RELCA flow

RELCA V.1 - LCA for Regional Bioenergy systems


Dr. Sinéad O' Keeffe

Through collaborative work with the DBFZ and CLE department (UFZ), regionally distributed databases were established. These were then used to form the basis modelling for the succeeding modelling steps.

CRAM (Wochele et al. 2014) produces the potential biomass availability for the different regional bioenergy plants. CAM modelling in collaboration with the DBFZ determines, based on regional data, the appropriate and regionally representative model plant concepts and hence the biomass demand functions for the CAM modelling. The CAM modelling links the technology concepts with the biomass availability and thus provides the spatially distributed life cycle inventory (catchment delimited) for each model plant concept within the region.

Other modelling components currently under construction enable the modelling of potential field GHG emissions. Thus RELCA V.1 provides the framework for a hybrid LCI of bioenergy conversion systems within a regional case study area, in order, as a first step to conduct a retrospective LCA to investigate the status quo of the potential environmental implications for the regional production of different energy products. Currently LCA software is implemented to integrate the regional foreground burdens with the assumed non-regional environmental burdens.


O’Keeffe, S., Wochele-Marx, S., Thrän, D. 2016. RELCA: a REgional Life Cycle inventory for Assessing bioenergy systems within a region. Energy, Sustainability and Society, 6(1), 1-19.

O’Keeffe, S., Majer, S., Bezama, A., Thrän, D. 2016. When considering no man is an island—assessing bioenergy systems in a regional and LCA context: a review. The International Journal of Life Cycle Assessment, 21(6), 885-902.

O’Keeffe S., Wochele S., Thrän D. (2013): Regional Bioenergy Inventory for the Central Germany Region. In: Geldermann J, Schumann M (eds) First International Conference on Resource Efficiency in Interorganizational Networks - ResEff 2013 -: November 13th-14th, 2013 Georg-August-Universität Göttingen, Papers, 2013. Niedersächsische Staats- und Universitätsbibliothek.

Wochele S., Priess J., Thrän D., O’Keeffe S. (2014): Crop allocation model “CRAM” - an approach for dealing with biomass supply from arable land as part of a life cycle inventory. In: Hoffmann C, Baxter, D., Maniatis, K., Grassi, A., Helm, P., (ed) EU BC&E Proceedings 2014, 2014. ETA-Florence Renewable Energies, Florence, p. 36 - 40.

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