Interpretation
The objective of this class is to provide students with expert guidance on carrying out the interpretation phase of an LCA, including instruction on the conceptual background and need for interpretation, review of the ISO guidelines and requirements for interpretation, practical methods and tools for interpretation, and helpful hints and strategies. Delivery of the course material will be facilitated by a detailed case study of a comparative LCA which the instructor will use to illustrate key points and which the students will work with in practical exercises on interpretation.
This course presents the details of how to conduct an ISO compliant interpretation that meets all the required completeness, sensitivity and consistency checks. You will learn how to use contribution, scenario, uncertainty, and sensitivity analyses to conduct a fully detailed interpretation that will ensure your study results are robust and well-founded.
The Interpretation phase of an LCA serves two purposes:
1) To gain insight so you can efficiently guide and refine the selected methodology and inventory model
2) To derive robust conclusions and well founded recommendations, as appropriate
This course presents the details of how to conduct an ISO compliant interpretation that meets all the completeness, sensitivity and consistency checks. You will learn how to do contribution, scenario, uncertainty, and sensitivity analyses. The course will use examples to illustrate how an iterative process is applied to refine a LCA study and develop robust conclusions.
- Concepts and Methods
- Conceptual background for interpretation
- Sources of uncertainty in LCA
- Guidance from ISO standards and key literature
- Description of tools and methods available for interpretation
- Consistency checks
- Completeness checks
- Data quality checks
- Interpretation tools and methods.
- Introduction of case study and interpretation practice assignment
Practical Exercises and Strategies
- Review and discussion of interpretation practice assignment
- Practical interpretation methods in SimaPro
- Data quality and uncertainty analysis
- Tips and strategies for interpretation
There are multiple levels of uncertainty introduced into your study when building LCA models which can result in misleading outcomes and faulty conclusions if not identified and accounted for. As a result, there is a tremendous amount of nuance involved in interpreting and communicating the results of LCAs. As the results of LCA studies become of increasing interest to consumers and policy-makers, the importance of proper interpretation on the part of LCA practitioners increases in turn.
Interpreting the results of an LCA is exacting, time consuming and not easy to learn. Done effectively, you will efficiently guide your study and strengthen your conclusions. Done ineffectively, you will miss critical details that could undermine your results. LCA findings need to be assembled and structured together with information on data quality, methodological choices, value-choices, interested parties and the results of a critical review, if conducted. Completeness, sensitivity and consistency checks need to be conducted and then presented in a manner that gives a clear understanding of the outcome of the study. Take this course and learn to strengthen your LCA study and effectively communicate its conclusions, limitations and recommendations
Pre-readings will be assigned and provided. You will also be given modeling and analysis assignments to be conducted individually between classes.
Students are required to have taken our Introduction to LCA online or onsite courses, and/or have a working knowledge of conducting an LCA. A college level course in chemistry is suggested, and we recommend that students purchase and read the ISO 14040 and 14044 (2006) standards before class. Before taking this course it is helpful to have taken our Modeling Recycling course and one of the two Impact Assessment Methods courses that are part of the Practitioner certificate program.


A simplified LCA tool for evaluating environmental impacts of packaging.