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Management of waste resources from an environmental perspective

This report is the result of an individual course of 10 ECTS carried out as a part of a PhD project at the Norwegian University of Life Sciences (NMBU). The PhD project is a part of the BioValueChain, funded by the EnergiX programme of the Norwegian Research Council.
The aim of the work was to give an overview of existing methodology and common practice when it comes to calculating environmental impacts from waste management systems, with emphasis on life cycle assessment methodology for organic household waste and anaerobic digestion.
The increasing amounts of waste in the industrialised countries due to the increase in populations and in consumption is magnifying the need for efficient and optimal treatment of waste. Waste treatment can generate valuable secondary products such as renewable energy and recycled materials, and should be considered as a resource rather than a problem.
Existing standards, guidelines and reviews performed on life cycle assessments (LCA) of waste management resources defines the current practice and methodological choices when comparing the environmental impact of different waste management options. The life cycle of waste services typically starts when the waste is discarded, followed by collection and further transport, waste processing and finally, the substitution of alternative products.
Three Nordic LCA waste management models were compared when it comes to general properties, methodological aspects and results from the use of the models. The comparison revealed that there are similarities on the general purpose of the models, the functional units, the system boundaries and assumptions of what products are substituted for the secondary products compost and liquid digestate.
The comparison of the results for GWP from use of the models in different case studies when comparing anaerobic digestion and incineration for organic solid waste, showed large variation in conclusions. The variation in the results may be caused by actual differences in the different regions of the case studies. They may also be caused by difference in background data sets, different assumptions during quantification of how much is substituted and the use of average or marginal perspective.
The implications of these results are that future research should involve improving the existing datasets for different technologies and practices. Further, sensitivity analysis on the quantification of the quality and quantity of the substituted product and the choices regarding average/marginal perspective should always be performed to increase the robustness of the result for each case study.

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