Agriculture and Environment

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Agriculture and environment

Contents 1. Agriculture and INPUT USE ...... 5 Farming intensity ...... 5 Livestock density ...... 6 Energy use in agriculture ...... 7 Energy use in the food industry ...... 8 Production of renewable energy ...... 9 Fertilizer consumption ...... 10 Pesticides consumption ...... 11 2. Agriculture and SOIL ...... 12 Soil quality ...... 12 Average Soil Organic Carbon (SOC) stock in agricultural soils ...... 13 Soil erosion by water ...... 14 Soil erosion by wind ...... 17 Soil sealing ...... 18 Potential threats to soil biodiversity in croplands and grasslands ...... 19 3. Agriculture and CLIMATE/AIR...... 20 Emissions from agriculture ...... 20 Air pollutant emissions ...... 20

NH3 emissions per total agricultural area (UAA) ...... 26

NH3 emissions per amount of protein produced (emission intensity)...... 26 GHG emissions ...... 28

Extreme weather events ...... 32 Risk of forest fires ...... 33 4. Agriculture and WATER ...... 34 Water abstraction ...... 34 Water exploitation and water stress ...... 35 Water quality ...... 36 Nitrogen water pollution ...... 36 Nitrates in fresh and ground water ...... 38 Phosphorus water pollution ...... 41 5. Agriculture and BIODIVERSITY ...... 43 Number of agriculture-related habitats protected under the Habitats Directive ...... 43 Conservation status of protected agriculture-related habitats ...... 44 Farmland birds index ...... 45 Grassland butterfly index...... 46 Protected forest ...... 47 6. Agriculture and LANDSCAPE ...... 48 Presence of linear elements ...... 48 Farmland Heterogeneity Index ...... 49 Useful links ...... 50 CAP Context Indicators: report and methodological fiches ...... 50 Eurostat: Environment statistics ...... 52 The Joint Research Centre: European Soil Data Centre (ESDAC) ...... 53 The European Environment Agency ...... 54

Figures Figure 1: Share of agricultural area managed by low, medium and high intensity farms, 2015 ...... 5 Figure 2: Share of UAA used for extensive grazing, 2013 ...... 6 Figure 3: Energy use in agriculture and forestry and share of total energy consumption, 2014 ...... 7 Figure 4: Energy use per ha of UAA and forest area ...... 7 Figure 5: Energy use in the food and tobacco industry and share of total energy consumption ...... 8 Figure 6: Production of renewable energy from agriculture and forestry ...... 9 Figure 7: Cereal yields and nitrogen fertilizer consumption, EU-15 ...... 10 Figure 8: Sales of pesticides (in tonnes) in the EU, 2015 ...... 11 Figure 9: Sales of pesticides (in tonnes) by EU groups, 2011-2015 ...... 11 Figure 10: Soil organic carbon stock, 2013 ...... 13 Figure 11: Soil loss by water erosion ...... 15 Figure 12: Soil erosion in agricultural lands, 2012 ...... 16 Figure 13: Soil loss due to wind erosion ...... 17 Figure 14: Agricultural land converted to artificial land, 2006 and 2012 ...... 18 Figure 15: Threats to soil biodiversity in cropland ...... 19 Figure 16: Threats to soil biodiversity in grassland ...... 19 Figure 17: Relative contributions of manure management, manure spreading+organic fertilizer, and mineral fertilizer to total NH3 emissions, 2016...... 20 Figure 18: NH3 emission distance in 2020 to 2020 and 2030 targets ...... 23 Figure 19: NH3 emissions for 2005-2020 ...... 24 Figure 20: Relative NH3 emission intensity indicators, 2010...... 25 Figure 21: NH3 emission density, 2010...... 27 Figure 22: Evolution of GHG emissions and share of agriculture in total emissions in the EU ...... 28 Figure 23: Evolution of GHG emissions from agriculture in the EU-28 ...... 28 Figure 24: Greenhouse gas emission intensity of beef production...... 31 Figure 25: Global frequency of extreme weather events ...... 32 Figure 26: Current and projected state and trend of fire danger ...... 33 Figure 27: Water abstraction in agriculture ...... 34 Figure 28: Irrigation requirements ...... 35 Figure 29: Water exploitation index ...... 35 Figure 30: Estimation of nitrogen water pollution from agriculture and other sources ...... 36 Figure 31: Trend of gross nutrient balance - surplus of nitrogen in the EU, 2003-2013 ...... 37 Figure 32: Gross nitrogen balance - surplus of nitrogen by Member State, 2003-2014* (4 year averages) ...... 37 Figure 33: Concentration of nitrates in surface waters (rivers), 2012 ...... 38 Figure 34: Trends of concentration of nitrates in rivers and groundwater ...... 39 Figure 35: Nitrogen diffuse emission ...... 39 3

Figure 36: Nitrates directive EU-27 - annual average nitrate concentration (2008-2011) ...... 40 Figure 37: Nitrates directive EU-27 - maximum nitrate concentration, 2008-2011 ...... 40 Figure 38: Estimation of phosphorous water pollution from agriculture and other sources ...... 41 Figure 39: Trend of gross nutrient balance - surplus of phosphorus in the EU, 2003-2014 (4-year averages) ...... 42 Figure 40: Gross Phosphorus balance - surplus of phosphorus in the Member States, 2003-2014 ...... 42 Figure 41: Number of agriculture-related habitats protected under the Habitats Directive, 2007-2012 ...... 43 Figure 42: Conservation status of habitats depending on agriculture ...... 44 Figure 43: Change in the farmland bird index, 2000-2013 and average annual rate of change 1990-2000 and 2000-2013 ...... 45 Figure 44: European grassland butterfly indicator ...... 46 Figure 45: Absolute and percentage change of protected FOWL area, 2000-2015 ...... 47 Figure 46: Average number of linear elements per transect with agriculture as main land cover, 2015 ...... 48 Figure 47: Farmland heterogeneity index...... 49

Tables Table 1: Soil organic matter in arable land, 2012 ...... 12 Table 2: Soil erosion by water, 2012 ...... 14 Table 3: National emission reduction commitments (%) for NH3 ...... 21 Table 4: Greenhouse gas emissions in the EU agricultural sector ...... 29 Table 5: Greenhouse gas emissions in EU agriculture by Member State and emission source ...... 30 Table 6: Water quality, 2010-2012 ...... 38

This document does not necessarily represent the official views of the European Commission Contact: DG Agriculture and Rural Development, Unit Farm Economics Tel: +32-2-29 91111 / E-mail: [email protected] © European Union, 2018 - Reproduction authorised provided the source is acknowledged

1. Agriculture and INPUT USE

Farming intensity Figure 1: Share of agricultural area managed by low, medium and high intensity farms, 2015  Farm input intensity is used as a "proxy" of % agricultural intensification, meaning an increase in 100 agricultural input use (fertilisers, pesticides and feedstuff) per ha of land. Farms are classified into 90 intensity categories according to an estimate of input 80 volume per hectare of UAA. Then, each farm is classified according to its average level of input use 70 per ha (high intensity if > 300 constant EUR/ha, low intensity if <130 constant EUR/ha, otherwise 60 medium intensity). 50

 In 2013, the agricultural area in the European Union 40 managed by farms with low input intensity represented 41.3% of the total Utilised Agricultural 30 Area (UAA) while the area with farms using 20 medium and high levels of inputs was 29.2% and 29.5% respectively. 10

 The most significant share of UAA managed by low 0

ES SE

DK RO intensity farms was observed in Bulgaria (60.8%), HU

Spain (63.8%), Lithuania (66.7%), Latvia (66.9%), UAA with low input intensity per ha UAA with medium input intensity per ha UAA with high input intensity per ha Romania (80.1%) and Portugal (83.6%). These countries registered input expenditures around or below EUR 150 per ha in constant input prices, with the exception of Spain where the level of input expenditure was EUR 242 per ha in constant input prices. See also Common Context Indicator 33: Farming intensity  In Belgium and in the Netherlands the average level of input expenditure was very high, ranging from EUR 1200 to EUR 1800 per ha in constant input prices.

