EN

(...PICT...)|COMMISSION OF THE EUROPEAN COMMUNITIES|

Brussels, 6.10.2008

SEC(2008) 2550

COMMISSION STAFF WORKING DOCUMENT Accompanying the

Green Paper on Territorial Cohesion Turning territorial diversity into strength {COM(2008) 616 final}

TABLE OF CONTENTS

1. Territorial cohesion in the Member States 3

1.1. Understanding the concept and its key components 3

1.2. Instruments of territorial cohesion policy 3

2. Territorial cohesion in the ERDF and Cohesion programmes of the period 2000-2006 5

3. Definition of territories 6

3.1. Settlement pattern 6

3.1.1. Agglomerations: Urban Audit Larger Urban Zones (LUZ) 6

3.1.2. Cities with at least 100 000 inhabitants 6

3.1.3. Cities with between 50 000 and 100 000 inhabitants 7

3.1.4. Small and medium-sized t o wns 7

3.2. The OECD Urban-Rural Classification 7

3.3. Metro regions based on functional urban areas 8

3.4. Island Regions 8

3.5. Mountain Regions 9

3.6. Sparsely Populated Regions 9

3.7. Border Regions 9

4. Definition of Indicators 9

4.1. Combined proximity to natural areas 9

5. List of Maps 10

6. Tables refered to in the Communication 24

COMMISSION STAFF WORKING DOCUMENT Accompanying the

Green Paper on Territorial Cohesion Turning territorial diversity into strength

1. Territorial cohesion in the Member States

In May 2007, a questionnaire was sent by the Commission to each of the Member States in order to see how the concept of territorial cohesion is understood and implemented across the EU A more detailed synthesis of the questionnaire will be published in the course of 2009. . Though Member States rarely have a policy labelled ‘territorial cohesion’, most of them have policies, or elements of policies, that they consider to be relevant in this regard. [1]

A more detailed synthesis of the questionnaire will be published in the course of 2009.

1.1. Understanding the concept and its key components

Policies related to ensuring territorial cohesion are centred on the sustainable use of specific territorial features which have the potential to reduce disparities and increase competitiveness. In a European context, the objective of territorial cohesion is recognised as complementing, or reinforcing, economic and social cohesion.

The main components of territorial cohesion policy are diverse but there are a few which are common. Respect for territorial diversity, development of territorial potential and territorial competitiveness were reflected – in one way or another – in all responses. There was also a strong consensus on the importance of accessibility (through infrastructure and to public services) as well as of sustainability. The particular features of different places were regarded as important by a third of the Member States. Territorial identity, a sense of belonging to certain places – as an intangible element of territorial potential – was also mentioned.

1.2. Instruments of territorial cohesion policy

Governance plays a major role in ensuring territorial cohesion. Some Member States, referring to the Territorial Agenda, even defined territorial cohesion as a permanent and cooperative process that encompasses the various stakeholders involved in territorial development (territorial governance). Territorial cooperation , and networking generally (the aim of European Territorial Cooperation more specifically), is regarded as a key instrument, though the European Grouping of Territorial Cooperation (EGTC) was relatively little mentioned.

The evolution of administrative structures (territorial organisation) is also related to the issue of governance: there are examples of structures crossing administrative and institutional boundaries so as to reflect functional realities better or to pool interests for shared development objectives. In Denmark, local government reform was linked to more coherent spatial planning (the establishment of a planning authority for both urban-rural areas) and in Finland, municipal reform and the reorganisation of services was aimed at reducing the cost of supply in peripheral areas and smaller municipalities.

Inter-municipal cooperation and coordination in France

As a response to territorial fragmentation, the State has encouraged the development of links between municipalities. There are two approaches to public-sector measures in France: one is to bring public utilities closer to the people who use them, drawing on the concepts of equity and efficiency associated with the production of services on a commensurate scale (inter-municipal management). The other is regional development, which brings into play the concepts of strategy, participation and competitiveness (inter-municipal projects).

The development of inter-municipal management was accelerated by the law of 12 July 1999 on strengthening and simplifying cooperation between municipalities. As at 1 January 2007, over 91% of municipalities, covering 85.5% of the French population, were part of a municipal grouping with tax-raising powers.

The inter-municipal approach transcends administrative borders to prepare development projects which are important from a geographical, economic and social point of view for a particular area.

Governance-based administrative reform: coordinated economic and spatial development – the Danish example

In the newly reformed regional development structure in Denmark, two parallel partnership processes are in operation: - regional councils preparing spatial development plans in cooperation with municipal councils, business representatives and other actors, covering all parts of the region - regional growth forums bringing together representatives of the business community, educational and research establishments and the social partners as well as local and regional authorities and serving as pivotal points for growth initiatives and implementation of the Government's globalisation strategy.

