Municipal solid waste (MSW) sorting

Semester project or master thesis Fall 2024 or Spring 2025

Context

The design and operation of the next generation of waste management and energy supply systems should ensure the industrial Global Warming Potential (GWP) reduction targets agreed internationally and enable transition towards a circular economy of materials. Related challenges stem from the range and complexity of involved technologies and engineering domains, variety of possibly conflicting performance criteria, and interaction potential within the system as well as with external interfaces, in the context of uncertain energy supply markets.

This project is part of the development of a simulation and optimization platform for decision-support in industrial decarbonization and value recovery pathways, focusing primarily on municipal solid waste (MSW) and organic waste treatment (“Waste-to-X” technologies). This work is a collaboration of IPESE and R&D at Kanadevia Inova AG (KVI), an Engineering, Procurement and Construction company active in the waste treatment sector (>600 plants built), based in Zürich (Switzerland).

Objective

This project tackles the Waste-to-X assessment at the beginning of the waste treatment chain, with the objective of studying waste sorting technologies. The following aspects will be covered:

  1. Review of the options for existing and more novel processes of mechanical waste sorting technologies

  2. Introduction & training into the simulation platform environment

  3. Modeling of selected technologies

  4. Analysis of output stream chemical composition and economic value, defining a set of relevant Key Performance Indicators (KPIs)

  5. Comparative Life-Cycle Impact Assessment (LCIA) of the scenarios for MSW sorting

This analysis will contribute to a more differentiated understanding of energy and economic burdens of the waste value chain.

Skills and Background

  • Understanding of energy systems (the following courses may be of advantage, but not regarded as strict requirements): ME-454 (Modelling and Optimisation of Energy systems), ME-451 (Advanced Energetics), ME-409 (Energy Conversion and Renewable Energy), ENV-510 (Life cycle assessment in energy systems)
  • Coding skills in Python or Modelica are of advantage
  • Willingness to work independently and interest for modeling tasks

Location & Organization

The project is done remotely, either on EPFL campus, IPESE laboratory (located in Sion - train fare Lausanne-Sion is reimbursed by EPFL) or as home office. Regular meetings with the supervisor are ensured (exact schedule to be determined, but typically 1-2x/week), and discussions with Professor Maréchal or industrial research colleagues may be organized in the current of the semester.

Contact

The work is supervised by Julie Dutoit, PhD candidate and R&D process engineer at KVI. If interested, please send your CV with a short description of your specific interest to julie.dutoit@hz-inova.com.

References