl.handle.net/1959.13/1435697
- Identifier
- uon:39791
- Identifier
- ISSN:0921-3449
- Language
- eng
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Goal 12: Responsible Consumption and Production
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