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Overview of the regions considered in the BioenNW-project

Assessment of sustainable biomass potentials in BioenNW regions

Using a GIS (Geographic Information System) based model approach developed by BioenNW partner KIT-ITAS (using Python-code to drive the ArcGIS-software), further modules to assess the potential of surplus grass are presented in this blog post. By applying the same approach as described by Martina Haase (March 2014 BioenNW blog post) and Ahssem Almehasneh (October 2014 BioenNW blog post), the potentials have been calculated for the five BioenNW model regions: West Midlands (UK), South Netherlands (Netherlands), North Rhine-Westphalia (Germany), Wallonia (Belgium) and Île-de-France (France), as well as for two German case studies: Rhineland-Palatinate (RLP) and Saarland (SLD).

In order to assess the grass potentials, the land use data from the CORINE-land cover classification and the latest statistical data from the five model regions were taken into account. The detailed approach is described in the paper “Development of a GIS-based spatial model for the estimation of sustainable biomass potentials in different regions of North West Europe” (Haase 2013) and the BioenNW blog post from March 2014 “Assessment of sustainable biomass potentials in the BioenNW model regions – First results from GIS-based modelling at KIT-ITAS”. The share of grassland varies strongly between the regions. In France, only 1.8% of the Île de France region is covered by grassland, while in the West Midlands 38.9% is classified as pasture or grassland (see Table 1). Consequently, the potentials differ from very low (taking into account the entire NUTS 1-region) to very high.

Two scenarios have been calculated – ‘Basis’ and ‘Restrict’. For grassland, yield potentials are classified as high, medium or low according to the elevation and the soil type (see Table 2). Therefore, data from SRTM digital elevation model (DEM) from the United States Geological Survey  and the European Soil Database has been used to define the class ‘high yield level’ for all areas below 100 m a.s.l. and good soil quality (sand content < 65%). The medium level contains all areas between 100 and 300 m a.s.l., and the low areas (< 100 m a.s.l.) with lower soil quality (sand content > 65%). The low level represents all areas above 300 m a.s.l. for all soil types. Spatially distributed yield estimations for grass are given by the Landwirtschaftskammer (2012) in North-Rhine-Westphalia, stating the conditions in relation to elevation, soil quality, and the number of cuts per year. These values have been used as a distribution scheme for all regions as no such detailed data has been available for the other regions. For all regions, an average value for the grass yields is available (for NUTS 1 or even NUTS 3 regions); this value has been applied as the medium yield level. The scenario ‘Basis’ takes into account four cuts per year, which is seen as a reasonable value in the literature for maximizing yields for biogas production. For the ‘Restrict’ scenario only two cuts per year are assumed, as this respects a more ecological and sustainable cultivation (see Table 2). The total potentials for surplus grass for the regions are then reduced by the need for fodder for cattle, dairy cows, horses, goats and sheep. The animal numbers and their specific fodder demand are taken from regional statistics and technical literature. Using the Livestock Unit (LSU) conversion factor for each animal type, the LSUs per hectare are calculated to locate the fodder demand within the regions (one value for each NUTS 3 region). An overview of the results is given in Table 1 and assumptions are given in Table 2.

KIT May 2015 graphs

The highest potential is located in North Rhine Westphalia  where around 12% of the total area is covered by grassland. There is an intensive cultivation of pastures for fodder and grass production and high yields per ha are achieved here (see Table 2, Figure 2 and Figure 3). After subtracting fodder demands in order to estimate a sustainable grass potential by satisfying existing grass demands, a potential of 6.7 mio tons of grass might be made available for energy purposes throughout North Rhine Westphalia (Basis scenario), in the restrict scenario it would be 5.9 mio tons. In contrast to this, only 318,000 tons are available in the region Île-de-France (Basis scenario), where arable land (48%) dominates. In SLD and RLP, 575,401 and 3.5 mio tons are available in the Basis scenario respectively. Figures 2 – 5 show the results for the German model regions as exemplary results for the above mentioned approach.

KIT May 2015 Graphs 2

The complete results will be incorporated in a Decision Support Tool (DST) which is being developed through BioenNW and which will allow information such as the availability of biomass to be linked to business development plans and economics to determine how viable bioenergy projects will be – further details about this coming soon!

Words by Daniel Ketzer
Karlsruhe Institute of Technology (KIT), Institute for Technology Assessment and Systems Analysis (ITAS)
Karlsruhe, Germany