LCA and standards
Nana Wilberforce (PNC)

Life-cycle assessment (LCA) is a methodology for analyzing the environmental of products and services. Over the past few years, life cycle assessment has played an integral role in the development environmental standards for products and services. The goal of this course is to identify benefits and values of life cycle assessment in developing and evaluating the effectiveness of environmental standards.

Introduction to LCA
Christoph Koffler (PE Americas)

This course aims at introducing the concept and methods of life cycle assessment. It will provide an overview of the science of Life cycle assessment from an historical perspective and its current applications. Attendees will also carry out a simple LCA, using no more than a pen and paper, in order to develop an understanding on the methods involved with carrying out a this types of studies. The focus of the exercise will be the calculation of the environmental and economic profile of a product across its life cycle.

Ethics in LCA
Rita Schenck (IERE)

Ethical behavior is essential for everyone, but every situation and every profession has different ethical issues whose solutions are not immediately obvious even to the professional. This course will discuss different approaches to ethical decision-making and how they apply to life cycle assessment. Examples of tricky situations will be provided and students will leave with a set of tools for compliance and ethical action, and a clearer understanding of the utility of the ACLCA ethics statement.

Statistical methods in LCA
Ron Wroczynski & Matt Pietrzykowski (GE)

This course aims to set the foundation for understanding and using basic statistical tools in LCA. It is targeted at attendees with no prior statistical training or those requiring a basic refresher course in fundamental concepts. The curriculum will start with a discussion of probability and the types and relevance of different parameters and data distributions and lead into discussions of sources of variability and propagation of error. The course will finish with a discussion of the application of Monte Carlo methods and introductory design of experiments concepts for conducting sensitivity and uncertainty analyses. (Advanced techniques for conducting sensitivity and uncertainty analyses will be discussed in more detail in the Advanced Statistics and Data Analysis for LCA course). This course will include hands-on exercises involving the use of common spreadsheet functions. Attendees are strongly encouraged to bring a laptop computer with spreadsheet software.

Value proposition of LCA
Peter Canepa and Liila Woods (PE Americas)

The objective of this course it to present the current and potential uses of LCA and the value it can generate for companies. A series of examples will be presented and discussed at different levels:

• LCA in support of cost reduction activities (manufacturing and sourcing)
• LCA in support of Marketing and brand activities
• LCA in support of Innovation
• LCA in support of business case development (with focus on venture capital gathering)

The focus of the course will be to develop a high level of knowledge on how to position and format environmental and economic life cycle assessment in support of each of the needs stated above.

LCA in Public Policy
Martina Prox (ifu Hamburg & Leuphana Univ)

This course will provide an overview on LCA studies used to support decisions in public Policy in several countries. The participants will develop an understanding of the type of decisions and legislation can be supported by conducting an LCA. Jointly with the participants it will be also developed which decisions in public policy could or should be supported with LCA studies, also identifying the limitations of the concept.

LCA and Recycling
Laurel McEwen (Earthshift)

Modeling reuse and recycling is not easy and yet is critical for many LCA’s. As companies work towards making more sustainable decisions, they are specifying recycled and recyclable materials in their designs and developing end of life plans to reclaim materials for recycling. Industry wants credit for these efforts in their LCA models, yet the credit may or may not be applied, depending on the recycling model chosen. Take this introductory course to learn the basics of building recycling scenarios. This class will familiarize you with both open and closed loop recycling procedures established by ISO guidelines as well as the commonly used cut-off and economic allocation methods. The class will help you understand the value choices inherent in each method which will ultimately help you understand and select a recycling method that drives sensible behavior in your market.

Carbon Foot printing
Martina Prox (ifu Hamburg & Leuphana Univ)

This course will give an introduction on carbon foot printing methodology using examples from practice; give an overview on attempts to standardize carbon foot printing on a global scale and discuss the benefits and possible short-comings of the methodology as well. The participants are encouraged to bring a Notebook (Windows-System) to experience in the end of the course a short hands-on session with the newly released tool Umberto for Carbon Footprint. Participants’ experience and background knowledge will enhance course discussions.

Advanced Statistics & Data Analysis for LCA
Matt Pietrzykowski & Ron Wroczynski (GE)

Please join us in this hands on course aimed at broadening the LCA practitioners depth and breadth in available data analysis tools. Have you ever wanted to conduct an uncertainty or sensitivity analysis in a structured way that adheres to proven statistical designs? When exploring your model at the inventory or impact assessment stage, have you found yourself wanting more tools to help understand what your data has to say? In this course, we will use common spreadsheet tools to design experiments aimed at providing experimental structure for uncertainty and sensitivity analysis. We will also use the R statistical software environment as a tool to explore our data with techniques like data transformations, data visualization, supervised and unsupervised clustering, and principal component analysis. While prior knowledge of general statistical and data modeling concepts would be useful, this background is not a prerequisite for the course. A laptop is required with a spreadsheet package, and R can be downloaded from http://cran.r-project.org/.