An Environmental Optimization Model for Bioenergy Plant Sizes and Locations for The Case of Wood-Derived SNG in Switzerland

Bernhard Steubing
Swiss Federal Laboratories for Materials Science and Technology (Empa), Switzerland \ Swiss Federal Institute of Technology (EPFL), Switzerland

Isabel Ballmer
Swiss Federal Institute of Technology (ETHZ), Switzerland

Oliver Thees
Swiss Federal Institute for Forest, Snow and Landscape Research (WSL), Switzerland

Léda Gerber
Swiss Federal Institute of Technology (EPFL), Switzerland

François Maréchal
Swiss Federal Institute of Technology (EPFL), Switzerland

Rainer Zah
Swiss Federal Laboratories for Materials Science and Technology (Empa), Switzerland

Christian Ludwig
Paul Scherrer Institute (PSI), Switzerland

Ladda ner artikelhttp://dx.doi.org/10.3384/ecp11057279

Ingår i: World Renewable Energy Congress - Sweden; 8-13 May; 2011; Linköping; Sweden

Linköping Electronic Conference Proceedings 57:38, s. 279-286

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Publicerad: 2011-11-03

ISBN: 978-91-7393-070-3

ISSN: 1650-3686 (tryckt), 1650-3740 (online)


Bioenergy from woodfuel has a considerable potential to substitute fossil fuels and alleviate global warming. One issue so far not systematically addressed is the question of the optimal size of bioenergy plants with regards to environmental and economic performance. The aim of this work is to fill this gap by modeling the entire production chain of wood and its conversion to bioenergy in a synthetic natural gas plant both with respect to economic and environmental performance. Several spatially explicit submodels for the availability; harvest; transportation and conversion of wood were built and joined in a multi-objective optimization model to determine optimal plant sizes for any desired weighting of environmental impacts and profits.

We find a trade-off between environmental and economic optimal plant sizes. While the economic optima range between 75 – 200 MW; the environmental optima are with 10 – 40 MW significantly smaller. Moreover; the economic optima are highly location specific and tend to be smaller if the biomass resource in the geographic region of the plant is scarcer. The results are similar with regards to the effect on global warming as well as with respect to the aggregated environmental impact assessment methods Ecoindicator ’99 and Ecological Scarcity 2006.


Biofuels; Wood energy; SNG; Life cycle assessment; Environmental optimization


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