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  • 1.
    Eriksson, Ola
    et al.
    Högskolan i Gävle, Akademin för teknik och miljö, Avdelningen för bygg- energi- och miljöteknik, Teknisk miljövetenskap.
    Baky, A.
    Swedish Institute of Agricultural and Environmental Engineering (JTI), Uppsala, Sweden.
    Identification and testing of potential key parameters in system analysis of municipal solid waste management2010Inngår i: Resources, Conservation and Recycling, ISSN 0921-3449, E-ISSN 1879-0658, Vol. 54, nr 12, s. 1095-1099Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    Life cycle assessment (LCA) and life cycle costing (LCC) are well-established methods used for many years in many countries for system analysis of waste management. According to standard LCA procedure the assessment should include improvement analysis, in many cases this is performed by simple sensitivity analyses. An obstacle to perform more thorough sensitivity analyses is that it is hard to distinguish input data important to the results, i.e. key parameters. This paper further elaborates sensitivity analyses performed in an environmental system analysis fora hypothetical Swedish municipality. In this paper, the method to identify and test input data that can be categorised as potential key parameters is described. The method and the results from computer simulations of the identified parameters are presented, and some conclusions are drawn regarding the robustness of the results for environmental impact from municipal solid waste management. The major conclusion is that the results are robust. Changes in results, when changing the preconditions, are often small and the changes observed do not lead to new conclusions; i.e., a change of ranking order between treatment options.

  • 2.
    Eriksson, Ola
    et al.
    Division of Industrial Ecology, Royal Institute of Technology, Stockholm, Sweden.
    Frostell, Björn
    Division of Industrial Ecology, Royal Institute of Technology, Stockholm, Sweden.
    Björklund, Anna
    KTH, Industriell ekologi (flyttat 20130630).
    Assefa, Getachew
    Division of Industrial Ecology, Royal Institute of Technology, Stockholm, Sweden.
    Sundqvist, Jan-Olov
    Swedish Environmental Reserach Institute (IVL), Stockholm, Sweden.
    Granath, J.
    Swedish Environmental Reserach Institute (IVL), Stockholm, Sweden.
    Carlsson, M.
    Department of Economy, Swedish Univinversity for Agricultural Sciences (SLU), Uppsala, Sweden.
    Baky, A.
    Swedish Institute of Agricultural (JTI), Uppsala, Sweden.
    Thyselius, L.
    Swedish Institute of Agricultural (JTI), Uppsala, Sweden.
    ORWARE: a simulation tool for waste management2002Inngår i: Resources, Conservation and Recycling, ISSN 0921-3449, E-ISSN 1879-0658, Vol. 36, nr 4, s. 287-307Artikkel i tidsskrift (Fagfellevurdert)
    Abstract [en]

    A simulation model, ORWARE (ORganic WAste REsearch) is described. The model is mainly used as a tool for researchers in environmental systems analysis of waste management. It is a computer-based model for calculation of substance flows, environmental impacts, and costs of waste management. The model covers, despite the name, both organic and inorganic fractions in municipal waste. The model consists of a number of separate submodels, which describes a process in a real waste management system. The submodels may be combined to design a complete waste management system. Based on principles from life cycle assessment the model also comprises compensatory processes for conventional production of e.g. electricity, district heating and fertiliser. The compensatory system is included in order to fulfil the functional units, i.e. benefits from the waste management that are kept constant in the evaluation of different scenarios. ORWARE generates data on emissions, which are aggregated into different environmental impact categories, e.g. the greenhouse effect, acidification and eutrophication. Throughout the model all physical flows are described by the same variable vector, consisting of up to 50 substances. The extensive vector facilitates a thorough analysis of the results, but involves some difficulties in acquiring relevant data. Scientists have used ORWARE for 8 years in different case studies for model testing and practical application in the society. The aims have e.g. been to evaluate waste management plans and to optimise energy recovery from waste.

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