Projects
Projects: Projects for Investigator |
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| Reference Number | WR0107 | |
| Title | Modelling the impact of lifestyle changes on household waste arisings | |
| Status | Completed | |
| Energy Categories | Not Energy Related 95%; Renewable Energy Sources(Bio-Energy, Production of other biomass-derived fuels (incl. Production from wastes)) 5%; |
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| Research Types | Applied Research and Development 100% | |
| Science and Technology Fields | ENVIRONMENTAL SCIENCES (Geography and Environmental Studies) 25%; SOCIAL SCIENCES (Sociology) 25%; BIOLOGICAL AND AGRICULTURAL SCIENCES (Agriculture, Veterinary and Food Science) 50%; |
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| UKERC Cross Cutting Characterisation | Not Cross-cutting 85%; Sociological economical and environmental impact of energy (Environmental dimensions) 5%; Sociological economical and environmental impact of energy (Consumer attitudes and behaviour) 10%; |
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| Principal Investigator |
Project Contact No email address given AEA Technology |
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| Award Type | Standard | |
| Funding Source | DEFRA | |
| Start Date | 01 June 2005 | |
| End Date | 31 January 2010 | |
| Duration | 56 months | |
| Total Grant Value | £179,314 | |
| Industrial Sectors | No relevance to Underpinning Sectors | |
| Region | London | |
| Programme | DEFRA Sustainable Resource Consumption and Management | |
| Investigators | Principal Investigator | Project Contact , AEA Technology (100.000%) |
| Web Site | ||
| Objectives | The specific objectives were: 1. Scoping and Data Gathering The scoping study led to a broad understanding of the potential inter-relationships between lifestyles and waste. Following the scoping study, the decision was made to design the forecasting tool as an ‘Input-Output’ model based around the fact that most household waste is generated by consumers’ expenditure. The prototype model showed very good agreement with historical trends when the model outputs were compared with published waste data. This model provided an excellent basis for the next stage; generating future forecasts. 2. Analysis and Consultation The analysis of the quantitative impact of different drivers led to the identification of twelve key drivers and trends that are likely to have the greatest impact (either positively or negatively) on household waste volume and composition over the next 15 years. These are: • Increase in consumer affluence • Increase in single society living • Culture of lifestyle change (e.g. house moves, divorce, retirement, etc.) • Growth of the ‘experience’ economy (e.g. spending on experiences rather than goods) • Shortening product life cycle • Growth of tele-working and the knowledge economy • Increasing life expectancy • Lifestyle choices of the ‘baby boom’ generation • Growth of online, convenience shopping • New regulations and legislation • Perceived effect of climate change • Increase in ethical consumption These findings were presented at a project research consultation workshop, involving a broad spectrum of stakeholders. The feedback demonstrated broad support for the proposed modelling approach and specific contributions were used to inform the development of the predictive model. 3. Model Construction There are two main ways in which the model was designed to be used. It can be used for future forecasting; the model can provide a range of predictions, including the overall level of household waste generated and a breakdown of this total into the key ‘product’ waste streams. The model can also be used in a backcasting mode. If the user begins from the baseline model predictions, they can investigate how far the assumptions used in the model would need to be changed in order for the model to come up with an alternative prediction. The assumptions and data varied may include those that are likely to be susceptible to waste policy interventions (e.g. local waste collection service arrangements) and also socio-economic factors beyond the realm of waste policy (e.g. disposable income; number of single person households). By assessing the changes needed to achieve the desired outcome, the user can make a judgement both about how sensitive the model is to the input data and assumptions, and about how difficult it would be to achieve the desired outcome. | |
| Abstract | Considerable work has been done into understanding the nature and arisings of household waste. However, the impact of economic, social and consumer trends on the volume and composition of household waste has not been fully analysed. This research aimed to identify these relationships and develop a model capable of predicting the impact of different lifestyle trends on the household waste composition over the next 20 years. The research aimed to develop an innovative and flexible model that would provide Defra with a clear idea of the economic, social, and consumer attitudinal and behavioural factors that are likely to have the greatest impact on future waste composition. The model was aimed to assist Defra by providing: - Better tools for forecasting and planning in sustainable waste management policy, because the model includes possible socio-economic impacts. - Inputs to help Defra prioritise policy strategies for waste reduction and behaviour change, thus mitigating future waste growth. - An interactive model that can be used to explore the possible policy options available at local, regional and national level, and their likely impacts on the household waste stream. The model that was constructed as a part of this research was developed using the most up-to-date data on waste arisings available in 2005, when the project began i.e. up to and including data for 2003/04. Following completion of the initial research and model development in July 2006, new data became available, which showed a divergence between the model predictions and the reported data from 2002-2006. Defra have commissioned further research to try to understand other factors that may have influenced these changes in waste growth patterns. The divergence observed between the model forecasts and recent waste growth limits the application of the model for policy purposes, and means that caution should be used when interpreting the figures contained in the report and associated research documents. However, this project still allows exploration of future trends in waste composition, if not total quantity. | |
| Data | No related datasets |
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| Projects | No related projects |
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| Publications | No related publications |
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| Added to Database | 12/01/12 | |
