Renewable Energy Directive

Thematic Data Layers for Commission Decision of [10 June 2010] on guidelines for the calculation of land carbon stocks for the purpose of Annex V to Directive 2009/28/EC

1. Climatic Zone

Climate Zones

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The Climatic Zone layer is defined based on the classification of IPCC (IPCC, 2006). The zones are defined by a set of rules based on :

  • annual mean daily temperature,
  • total annual precipitation,
  • total annual potential evapo-transpiration (PET) and
  • elevation.

The classification presented as Figure 3A.5.1 Classification scheme for default climate regions” (IPCC, 2006) could not be accessed in electronic form and generated from an independently developed set of base data layers. Climatic information on temperature and precipitation was provided by the 5 arc min. dataset Version 1.4 from the WorldClim project (Hijmans et al., 2005). PET was computed according to the temperature-based formula investigated by Oudin et al. (2005) and used by Kay & Davis (2008). The computation of the extraterrestrial radiation was based on Duffie & Beckman (1991) and Allen et al. (1994). The formulas were supplemented by the information provided by the “Solar Radiation Basis” Web-page of the University of Oregon: http://solardat.uoregon.edu/SolarRadiationBasics.html.

2. Soil Type Classification

Soil type

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Soil types are classified according to the World Reference Base (WRB). The scheme for translating soil types into IPCC classes is presented “Figure 3A.5.4 Classification scheme for mineral soil types based on World Reference Base for Soil Resources (WRB) classification” (IPCC, 2006). The layer was generated by applying the IPCC soil classification to the Harmonized World Soil Database (HWSD; http://www.iiasa.ac.at/Research/LUC/luc07/External-World-soil-database/HTML/index.html) (Fisher et al., 2008) from IIASA and FAO.

3. Common Spatial Layer Specifications

The thematic layers are stored in Idrisi file format. The technical specifications of the spatial data layers are given in Table 1.

FEATURE VALUE
Data type 16-bit integer
File type binary
No. of columns 4320
No of rows 2160
Reference system ETRS89*
Reference units Degrees
Min. x coordinate -180.00
Max. x coordinate 180.00
Min. y coordinate -90.00
Max. y coordinate 90.00

* Annoni, et al., 2001

Citations

Additional references

  • Allen, R.G., M. Smith, A. Perrier and L.S. Pereira, 1994. An update for the calculation of reference Evapotranspiration. ICID Bulletin of the International Commission on Irrigation and Drainage 43(2). p. 35-92.
  • Annoni, A., C. Luzet, E. Gubler and J. Ihnde (2001) Map Projections for Europe. European Commission Joint Research Centre, Ispra, Italy. EUR 20120 EN. 131pp.
  • Duffie, J. A. and W.A. Beckman, 1991. Solar Engineering of Thermal Processes, 2nd ed. J. Wiley and Sons, New York. 919pp.
  • Fischer, G., F. Nachtergaele, S. Prieler, H.T. van Velthuizen, L. Verelst, and D.Wiberg, 2008. Global Agro-ecological Zones Assessment for Agriculture (2008). IIASA, Laxenburg, Austria and FAO, Rome, Italy. http://www.iiasa.ac.at/Research/LUC/luc07/External-World-soil-database/HTML/index.html?sb=1
  • Hijmans, R.J., S.E. Cameron, J.L. Parra, P.G. Jones and A. Jarvis, 2005. Very high resolution interpolated climate surfaces for global land areas. International Journal of Climatology 25, p.1965-1978. http://www.worldclim.org/current
  • Intergovernmental Panel on Climate Change (IPCC), 2006. IPCC Guidelines for National Greenhouse Gas Inventories – Volume 4. Egglestone, H.S., L. Buendia, K. Miwa, T. Ngara and K. Tanabe (Eds). Intergovernmental Panel on Climate Change (IPCC), IPCC/IGES, Hayama, Japan.http://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html
  • Kay, A.L. and H.N. Davis, 2008. Calculating potential evapotranspiration from climate model data: A source of uncertainty for hydrological climate change impacts. Journal of Hydrology (358) p. 221-239.
  • Oudin, L., F. Hervieu, C. Michel, C. Perrin, V. Andréassian, F. Anctil and C. Loumagne, 2005. Which potential evapotranspiration input for a limped rainfall-runoff model? Part 2 - Towards a simple and efficient potential evaportranspiration model for rainfall-runoff modelling. Journal of Hydrology 303, p. 290-306.

 


ADDITIONAL DATA

Introduction to Spatial Layers for Estimating Soil GHG Emissions from Indirect Land Use Changes(ILUC) due to the Production of Biofuels

The Directive on Renewable Energy (Directive 2009/28/EC, RED) sets ambitious targets for all Member States. Under the RED the EU should reach by 2020 a 20% share of energy from renewable sources and a 10% share of renewable energy specifically in the transport sector. Renewable energy from biofuels, including those imported into the EU, should come from sustainable sources and deliver high greenhouse gas (GHG) savings, at least 35% when compared to fossil fuels. In growing biofuels land use changes can lead to changes in carbon stocks in soils and biomass and subsequent changes in GHG emissions, which forms an important factor in the sustainability assessment. To encourage industry, governments and NGOs to set up voluntary certification schemes for all types of biofuels a new scheme was adopted by the European Commission as Commission Decision of 10 June 2010 on guidelines for the calculation of land carbon stocks for the purpose of Annex V to Directive 2009/28/EC (notified under document C(2010) 3751).

