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It’s Written on the Bin! A Snapshot Evaluation of Kerbside Bin Contamination from the Perspectives of Council-Based Waste Educators

Published online by Cambridge University Press:  16 April 2026

Esther Landells*
Affiliation:
Appleton Institute of Behavioural Science, CQUniversity - Adelaide Campus, Wayville, Australia
Olav Muurlink
Affiliation:
Business and Law, CQUniversity Brisbane, Australia
Anjum Naweed
Affiliation:
Appleton Institute of Behavioural Science, CQUniversity - Adelaide Campus, Wayville, Australia
*
Corresponding author: Esther Landells; Email: esther.landells@cqumail.com
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Abstract

As kerbside waste and recycling management practices evolve, integrating technology, community engagement, and policy enforcement are essential for achieving the transition from linear disposal to circular resource economies. Yet, where councils are the focus, research tends to determine what they should do rather than what they can do, arguably contributing to policy development that shifts waste and recycling management expectations onto local councils rather than producers, consumers and processors. In this study, responses to a poll of Australian council-based waste services staff (n = 82) are analysed, providing a snapshot of current contamination management processes to assess the efficacy and trends in kerbside collections. Focusing on New South Wales – an Australian state currently transitioning its waste and recycling management practice – the poll revealed trends in contamination strategies, policy responses, and community engagement processes. It also showed an increase in the use of in-truck technology as a tool for identifying contamination events. Results indicated that contamination remains a persistent, increasing, and pernicious issue, with recycling bins exhibiting the highest contamination rates, exceeding 11% in many cases, and 60% of participants noting an increase over the past decade, despite public education efforts. Garden Organics and Garden/Food Organics bins generally have contamination levels below 5%. This study seeks to encourage discussion between policymakers, councils, and researchers on how to optimise kerbside waste and recycling collection systems and promote circular economy principles, thereby narrowing the gap between theory and effective practice.

Information

Type
Article
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (https://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided that no alterations are made and the original article is properly cited. The written permission of Cambridge University Press or the rights holder(s) must be obtained prior to any commercial use and/or adaptation of the article
Copyright
© The Author(s), 2026. Published by Cambridge University Press on behalf of Australian Association for Environmental Education
Figure 0

Figure 1. Garden organics (lime green lid), food organics (dark green lid), recycling (yellow lid) and general waste (red lid) examples of information hot stamped on kerbside bin lids (reproduced with permission from Mastec.com.au).

Figure 1

Figure 2. Examples of bin tags used to advise residents of incorrect materials in placed in the bin. Where bin audits are carried out more broadly, positive messaging tags are also used to acknowledge correctly used bins. (Images used with permission of Willoughby City Council, Chatswood, NSW).

Figure 2

Table 1. Introductory poll questions and their aligned goals

Figure 3

Figure 3. Participants reported contamination changes in the past 10 years.

Figure 4

Figure 4. Responses to contamination policy differentiations.

Figure 5

Figure 5. Contamination response strategies by councils.

Figure 6

Figure 6. Common types of engagement activities used by participants to address and pre-empt kerbside bin contamination.

Figure 7

Table 2. Descriptive analysis to identify potential correlations from the data