Interpretation

Question 1

What is the general definition of the interpretation phase?

Answer 1

Systematic method to identify, qualify, control, evaluate, and present conclusion based on the results of the LCI and/or LCIA phases, in order to fulfil the goal of the study.

Iterative method.

Question 2

What is the interpretation procedure?

Answer 2

1. Identification of significant issues
2. Evaluation
3. Conclusions, recommendations, limitations, and report

Question 3

How to identify significant issues?

Answer 3

• Structure results of LCA and LCIA
• Account for different methodological choices (hypotheses, multifunctional processes, excluded processes, impact assessment method, etc.)
• The ISO standard does not indicate what are the significant issues for a specific case

Question 4

How do you perform the evaluation step?

Answer 4

• Establish and increase confidence in study’s conclusions

- 3 types of checks: completeness, consistency, sensitivity

Question 5

Define the completeness check during the evaluation process?

Answer 5

Ensure that all relevant information and data needed were available and used

Question 6

Define the consistency check during the evaluation step?

Answer 6

To determine whether the assumptions, methods, and data were consistent with the G&S and were applied consistently throughout the study (esp for comparative)

Question 7

Define the evaluation sensitivity check?

Answer 7

To assess the reliability of the final results and conclusions by determining how they are affected by uncertainties in the data and the various methodological choices made

(uncertainty analysis)

Question 8

Define uncertainty, variability, and sensitivity?

Answer 8

Uncertainty: what we do not know
Variability: how much what we know may change/vary
Sensitivity: how much does a specific change affect the result

Question 9

Why do we care about uncertainties in LCA?

Answer 9

• Support decision making by making available information on the confidence that one can have in LCA results
• Plan uncertainty reduction in a structured way
• Transparency, avoiding to exaggerate the value of the results

Question 10

What are the types of uncertainty?

Answer 10

1. Parameter uncertainty
2. Model uncertainty
3. Scenario uncertainty
4. Relevance uncertainty

Question 11

What is the definition of parameter uncertainty?

Answer 11

Variability and uncertainty of model input parameters. Part of overall uncertainty about the model result.

(Ex. Non-representative inventory data, inaccurate data, etc.)

Question 12

What is the definition of model uncertainty?

Answer 12

Uncertainty about the model itself. Part of overall uncertainty about the model result.

(Ex. Lack of LCI data, no consideration of non-linear processes, lack of spatial or temporal information, etc.)

Question 13

What is the definition of scenario uncertainty?

Answer 13

Uncertainty related to choices, preferences, and scenarios. Part of both the overall uncertainty about the model result and conclusion/decision.

(Ex. choice of functional unit, allocation method chosen, assumptions about future efficiencies, etc.)

Question 14

What is the definition of relevance uncertainty?

Answer 14

Uncertainty in relevance and representativeness of indicators for the decisions at hand. Part of overall uncertainty of the conclusion/decision.

Question 15

What are the different ways to represent an uncertainty?

Answer 15

Qualitatively (Pro: Quick, Con: Cannot be propagated, Subjective)
Quantitatively (Pro: Allows propagation, Con: Requires lots of data)
Semi-quantitatively (Pro: Quick + Prop, Con: Estimates)

Question 16

What are the steps of parameter uncertainty assessment?

Answer 16

1. Estimate uncertainty of individual parameters
   - choose probability distribution function (PDF)
   - estimate parameters of PDF (statistical data, expert judgement, literature, pedigree)
2. Cumulate uncertainty to find the final result

Question 17

What is significant vs. insignificant uncertainty?

Answer 17

< 10% is not considered significant for the energy and global warming scores.

> 30% is significant for respiratory inorganics, acidification, and eutrophication

An order of magnitude difference is required for significance in toxicity categories

Question 18

Describe the formula used for uncertainty in databases using the pedigree matrix approach?

Answer 18

Total uncertainty = Basic uncertainty x Additional uncertainty

(Look at specific formula in slides)

Question 19

What are the different types of variability?

Answer 19

1. Temporal variability
2. Spatial variability
3. Inter-individual variability

Question 20

What are the two main ways sensitivity is used?

Answer 20

1. Global sensitivity analysis

2. Local sensitivity analysis

Question 21

Define accuracy and precision

Answer 21

Accuracy: describes the closeness of a measured or modelled value to its “true” value.

Precision: represents the quality of being reproducible in amount
or performance

Question 22

How does uncertainty vary between midpoints and endpoints?

Answer 22

Midpoint indicator result will be more precise but less environmentally relevant, while it will be the opposite for an
endpoint indicator (i.e. less precise but more environmentally relevant). 
Therefore, endpoint indicators are typically perceived as more uncertain based on their usually lower precision (due to a larger number of choices and hypotheses involved in their modelling compared to midpoint indicators).

Question 23

What is a common misconception with uncertainty for midpoints and endpoints?

Answer 23

if minimal or avoided environmental consequences are the objective of a decision, choosing midpoint indicators because they can be quantified with higher precision will still not avoid the uncertainty of that decision’s environmental consequences since a midpoint indicator is less relevant (representative) for the environmental consequences to be avoided.

Question 24

What are the three main methods for reporting uncertainty levels?

Answer 24

1. Pedigree matrix approach used for example by ecoinvent for the quantification of variability and uncertainty of LCI data
2. Monte Carlo simulation used in LCA software like SimaPro, GaBi, openLCA, and the more explorative/educational LCA tools CMLCA and Brightway 2
3. Taylor series expansion used in CMLCA

Question 25

Describe the types of uncertainty analyzed in the pedigree matrix approach?

Answer 25

It quantifies (exclusively) parameter uncertainty via combining two different kinds of uncertainty:

1. Basic uncertainty due to variation and stochastic error of the values for elementary flows, from measurement uncertainties, activity specific variations, temporal variations, etc.
2. Additional uncertainty based on data quality indicators using a qualitative assessment of “reliability”, “completeness” and representativeness in terms of “temporal correlation”, “geographical correlation”, and “further technological
   correlation”.

Question 26

What are the types of uncertainty distributions?

Answer 26

1. Uniform
2. Triangle
3. Normal
4. Log Normal (most used in LCA)

Question 27

What is the outline of the Monte Carlo simulation method?

Answer 27

1. Generate samples of random values for all input variables
2. Apply the model on the generated values to calculate the model output in terms of LCA results
3. Analyze statistically the model output

The model output is represented by a probability distribution instead of a single value, accuracy increases as number of iterations increases