The data made available on these pages are referred to in the Guide for Calculation of Carbon Stock Changes in Soil and Above and Below Ground Vegetation due to Land Use Conversion, which was prepared in support to Commission Decision C(2010) 3751). The thematic spatial layers complement the data already published on the reference climate region and soil type classification.

 

Access to the data:

In order to obtain access to these databases : Fill in the online form; after which you will receive further instructions how to download the data. 
(April 2011) Data available for: Reference Grid, Global Land Cover, Climate and Ecological Zones, Soil Default C-Stocks, Land Use System Factor(FLUSYS), IFPRI Global Regions, Crop Surface Area.


1. BASE DATA

The basic data cover the layers needed to set the framework for the spatial analysis of the land use change analysis. Details on the characteristics of the spatial layers are provided in Table 1.

Table 1: Technical Specifications of Spatial Data Layers

FEATURE VALUE
Data type 16-bit integer
File type binary
No. of columns 4320
No of rows 2160
Reference system ETRS89
Reference units Degrees
Min. x coordinate -180.00
Max. x coordinate 180.00
Min. y coordinate -90.00
Max. y coordinate 90.00

1.1 Reference Grid

Reference Grid

The reference grid defines the common spatial layer specifications and specifies for position of a grid cell on land a unique identifier (ID) between 330053 and 7561355. The grid resolution was set to a regular size of 5 arc minutes (0.083333 deg). This grid spacing corresponds to approx. 10km at the equator.

1.2 Grid Cell Area

The reference grid layer is also used to define the land-sea mask applied to all layers of the series. In all layers the area covered by Antarctica was not included.

Reference Grid Area

For each grid cell the surface area is represented in a separate layer. Since the layers are not projected the surface area changes with latitude. This uneven weight in computations related to areas with latitude has to be considered in calculations for changes in land use classes. For convenience the area layer is therefore provided.

 


2. THEMATIC DATA

The data forming the set of thematic layers define the input information for the computation of the default values to calculate GHG emissions from changes in soil C-stocks according to the factors defined in the Guide (Carré, et al., 2010) .

2.1 Land Cover

land use

The land cover layer compromises a merge between data from the GlobCover project (Version 2.2, released 10.12.2008; Bicheron et al., 2008), and the McGill University M3-Cropland data (Ramankutty et al., 2008. The land cover classes were aligned to correspond to the specifications of the RED:

  • Open Forest, < 30% cover
  • Closed Forest, >= 30 % cover
  • Cropland
  • Grassland
  • Shrub
  • Sparse vegetation
  • Wetland
  • Artificial areas
  • Other land areas

The layers contain for each grid the relative proportion of the land cover type at the resolution of 5 arc min..

2.2 Ecological Zones

Ecological Zones

In addition to the climatic regions a layer containing ecological zones was defined. The definition of the ecological zones is described in Chapter 4 – Forest Land of the 2006 IPCC Guidelines for National Greenhouse Gas Inventories rather than in Chapter 3 – Consistent Representation of Lands. The map of global ecological zones given in Figure 4.1 of the report originates from Global Forests Resources Assessment 2000 (FAO, 2001), FRA2000. Spatial layers of ecological zones and domains can be downloaded from the FAO GeoNetwork server. The definition of the ecological zones is described in Table 4.1 (IPCC, 2006).

To maintain compatibility with the Climate Region map a spatial layer of Ecological Zones was generated with the minimum of modifications. The Ecological Zone data is therefore only an approximation of the FAO map on Global Ecological Zones. The main difference in the definition of the ecological zones between the two maps is the use of only climatic data to guide the classification in the study data and not incorporate information on the vegetation pattern. This difference is of some significance because the layer is employed to map the carbon estimates in above and below ground vegetation by land cover type. This leads to some of the ecological zones not being present in the layer.

 

2.3 Soil Default C-Stocks

Soil organic Carbon

From the combination of the soil classes with the climate regions the default reference soil organic C-stocks can be generated. The corresponding layer provides the soil organic C-stocks in a depth of 0-30 cm in t C ha-1 for mineral soil types. The C-stocks were calculated from the Harmonized World Soil Database (HWSD) V. 1.1, using information from all typological units. Areas missing in the HWSD were substituted from the FAO-UNESCO Soil Map of the World.

 

2.4 Land Use System Factor

Land use

In the approach used the variation of soil C-stocks from the default value are governed by the Land Use System Factor (FLUSYS). The FLUSYS is a combination of the

  • land use type, (FLU)
  • management system (FMGM) and
  • input (FI).

A FLUSYS of 1 is applied to all native ecosystems and non-degraded grassland with nominal management. For cultivated areas, including areas of set-aside, the nominal value may deviate from 1, depending on the management practice and input factors.

