PhD opportunity in industrial ecology:
https://www.aau.at/wp-content/uploads/2015/08/Alpen-Adria-Universita¦êt-Klagenfurt-2015-06-25_0536.jpg 1600 1067 Institut für Soziale Ökologie https://www.aau.at/wp-content/uploads/2015/09/aau-logo-300x110-300x110without-background3.png Institut für Soziale Ökologie2017-10-03 16:56:142019-09-24 21:27:34PhD opportunity in industrialecology, Uni Freiburg
Method and software development for supply chain studies
70% position, starting January 1st, 2018
As part of the Swiss-funded research project OASES (Open Assessment of Swiss Economy and Society), which runs under
the funding stream NFP 73 «Sustainable Economy», the industrial ecology group in Freiburg seeks to employ a talended
scientist to work on method and software development for the integration of supply chain databases.
Existing supply chains models either rely on scattered process data that only partially cover global supply chains (Life Cycle Inventory (LCI) databases like ecoinvent, ‘bottom up’) or contain complete, but very aggregate accounts in form of environmentally extended multiregional input-output models (MRIO tables, ‘top down’). While LCA and IO share the
same computational structure, they differ in their resolution, system coverage, and unit of measurement, leading to differences in calculated impact scores of individual products between 20 and 50 percent.
Both database types are often combined (‘hybridized’), but this procedure happens in an ad-hoc fashion and a
commonly accepted methodology to integrate both methods to produce detailed and accurate product footprints has yet to be established.
There is a need for a set of scientific principles and computational routines to
a) Determine the optimal sectoral and product resolution of the hybrid supply chain model given the available information and its reliability,
b) Quantify and maximize the information content of the combined hybrid life cycle assessment (LCA) model,
c) Quantify the uncertainty of the datasets and the footprint results.
The successful candidate will
Contribute to the development of a general methodology for data integration for supply chain studies bas
ed on the maximum entropy principle.
Estimate the entropy (complement of information content) of different process, trade, and emissions databases,
including ecoinvent and EXIOBASE
Design an open source software library to apply maximum entropy estimation to combine different life cycle databases
A pply the software developed to determine the optimal resolution and uncertainty of supply chain models for
the environmental footprint of Swiss consumption.
Develop sample datasets for unit-testing and teaching purposes
Help to integrate the work into the OASES project and disseminate it at conferences and in scientific publications
For more information see: https://www.indecol.uni-freiburg.de/de/phd-supply-chain-studies