The two processes are linked in that each growth forum is intended to make recommendations to regional councils on support for business development projects as well as to the State on the use of Structural Funds, while each regional councils has to base its spatial development plan on the business development strategy which emerges from the forum.

Territorial aspects of sectoral policies and coordination between these were also mentioned as crucial elements of territorial cohesion. The most “territorialised” Member State policies concern transport, telecommunications, sustainable development and the environment. In some Member States, the cohesion policy programming exercise encourages more attention to be given to territorial aspects in sectoral policies and to better coordination between them. In some cases, sectoral and regional measures complement each other and are coordinated in growth pole programmes. Consequently, polycentric territorial development and the concept of growth poles were also mentioned as important elements of territorial cohesion policy.

Almost all Member States produced some kinds of national spatial plans (Belgium, Spain and the UK were exceptions because of the lack of the competence for these at national level) and these have strong EU influences (e.g. the ESDP and the adjusted time frame for Structural Funds programming). EU cohesion programming apart, spatial planning is considered by many of the respondents the strongest mechanism at national level for coordination between actors in different sectors and administrative levels (e.g. schema directeur – master plan – in the Brussels Capital Region). Limited attention, however, is given to the monitoring of territorial trends and the territorial impact of intervention (with little use of observatories or indicators).

2. Territorial cohesion in the ERDF and Cohesion programmes of the period 2000-2006

To improve understanding of the types of intervention financed in different types of region, a study was undertaken to analyse the commitments of ERDF and Cohesion Fund projects in NUTS3 regions Final Report - ERDF and CF Regional Expenditure. 2008 SWECO. The report (as well as the underlying data in a user-friendly and searchable form) can be found at: http://ec.europa.eu/regional_policy/sources/docgener/evaluation/evaluation_en.htm . . The preliminary results of this study are presented below. Since equivalent information is not available for EAGF and the ESF, the results cover only part, even if the largest part, of cohesion policy.[2]

Final Report - ERDF and CF Regional Expenditure. 2008 SWECO. The report (as well as the underlying data in a user-friendly and searchable form) can be found at: http://ec.europa.eu/regional_policy/sources/docgener/evaluation/evaluation_en.htm .

Aid intensity (support per person) in Objective 1 regions was broadly similar in the 2000-2006 period in metro, intermediate and rural regions close to a city. In remote rural regions, however, where GDP per head was on average well below the EU average, aid was almost double the intensity elsewhere. In the eligible NUTS3 regions outside Objective 1, aid intensity was around 50% higher in rural regions than in the others.

The ERDF and Cohesion Fund, therefore, assisted all types of region and with higher intensities in (remote) rural regions ones, helping them to face territorial challenges and improve cohesion.

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Aid intensity under Objective 1 was also high in both mountain and island regions.

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Similar financial data are not available for the current programming period. However, a review of national strategies indicates that few Member States have applied a comprehensive and integrated framework for ensuring that proper account is taken of the territorial context when determining how funds are spent.

3. Definition of territories

The main objective of cohesion policy is to reduce disparities between regions, defined at the NUTS2 level, the level at which eligibility for support (though not for the Cohesion Fund) and the distribution of financial resources is also defined, though operational programmes may be designed at a higher level (either NUTS1 or national).

One of the most interesting ideas arising from the concept of territorial cohesion is that there may be other territorial levels (intra-regional or supra-national) which might be relevant for policy intervention. The second section of the Green Paper is, therefore, based on a more finely defined unit than NUTS2. Indeed, the Green Paper uses different classifications of NUTS3 regions in the analysis of settlement patterns. This section briefly explains how they were created.

3.1. Settlement pattern

The settlement pattern is based on three types of area:

3.1.1. Agglomerations: Urban Audit Larger Urban Zones (LUZ)

All the larger urban zones were defined by Eurostat in cooperation with the National Statistical Institutes. The objective was to find the group of LAU2s (local administrative units at level 2, formerly known as NUTS5) that most closely corresponds to a commuting area or a functional urban area.

The principle is that if a LAU2 has at least 20% commuting to the central city it is included in the LUZ. In some cases, the central city consists of multiple LAU2s, depending on job densities. In dense conurbations, one LUZ may include multiple cities such as in the Ruhr area For more information see www.urbanaudit.org and ec.europa.eu/eurostat . . [3]

For more information see www.urbanaudit.org and ec.europa.eu/eurostat .

