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ATEAM final report Section 5 and 6 (2001-2004) 20 Ammonium globally accounts for more than half of total nitrogen emission (Holland et al. 1999). The main ammonium source is domestic animal production. Especially for agricultural centres like the Netherlands and Belgium ammonium sources have to be taken into account in nitrogen deposition scenarios. WU is currently exploring the possibilities to include these sources in an advanced version of the ATEAM nitrogen deposition scenarios. Nevertheless, even our current nitrous oxide deposition scenarios are an important step forward in considering the global trend in eutrophication due to atmospheric deposition of nutrients when acknowledging this limitation. Previously estimated nitrous oxide emissions available from EMEP and IIASA (IIASA - International Institute for Applied Systems Analysis, Laxenburg, Austria) are smaller, because they neglect background emissions from natural ecosystems and agriculture (Table 4). In regional comparison within Europe, emissions are estimated to be highest in Central Europe as well as in Ireland and Wales Figure 7). Table 4. Comparison of ATEAM (from IMAGE) and IIASA European NOx emission scenarios. Country IMAGE emissions (kt NOx) EMEP/IIASA emissions (kt NOx) Austria 377 202 Belgium 599 321 Denmark 517 277 France 3548 1899 Germany 5056 2706 Italy 3621 1938 Luxemburg 43 23 Netherlands 1072 574 Portugal 592 317 Spain 2390 1279 Sweden 652 349 Others 15801 11182 6.2.1.5 Overview over the complete ATEAM global change input data set To facilitate collaboration with other projects and institutions we have compiled an overview of the data sets available from ATEAM in Table 5. Table 5. Overview over the complete ATEAM global change input data set. Data Set Source Parameters and Classification Climate Climate data set (New et al. 2000, Mitchell et al. 2004) 1 Monthly observed climatology 1901 - 2000 16 monthly climate scenarios 2001 - 2100 4 SRES scenarios (A1fi, A2, B1, B2) 4 GCMs (HadCM3, PCM, CGCM2, CSIRO2) Atmospheric CO2 concentration Nitrogen deposition Soil properties “Post SRES Scenario Webpage” (http://crga.atmos.uiuc.edu/research/post-sres.html) “Mauna Loa CO2 records” (Keeling & Whorf, 2002, http://cdiac.esd.ornl.gov/ndps/ndp001.html) IMAGE2.2 SRES scenario implementation data (RIVM 2001) Posch 2002, Alcamo et al. 2002, IMAGE 2001 Global Soil Data Task (Global Soil Data Task, 2000) Terrain CRU elevation data set Elevation 10’ x 10’ Temperature, diurnal temperature range, precipitation, cloud cover, vapour pressure: Transition data 2001 - 2100 also with modified vapour pressure 10 and 30 year time slices 1990, 2020, 2050, 2080 (year is the last year of the time slice) Annual atmospheric CO2 concentration (ppmv) per SRES scenario (A1f, A2, B1, B2) Mean annual NOx and NHy deposition per 10’ x 10’ grid-cell in 5 year time steps for 1970 - 2100 and per SRES scenario (A1fi, A2, B1, B2) Soil type, texture, physical, chemical parameters per soil unit and layer
ATEAM final report Section 5 and 6 (2001-2004) 21 Land cover Land use Land use scenarios Land use history Socioeconomic scenarios (http://www.cru.uea.ac.uk/~timm/grid/table.html) European HYDRO1k data (USGS EROS Data Center /Distributed Active Archive Center, http://edcdaac.usgs.gov/gtopo30/hydro/europe.html) CORINE except Sweden, Croatia and Yugoslavia, Russia 250m x 250m (Corine 1997, BFS 2002) PELCOM, pan-European land-cover 1100m x 1100m (Mücher et al. 1999) IMAGE2.2 SRES scenario implementation data (RIVM, 2001) Forest species maps (Köble & Seufert, 2001) aggregated to Plant Functional Types (PFTs) Land-use change scenarios created by UCL (see this report work package WP 4 and Ewert et al. 2004 in press) Historic land cover changes (Ramankutty & Foley, 1999) HYDE data set (Goldewijk, 2001) Forest area 1960-1994 (FAO, 2000; http://dataservice.eea.eu.int/dataservice/) FAO forest resource assessment 1948-2000 (Efidas, 2000; http://www.efi.fi/efidas/) Indicators for adaptive capacity: national data downscaled to NUTS2 18 Region via urban area) (Klein et al., in prep.; http://www.ciesin.org/) Elevation, slope, aspect, topographic index, flow direction, flow accumulation, watersheds, streams Urban areas, arable land, permanent crops, pastures, heterogeneous agricultural areas 2 , forests, shrub and/or herbaceous vegetation associations, open spaces with little or no vegetation, inland wetlands, coastal wetlands, inland waters C3 grass, fodder, cereals other than rice or maize, rice, maize, pulses, roots & tubers, oil crops temperate needleaved evergreen, temperate broadleaved evergreen, temperate broadleaved summergreen, boreal needleleaved evergreen, boreal needleleaved summergreen, boreal broadleaved summergreen Change in arable land, grassland, forests, urban area, biofuels, surplus land, others projected for the time slices 2020, 2050, 2080 and the 4 SRES scenarios (A1f, A2, B1, B2) Change in arable land, grassland, forests, urban area, others in 10 years time steps from 1900 onwards Inequality, telephone mainlines, number of physicians, enrolment (number of people attending higher education), GDP and population density per administrative region (NUTs level 2) for 2000, 2020, 2050, 2080 per SRES scenario (A1f, A2, B1, B2) 6.2.2 Modelling of ecosystem service supply (WP2) We modelled potential impacts using the input scenarios of global change and a range of state-of-theart ecosystem models that represent the sensitivity of the human-environment system. The ATEAM modelling framework consists of models for agricultural systems, for forest systems, for biogeochemistry and vegetation cover, for fire driven dynamics, for water catchments, for biodiversity, and for mountain ecosystems (Table 6). We have adapted the structure and content of these ecosystem models to optimise their use for vulnerability assessment at the regional scale for Europe. Where needed and possible, models were enhanced, recalibrated and modified, based on the outcomes of the testing of their performance. In the following we will report on potential impacts that were estimated using these models for European sectors. 18 NUTS2 = Nomenclature des Units Territoriales Statistiques 2: regions or provinces within a country. There are around 500 NUTS2 units, as apposed to only 17 EU countries.
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