Livestock density

 Areas of extensive grazing are classified here as Figure 2: Share of UAA used for extensive grazing, 2013 areas where the stocking density of grazing livestock does not exceed 1 livestock unit per ha of forage area.  In 2013, 29.4% of the UAA in the EU-28 was devoted to extensive grazing, with a total amount of 51.3 million hectares, of which around 70% was located in the EU-15.  At regional level, there was a concentration of extensive grazing in Scotland, Wales and Highlands and Islands, northern Scandinavia, the Baltic countries, in the mountainous regions in Slovakia, Austria, and Italy, in the West part of Ireland and in the whole of Portugal and large parts of Spain and Romania.

See also Common Context Indicator 33: Farming intensity

Energy use in agriculture Figure 4: Energy use per ha of UAA and forest area

kg of oil  In 2014, the direct energy use in agriculture and forestry in the EU-28 equivalent accounted for 23.608 kilotons of oil equivalent (ktoe), which amounts to 1600 2.2% of total final energy consumption. Nearly 75% of this was used in the EU-15 countries (17.537 ktoe or 2% of their total energy 1400 consumption). 1200  France, Poland and the Netherlands have the highest direct use of energy 1000 in agriculture and forestry, between 3 383 and 4 237 kilotonnes. The 800

Netherlands and Poland show the highest share of agriculture/forestry in 600 the total final energy consumption, at 7.2% and 5.6% respectively (no data are available for Germany). 400 200 0

Figure 3: Energy use in agriculture and forestry and share of total

ES SE

DK RO

energy consumption, 2014 HU

EU-28 EU-15

kg of oil equivalent per ha of (UAA + forestry) EU-N13

 Energy use per ha of agricultural or forest land is particularly high in the Netherlands (1 527 kg/ha), probably due to the intensive use of greenhouses for the production of vegetables.  See also Common Context Indicator 44: Energy use in agriculture, forestry and the food industry

Energy use in the food industry

 The direct use of energy in the food and tobacco industry in 2014 accounted for 28 191 kilotonnes for the EU-28, with the EU-15 taking a share of 83.8% of this value.  The EU-28 Member States with the highest direct use of energy in food production are Germany, France, the United Kingdom and Italy, with values ranging from 2 621 to 5 001 ktoe.  As a share of direct use of energy in food of the total final consumption of energy, the countries with the highest share were the Netherlands and Denmark, with 4.2%. The next highest countries were Ireland and Belgium, both with 3.9%. The equivalent EU-28 value is 2.7%, with little difference between the EU-15 and EU-N13.

Figure 5: Energy use in the food and tobacco industry and share of total energy consumption

KTOE % 5000 10

4500 9

4000 8

3500 7

3000 6

2500 5

2000 4

1500 3

1000 2

500 1

0 0

ES SE

BG MT

HU RO EU-15

Food and tobacco Share of food and tobacco EU-28 EU-N13

Production of renewable energy

 In 2013 European production of renewable energy from agriculture and forestry continued to increase by 4% compared to 2012, mainly coming from the agricultural sector (+14.2), rather than from forestry (+1.9%).  In 2013 the contribution from forestry amounted to 88 million tonnes of oil equivalent (or 45.9% of the total), the one from agriculture to 20.9 million tonnes of oil equivalent (or 10.9% of the total).  The share of forestry in the total production of renewable energy showed a decreasing trend, the share of agriculture has grown at an average annual rate of 4% since 2008.  The EU-15 production accounted for 87.4% of the total in the agricultural sector of the EU-28, whilst the production in the EU-N13 represented 12.6%. In the forestry sector the production of renewable energy in the EU-15 and in the EU-N13 represented 76% and 24% respectively, of the total production in the EU-28. Figure 6: Production of renewable energy from agriculture and forestry

Production of renewable energy from agriculture and forestry and as a share of the total production of renewable See also Common energy, 2008-2013 Context Indicator 43: Production of renewable energy from agriculture and forestry

Fertilizer consumption

Figure 7: Cereal yields and nitrogen fertilizer consumption, EU-15  While overall consumption of nitrogen fertiliser has decreased over the last decades, 12 000 70 cereal yields have shown an increasing trend, indicating a more efficient use of fertiliser. 65 11 000

10 000 55

9 000 50

fertilizer, fertilizer, tonnes 000 1 8 000

Cereal yields, Cerealyields, kg/ha 100 N 40 7 000 35

6 000 30 1986 1988 1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012 2014

Nitrogen fertilizer consumption (left axis) Cereal yield (right axis)

Pesticides consumption Figure 8: Sales of pesticides (in tonnes) in the EU, 2015  Consumption of pesticides is measured by the sales of pesticides in tonnes. The term "pesticides" refers to the plant protection product and covers the following categories: fungicides and bactericides, herbicides, haulm destructors and moss killers, insecticides and acaricides, molluscicides, plant growth regulators and other plant protection products.  The total quantity of pesticides sold significantly increased (with variations among +16% to +40%) between 2011 and 2015 in Bulgaria, the Czech Republic, Estonia, Latvia, Malta, Slovakia, and Finland.

 The pesticide sales decreased (from - 15% also to -50%) from 2011 to 2015 in Denmark, Source: Eurostat, DG AGRI calculations Ireland, Luxembourg, and Portugal.

 More in general, the EU-15 countries showed a Figure 9: Sales of pesticides (in tonnes) by EU groups, 2011-2015 more stable path in 2011-2015, with a higher level of consumption compared to the EU-N13 which had an increasing trend in the same period, but with lower volumes.

Source: Eurostat, DG AGRI calculations.

2. Agriculture and SOIL1 Table 1: Soil organic matter in arable land, 2012

Soil quality

 Soil organic matter is a key component of soil as it influences its structure, aggregate stability, nutrient availability, water retention and resilience.  In 2012, the total organic carbon of arable land in the EU-27 (data for Croatia are not available) amounted to 14 017 megatons, with a mean value per kg ranging from 14.4 in Spain to 84.9 g per kg in Ireland.  Among the categories of land use, grassland registered the largest organic carbon content in arable land of the EU-28, while permanent crops had the smallest value.  See also Common Context Indicator 41: Soil organic matter in arable land

1 For information on land cover and agricultural land use, see the dedicated chapter "Land cover and land use" 12

Average Soil Organic Carbon (SOC) stock in agricultural soils Figure 10: Soil organic carbon stock, 2013

 This map depicts the SOC stock in the topsoil layer (0-30 cm), derived from the aggregation at NUT3 level of a high resolution map (1 km2)1. A higher soil organic carbon stock is beneficial for climate change (carbon sequestration) and for soil fertility.  The values were generated by a large-scale modelling with a state-of-the-art process based model1. The model was ran in agricultural areas (arable, orchard and grassland) of the EU and validated with ground-based measurements.  In general, Mediterranean countries registered lower SOC stock compared to northern countries.  Comparing the different land uses, the average SOC stock was 64, 55 and 150 t/ha of C in arable, orchard and grassland, respectively.

