![]() ![]() Advanced Life Cycle Impact Assessment This course begins by giving an overview of the life cycle impact assessment (LCIA) phase of LCA studies.The course will provide the background for understanding the basic math of LCA-modeling, uncertainty propagation, correlations between variables and global sensitivity analysis. Practical uncertainty analysis in Life Cycle Assessment This course aims to strengthen practice of uncertainty assessment in Life Cycle Assessment.Modelling indirect land-use changes in Life Cycle Assessment This course is dedicated to the state-of-the-art modelling of agricultural systems that incur in indirect land-use changes (iLUC), which arise from increasing demand for agricultural products (particularly biofuels).uncertainty) of the different types of data are examined. Life cycle data and data quality management This course looks at effective and efficient ways to collect, store, retrieve and edit data for Life Cycle Inventory (LCI) Analysis.Economic equilibrium in LCA: assumptions, data and modelling This course is dedicated to the modelling of markets in LCA, with special focus on the assumptions adopted and the data required.The challenges of completeness, consistency, uncertainty etc. The relation to the ISO standards for LCA. Consequential Life Cycle Assessment modelling An in-depth introduction to the technique of consequential Life Cycle Assessment (LCA) modelling via case studies of real life applications.With hands-on exercises we construct detailed IO databases and discuss challenges and developments. Advanced IO and Hybrid Life Cycle Assessment – Constructing and Improving IO Databases in Hybrid Units This course start with the intro-course but then provides the practical skills for building and improving IO LCA databases.IO and Hybrid Life Cycle Assessment – An Introduction for LCA Practitioners This course gives a thorough background for understanding both monetary and physical input-output models and gives an introduction to the most advanced and detailed hybrid IO-database: Exiobase v3.The matrix foundations of LCA, their adaptation for different types of regionalisation, and its use for uncertainty analysis. Regionalised Life Cycle Assessment with the Brightway 2.5 LCA software An introduction to the use of the Brightway 2.5 Open Source LCA software with a particular focus on applying it to regionalised assessments.The course introduces advanced inventory modelling using the techniques of consequential LCA and input-output (IO) LCA. Advanced LCA – Consequential and IO-based Life Cycle Assessment This course aims at strengthening skills in life cycle inventory analysis.From LCC to LCSA – The whole journey in one week Life Cycle Sustainability Assessment (LCSA) = Life Cycle Costing (LCC) + Life Cycle Assessment (LCA) in its most comprehensive form, including economic, social, and ecosystem impacts.Spatiotemporal life cycle assessment with Brightway Practical application of spatially- and temporally-dependent life cycle assessment (LCA) using the open source Brightway software framework. The course gives an introduction to the most advanced and detailed hybrid IO-database: Exiobase v4 hybrid version – and how it is used for LCA studies. This 2.5 day course gives a thorough background for understanding both monetary and physical input-output models, and how the quality of an IO-table depends on the way it is made. We have no current courses, but we are working to set up an replacement date for below course: Courses are updated for each edition, and therefore we do not have ‘standard’ prices listed. You can also request a tailor-made course for your organisation. Based on this you can request to join similar courses via a waitlist. To inspire teachers of life cycle based quantitative sustainability assessment, the Academy is developing course plans and high-quality content, and runs pilot demonstrations of the developed courses.īelow you can see a dynamic list of current course offerings and below that examples of course plans developed by the International Life Cycle Academy. ![]()
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