Spatial layers of the FLUSYS were thus generated for to following land use types:

  • Cultivated, annual
  • Cultivated, perennial
  • Rice, paddy
  • Set-aside
  • Grassland

Where cropland expands to areas previously without cropland the FLUSYS of the neighbouring land can be applied. The potential FLUSYS of these areas was estimated from the reference data using an expansion function based on the inverse distance. Since the land use types “rice, paddy” and “set-aside” only have a single value for the FLUSYS the expansion was only performed for the annual and perennial land use type layers.

 


3. PROJECT DATA

Data needed to evaluate the output from an economic model for GHG emissions from ILUC can be specific to that model. The main areas of variations concern the definition of the economic regions and the crops or groups of crops used. It should be noted that the composition of the groups of crops used in the economic models are not necessarily identical to those of the crop groups defined in the ancillary spatial data. Where needed, crop groups of sugar or oil crops can be generated from corresponding individual crops.

3.1 IFPRI Global Regions

IFPRI Regions

The International Food Policy Research Institute, Washington (IFPRI) evaluates the area needs for biofuels based on a set of economic scenarios. Estimates are provided by global economic region. The attribution of countries to an economic region as used in the project is given in this layer. There can be areas with a different attribution in the layer from the one used by IFPRI, such as French Guyana or some of the disputed regions in Asia and Africa. In Europe the attribution of the areas covered by the Former Republic of Yugoslavia were assigned to the rest of the World (RoWorld).

3.2 Crop Surface Area

Cropland

The proportional surface area of crops used in the economic models was derived from the harvested area of the McGill University M3-Crops data (Monfreda, et al., 2008). The conversion of harvested to proportional surface area was based on the estimation of multi-cropping systems.

Spatial layers for the following crops were generated:

  • Wheat
  • Grain Maize
  • Rice
  • Sugar beet
  • Sugarcane
  • Oil palm
  • Rapeseed
  • Soybean
  • Sunflower
  • Vegetables & Fruit
  • Other crops
  • Rest

The crop "Other Crops" includes any crops not otherwise covered by a specific crop type. The layer “Rest” accounts for the difference in area between the M3-Cropland data (Ramakutty, et al., 2008) and the sum of the crop group area.


References

Carré, F., R. Hiederer, R., Blujdea, V. and Koeble, R. (2010) Background Guide for the Calculation of Land Carbon Stocks in the Biofuels Sustainability Scheme Drawing on the 2006 IPCC Guidelines for National Greenhouse Gas Inventories. EUR 24573 EN. Luxembourg: Office for Official Publications of the European Communities. 109pp.

Hiederer, R., F. Ramos, C. Capitani, R. Koeble, V. Blujdea, O. Gomez, D. Mulligan and L. Marelli. (2010) Biofuels: a New Methodology to Estimate GHG Emissions from Global Land Use Change. EUR 24483 EN. Luxembourg: Office for Official Publications of the European Communities. 150pp.

Bibliography

Bicheron P., P. Defourny, C. Brockmann, L. Schouten, C. Vancutsem, M. Huc, S. Bontemps, M. Leroy, F. Achard, M. Herold, F. Ranera and O. Arino (2008) CLOBCOVER: Products Description and Validation Report. MEDIAS France, 18, avenue E. Belin, bpi 2102, 31401 Toulouse Cedex 9, France. 47pp.ftp://us-ext-nas.eo.esa.int/global/GLOBCOVER_Products_Description_Validation_Report_I2.1.pdf

FAO (2001) Global Forest Resources Assessment 2000. FAO, Rome. 479pp.

FAO/IIASA/ISRIC/ISSCAS/JRC (2009) Harmonized World Soil Database (version 1.1). FAO, Rome, Italy and IIASA, Laxenburg, Austria.

Intergovernmental Panel on Climate Change (IPCC) (2006) 2006 Guidelines for National Greenhouse Gas Inventories. Eggelstone, S., L. Buemdia, K. Miwa, T. Ngara and K. Tanabe (Eds.). IPCC/OECD/IEA/IGES, Hayama, Japan

Monfreda C., N. Ramankutty and J. Foley (2008) Farming the planet: 2. Geographic distribution of crop areas, yields, physiological types, and net primary production in the year 2000. Global Biochemical Cycles, Vol. 22, GB1022, doi : 10.1029/ 2007GB002952

Official Journal L140, 05.06.2009, p. 16-62.

Official Journal L151, 17.06.2010, p. 19-41.

Ramankutty, N., A. T. Evan, C. Monfreda, and J. A. Foley, 2008. Farming the planet: 1. Geographic distribution of global agricultural lands in the year 2000. Global Biogeochemical Cycles, Vol. 22, GB1003, doi:10.1029/2007GB002952.

 

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Title: Support to Renewable Energy Directive
Resource Type: Datasets, Soil Projects Data
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Title: Global Spatial Layers for Estimating Soil GHG Emissions from Indirect Land Use Changes(ILUC) due to the Production of Biofuels
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Year: 2011
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