Industrial Ecology Freiburg

Research group at the Faculty of Environment and Natural Resources



Industrial Ecology Open Online Course



The Industrial Ecology Open Online Course (IEooc) is a collection of web content on industrial ecology background, methods, and applications. It has two purposes: First, to document and explain some of the ‘soft’ knowledge around industrial ecology concepts, methods, data, and applications that is needed to conduct state-of-the-art industrial ecology research. Second, to guide new industrial ecology researchers towards having fun and impact with properly conducted science for sustainability.

The course was developed for university students. It features the following items, which are freely available for educational use: lectures (screencasts and webinars of 15-60 minutes), exercises with sample solutions, code samples or notebooks, and reading material (papers, essays, reports, blog entries). There are more than 25 exercises and tutorials, and these form the core of this course.

The course is divided into three broad sections: background, methods, and applications. In the background section a general introduction to the topic is given and the theoretical foundations of interdisciplinary systems science in general, and industrial ecology in particular, are laid. In the methods section the core industrial ecology methods material flow analysis, life cycle assessment, and input-output analysis are introduced. In the application section a number of selected case studies and other examples are presented. Readers can choose their preferred level of exposure to conceptual foundations, and can jump to the methods section, which also contains most of the exercises, at any point. For fully appreciating the origin, structure, and interrelation of the different industrial ecology methods, however, some extra work with the background material will be helpful. To grasp the content of the application section some familiarity with the industrial ecology methods is necessary. For each course item a quick summary of the content is provided, the prerequisites are stated, and the level of difficulty is indicated on a scale reaching from (+) (not very difficult) to (+++) (rather difficult).

The course is built using freely available tools and data wherever possible. For the basic parts of the course a pdf reader, Excel or a similar spreadsheet tool, and access to Youtube are sufficient. The more advanced parts make use of the programming language Python via Jupyter notebooks, and some of the LCA exercises use openLCA in connection with the ecoinvent life cycle database. For some exercises reading material that is not generally available is required.

The course consists of a combination of own and external material. I took the liberty of linking to content created by other scholars of the industrial ecology and other communities where appropriate. If you would like to have a link removed, let me know. If you would like to see your own content added, drop a line to stefan.pauliuk[at]indecol.uni-freiburg.de, and I will check whether it fits into the course. The course material will be improved and expanded over the next years, so that the syllabus can grow bit by bit.

The course and its parts are designed for self-study. I don't have the capacity for individual supervision and guidance and will decline such requests unless they are related to mistakes in the material or parts of it that are confusing. There is no exam for this course and no certificate of participation.

Suggestions for improvements or new content are welcome.

Have fun!

Stefan Pauliuk
University of Freiburg, Germany.


IEooc Syllabus

Last update: October 25th, 2018.


Part I: Background


Background 1: Conceptual Foundations
Introductory text about systems thinking: "Quantitative Analysis of Industrial Systems: Intellectual Framing". The text (16 pages) gives a brief introduction to systems thinking, contains a general theory for analysing coupled human-environment systems, and provides an explanation of what industrial ecology exactly is.
IEooc_Background1_Reading1

Introductory video: 17 min video lecture about industrial ecology:
IEooc_Background1_Lecture1 (part of an online course on Systems Ecology by Complexity Labs.)

Classical reading: "The Economics of the Coming Spaceship Earth", by Kenneth E Boulding (1968):
IEooc_Background1_Reading2

Classical reading: "Strategies for Manufacturing", by Frosch and Gallopoulus (1989):
IEooc_Background1_Reading3

Background 2: Climate, sustainability, and the contribution of industrial ecology
Video lecture on the big picture: Climate change:
IEooc_Background2_Lecture1

Video lecture on the big picture: Sustainability:
IEooc_Background2_Lecture2

Video lecture on the big picture: The scaling behaviour of cities:
IEooc_Background2_Lecture3

