Original scientific paper
Effects of Moisture Content on Supply Costs and CO2 Emissions for an Optimized Energy Wood Supply Network
Christian Kanzian
orcid.org/0000-0002-1198-9788
; University of Natural Resources and Life Sciences, Vienna Department of Forest and Soil Sciences Institute of Forest Engineering Peter Jordan Strasse 82 A-1190 Vienna AUSTRIA
Martin Kühmaier
; University of Natural Resources and Life Sciences, Vienna Department of Forest and Soil Sciences Institute of Forest Engineering Peter Jordan Strasse 82 A-1190 Vienna AUSTRIA
Gernot Erber
; University of Natural Resources and Life Sciences, Vienna Department of Forest and Soil Sciences Institute of Forest Engineering Peter Jordan Strasse 82 A-1190 Vienna AUSTRIA
Abstract
The supply of wood for energy is challenging due to high supply costs and rapidly increasing demand. As an important quality criterion, moisture content (MC) influences the revenues, demand and supply costs. For transport, the limiting factor is payload, if the MC is high.
The effects of MC on costs and greenhouse gas (GHG) emissions for an optimized supply network have been analyzed using a previously developed multi-criteria optimization model by using different MCs in the range from 50 to 20%. The weighted sum scalarization approach was used to derive Pareto optimal points by changing weights stepwise from maximum profit to minimal GHG on a relatively large scale network of 356 storage locations, 119 freight stations and 228 plants. A decrease of 10% in MC from 40 to 30% will double the profit from 5.10 to 12.00 EUR × t–1. In the case of MC independent revenues, the sensitivity of the model is lower but clearly visible, with a profit increase from 6.00 EUR × t–1 at the MC of 40% to 10.00 EUR × t–1 at the MC of 30%. As expected, emissions will decrease with a decreasing MC. However, the effect on emissions is less prominent than the effect on profit. Reducing MC from 40 to 30% will save approximately 4% of the GHG per dry t.
Keywords
supply network; moisture content; forest biomass; chips; transport; multi-objective optimization
Hrčak ID:
153470
URI
Publication date:
1.2.2016.
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