Household Simulation Model: A Dataset for Evaluating Interventions to Reduce Packaging and Chicken Waste in UK Households, 2021-2023

DOI

This dataset provides the input files and results for the new Household Simulation Model, which explores the impact of four interventions on the amount of packaging and chicken waste generated in UK households. The interventions studied include pack size availability in the market shelves (PCK), shelf life extension for unopened and opened chicken packs (SFH), food portioning in households (PRT), and the likelihood of checking storage and writing a shopping list before the main shopping event (LST). The dataset is organised into four folders, each representing an intervention, with subfolders containing input files for different scenarios and a summary file with the results. The provided data can be used to analyse the effectiveness of various strategies in reducing packaging and food waste and to inform policy-making and consumer behavior change efforts.THE PROBLEM Plastic packaging waste is a major issue that has recently entered public consciousness, with the British government committing to a 25-year plan that would phase out disposable packaging by 2042. Around 41% of plastic packaging is used for food, with the UK generating 1 million tonnes per year of packaging waste. Food packaging has had a 1844% increase in recycling since 2007, yet still only one third of food packaging is currently recycled [3]. Currently many consumers are boycotting plastic packaging. However, this is leading to a rise in food waste (and foodborne illness risk) due to decreased shelf life. Up to a third of the resources used to produce food could be saved by eliminating food waste [1]. In the UK, approximately 10 million tonnes of food are wasted every year, with the average family (i.e. a household containing children) spending £700 a year on food that is wasted. 31% of avoidable household food waste (1.3 million tonnes), is caused by a mismatch of packaging, pack, and portion size, and household food habits [2]. Plastic pollution and food waste can be reduced through product re-design and other household interventions. However, there is little evidence to determine the best solutions to reduce plastic pollution and food waste. The food industry and consumers have a variety of possible solutions, but no way of knowing the impacts and unintended consequences (without costly, time consuming trials and measurement). This is a major barrier to empowering the food system to enable the rapid reduction of plastic waste. THE VISION This project reduces plastic pollution (and food waste) by providing a decision support tool to trigger action in the food industry and by consumers. Evidence concerning plastic and food waste reduction (and trade-offs with cost, and environmental impacts) will be generated by updating the Household Simulation Model (HHSM). The HHSM was piloted by the University of Sheffield and WRAP (the Waste & Resources Action Programme) to model the impacts of food product innovation quickly, to enable manufacturers to select the best innovations and interventions, and to prioritise their development and deployment. This project will incorporate into the current HHSM, data on 1) plastic packaging options and composition (from Valpak/WRAP), 2) household behavioural insights around packaging (single and reuse options) and food (provided by UoS/WRAP), with specific fresh produce data (from Greenwich) 3) plastic in the supply chain and environmental impacts (via SCEnATi- a big data analytics tool of the food supply chain processes (provided by Sheffield). The updated HHSM will enable the quantification of plastic and food waste reduction, and the environmental and monetary trade-offs of various solutions. This will be done by developing an optimization engine and integrating it with the updated HHSM which will further the simulation optimization methodology with the findings from applying developed meta-heuristic algorithms to this problem. Possible solutions include offering consumers different pack sizes, or changing packaging type/shape/reusability/durability. The most successful solutions will be translated into consumer and industry guidance focusing on the top 30 foods linked to the highest waste and tradeoff potential. This will enable rapid product and food system redesign. This guidance will be open access, and deployed through WRAP and global industry networks, and open access web tools. WRAP is coordinating the voluntary agreements UK Plastics Pact and the Courtauld Commitment 2025 (focused on food waste and carbon reduction). This allows rapid scaling of the HHSM outputs throughout the UK. References: [1] Institution of Mechanical Engineers, "Global food - Waste not, want not" London, 2013 [2] Quested, T. E., et al. "Spaghetti soup: The complex world of food waste behaviours." RCR 79 (2013): 43-51. [3] Recoup 2018, UK Household Plastics Collection

The Household Simulation Model was developed using a Discrete Event Simulation approach to simulate the behavior of various household archetypes in response to different market and consumer interventions. The input files were created using Excel and contain multiple tabs, each representing a specific aspect of the simulation: input market, input initial, input storing, input purchase, input consumption and input expiry. Each scenario was run using different input values to simulate the effect of the intervention on the amount of packaging and chicken waste generated. The output results were generated in the tab ‘Results A’ in the input files and were then analysed and summarised in a pivot table for visualization and comparison.

Identifier
DOI https://doi.org/10.5255/UKDA-SN-856483
Metadata Access https://datacatalogue.cessda.eu/oai-pmh/v0/oai?verb=GetRecord&metadataPrefix=oai_ddi25&identifier=ceb8fad2c797b5748a43508d9ae99986bc6861c246aa7149dba1eca212545ace
Provenance
Creator Martin Torrejon, V, City, University of London; Kandemir, C, The University of Sheffield
Publisher UK Data Service
Publication Year 2023
Funding Reference NERC
Rights Christian Reynolds, City, University of London; The UK Data Archive has granted a dissemination embargo. The embargo will end on 25 November 2024 and the data will then be available in accordance with the access level selected.
OpenAccess true
Representation
Resource Type Numeric
Discipline Social Sciences
Spatial Coverage London; United Kingdom