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What does your recycling residue tell you?

The quality of resource that results from local authority commingled dry mixed recycling collections varies. The output quality, and subsequent value, can differ for a range of reasons including (but not limited to): treatment, demography, location, season, type of collection method, local understanding and behaviours, communications and variety of materials collected.

As you’d expect (and as the recycling league tables show) some authorities achieve better results than others. But that’s only a small part of the story. Local authorities, working in conjunction with their recycling partners, need to continuously review their commingled service to ensure that they not only maintain standards but drive further improvements.

Signing a MRF contract is just the beginning. Thereafter, you should expect to work with your MRF operator to understand the makeup of the input material, which can change as a result of the stimuli mentioned above, and outputs. Certainly, that’s standard service here at Casepak.

Real improvements, however, can be made by making a further study of the residues.

By running regular checks on the material that does not make the grade we can easily identify common recycling problems – such as misunderstandings about plastics suitable for recycling. This information can then be used by the authority to develop new communications materials or promotions to encourage new behaviours and improved performance.

Where a deep rooted problem is identified, for example where the recycling is significantly contaminated, Casepak deploys a more granular approach, often working side-by-side with the authority, checking loads from specific areas to identify micro-campaigns to drive improvements.

The results can be illuminating, identifying problem areas down to specific streets and even properties.

We’ve already instigated residue reporting for a number of local authorities as part of their continuous recycling improvement programmes. Six months down the line, we’ll have a fuller dataset to feedback on.