Transcript Phases of LCA - Systeemianalyysin laboratorio: Etusivu

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