3.1.2. Cities with at least 100 000 inhabitants

The Urban Audit covers all EU cities with over 100 000 inhabitants. These cities were identified using a harmonised approach across the EU as a whole, taking account of where a city is part of a large LAU2 and where it is spread over multiple LAU2s. As a result, this approach corrects for the distortions created by only allowing for densities (as in the case of OECD) or the size of individual LAU2s (as the case of the UN).

3.1.3. Cities with between 50 000 and 100 000 inhabitants

The Urban Audit includes 121 towns and cities with a population of between 50 000 and 100 000, but it includes by no means all of them. As a result, data for these cities had to be complemented by another source of information: the urban morphological zones (UMZ), as defined by the European Environmental Agency, supplemented by the disaggregated population grid of the Joint Research centre (JRC) combined with a grid of registered population in Sweden and Finland For more information see "Remote rural regions: How proximity to a city influences the performance of rural regions", Regional Focus 1/2008 . . [4]

For more information see "Remote rural regions: How proximity to a city influences the performance of rural regions", Regional Focus 1/2008 .

These sources of information enable UMZs to be identified with populations of between 50 000 and 100 000 which are at present not captured by the urban audit. The UMZs The drawback of the UMZs is that there is very little data available for them because they do not correspond to any administrative area. have the same advantage as the urban audit cities in the sense that they enable both cities within a large LAU2 or a city spread over several LAU2 to be identified. [5]

The drawback of the UMZs is that there is very little data available for them because they do not correspond to any administrative area.

3.1.4. Small and medium-sized towns

Small and medium-sized towns with a population of between 5 000 and 50 000 were also identified using the UMZs and population grids as well as by drawing on the ESPON project, " The role of small and medium-sized towns" See www.espon.eu .[6]

See www.espon.eu

The benefit of this approach is that it provides a more nuanced and realistic indication of the share of a population living in an urban area. For example, the World Urbanization Prospects, Revision 2005 estimates that 73% of the EU27 population lives in an urban LAU2, while the approach adopted here produces an estimate of 57% of the EU population living in cities or agglomerations of over 50 000 and another 14% living in small and medium-sized towns.

3.2. The OECD Urban-Rural Classification

The OECD Urban-Rural classification has three steps:

The first step consists in classifying LAU2 as rural if their population density is below 150 inhabitants per square kilometer.

The second step consists in aggregating this lower level into NUTS3 regions and classifying the latter as predominantly urban, intermediate and predominantly rural using the percentage of population living in local rural units.

A NUTS3 region is classified as:

· Predominantly Urban (PU), if the share of population living in rural local units is below 15%;

· Intermediate (IN), if the share of population living in rural local units is between 15% and 50%;

· Predominantly Rural (PR), if the share of population living in rural local units is higher than 50%

In a third step the size of the urban centres in the region is considered:

· A region classified as predominantly rural by steps 1 and 2 becomes intermediate if it contains an urban centre of more than 200 000 inhabitants representing at least 25% of the regional population.

As in the 4 th Cohesion Report, predominantly rural regions are divided according to travel time to the nearest city with 50 000 or more inhabitants. If more than half the population lives over 45 minutes drive away, the region is classified as remote, otherwise it is classified as close to a city For more information see Regional Focus 1/2008 "Remote rural regions: How proximity to a city influences the performance of rural regions." http://ec.europa.eu/regional_policy/sources/docgener/studies/study_en.htm . [7]

For more information see Regional Focus 1/2008 "Remote rural regions: How proximity to a city influences the performance of rural regions." http://ec.europa.eu/regional_policy/sources/docgener/studies/study_en.htm

3.3. Metro regions based on functional urban areas

To analyse metropolitan regions using NUTS3 data, metro regions were created based on Urban Audit's Larger Urban Zones (see above). To ensure that the metro regions are sufficiently representative of the wide diversity of cities and their sizes within EU Member States, all of the LUZ with more than 250 000 inhabitants were included.

To identify which NUTS3 regions to include in a metro region, a threshold of 40% or more was used. In most cases NUTS3 regions had far higher shares of their population living inside the LUZ. In a few cases, a NUTS3 region which contain a LUZ of more than 250 000 inhabitants but had less than 40% of their population within a LUZ were added to ensure that all agglomeration over 250 000 inhabitants could be included. (see Map 3.2)

Since this is a functional and not physically or morphological definition, metro regions contain areas with a low population density. As a result, a small number of NUTS3 regions that are classified as predominantly rural by the OECD are included in the metro regions. For example, the metro region of Poznań includes the surrounding region Poznański, which the OECD approach classifies as rural.

