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Title: Development of a multi-criteria, GIS-based, backcasting framework model (G-BFM) for progression towards zero waste futures, for holistic resource management policy and practice in Northamptonshire by 2050
Author: Head, Nicholas
ISNI:       0000 0004 5990 4928
Awarding Body: University of Northampton
Current Institution: University of Northampton
Date of Award: 2015
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The complex nature of waste management and planning requires a long-term strategic policy formation approach incorporating sustainable development principles. Consequently, the transition from a waste paradigm to valuing materials as resources is central for transitioning towards a 'zero waste' future. A need is identified, via infrastructure planning, to move beyond short-term forecasting and predictive methods previously used in waste research in order to overcome target-driven decision-making. The application of a participatory backcasting methodology: visioning, baseline assessment, scenario development and feasibility testing; produced transformative scenarios which are visualised using GIS reflecting the choices, ideas and beliefs of participants. The structural governance (e.g. waste infrastructure planning and strategic waste policy) of an English county is used to evaluate the efficacy of waste management scenarios. A quantitative model was developed to test scenarios for three metrics (tonnages, economics and carbon). The final model utilises the synergy between backcasting and GIS to spatially and temporally analyse empirically quantified outputs. This structured approach produced three transformative scenarios and one reference scenario. Waste prevention and changes to systemic waste generation produced long-term tonnage reductions across the transformative scenarios. Costs of future waste management witnessed the reference scenario outperforming one of the transformative scenarios; while the highest emissions savings were attributable to the scenario most closely reflecting the notion of 'deep sustainability'. In terms of waste infrastructure planning, a centralised pattern of large integrated facilities emphasising catchments rather than administrative boundary were most effective. All three transformative scenarios surpassed the 90% recycling and recovery level used as the zero waste benchmark. The research concludes that backcasting can offer a range of potential futures capable of achieving an arbitrary definition of zero waste. Further, these futures can be visualised and analysed via GIS; enhancing stakeholder engagement. Overall, the GIS-based Backcasting Framework Model (G-BFM) produced has the potential to benefit a range of stakeholders and practitioners and is strategically scalable.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available
Keywords: TD793.9 Waste minimisation ; GE300 Environmental management ; GE170 Environmental policy