See also: 1 http://esdac.jrc.ec.europa.eu/content/pan-european-soc-stock-agricultural-soils

Soil erosion by water Table 2: Soil erosion by water, 2012

 Soil erosion by water is one of the most widespread forms of soil degradation in Europe.  In 2012, the estimated average rate of soil loss by water erosion in the EU-28 amounted to 2.4 t/ha/year and was higher in the EU-15 (2.7 t/ha/year) than in the EU-N13 (1.7 t/ha/year).  The erosion has decreased between 2000 and 2012 mainly due to the application of GAEC and agricultural practices (reduced tillage, plant residues, cover crops, etc.) Data show a moderate decrease at EU-28 level (-0.29 t/ha/year) with a slight difference between the EU-15 (-0.31) and the EU-N13 (-0.23 t/ha/year).

Figure 11: Soil loss by water erosion  Around 6.6% of the EU-28 total agricultural area was estimated to suffer from moderate to severe erosion (>11 t/ha/year) in 2012. This share is higher in the EU-15 (7.7%) than in the EU-N13 (4.3%). Cultivated land (arable and permanent cropland) is more affected (7.5%) than permanent grasslands and pasture (4.2%).  The share of agricultural land estimated to suffer from moderate to severe erosion is the highest in SI (42.2%), IT (32.6%) and AT (20.9%) while it is very low 5<0.1% in FI, DK, NL, EE, LT and LV

See also Common Context Indicator 42: Soil erosion by water

 This map is a further elaboration of the soil Figure 12: Soil erosion in agricultural lands, 2012 erosion by water depicted above.

 This map classifies the NUTS3 per % of severe erosion in agricultural lands. As severe erosion, it is considered the rate of higher than 11 tonnes per ha annually.

 The great majority of NUTS3 (43.3%) have less than 0.5% of their agricultural land under severe erosion. Most of those areas are in North and Central Europe. In almost ¾ of the NUTS3 areas the share of agricultural land estimated to suffer from severe erosion (>11 t/ha/year) in less than 5%.

 In Italy, Slovenia and Austria are the majority of the NUTS3 regions having high share of agricultural land under severe erosion. In conclusion, around 153 NUTS3 have more than 20% of their agricultural lands under severe erosion.

Soil erosion by wind Figure 13: Soil loss due to wind erosion

 This map is the first quantitative assessment of soil loss by wind in European Union. The map focused in EU arable lands.  The main factors that are influencing wind erosion (included in the GIS-RWEQ model) are: Climate (wind speed and direction, rainfall amount and evapotranspiration), soil characteristics (texture, calcium carbonate, organic matter, soil moisture and water –retention capacity) and Land use (land use type, vegetation cover and landscape roughness).  The average annual soil loss predicted in the EU arable land totalled 0.53 t ha-1 yr-1. The 2nd quaintly is equal to 0.3 and the 4th quantile equal to 1.9 t ha-1 yr-1.  The highest mean wind erosion rates are in Denmark, Netherlands and Bulgaria. In northern Europe, the locations most susceptible to wind erosion were found along the North Sea coasts of Denmark, UK, the Netherlands, Germany, France and Belgium. In the Mediterranean area, higher erosion rates occurred in certain zones (Aragón, Castilla y Leon, Apulia, Tuscany, Sardinia, the Provence in France, Central and Eastern Macedonia and Thrace).  Wind erosion rates were at their peak between December and February (57% of total)

Soil sealing Figure 14: Agricultural land converted to artificial land, 2006 and 2012 Agricultural land (in 2006) converted to artificial land (in 2012)

 This map depicts the conversion of agricultural lands into artificial areas derived from the aggregation at NUT3 level of the CORINE Land Cover (CLC) Change 2006-2012 map.  The values were generated by summing, at NUT3 level, the areas that changed their cover from 2006 to 2012, passing from one of the CLC agricultural classes (i.e. CLC class 2) to one of the artificial classes (i.e. CLC class 1)1. The sums were then recalculated as percentage of the NUT3 region in which modified areas were located, that means where agricultural soil sealing took place.  In general, common soil sealing trends are not present. Indeed, the areas subjected to higher soil sealing rate are distributed across the European Union.

For more information on CLC classes refer to: http://land.copernicus.eu/pan-european/corine-land-cover

Potential threats to soil biodiversity in croplands and grasslands  These maps depict the potential threats to soil biodiversity, derived from the aggregation at NUT3 level of a high resolution map (500m)1. A healthy soil biodiversity may ensure the provision of several ecosystem services (e.g. food production and nutrient cycling regulation).  The values are averaged from risk maps covering potential threats to three categories: soil microorganisms, fauna, and biological functions. The risk accounts for 13 potential threats to soil organisms that were analysed and ranked by scientific experts.  In general, northern countries showed higher potential risks compared to southern ones, with the exception of Spain.

Figure 15: Threats to soil biodiversity in cropland Figure 16: Threats to soil biodiversity in grassland

3. Agriculture and CLIMATE/AIR Figure 17: Relative contributions3 of manure management, manure spreading+organic Emissions from agriculture 4 fertilizer, and mineral fertilizer to total NH3 emissions , 2016. Air pollutant emissions

 Ammonia (NH3) affects human health through the formation of ammonium-nitrate particulate matter and ecosystems through nitrogen deposition.

 In 2016, agricultural NH3 emissions in the European Union amounted to 3 849 ktonnes. This accounts for about 92 % of total EU-28 2 NH3 emissions for that year (EEA, 2018) .

 High shares of agriculture in total NH3 emissions are found in Ireland (99 %), Poland (97 %), Germany (95 %) and (France (94%), while lower shares are shown by Portugal (79%), the United Kingdom (87%) and Sweden (88 %).  In the EU-28 the manure management contributes by 45 % to the total emissions, manure spreading and grazing 30% and

inorganic fertilizer emissions by 17 %. with a somewhat larger share of manure management emissions in the EU-N13 than EU-15.

2 Preliminary 2018 submission of EU member states under NECD – 3 data received 23 May 2018. Data pertain to 2016 and backwards in Manure management NFR category 3B; mineral fertilizer 3DA1, manure spreading+organic fertilizer,3DA2, 3DA3,3F and 3I. time. Data are subject to revisions. Courtesy European Environment 4 2016 emissions of Malta- extrapolated from 2015 in the 2017 submission. 2016 emissions of Greece are taken equal to the latest Agency. submission with emissions values pertaining to 2014. 20

Table 3: National emission reduction 2020 2030  The current (2001) National Emission commitments (%) for NH3 Ceiling Directive (NECD) will be in place Lithuania 10 10 2020 2030 until 31 December 2019, and replaced by the 2016 NECD5 in 2020. The 2016 NECD Luxembourg 1 22 Austria 1 12 sets the countries’ emission targets for Malta 4 24 2020-2029 and beyond 2030 relative to the Belgium 2 13 reference year 2005 (Table 1)., Reduction Netherlands 13 21 targets range between 1 and 24 % for Bulgaria 3 12 individual member states, with an average Poland 1 17 for the EU-28 of 6 %. After 2030, the Croatia 1 25 aspirational NH3 emission reductions are Portugal 7 15 on average 19 %, ranging between 1-32 %. Cyprus 10 20 Romania 13 25 Czech  These targets pertain to economy wide NH3 Republic 7 22 Slovakia 15 30 emissions, however they are of direct relevance for agriculture due to the high Denmark 24 24 Slovenia 1 15 contribution of agriculture to the overall NH3 emissions. The NECD improves, but Estonia 1 1 Spain 3 16 does not solve all environmental issues related to NH3 and other air pollutant Finland 20 20 Sweden 15 17 emissions. Since the residence time of NH3 and the particulate matter formed from it is France 4 13 United in the order of hours to days, it is important Kingdom 8 16 to know where the emissions are taking Germany 5 29 place to understand the exposure of EU28 6 19 population and vegetation to air pollution. Greece 7 10