Exercise: Systems thinking for renewable energy. Learn about the main types of renewable energy, the main barriers for their implementation, and the system linkages that determine their future contribution to climate change mitigation by reading the relevant chapter of the IPCC 5th Assessment Report. Prerequisites: None. Level of difficulty: (+)
IEooc_Background2_Exercise1.
Chapter 7 of part III of the IPCC 4th Assessment report is the reading material for this exercise:
Reading material: Chapter 7 of part III of the IPCC 4th assessment report (pdf)
For this exercise a sample solution is available:
IEooc_Background2_Exercise1_Solution (pdf)

Background 3: Open science for sustainability
Reading: Proposal for higher data transparency in industrial ecology: With the growth of the field of industrial ecology (IE), research and results have increased significantly leading to a desire for better utilization of the accumulated data in more sophisticated analyses. This implies the need for greater transparency, accessibility, and reusability of IE data, paralleling the considerable momentum throughout the sciences. It is argued that increased transparency, accessibility, and reusability of IE data will enhance IE research by enabling more detailed and reproducible research, and also facilitate meta-analyses. Two initial actions intended to advance these goals are presented:
IEooc_Background3_Reading1

Reading: Guidelines for software development for industrial ecology:
IEooc_Background3_Reading2

Webinar on open LCA software:
IEooc_Background3_Lecture1

Reading: Input from other communities: A comment on transparency in energy system modelling:
IEooc_Background3_Reading3




Part II: Methods

Methodology 1: Basics of industrial ecology data and accounting.
Video lecture on the basic principles of industrial ecology data modelling and accounting: material and energy flow analysis:
IEooc_Methods1_Lecture1
In this lecture the definitions and basic methodology for material and energy flow accounting are presented, including the basic elements of the quantitative system definition, the process balancing equations, indicator elements, units of measurement, multi-layer system descriptions, and a number of examples. Prerequisites: No advanced math is required at this stage. Level of difficulty: (+)

Exercise: Locating data in a system definition and indicator development. Learn how to establish a system definition to allocate quantitative information that is given as text. Define and calculate indicators based on the system definition. Prerequisites: No advanced math is required at this stage. Level of difficulty: (+)
IEooc_Methods1_Exercise1.
For this exercise a sample solution is available:
IEooc_Methods1_Exercise1_Solution (pdf)

Reading: The supporting documents of the material and energy flow analysis software STAN are a good reference for building proper system definitions and for data modelling in material and energy flow analysis and industrial in general. An overview of the different documents can be found here.
Recommended STAN reading 1: Glossary of basic systems analysis terms:
IEooc_Methods1_Reading1
Recommended STAN reading 2: Principles of establishing a system definition:
IEooc_Methods1_Reading2

Reading: A more theoretical paper explains the underlying system structure of material and energy flow analysis, life cycle assessment, and input-output analysis: Level of difficulty: (++)
IEooc_Methods1_Reading3
Related video lecture (17 minutes)
IEooc_Methods1_Lecture2

Video lecture on a general data model for socioeconomic metabolism:
IEooc_Methods1_Lecture2
In this lecture, a general data model for locating data in the systems context is presented. It allows researchers to format data describing stocks, flows, material composition of products, lifetimes, prices, life cycle inventories, IO tables, etc. in a common structure. The data model can be used to build databases that combine data that are commonly associated with specific methods, but which are of use to many researchers. It can also be used to develop data sharing infrastructure for research groups, institutions, and the entire community. Prerequisites: No advanced math is required at this stage. Level of difficulty: (++)

Exercise: Basic data reconciliation. You will learn about the principles of data reconciliation and apply data reconciliation to a simple system. You will make use of the mass balance to formulate constraints and to determine non-measured variables. You will understand the basics of the maximum entropy principle. Note: For this exercise a copy of "Data Reconciliation and Gross Error Detection. An Intelligent Use of Process Data" by Shankar Narasimhan and Cornelius Jordache, ISBN: 978-0-88415-255-2, is required. Prerequisites: Linear programming and its application in Excel. Level of difficulty: (++)
IEooc_Methods1_Exercise2 (pdf).
IEooc_Methods1_Exercise2 (data).
For this exercise a sample solution is available:
IEooc_Methods1_Exercise2_Solution (xlsx)

