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The use of uncertainty analysis as a food waste estimation tool

Human Centred Engineering, Sheffield Hallam University, Sheffield, UK, j.langley{at}shu.ac.uk

Alaster Yoxall

Human Centred Engineering, Sheffield Hallam University, Sheffield, UK

Graeme Manson

Department of Mechanical Engineering, The University of Sheffield, UK

Walter Lewis

The Faraday Packaging Partnership, Leeds, UK

Alison Waterhouse

The Faraday Packaging Partnership, Leeds, UK

David Thelwall

Prospect Management Services, Ripon, Yorkshire, UK

Sarah Thelwall

Prospect Management Services, Ripon, Yorkshire, UK

Andrew Parry

WRAP, Banbury, Oxfordshire, UK

Barbara Leech

WRAP, Banbury, Oxfordshire, UK

Food waste going to landfill is a significant environmental issue with 33% of all food we buy simply being thrown away. Not only is this extremely wasteful but rotting food produces gases that are harmful to the environment and contributes to global warming. The UK government is committed to reducing the amount of household waste directly being disposed of at landfills by 10.1 million tonnes tonnes over 20 years from 2000 (Waste Composition Analysis: Guidance for Local Authorities, Defra, 2004). As part of this the Waste Reduction Action Programme was set up to fund and facilitate innovative solutions to reduce waste to landfill. Part of that process was to assess bids by solution providers with regards the effectiveness of the technologies that they were offering. This was found to be a non-trivial task, with multiple input parameters and large variations in data. Establishing which parameters have the greatest effect on food waste estimation was therefore essential in any decision-making process. However, the large number of unknowns, assumptions and parameters makes this understanding both difficult and time consuming. A branch of mathematics known as uncertainty analysis can be used to analyse these types of situations quickly and effectively and is easily adapted to understanding of food waste estimation. This paper outlines the techniques used to develop an internet-based decision-making tool and demonstrates the methodology used with simple case studies.

Key Words: Uncertainty analysis • food waste • decision analysis • wmr 1379—5

This version was published on May 1, 2009

Waste Management & Research, Vol. 27, No. 3, 199-206 (2009)
DOI: 10.1177/0734242X08095231


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