Hungary 10 32

National emission reduction commitments [%] for NH3 Ireland 1 5 relative to the base year 2005 under the 2016 National Emissions Ceiling Directive 2016/2284/EU. Italy 5 16

5 NECD, 2016/2284/EU) 21

In the following we provide 3 indicators:  This dataset provides for each country reported NH3 emissions in all sectors, including agriculture. The difference of the extrapolation of 1) Distance MS NH3 emissions to the targets set in the 2016 NECD. the linear trend between 2005-2016 to 2020 and the 2020 NECD 2 NH3 emission density per unit of agricultural land and targets is the distance to target (in percent). For 2030 we did not 3) per unit of crop and meat production (scaled to protein content) - extrapolate emissions trends beyond 2020, demonstrating the absolute and relative to the EU-28 average. additional effort required in the period 2021 to 2030.

Distance-to-target indicator  Distances in 2020 range between 15 % positive (target reached) and -20 % meaning emissions to be further reduced. 10 countries have  Here we focus on the revised 2016 NECD, as it will influence air a substantial distance to 2020 target, Among these are Austria, pollution policy in the next decade. Detailed country time-series of Denmark, France, Spain and Germany. In contrast, for instance sectorial emissions (including NH3) are reported for 1990-2016 Belgium, the Netherlands and Poland will likely reach their 2020 including the base year 2005. targets.. Almost all countries will have to achieve further emission reductions beyond 2020 to meet the 2030 targets. EU-28 wide NH3 emissions are about reached for 2020 and -19% away from the target for 2030.

Figure 18: NH3 emission distance in 2020 to 2020 and 2030 targets

6 NH3 emissions distance to 2020 and 2030 targets [%] in the 2016 NEC Directives (operational in 2020) . Emissions in 2020 are estimated from linear extrapolation of timeseries between 2005-2016. Comparison of the 2020 emissions to 2030 target shows the additional effort required in this decade..

6 Emissions in 2020 are estimated from linear extrapolation of time series between 2005-2016 to account for likely trends (see Figure 19). Comparison of the estimated 2020 emissions to the 2030 target shows the additional effort required between 2020-2030.

Figure 19: NH3 emissions for 2005-2020

MS NH3 emissions for 2005-2020: Total (all sector- green), agricultural emissions (red), and linear fit through the total emissions (dashed black), 2020 NECD target (blue symbol) for France, Denmark, Germany and Finland.

Agricultural land area and production weighted NH3 emissions Figure 20: Relative NH3 emission intensity indicators, 2010. "Efficiency" indicators.

 A second set of emission ”intensity” indicators relates agricultural NH3 emissions to utilized agricultural area and agricultural production of meat and crops (scaled to the their protein content) and provides insights on the feasibility of further emission reductions, when compared to the ‘best-practice’ performance in the EU MS and at NUTS2.

 Disaggregation of reported NH3 manure and mineral fertilizer emissions (EEA)7 for 2010 to NUTS2 regions used animal statistics (Livestock Units) and cereal crop area (ha), taken from the EUROSTAT Farm Structure Survey for 2010 (FSS2010).

Member state relative NH3 emission intensity [%] (red) per protein produced

(compared to EU average) and relative NH3 emission density relative to EU average (blue). Positive numbers indicate larger than average emission intensities and densities.

7 Based on 2016 submission under the old NECD and pertaining to 2010 inventory data. 25

NH3 emissions per total agricultural area (UAA) NH3 emissions per amount of protein produced (emission intensity)

 The sum of total manure and mineral fertilizer related NH3 emissions  Meat (beef, pork, poultry) and milk production for 2010, as well as in a MS or NUTS2 region per total agricultural area (UUA) represent cereal and oil crop production were used to estimate total protein agricultural NH3 emission area density [kg/ha]. This indicator is production for NUTS2 regions based on data from EUROSTAT as somewhat hypothetically assuming that all agricultural NH3 emissions included in the CAPRI model. To avoid double counting, cereal and can be attributed to agricultural land- whereas in reality a large fraction oil crop production used in fodder were discounted. In countries with of NH3 emissions occur from manure handling at the farm. Values large imports of cereals for fodder (e.g. the Netherlands) we assumed range from <10 to ca. 130 kg NH3/ha/yr. We note that inconsistencies that all production was fed to animals. may exist in the national animal and fertilizer statistics underlying the  The MS ammonia emissions relative to the amount of protein produced reported NH emission inventories, and the FSS2010 farm statistics. 3 in cereal crops, beef, pork, and poultry, shown in Figure 20 (red bars),  The relative emission area density compares the MS and NUTS2 indicate that the UK, Poland, Finland Denmark, Belgium are relatively intensity to the EU average of 20.9 kg NH3 emission/ha/yr, with a efficient in terms of agricultural production of proteins. On the other range of ca. -90 to more than 100 % (Figure 20, blue bars). Positive hand less efficient are: Spain, Italy, Greece, the Netherlands, and percentages denote relatively large emissions compared to the EU Ireland. average, typically related to high livestock density decoupled from  Figure 21b and d show substantial fluctuations of the absolute and crop production- e.g in Italy, the Netherlands, Germany, and Belgium. relative NH emissions per unit of protein production. NUTS2 region Lower NH emissions per agricultural area are found in the UK, Spain, 3 3 in Southern Europe and Ireland stand out as particularly inefficient and Poland. with regard to losses of NH3 per protein produced. We note that  Figure 21 a and c show that emission densities disaggregated on uncertainties and inconsistencies in reported emissions, animals, area NUTS2 are high in the Benelux, parts of Germany, Central Europe, and production statistics may have contributed to these variations, Bretagne, some regions of Spain. which should be interpreted as indicative and with caution.  We note that if the agricultural area (and the associated emissions) is relatively small compared to the total area in the MS or NUTS2 region, the air quality impacts may be limited. On the other hand, several neighbouring high emission intensity regions will amplify the impacts. Further important factors are meteorological conditions and emissions of other air pollutants that form particulate matter in the atmosphere.

Figure 21: NH3 emission density, 2010.

a c

Figure 21– NH3 emission density kg NH3 per ha Utilized Agricultural Area (a), relative to EU average

(b), and NH3 emission density intensity g/kg b d protein produced (c), and relative to the EU average (d).

