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Life Cycle of Products Source: Melanen et al. 2000. Metals flows and recycling of scrap in Finland. The Finnish Environment 401. Finnish Environment Institute, Helsinki Phases of life cycle assessment (LCA) Goal and scope definition Purpose, system boundaries, functional units and assessment criteria Inventory analysis Quantifying environmental interventions (emissions, resource extractions and land use) of a product system under study Impact assessment Selection of categories Selecting impact categories and their indicators under study Classification Assigning inventory data to the impact categories Characterisation Evaluating impact category indicator results Normalisation Referring relative magnitude for each impact category of a product system under study Weighting: Aggregating category indicator results according to their relative importance Interpretation Phases of life cycle impact assessment (LCIA) Selection of impact categories Selecting impact categories (e.g. climate change and acidification) and their indicators (e.g. radiative forcing in climate change, H+ release in acidification) Classification Assigning inventory data to the impact categories Emissions E.g. Impact category CO2 CH4 N2 O Climate change Characterisation: evaluating impact category indicator results m I i Ci , j x j , i =1,…,n (4) j 1 where Ii = indicator result of impact category i Ci,j = characterisation factor for intervention j within impact category i xj = amount of intervention (emission, resource extractions or land use) j Normalisation: referring relative magnitude for each impact category of a product system under study m I i (a ) Ni C j 1 m C j 1 where i,j i,j x j (a ) , i =1,…,n x j (R ) Ii(a) = indicator result of impact category i caused by product system a Ni = normalisation value of impact category i Ci,j = characterisation factor for intervention j within impact category i xj (a) = amount of intervention j caused by product system a xj (R) = amount of intervention j caused by reference system R (11) Weighting Aggregating category indicator results according to their relative importance n I (a ) w i i 1 I i (a ) Ni which consists of impact category weights, wi, and normalisation results of impact categories i. THE DEVELOPMENT OF LCIA IS STILL IN PROGRESS The thesis aims at illustrating the basic theoretical foundations for life cycle impact assessment (LCIA) on the basis of decision analysis (DA) From DA methods, multiattribute value theory (MAVT) was chosen due to its - well established theoretical foundations - similarities with the current aggregation practices used in LCIA Selection of impact categories and classification correspond to the problem structuring phase of DA. A value tree is a valuable tool for this stage. Impact categories Attributes k 1,1 Climate change k 1,3 w1 Acidification w2 CO2(F) k 1,2 Life cycle stages Forestry N2O k 1,4 CH4 Halo k 2,5 SO2 k 2,6 NOx k 2,7 NH3 Production k 3,6 NOx Energy production Tropospheric k 3,8 NMVOC outside forest industry ozone formation k 3,9 CO w3 kb 1,14 Acute Ecological impacts ka 1 aquatic ka 2 Chronic w7 Ecotoxicity aquatic w4 TOX(W) kb 2,15 H-metals(A) Chemical production kb 2,16 POP(A) outside forest industry kb 2,14 TOX(W) ka 3 kb 3,15 Chronic w5 Eutrophication w6 H-metals(A) terrestrial kb 3,16 POP(A) k 4,6 NOx k 4,7 k 4,11 Impacts on biological diversity k 5,12 Oxygen depletion k 6,13 NH3 k 4,10 P(W) N(W) Forestry practices BOD/COD Waste treatment outside forest industry Transports Characterisation can be described as an aggregation model of MAVT MAVT can assist in answering the following questions: -- how to derive scientifically based characterisation factors -- what measurement techniques for subject judgements can be used -- what aggregation rule is theoretically required (additive, multiplicative or multilinear) In the thesis it is shown how site-dependent characterisation methods can be fitted into the developed decision analysis impact assessment framework. - two case studies: the Finnish forest industry, the Finnish metals industry Findings about relationships between characterisation, normalisation and weighting MAVT can give answers to questions such as - - what characterisation factors should be used in normalisation whether or not use normalisation in weighting what type of denominator in normalisation should be used how to utilize techniques, knowledge and experiences of decision analysis in the determination of weights. In the determination of impact weights, impacts caused by a reference system used in normalisation should be taken into account how the non-linearity aspects can be taken into account in the impact assessment framework what aggregation model is appropriate In addition - it was demonstrated how experiences and techniques for the sensitivity analysis of multi-criteria decision making models can be utilised in LCIA - an interval ratio estimation method for the elicitation of impact category weights was developed, allowing a solution in which interval-valued ratio judgements can be used in the uncertainty analysis of the model LCIA with the help of decision analysis can - provide a learning process among participants - enhance findings of the most serious data gaps - provide an overview about the assessment problem, even in situations where ”objective” data are missing In the future there is a need - to study the strengths and weaknesses of the different decision analysis methods for LCIA purposes - to demonstrate quantitatively the differences between LCIA conducted according to MAVT and according to the current practices Why has the use of DA tools not been common in LCIA applications? Only few LCA practitioners have enough information to use decision analysis tools