Methodology 2: Basics of material flow analysis.
Video lecture on MFA system models and their analytical and numerical solution. Prerequisites: Matrix algebra and its implementation in Excel. Level of difficulty: (++)
IEooc_Methods2_Lecture1

Video lecture on data uncertainty and sensitivity of results in MFA system models. Prerequisites: Calculus. Random variables, discrete and continuous probability distributions. Level of difficulty: (+++)
IEooc_Methods2_Lecture2

Exercise: Cement production, efficiency strategies and related indicators: The goal of this exercise is to consolidate your understanding of basic quantitative system analysis. Also, to get some detailed knowledge about energy use and greenhouse gas emissions of the cement industry. Prerequisites: No advanced math required. Level of difficulty: (++)
IEooc_Methods2_Exercise1.
For this exercise a sample solution is available:
IEooc_Methods2_Exercise1_Solution (pdf)
IEooc_Methods2_Exercise1_Solution (xlsx)

Exercise: Recycling systems: Efficiency strategies and uncertainty propagation: From a systems perspective, you will gain basic insights into material cycles and recycling systems using the example of beverage cans in Germany. You will conduct a sensitivity analysis, error propagation and calculation of result elasticities. Prerequisites: Calculus. Random variables and analytical error propagation. Level of difficulty: (+++)
IEooc_Methods2_Exercise2.
For this exercise a sample solution is available:
IEooc_Methods2_Exercise2_Solution (pdf)

Check also this exercise from the application section, which contains a Monte-Carlo Simulation: "Inclusion of Consumption of carbon intensive materials in emissions trading. You will gain a basic systems understanding of material markets, learn about the material content of merchandise groups, error propagation, and the application of Monte-Carlo-Simulation in material flow analysis." Prerequisites: Calculus. Random variables, discrete and continuous probability distributions, Monte-Carlo-Simulation. Level of difficulty: (+++)
IEooc_Application3_Exercise1 (pdf)
IEooc_Application3_Exercise1 (data and workbook)
For this exercise a sample solution is available:
IEooc_Application3_Exercise1_Solution (pdf) and
IEooc_Application3_Exercise1_Solution (xlsx)

Video lecture on the concept 'urban metabolism' and how it can be useful to local governments. Urban metabolism studies help cities and city regions assess current resource use and identify pathways for improvement. (from UN Environment):
IEooc_Methods2_Lecture3

Methodology 3: Dynamic Material Flow Analysis.
Video lecture introducing the basic principles of dynamic material flow analysis, the main data sources for dynamic MFA models, some examples of dynamic MFA, and the most important approaches to solving mathematical models of dynamic MFA systems: Prerequisites: Calculus. Linear difference equations, simple differential equations. Level of difficulty: (+++)
IEooc_Methods3_Lecture1

Video lecture on dynamic stock models. The following concepts are introduced and explained: Population balance models, the leaching model, impulse response functions, age-cohorts, and the lifetime model. Prerequisites: Calculus. Simple differential equations. Discrete and continuous random variables. Convolution. Level of difficulty: (+++)
IEooc_Methods3_Lecture2

Video lecture on inflow-driven and stock-driven modelling: With inflow-driven modelling stocks can be determined from historic inflows using a convolution operation. With stock-driven modelling the inflow can be determined from a given stock scenario using inverse convolution. Prerequisites: Calculus. Simple differential equations. Discrete and continuous random variables. Convolution. Level of difficulty: (+++)
IEooc_Methods3_Lecture3

Exercise: "Dynamic model of the German steel cycle, 1800-2008." The goals of this exercise are twofold: first, to develop a systems understanding regarding the development of flows and stocks in material cycles, using the example of the steel cycle in Germany. Second, to estimate steel stocks using dynamic stock modelling. Prerequisites: Calculus. Simple differential equations. Discrete and continuous random variables. Convolution. Level of difficulty: (+++)
IEooc_Methods3_Exercise1 (pdf)
IEooc_Methods3_Exercise1 (Data, xlsx)
For this exercise a sample solution is available:
IEooc_Methods3_Exercise1_Solution (pdf) and
IEooc_Methods3_Exercise1_Solution (xlsx)