GHG emissions  In 20158 agricultural emissions of GHG9 in the EU-28 amounted to Figure 22: Evolution of GHG emissions and share of agriculture in total 430 million tonnes of CO2 equivalents. This accounts for 10.2% of emissions in the EU total EU-28 emissions for that year.  In the EU-28, long term agricultural GHG emissions over the period 1990-2015 decreased by 21% from 542 Mio tons of CO2eq in 1990 to 430 Mio tons of CO2eq in 2015. Decreases can be observed for almost all member states, except for Spain (+1%). Decreases are generally higher in the Eastern Europe, ranging from 32% to 68% - with the exception of Slovenia (-9%), while in the EU-15 decreases are more modest, exceeding 20% only for the Netherlands and Greece.  Comparing the last two decades, from 1990 to 2000 and from 2000 to 2010, the decreasing trend shows a general slowdown. The average annual rate of decrease passed from -1.67% in the first period to -0.87% in the second. From 2010 onwards the trend starts increasing at a slow pace, with an average annual rate of 0.46 (See Figure 23). Figure 23: Evolution of GHG emissions from agriculture in the EU-28  Methane emissions, more or less constantly over time, represent around 55% of total agricultural emissions, N2O emissions around 600 000 43%. Non-energy CO2 emissions, with around 2% of the agricultural emissions, are less important in the sector. 45% of total emissions Average annual rate of decline (1990-2015): -0.93% are methane emissions from enteric fermentation (the share is 550 000 slightly decreasing over time), while manure management (methane and N2O) contributes with 15%, and soils by 40%. Other emission

sources are negligible. 500 000

equivalent

450 000 8 ktCO EEA, 2017. Annual European Union greenhouse gas inventory 1990 – 2015 and inventory report 2016. Submission to the UNFCCC Secretariat. Technical report No 15/2016. European Environment Agency, Copenhagen, Denmark. Available at: https://www.eea.europa.eu//publications/european-union-greenhouse-gas-inventory- 400 000 2017

9 Agricultural emissions refer to IPCC sector 3. Carbon stock changes in agricultural soils

1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 are under the UNFCCC reporting system included under the LULUCF sector (IPCC sector 4). Further emissions are e.g. related to energy use and industrial fertilizer production included in IPCC sectors 1 and sector 2. Life cycle assessment of emissions includes all emissions related to production. 28

Table 4: Greenhouse gas emissions in the EU agricultural sector

Greenhouse gas emissions in the EU agricultural sector from 1990 – 20230* by member states and gases (in 1000 tons of CO2eq). Agricultural emissions refer to IPCC sector 3, and do not include carbon stock changes. Enteric Man Soils Change N2O CH4 CO2 Total GHG emissions ferm Man (Total GHGs) 2015 2015 2015 2015 2015 2015 1990 2005 2015 2025* 2030* 2005-2030* Denmark 35% 25% 40% 45% 53% 2% 12673 10818 10392 10975 11146 3.0% Germany 37% 15% 45% 47% 48% 5% 79398 63254 66690 61535 61181 -3.3% Greece 48% 12% 40% 42% 58% 0% 10140 8959 7846 8757 9062 1.2% Spain 41% 26% 34% 36% 62% 1% 34160 36594 34533 35617 36630 0.1% France 45% 9% 46% 46% 51% 3% 82980 78031 77808 74410 73697 -5.6% Greenhouse gas emissions in the EU agricultural sector by Ireland 58% 10% 32% 32% 66% 2% 19514 18754 18744 20059 20714 10.5% member states and gases, 1990-2015 Italy 47% 18% 36% 36% 63% 1% 35078 32083 29435 29228 28111 -12.4% Netherlands 45% 24% 30% 34% 66% 0% 25016 18353 18787 18063 18028 -1.8% Source: EEA, 2017. Annual European Union greenhouse gas Austria 58% 12% 30% 35% 64% 2% 8189 7104 7178 6913 6888 -3.0% inventory 1990 – 2015 and inventory report 2016. Submission to Portugal 52% 13% 34% 34% 65% 1% 7144 6760 6725 7513 7555 11.7% the UNFCCC Secretariat. Technical report No 15/2016. Sweden 44% 9% 48% 51% 47% 2% 7630 7040 6864 6406 6434 -8.6% European Environment Agency, Copenhagen, Denmark. Finland 33% 12% 56% 57% 40% 3% 7525 6461 6491 6062 6017 -6.9% Available at: UK 52% 17% 30% 34% 63% 3% 49999 44401 41922 39285 38465 -13.4% https://www.eea.europa.eu//publications/european-union- Cyprus 48% 25% 26% 40% 60% 0% 476 541 465 609 659 21.9% greenhouse-gas-inventory-2017. Czech Rep. 35% 19% 45% 51% 44% 4% 15898 7803 8158 7501 7452 -4.5% Estonia 40% 10% 49% 53% 46% 1% 2665 1117 1343 1358 1397 25.1% Hungary 31% 17% 52% 56% 41% 3% 9878 6067 6671 5949 5847 -3.6% * For 2025 and 2030 we have used relative emission projections Lithuania 35% 10% 54% 58% 41% 1% 8935 4185 4617 4482 4480 7.1% carried out with the CAPRI model by JRC.D4, and applied the Latvia 32% 7% 61% 63% 36% 1% 5612 2340 2672 2627 2677 14.4% relative changes to inventory numbers (three years average Malta 47% 24% 30% 46% 54% 0% 77 75 66 61 62 -17.4% 2007-2009). Poland 42% 12% 45% 50% 48% 2% 47156 29512 29546 32961 33166 12.4% Slovenia 53% 20% 27% 31% 68% 1% 1933 1780 1754 1791 1841 3.4% Slovakia 38% 13% 49% 52% 45% 3% 6068 2610 2565 2209 2174 -16.7% Croatia 41% 21% 37% 41% 57% 2% 4398 3321 2875 2899 2962 -10.8% Bulgaria 25% 10% 65% 71% 29% 1% 12462 5170 6236 6275 6306 22.0% Romania 57% 12% 27% 31% 69% 1% 34222 20506 18612 18386 18223 -11.1% Belgium 46% 19% 35% 40% 58% 2% 12288 10319 10089 9537 8971 -13.1% Luxemburg 58% 14% 28% 32% 67% 1% 774 684 736 643 610 -10.8%

EU28 44% 15% 40% 42% 55% 2% 542287 434640 429820 422110 420757 -3.2%

 Based on agro-economic modelling with CAPRI, from 2005-2030 emissions are projected to decrease by 3.2% in the EU-28, not accounting for specific mitigation technologies. The development, however, is quite diverse among the Member States, and ranges from an expected 25% emission increase in Estonia to an expected decrease of 17% in Malta. N2O emissions and emissions from soils are increasing according to the projections, while methane emissions from livestock will decrease. The shifts from beef to pork and poultry meat production, as well as significant milk yield increases per head both reduce emissions from livestock production, while the growth of emissions from soils is related to crop production increases, particularly in the Member States that joined the EU after 2004.

 In order to assess the regional potential for improvements, a measure on emission efficiency (emissions per product) is more meaningful than total emissions, which vary in first line with total production.