More research is required to find an appropriate method to combine metropolitan regions with a classification of rural regions.

3.4. Island Regions

For analytical purposes, island regions are defined as NUTS3 regions composed completely of one or more islands, an island being defined according to the criteria used in the Eurostat publication " Portrait of the Islands " and in the DG REGIO study on island regions 2003-2004. These criteria are:

· Minimum surface area of 1 square km

· Minimum distance between the island and the mainland of 1 km

· Resident population of 50 or more

· No fixed link (bridge, tunnel or dyke) between the island and the mainland

· No Member State capital on the island

3.5. Mountain Regions

Mountain regions are defined as NUTS3 regions with at least 50% of their population living in topographically defined mountain areas, as identified in the DG REGIO study on mountain areas in Europe (2004) The classification is based on altitude, slope, local elevation range and temperature contrast. . [8]

The classification is based on altitude, slope, local elevation range and temperature contrast.

3.6. Sparsely Populated Regions

Sparsely populated areas are defined as NUTS3 regions with a population density of less than 12.5 inhabitants per square km See paragraph 30.b of the Guidelines on national regional aid for 2007-2013 (2006/C 54/08). .[9]

See paragraph 30.b of the Guidelines on national regional aid for 2007-2013 (2006/C 54/08).

3.7. Border Regions

Internal border regions are NUTS3 regions eligible for cross-border cooperation under Structural Funds 2007-2013.

External border regions are NUTS3 regions eligible for cross-border cooperation under the Instrument for Pre-accession Assistance (IPA) or the European Neighborhood and Partnership Instrument (ENPI).

4. Definition of Indicators

4.1. Combined proximity to natural areas

This indicator is based on the proximity to:

· Bodies of water

· Natura 2000 areas

· Natural areas as defined by CORINE land cover, which includes green urban, leisure and sport facilities, forests, semi-natural areas and wetlands. It does not include agricultural land.

The combined indicator is the average of the three proximity indicators. Each of the three indicators is calculated in a similar way:

(1) Each 1 km grid cell is assigned a value inversely related to the distance to all natural areas within a radius of 10 km. If the natural area is more than 10 km away the value is zero.

(2) Each 1 km grid cell is weighted according to its population to obtain a population weighted average per NUTS3 region.

Some grid cells contain both water and Natura 2000 areas or natural areas and Natura 2000 areas in which case they count double since they can be regarded as doubly attractive.

5. List of Maps

(1) Potential GDP (PPS), 2005

(2) Change in GDP per head in PPS at NUTS3 level, 1995-2004

(3) Urban-rural typology of NUTS3 regions

(4) Change in the share of GDP of metro regions, 1995-2004

(5) Authors of EPO patent applications, average 2004-2005

(6) Proximity to natural areas

(7) Emission of Particulate Matter 2.5, 2006

(8) Road efficiency between major urban agglomerations in km per hour

(9) Accessibility to passenger flights, 2006

(10) Freight transport, 2006

(11) Border disparities in GDP per head (PPS), 2004

(12) GDP per head (€) in EU and surrounding regions, 2004

(13) Population growth in the EU and surrounding regions, 2000-2005

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6. Tables refered to in the Communication

Table 1 : Main characteristics of urban, intermediate and rural regions and metro regions

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Table 2 : Access to hospitals, universities and passenger flights, proximity to natural areas and particulate matter 2.5µm emissions

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Table 3 : Main characteristics of border regions

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Table 4 : Main characteristics of mountain and island regions

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[1] A more detailed synthesis of the questionnaire will be published in the course of 2009.

[2] Final Report - ERDF and CF Regional Expenditure. 2008 SWECO. The report (as well as the underlying data in a user-friendly and searchable form) can be found at: http://ec.europa.eu/regional_policy/sources/docgener/evaluation/evaluation_en.htm .

[3] For more information see www.urbanaudit.org and ec.europa.eu/eurostat .

[4] For more information see "Remote rural regions: How proximity to a city influences the performance of rural regions", Regional Focus 1/2008 .

[5] The drawback of the UMZs is that there is very little data available for them because they do not correspond to any administrative area.

[6] See www.espon.eu

[7] For more information see Regional Focus 1/2008 "Remote rural regions: How proximity to a city influences the performance of rural regions." http://ec.europa.eu/regional_policy/sources/docgener/studies/study_en.htm

[8] The classification is based on altitude, slope, local elevation range and temperature contrast.

[9] See paragraph 30.b of the Guidelines on national regional aid for 2007-2013 (2006/C 54/08).