Blog entry: "The lifetime of materials in the technosphere" introducing a simple dynamic MFA model of a material cycle to study the dispersion of materials in the technosphere. Prerequisites: Analytical solution of MFA systems, geometric series. Level of difficulty: (++)
IEooc_Methods3_Reading1

Exercise on estimating the number of life cycles of metals: Goal of this exercise is to develop and solve a basic model of the recycling loop, to define and calculate the lifetime of a material in the technosphere and the average number of life cycles. Prerequisites: Analytical solution of MFA systems, geometric series. Level of difficulty: (++)
IEooc_Methods3_Exercise2.
For this exercise a sample solution is available:
IEooc_Methods3_Exercise2_Solution (pdf)

Jupyter notebook with a tutorial on inflow-driven and stock-driven modelling, using the dynamic_stock_model class in Python and the Chinese steel stock as an example: In this workbook it is shown how inflow-driven and stock-driven modelling can be implemented in Python using the dynamic_stock_model class. Prerequisites: Calculus. Simple differential equations. Discrete and continuous random variables. Convolution. Basic programming and data visualisation in Python. Level of difficulty: (+++)
IEooc_Methods3_Software1 (Jupyter notebook) (Save link as .ipynb file!)
IEooc_Methods3_Software1 (data file)

Jupyter notebook with a tutorial on stock-driven modelling for material stocks in products, using the dynamic_stock_model class in Python and the global passenger vehicle fleet as an example: In this workbook it is shown how stock-driven modelling can be implemented in Python using the dynamic_stock_model class and applied to calculate the material flows and stocks in the products that we use. Prerequisites: Calculus. Simple differential equations. Discrete and continuous random variables. Convolution. Basic programming and data visualisation in Python. Level of difficulty: (+++)
IEooc_Methods3_Software2 (Jupyter notebook) (Save link as .ipynb file!)
IEooc_Methods3_Software2 (data file)

Methodology 4: Life cycle assessment.
For LCA some very good open teaching material exists. The list of open teaching material of the International Life Cycle Academy (ILCA) provides an overview of the available open content. In particular, the LCA text book is highly recommendable. It is developed by colleagues from Carnegie Mellon University in Pittsburgh.
The UN Environment Life Cycle Initiative also provides LCA training material on its homepage.

Video lecture on the computational structure of LCA: In this lecture the maths of LCA are explained, following the Leontief input-output model. First, the processes and flows that are modeled and calculated are defined and located in the system. Then, the different calculation steps are explained step by step. Prerequisites: Matrix algebra. Level of difficulty: (+++)
IEooc_Methods4_Lecture1

Basic LCA exercises, no LCA software and database required:

LCA basics: Simple comparative LCA: Practice systems thinking and quantitative systems analysis, work with system definitions, apply life cycle thinking to electric vehicles and electric transportation. Prerequisites: No advanced math required. Level of difficulty: (+)
IEooc_Methods4_Exercise1.
For this exercise a sample solution is available:
IEooc_Methods4_Exercise1_Solution (pdf)

LCA basics: Process-based LCA: Practice systems thinking and quantitative systems analysis, work with system definitions, apply life cycle thinking to solar power by conducting a quick process-based LCA of PV module production. Prerequisites: No advanced math required. Level of difficulty: (+)
IEooc_Methods4_Exercise2.
IEooc_Methods4_Exercise2 (data and workbook)
For this exercise a sample solution is available:
IEooc_Methods4_Exercise2_Solution (xlsx)

LCA basics: Matrix algebra and the LCA master equation: Apply the life cycle perspective, understand the computational structure of LCA, understand and implement basic matrix algebra operations on paper. Prerequisites: Matrix algebra. Level of difficulty: (++)
IEooc_Methods4_Exercise3.
For this exercise a sample solution is available:
IEooc_Methods4_Exercise3_Solution (xlsx)