Table 5: Greenhouse gas emissions in EU agriculture by Member State and emission source

Total N2O emissions Total CH4 emissions Total CO2 emissions Source: EEA, 2017. Annual European Union 1990 2005 2015 2025* 2030 1990 2005 2015 2025* 2030 1990 2005 2015 2025* 2030 greenhouse gas inventory 1990 – 2015 and inventory report 2016. Submission to the Denmark 6469 4912 4676 5221 5313 5586 5685 5539 5545 5623 619 222 177 209 211 UNFCCC Secretariat. Technical report No Germany 33477 28876 31325 29672 29770 42737 32053 32294 29715 29346 3184 2325 3071 2147 2066 15/2016. European Environment Agency, Greece 5165 3962 3278 3627 3737 4915 4965 4545 5104 5299 60 32 23 26 26 Copenhagen, Denmark. Spain 11675 11894 12584 12129 12187 21986 24283 21445 23014 23986 499 417 505 474 457 Available at 38766 36570 36055 34949 34216 42448 39661 39750 37880 37986 1765 1800 2003 1581 1496 France http://www.eea.europa.eu/publications/european- 6352 6263 6042 6589 6765 12763 12196 12281 13077 13546 400 295 421 393 403 Ireland union-greenhouse-gas-inventory-2017 Italy 13289 12473 10522 11444 11082 21323 19089 18475 17383 16662 466 521 438 401 367 Netherlands 10158 7006 6308 6130 6071 14675 11272 12411 11886 11916 183 75 69 47 42 For the year 2025 we have used relative emission Austria 2685 2391 2496 2499 2513 5409 4610 4570 4292 4251 94 103 112 123 124 projections carried out with the CAPRI model by JRC.D4, and applied the relative changes to Portugal 2604 2242 2303 2598 2644 4506 4488 4371 4858 4852 34 30 52 57 59 inventory numbers (three years average 2007- Sweden 3930 3481 3482 3351 3372 3523 3442 3258 2950 2957 178 117 124 105 105 2009). Finland 4082 3632 3727 3569 3534 2796 2538 2582 2201 2192 647 291 182 292 291 UK 17337 15069 14220 14294 14132 31319 27721 26431 23452 22861 1343 1612 1271 1538 1472 Cyprus 207 222 187 224 229 268 318 278 384 429 2 1 0 0 0 Czech Rep. 7152 3873 4183 4229 4140 7450 3791 3623 3048 3097 1296 139 352 223 215 Estonia 1258 528 713 760 784 1394 575 620 584 599 13 15 11 14 15 Hungary 4498 3297 3768 3698 3744 4995 2627 2715 2104 1949 385 142 187 147 153 Lithuania 3898 2132 2663 2608 2622 4980 2014 1915 1826 1805 56 38 39 48 52 Latvia 2836 1489 1686 1788 1856 2411 848 959 831 811 365 3 26 9 10 Malta 34 33 31 27 27 43 42 35 34 35 0 0 0 0 0 Poland 20714 14533 14747 18447 18505 23848 13687 14062 13533 13689 2593 1292 736 981 972 Slovenia 603 575 546 504 506 1277 1180 1189 1271 1319 53 25 20 16 16 Slovakia 2877 1238 1345 1219 1227 3132 1342 1144 942 899 60 29 76 47 48 Croatia 1762 1475 1175 1249 1275 2586 1760 1630 1580 1619 50 85 69 69 68 Bulgaria 6771 3079 4417 4643 4726 5645 2073 1788 1589 1536 45 18 31 43 44 Romania 10248 6243 5737 6929 7089 23791 14125 12780 11242 10908 183 139 94 215 227 Belgium 5399 4326 4059 4201 3861 6710 5827 5854 5151 4930 179 166 176 185 180 Luxemburg 287 232 237 231 213 486 448 494 407 393 1 4 6 4 4

EU28 224535 182045 182512 186827 186141 302999 242660 237036 225886 225493 14753 9934 10272 9396 9123

 According to a study carried out in 2010 by the JRC10 average EU- 27 emissions amount to 22 kg of CO2eq per kg of beef produced Figure 24: Greenhouse gas emission intensity of beef production (for 2004), the agricultural product with the highest contribution to GHG emissions. That study included not only emissions accounted under the agricultural sector in the inventories, but also emissions from land use and land use change related to feed (including carbon sequestration on grassland), as well as emissions from energy use on the farm, feed transport, and fertilizer production. Consideration of all life-cycle emissions is important to estimate the impact on climate, given that emissions can ‘leak’ from the EU to other world regions or other economic sectors might counteract emission savings within the agricultural sector.  Methane accounts for 40% of emissions from beef production, N2O for 26%, while 34% are CO2-emissions, from which 18% are from land use and land use change, and 16% from energy use, fertilizer production and feed transport.  Figure 24 presents the regional emission intensities of beef related to the EU average (with 100 % the EU average). Generally, regions with more efficient production systems show lower per- product emissions (i.e. the Netherlands or Italy). However, there is also a trade-off since very efficient production systems frequently rely on imported protein-rich feed. This can create high emissions from land use change (i.e. in Belgium), while slightly less efficient grass-based systems can compensate disadvantages by removals via carbon sequestration (i.e. Austria, Ireland, United Kingdom). Medium or low efficient production systems with high dependence on imported feed show the highest emission intensities (i.e. Spain, Portugal, Finland, Latvia, Bulgaria).

10 Leip, A., Weiss, F., Wassenaar, T., Perez, I., Fellmann, T., Loudjani, P., Tubiello, F., Grandgirard, D., Monni, M., Biala, K., (2010): Evaluation of the livestock sector’s contribution to the EU greenhouse gas emissions (GGELS), Final report of the administrative arrangements AGRI-2008-0245 and AGRI-2009-0296. 31

Extreme weather events Figure 25: Global frequency of extreme weather events

The global frequency of extreme weather events (storms, floods, droughts and forest fires) has increased from just above 200 in 1980 to almost 700 in 2016.

Risk of forest fires Figure 26: Current and projected state and trend of fire danger  Fire risk depends on many factors, including climatic conditions, vegetation, forest management practices and other socio-economic factors.  The burnt area in the Mediterranean region increased from 1980 to 2000; it has decreased thereafter.  In a warmer climate, more severe fire weather and, as a consequence, an expansion of the fire-prone area and longer fire seasons are projected across Europe. The impact of fire events is particularly strong in southern Europe.

See https://www.eea.europa.eu/data-and-maps/indicators/forest-fire- danger-2/assessment

4. Agriculture and WATER

Water abstraction Figure 27: Water abstraction in agriculture

 Agriculture accounts for more than half (51.4% in 2014) of the freshwater use in Europe, more than all other sectors combined.  Contrary to other sectors, water use in agriculture is seasonal, occurring mainly during the growing season between April and September.  Irrigation is the primary water use of agriculture.  In the EU-28, the total water used for irrigation by agricultural holdings was around 40 billion m3 in 2010. Countries in the EU-15 account for 98% of this volume while the EU-N13 represents only 2%.  This difference is particularly important between southern and northern European countries. Spain, Italy, Greece, Portugal and France together account for more than 96% of the total water used for irrigation in the European Union, whilst all the other Member States show an average share of 0.2% each.

See also Common Context Indicator 39: Water abstraction in agriculture and the dedicated page on the use of freshwater resources of the European Environmental Agency.

Water exploitation and water stress Figure 28: Irrigation requirements

 Most of irrigation occurs in areas affected by water stress, and where water scarcity might increase under future climate change.  The Water Exploitation Index plus (WEI+) compares water use against renewable water resources. An interactive map is available from the European Environment Agency (http://www.eea.europa.eu/data-and- maps/indicators/use-of-freshwater-resources- 2/assessment-2)  Around 40 % of the inhabitants in the Mediterranean region lived under water stress conditions in the summer of 2014.

 Groundwater resources and rivers continue to be affected by overexploitation in many parts Source: DG JRC D2. Estimations refer to 2010. of Europe, especially in the western and Figure 29: Water exploitation index eastern European basins.  A positive development is that water abstraction decreased by around 7 % between 2002 and 2014.

Water Exploitation Index (WEI, De Roo et al. 2017). It is defined as the ratio of water abstraction over average freshwater resources, indicates areas where water stress occurs (high values of the index). 35

Water quality Figure 30: Estimation of nitrogen water pollution from agriculture and other sources

 Pollution by nitrates and phosphates shows the impact of agriculture on water quality. It gives an indication of the potential risk to the environment due to these two inputs surplus.

Nitrogen water pollution

 Agriculture contributes a significant amount of nutrients into freshwater resources, impairing their ecological status and leading to eutrophication, especially in lakes and coastal waters11.  It is estimated that European rivers export about 4 million tons of nitrogen per year to coastal waters, more than half of which is originated by agriculture (estimated 55% in 2005 in the work in reference).

A point source is a single identifiable source of air, water, thermal, noise or light pollution. A point source has negligible extent, distinguishing it from other pollution source geometries. The sources are called point sources because in mathematical modeling, they can be approximated as a mathematical point to simplify analysis. https://en.wikipedia.org/wiki/Point_source_pollution

DG JRC D2. Estimation of nitrogen water pollution coming from agriculture compared to other sources. Spatial unit: EU river basins. Reference year 2005. The analysis is based on modelling. For more information, see: Bouraoui et al. 2011 http://publications.jrc.ec.europa.eu/repository/bitstream/JRC62873/lbna24726enc.pdf;

Grizzetti et al. 2012 http://onlinelibrary.wiley.com/doi/10.1111/j.1365-2486.2011.02576.x/epdf.

11 Important point sources are urban wastewater and waste of certain food processing industries. The other contributions originate from atmospheric deposition, scattered dwellings and biological fixation. 36

 Contribution of agriculture to N water pollution can Figure 31: Trend of gross nutrient balance - surplus of nitrogen in the EU, 2003-2013 be very important in quantity and share in certain regions/ water basins with high livestock density such as the UK, Ireland, North Western Europe (North France, Belgium, the Netherlands), North Spain, Catalonia and North Italy.

 Between 2010 and 2013 the average nitrogen surplus for the EU-28 was 51 kg nitrogen per ha (kg N/ha). It was much lower in the EU-N13 (27 kg N/ha, 2009-2012 average) than in the EU-15 (59 kg N/ha). The nitrogen surplus decreased by 15.6%.

 The nitrogen surplus decreased by 7.4% between 2003 and 2013 in the EU-28, from an estimated average of 55 kg N/ha in the period "2003-2006" to 51 kg N/ha in the period "2010-2013". This is Figure 32: Gross nitrogen balance - surplus of nitrogen by Member State, 2003-2014* mainly caused by the EU-15, where the nitrogen (4 year averages) surplus steadily decreased by 12% during this period. In the EU-N13 it increased by 1.6% between 2003 and 2012.

*For EU-28, EU-15, EU-N13, DE, IE, SE no data for 2014; for EU-N13 no data for 2013; for EU-28 no data for 2003.

Nitrates in fresh and ground water Table 6: Water quality, 2010-2012  Agriculture is the greatest contributor to elevated nitrate levels in freshwater in the EU  In 2012, the average nitrate concentration in rivers in all Member States for which data are available was below the 11.3 mg-N/L limit

(equivalent to 50 mg-NO3/L) enshrined in the Nitrates and Drinking Water Directives.  The Member States with the lowest concentrations are Finland (0.3 mg-N/L), Sweden (0.5 mg-N/L) and Latvia (0.6 mg-N/L), which together with Slovenia (1.1 mg-N/L), Romania (1.2 mg-N/L), Ireland (1.3 mg-N/L) and Italy (1.3 mg-N/L) are the only ones that show levels of concentration close to the natural one (about 1 mg-N/L). Figure 33: Concentration of nitrates in surface waters (rivers), 2012

mg-N/L 6.0

5.0

4.0

3.0

2.0

1.0

0.0 BE BG DK DE EE IE FR IT CY LV LT LU NL AT PL RO SI SK FI SE UK

 In 2012, average groundwater nitrate concentrations at national level were still well below the 50 mg-NO3/L limit of the Nitrates and Drinking Water Directives. Only 4 Member States, Finland (0.9 mg- NO3/L), Lithuania (1 mg- NO3/L), Estonia (7.1 mg-NO3/L) and the United Kingdom (5.1 mg-NO3/L), show average concentrations in line

with the natural level (below 10 mg-NO3/L).

Figure 34: Trends of concentration of nitrates in rivers and Figure 35: Nitrogen diffuse emission groundwater

(3-year moving average, base 1992-1994 = 100), 1992-2012

 The 3-year average for 2010-2012 for nitrates in rivers shows a reduction of 18% compared to that registered for 1992-1994, with an annual average decrease of 1.1%.  The data for 2012 are in line with the trend registered for the last 20 years. Nitrate concentrations in groundwater have remained relatively Spatial unit: catchments (~180 km2) stable across the countries with available data. Reference year: 2005. The analysis is based on modelling (Bouraoui et al. 2011; Grizzetti et See also Common Context Indicator 40: Water quality al. 2012) Source JRC, 2017

Figure 36: Nitrates directive EU-27 - annual average nitrate Figure 37: Nitrates directive EU-27 - maximum nitrate concentration, concentration (2008-2011) 2008-2011

Source European Commission, 2013 Source European Commission, 2013 Report of the European Commission on the implementation of Council Directive Report of the European Commission on the implementation of Council Directive 91/676/EEC (Nitrates Directive) for the period 2008-2011. SWD(2013) 405 final 91/676/EEC (Nitrates Directive) for the period 2008-2011. SWD(2013) 405 final

Phosphorus water pollution Figure 38: Estimation of phosphorous water pollution from agriculture and other sources

 It is estimated that European rivers export about 0.2 million ton of phosphorus per year to coastal waters, originated by both by point sources and agriculture (the share of agriculture in the total load is estimated to be around 25% in 2005).

Draft version. DG JRC D2. Estimation of phosphorus water pollution coming from agriculture compared to other sources. Spatial unit: EU river basins. Reference year 2005. The analysis is based on modelling. For more information, see: Bouraoui et al. 2011 http://publications.jrc.ec.europa.eu/repository/bitstream/JRC62873/lbna24726enc.pdf;

 Contribution of agriculture to P water pollution Figure 39: Trend of gross nutrient balance - surplus of phosphorus in the EU, 2003-2014 can be very important in quantity and share in (4-year averages) certain regions / water basins such as Northern Italy, Ireland or Scotland, while limited in other areas like southern Spain and Portugal, Germany or Scandinavia. Indeed, While the EU-N13 actually had a deficit of -1 kg P/ha (average 2009-2012), the surplus amounted to 2 kg P/ha in the EU-15.  The average phosphorus surplus decreased by 50% between 2004 and 2013 in the EU-28, being steady at 2 kg P/ha from 2008 onwards. While the EU-15 experienced on average a similar reduction (-59%), in the EU-N13 this decrease went from 0 to -1 on average in the same period All Member States experienced a reduction of the phosphorus surplus between 2003 and 2014, except Cyprus, which increased Figure 40: Gross Phosphorus balance - surplus of phosphorus in the Member States, the value and Austria and Latvia which kept the 2003-2014 same value all over the period. *For EU-28, EU-15, EU-N13, DE, IE, SE no data for 2014; for EU-N13 no data for 2013; for EU-28 no data for 2003.