LCA basics: LCA with matrix algebra in Excel: Understand the computational structure of LCA, understand and implement basic matrix algebra operations in Excel. Prerequisites: Matrix algebra. Level of difficulty: (++)
IEooc_Methods4_Exercise4.
IEooc_Methods4_Exercise4 (data and workbook)
For this exercise a sample solution is available:
IEooc_Methods4_Exercise4_Solution (xlsx)

LCA basics: Life Cycle Impact Assessment: Practice life cycle thinking, work with the LCIA method LC impact, calculate regional endpoint indicators, understand and implement basic matrix algebra operations. Prerequisites: Matrix algebra. Level of difficulty: (++)
IEooc_Methods4_Exercise5.
IEooc_Methods4_Exercise5 (data and workbook)
For this exercise a sample solution is available:
IEooc_Methods4_Exercise5_Solution (pdf)
IEooc_Methods4_Exercise5_Solution (xlsx)

Advanced LCA exercises with openLCA. An ecoinvent license is required:

A list of openLCA tutorials and info videos can be found on GreenDelta's
Youtube channel.

Getting started with openLCA: The goal of this tutorial is to install and learn how to use the openLCA software for life cycle assessments using ecoinvent v3.2 and several impact assessment methods. The use of parameters, choice of electricity mix, sensitivity analysis, export of data, and a small test case are described. Level of difficulty: (++)
IEooc_Methods4_Exercise6.

Modifying processes in openLCA: Copy processes, modify processes, change the electricity source, and conduct a comparative LCA of different steel recycling routes. Level of difficulty: (++)
IEooc_Methods4_Exercise7.
For this exercise a sample solution is available:
IEooc_Methods4_Exercise7_Solution (pdf)

Allocation and recycling in ecoinvent: Learn how waste treatment, recycling, and allocation are handled in ecoinvent and openLCA. Level of difficulty: (+++)
IEooc_Methods4_Exercise8.
For this exercise a sample solution is available:
IEooc_Methods4_Exercise8_Solution (pdf)

Other advanced LCA exercises:

Reading exercise on a comparative LCA of electric and conventional passenger vehicles: Understand the content and policy relevance of a recent LCA research article on electric transportation.
IEooc_Methods4_Exercise9.
Material for reading exercise:
IEooc_Methods4_Exercise9_Reading.

The matrix method for LCA: Equivalence of two approaches: Learn more about the two matrix approaches to LCA: The Heijungs and Suh (2002) technology matrix and the Leontief input-output model. Show that both approaches are equivalent. Level of difficulty: (+++)
IEooc_Methods4_Exercise10.
For this exercise a sample solution is available:
IEooc_Methods4_Exercise10_MatrixMethods_Solution (pdf)
IEooc_Methods4_Exercise10_MatrixMethods_Solution (xlsx)


Methodology 5: Input-output analysis.
Lecture on the basics of input-output analysis, IO tables and the Leontief IO model, part I: Prerequisites: Matrix algebra. Level of difficulty: (++)
IEooc_Methods5_Lecture1_Part1

Lecture on the basics of input-output analysis, IO tables and the Leontief IO model, part II: Prerequisites: Matrix algebra. Level of difficulty: (++)
IEooc_Methods5_Lecture1_Part2

Lecture on the basics of input-output analysis, IO tables and the Leontief IO model, part III: Prerequisites: Matrix algebra. Level of difficulty: (++)
IEooc_Methods5_Lecture1_Part3

Lecture on the basics of input-output analysis, IO tables and the Leontief IO model, part IV: Prerequisites: Matrix algebra. Level of difficulty: (++)
IEooc_Methods5_Lecture1_Part4

Exercise on IO basics: This is an introductory exercise to IO analysis, covering the mathematical basics of IO modelling and the system structure of IO models. Prerequisites: Matrix algebra on paper and Excel. Level of difficulty: (+++)
IEooc_Methods5_Exercise1.
IEooc_Methods5_Exercise1 (data and workbook)
For this exercise a sample solution is available:
IEooc_Methods5_Exercise1_Solution (pdf)
IEooc_Methods5_Exercise1_Solution (xlsx)

Lecture on multiregional input-output analysis. Prerequisites: Matrix algebra on paper and Excel. Level of difficulty: (+++)
IEooc_Methods5_Lecture2