5. Agriculture and BIODIVERSITY

Number of agriculture-related habitats protected under the Habitats Directive Figure 41: Number of agriculture-related habitats protected under the Habitats Directive, 2007-2012  Under the Habitats Directive 92/43/EEC, 63 habitat types are protected, which depend on the continuation of agricultural activities.  Such habitats are threatened by intensification and abandonment of agricultural practices.  Identified habitats mostly depend on mowing and grazing and are grassland habitats.  Article 17 of the Habitats Directive requires Member States to report every six years about the progress made with the implementation of the Habitats Directive.  The map shows the occurrence of protected agriculture-related habitats in a 10 km x 10 km grid (MS data, reporting period 2007-2012).  Large parts of the EU host up to 6 different habitats in each 100 km2 cell (yellow colour range); in particular, mountain areas and the Boreal zone are hotspots of grassland habitat richness. For more information, see: https://ec.europa.eu/jrc/en/publication/indicators-biodiversity-agroecosystems-insights-article-17- habitat-directive-and-iucn-red-list https://link.springer.com/article/10.1007/s10531-011-9989-z

Conservation status of protected agriculture-related habitats Figure 42: Conservation status of habitats depending on agriculture

 Habitats conservation status is classified as either ‘Favourable’ (FV), ‘Unfavourable-inadequate’ (U1) and ‘Unfavourable-bad’ (U2). ’Favourable Conservation Status’ is defined in the Habitats Directive as a situation where the habitat or species is prospering (in both quality and extent) and this trend is expected to continue in the future. ‘Unfavourable-Inadequate’ describes a situation where a change in management or policy is required to return the habitat/species to favourable status but there is no danger of extinction in the foreseeable future; ‘Unfavourable-Bad’ is for habitats or species in serious danger of becoming extinct, at least regionally.  The map shows the average conservation status (based on structure/function parameter) of selected habitats in each 10 km x 10 km cell, where FV=1, U1=2, U2 =3  Results show that the Atlantic zone is the one mostly characterised by habitats in Unfavourable-bad conservation status, while the Mediterranean zone has a higher percentage of habitats in Favourable conservation status.  For species and habitats protected by EU law, the last Natura 2000 report (2007/2012) shows that only 11% of habitats of Community interest associated with agricultural ecosystems are in favorable conservation status12 and 39 % have deteriorated in comparison to the previous reporting period.

12 MTR Review of the EU Biodiversity Strategy (COM (2015) 478 final), p 9 http://eur- lex.europa.eu/legal-content/EN/TXT/PDF/?uri=CELEX:52015DC0478&from=EN. Staff Working Document (SWD (2015) 187 final) page 19 http://eur- lex.europa.eu/resource.html?uri=cellar:5254559f-68eb-11e5-9317- 01aa75ed71a1.0001.02/DOC_2&format=PDF

44 Source: JRC elaboration, 2017

Farmland birds index

Figure 43: Change in the farmland bird index, 2000-2013 and average annual rate of change 1990-2000 and 2000-2013

 At EU level, a decline in the farmland bird population was registered from 1990 to 2010, continuing also between 2010 and 2013 at a more stable pace, with a reduction of 2.9 points over the last four years.

 Since 2000, the downward trend seems to have slowed down compared to the previous period:-15.6 points from 2000 to 2013 compared to -22.8 points from 1990 to 2000. The annual average change remained the same (-1.63) between 1990-2000 and 2000-2013.

See also Common Context Indicator 35: Farmland Birds Index (FBI)

Grassland butterfly index

Figure 44: European grassland butterfly indicator

 Grassland butterflies have shown a significant rate of decline of 30 % between 1990 and 2013 in Europe (21 European countries). In the last 10 years, the rate of loss is slowing down.  See also http://www.eea.europa.eu/data-and-maps/indicators/abundance-and-distribution-of-selected-species/abundance-and-distribution-of-selected-4

Protected forest

 In 2015, the area of forest and other wooded land (FOWL) protected for biodiversity, landscape and specific natural elements accounted for around 24.5 million ha and represented around 17% of the total area of FOWL.

 13% of FOWL were protected for biodiversity (MCPFE class 1). 85% Figure 45: Absolute and percentage change of protected FOWL area, of this protected area was located in the EU-15. Within this objective, 2000-2015 the share of the category "conservation through active management" (MCPFE Class 1.3) was visibly the highest (6.8% of the total FOWL) while the category "no active conservation" (MCPFE Class 1.1) covered only 2.2% of the total FOWL area in the EU-28.

 FOWL protected for landscape and specific natural elements (MCPFE class 2) amounted to 5.9 million ha (4.2% of the total FOWL). The share of FOWL under this objective was higher in the EU-N13 (10.9%) than in the EU-15 (2.2%).

 Between 2000 and 2015, the area of protected FOWL in the EU-28 decreased by 4 million ha (18%). This change is mainly due to a decrease of the MCPFE class 1.3 (-31.6%) and of MCPFE class 2 (- 82.6%).

See also Common Context Indicator 38: Protected Forest

Figure 46: Average number of linear elements per transect with 6. Agriculture and LANDSCAPE agriculture as main land cover, 2015

Presence of linear elements  The LUCAS survey includes information on the presence of linear elements, recorded by a surveyor who walks a transect of 250m from the point to the east direction, recording all transitions of land cover and existing linear features.  The map shows the density of linear features in agricultural land per NUTS3 region (average number of linear elements per point), according to the following list:  Heath/Shrub, tall herb fringes < 3m  Single bushes, single tree  Avenue trees  Conifer hedges < 3 m  Bush/tree hedges/coppices, visibly managed (e.g. pollarded) < 3 m  Bush/tree hedges, not managed, with single trees, or shrubland deriving from abandonment < 3 m  Grove/Woodland margins (if no hedgerow) < 3 m  Dry stone walls  Ditches, channels < 3 m  Rivers, streams < 3 m  Ponds, wetlands < 3 m  Rock outcrops with some natural vegetation

 Only points having agriculture (cropland or grassland) as main land cover have been considered.  The map shows in yellow and orange the regions with a low density the linear elements listed above. In some cases this is related to the presence of large Alpine pastures.

Source: JRC, 2017 48

Farmland Heterogeneity Index

Figure 47: Farmland heterogeneity index  The Farmland Heterogeneity Index (FHI) was derived from segmentation and landscape metrics (edge density and image texture respectively) of IMAGE 2006 (549 tiles)13. The indicator assesses the FARMLAND HETEROGENEITY INDEX density of field edges or other structural elements that delineate agricultural patches (roads, buildings,etc.) and are detectable from

satellite-based spectral remote sensing data for agricultural lands. By showing the density of borders of homogeneous patches, the higher the number of borders, the smaller the objects.  The map legend describes the approximate patch size (lower and upper limits) per each of five percentile classes. Such measures are linked to

field size.  The map shows that there are areas in the EU where agricultural patches are larger than in surrounding regions, in particular it is interesting to note the marked difference in former West and East Germany.

13 Source: Weissteiner C.J., Garcia-Feced C., Paracchini M.L. (2016). A new view on EU agricultural landscapes: Quantifying patchiness to assess farmland heterogeneity. Ecological Indicators 61(2): 317-327 49

Useful links

CAP Context Indicators: report and methodological fiches https://ec.europa.eu/agriculture/cap-indicators/context_en

Eurostat: Agri-environmental indicators http://ec.europa.eu/eurostat/statistics-explained/index.php/Agri-environmental_indicators

Eurostat: Environment statistics http://ec.europa.eu/eurostat/statistics-explained/index.php/Environment

The Joint Research Centre: European Soil Data Centre (ESDAC) http://esdac.jrc.ec.europa.eu/

The European Environment Agency http://www.eea.europa.eu/