Exercise: "Multiregional input-output analysis (Excel-based)." This exercise contains a simple application of the MRIO analysis: construction of supply chains, carbon footprint calculations of final consumers in the EU, investigation of fine particulate matter and mercury emissions along the supply chain. Prerequisites: Matrix algebra on paper and Excel. Level of difficulty: (+++)
IEooc_Methods5_Exercise2 (pdf)
IEooc_Methods5_Exercise2 (data and workbook)
For this exercise a sample solution is available:
IEooc_Methods5_Exercise2_Solution (pdf) and
IEooc_Methods5_Exercise2_Solution (xls)

Jupyter notebook with a tutorial for calculating consumption-based emissions and breaking them down into products, region, and industry. Prerequisites: Matrix algebra, basic Python programming. Level of difficulty: (+++)
IEooc_Methods5_Software1 (Jupyter notebook) (Save link as .ipynb file!)
IEooc_Methods5_Software1 (data file)

Jupyter notebook with functions and a tutorial for aggregating MRIO results along the products, region, and industry dimensions. A 163 products x 48 regions x 163 industries footprint result is aggregated to 11 product groups, six regions, and five industrial sectors. Prerequisites: Matrix algebra, Python programming. Level of difficulty: (+++)
IEooc_Methods5_Software2 (Jupyter notebook) (Save link as .ipynb file!)
IEooc_Methods5_Software2 (data file (.mat) and aggregation table (.xlsx))


Methodology 6: Method integration.
Reading material (blog entry) on the differences between process-based LCA and monetary MRIO. Knowing about these differences is important when comparing MRIO and LCA results and when combining the two methods.
IEooc_Methods6_Reading1

Reading material (book chapter) on prospective (forward-looking) assessment of sustainable development strategies using industrial ecology tools. In this text the general principles of prospective modeling are lined out and the current development status of two prospective model types is described: extended dynamic material flow analysis and THEMIS (Technology-Hybridized Environmental-Economic Model with Integrated Scenarios). These models combine the high level of technological detail known from life-cycle assessment (LCA) and material flow analysis (MFA) with the comprehensiveness of, respectively, dynamic stock models and input/output analysis (I/O). These models are dynamic; they build future scenarios with a time horizon until 2050 and beyond. They were applied to study the potential effect of a wide spectrum of sustainable development strategies, including renewable energy supply, home weatherization, material efficiency, and light-weighting.
IEooc_Methods6_Reading2

Exercise: "Passenger vehicle light-weighting. A quantitative analysis of the coupling between the transportation and material production sectors. Application of material flow analysis and life cycle assessment in a common framework." Estimate the system-wide impact of a climate change mitigation strategy in a specific sector. Learn about light-weighting of vehicle as a strategy to reduce GHG emissions on the medium scale. Prerequisites: No advanced math required. Level of difficulty: (+)
IEooc_Methods6_Exercise1 (pdf)
For this exercise a sample solution is available:
IEooc_Methods6_Exercise1_Solution (pdf) and
IEooc_Methods6_Exercise1_Solution (xlsx)




Part III: Applications

Application 1: Sociometabolic regimes and transitions
Webinar about sociometabolic regimes, from the ISIE webinar series on socioeconomic metabolism:
IEooc_Application1_Lecture1

Exercise on land constraints in agricultural societies: Develop a simple engineering model, learn about the physical distance and population constraints in the agricultural society, and estimate the area yield of modern renewable energy technologies. Prerequisites: Calculus. Level of difficulty: (+++)
IEooc_Application1_Exercise1.
For this exercise a sample solution is available:
IEooc_Application1_Exercise1_Solution (pdf) and
IEooc_Application1_Exercise1_Solution (xlsx)

Exercise on decoupling emissions from societal development at the large scale - The IPAT equation: Understand how population, affluence, and a cap for a certain emission to the environment determine how industry must decouple from that emission. Learn about and apply the IPAT equation and link it to global climate and development targets. Prerequisites: Exponential function. Level of difficulty: (++)
IEooc_Application1_Exercise2.
For this exercise a sample solution is available:
IEooc_Application1_Exercise2_Solution (pdf)

Application 2: Circular economy
Introductory blog entry: Circular economy: Breakthrough or distraction?
IEooc_Application2_Reading1

Core reading: "Critical appraisal of the circular economy standard BS 8001:2017 and a dashboard of quantitative system indicators for its implementation in organizations":
IEooc_Application2_Reading2

Blog entry about circular economy and in-use stocks: In this piece the role played by in-use stocks of products, buildings, and infrastructure in closing material cycles (or the 'circular economy transition') is highlighted.
IEooc_Application2_Reading3

Exercise on estimating the number of life cycles of metals (from methods section): Goal of this exercise is to develop and solve a basic model of the recycling loop, to define and calculate the lifetime of a material in the technosphere and the average number of life cycles. Prerequisites: Analytical solution of MFA systems, geometric series. Level of difficulty: (++)
IEooc_Methods3_Exercise2.
For this exercise a sample solution is available:
IEooc_Methods3_Exercise2_Solution (pdf)

Application 3: Supply chain studies
Research article about environmental footprints of households by regions: This study develops an inventory of carbon footprints associated with household consumption for 177 regions in 27 EU countries, thus, making a key contribution for the incorporation of consumption-based accounting into local decision-making.
IEooc_Application3_Reading1

Blog entry about the current limits and possible extensions of emissions trading: A new policy proposal recommends charging consumers of emissions intensive materials such as steel and aluminium for the carbon emissions of material production. The proposal was developed to be considered for implementation in Phase IV of the EU Emissions Trading System commencing in 2021. Material flow cost accounting was applied to quantify the distribution of the carbon charge across commodity groups and to estimate the resulting price changes.
IEooc_Application3_Reading2

Related Policy paper about "Inclusion of Consumption of carbon intensive materials in emissions trading":
IEooc_Application3_Reading3

Related assessment of "Inclusion of Consumption of carbon intensive materials in emissions trading" using material flow cost accounting:
IEooc_Application3_Reading4

Exercise: "Inclusion of Consumption of carbon intensive materials in emissions trading. You will gain a basic systems understanding of material markets, learn about the material content of merchandise groups, error propagation, and the application of Monte-Carlo-Simulation in material flow analysis." Prerequisites: Calculus. Random variables, discrete and continuous probability distributions, Monte-Carlo-Simulation. Level of difficulty: (+++)
IEooc_Application3_Exercise1 (pdf)
IEooc_Application3_Exercise1 (data and workbook)
For this exercise a sample solution is available:
IEooc_Application3_Exercise1_Solution (pdf) and
IEooc_Application3_Exercise1_Solution (xlsx)








Contact: stefan.pauliuk[at]indecol.uni-freiburg.de
International Society for Industrial Ecology: https://is4ie.org







More online teaching resources for industrial ecology and related methods:



+ Webinar series of the International Society for Industrial Ecology. Some of the webinars listed there are part of the IEooc syllabus.

+ Video library of the International Society for Industrial Ecology.

+ Industrial Ecology of Earth Resources, online course material from Columbia University.

+ Massive Open Online Course ’A Circular Economy of Metals: Towards a Sustainable Societal Metabolism’ by Ester van der Voet, CML Leiden.

+ Open teaching material of the International Life Cycle Academy (ILCA).

+ The UN Environment Life Cycle Initiative provides LCA training material.

+ Massive Open Online Course ’Urban Metabolism for Policy Makers’ by provided by the GI-REC (Global Initiative for Resource Efficient Cities), produced and run by Metabolism of Cities, in partnership with the League of Cities of the Philippines and UN Environment.

+ Online material for Introducing Process Integration for Environmental Control in Engineering provided by a group of North American Universities and hosted by the Ecole Polytechnique de Montreal.

+ Teaching material for Environmental Life Cycle Assessment, provided by H. Scott Matthews from Carnegie Mellon University.




PS: The IEooc is not to be confused with the Idaho-Eastern Oregon Onion Committee (IEOOC).