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Contents

• Highlights
• Goal 1 – end poverty in all its forms everywhere
• Goal 2 – end hunger, achieve food security and improved nutrition and promote sustainable agriculture
• Goal 4 – ensure inclusive and equitable quality education and promote lifelong learning opportunities for all
• Goal 5 – achieve gender equality and empower all women and girls
• Goal 8 – promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all
• Goal 9 – build resilient infrastructure, promote inclusive and sustainable industrialisation and foster innovation
• Goal 10 – reduce inequality within and among countries
• Goal 11 – make cities and human settlements inclusive, safe, resilient and sustainable
• Goal 13 – take urgent action to combat climate change and its impacts
• Goal 15 – protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss
• Goal 16 – promote peaceful and inclusive societies for sustainable development, provide access to justice for all, and build effective, accountable and inclusive institutions at all levels
• Source data for figures and maps
• Data sources
• Context
• Explore further

Data extracted in spring/summer 2024.

Planned article update: September 2025.

Highlights

Eurostat has a set of 102 indicators that are used to measure progress towards implementing the United Nations’ sustainable development goals – many of them are provided with a regional breakdown.

Regional data plays a crucial role in tracking progress towards the sustainable development goals. It highlights disparities, identifies challenges and guides targeted policies, aiming for more equitable and sustainable development across EU regions.

Source: Eurostat (edat_lfse_04)

Sustainable development aims at balancing social, economic and environmental aspects, through economic growth and social progress which are sustainable for younger and future generations. In September 2015, the United Nations General Assembly (UNGA) adopted the 2030 Agenda for Sustainable Development. The 2030 Agenda is a bold and transformative step designed to stimulate action through to 2030, shifting the world onto a sustainable and resilient path with the aim of leaving no one behind. At its core is a list of 17 sustainable development goals (SDGs) and 169 related targets that can be categorised under what are often referred to as the 5 P’s

• people – end poverty and hunger
• planet– protect the planet from degradation
• prosperity – ensure that all human beings can enjoy prosperous and fulfilling lives
• peace – foster peaceful, just and inclusive societies
• partnership – mobilise the means required to implement the Agenda.

A set of indicators to track progress towards the SDGs was agreed under the supervision of the UN Statistical Commission. A comprehensive review of this indicator framework was conducted in early 2020 and another review is planned for 2025. At the time of writing (August 2024), the SDG indicator framework consists of 231 indicators.

The European Union (EU) has fully committed to delivering on the 2030 Agenda. Indeed, sustainable development objectives are at the heart of European policymaking and are firmly anchored in the European treaties, the European Commission’s political priorities and its work programme. The 2030 Agenda provided the Commission with a new impetus for achieving sustainable development, as described in Delivering on the UN’s Sustainable Development Goals — A comprehensive approach. The EU measures progress towards implementing the SDGs through a set of 102 indicators that have been adapted to the EU context. Eurostat publishes annual monitoring reports on the results and EU countries prepare voluntary national reviews, in line with UN guidelines.

The initial focus of the 2030 Agenda was on supranational and country-based programmes. However, over time there have been efforts to localise SDGs, highlighting the links between local actions and global challenges. Sustainable development strategies have increasingly focused on involving regional, local and civil society stakeholders, while monitoring different territorial typologies has reinforced national efforts, supported regional development strategies and provided a broader picture of developments within countries.

This article looks at sustainable development indicators from a regional perspective. While the regional dataset is less complete than those that exist for the EU as a whole or for EU countries, a broad range of information is nevertheless available. Some of this information is presented below, providing a summary of SDG indicators that are available for EU regions. This information has been taken from the 2024 editions of Eurostat’s flagship publications, the Eurostat Regional Yearbook and Sustainable development in the European Union: monitoring report on progress towards the SDGs in an EU context.

Regional statistics, structured by SDG, offer a detailed view of the progress being made and challenges to be faced for a wide range of topics covering areas such as living conditions, health, education, equality, economic growth or climate action. Regional statistics make it possible to pinpoint specific areas that require targeted interventions, address disparities between regions and ensure that no one is left behind. Indeed, regional insights are increasingly viewed as being essential to foster sustainable, inclusive growth throughout the EU. The regional statistics presented below are grouped according to the individual SDGs; they provide a snapshot of the latest information available.

Goal 1 – end poverty in all its forms everywhere

SDG 1 calls for the eradication of poverty in all its manifestations. It envisions shared prosperity, a basic standard of living and social protection benefits for people everywhere, including the poorest and most vulnerable. People at risk of poverty or social exclusion

More about the data: at risk of poverty or social exclusion

The indicator for people at risk of poverty or social exclusion is based on measures of relative poverty, severe material and social deprivation, and quasi-joblessness. The number/share of people at risk of poverty or social exclusion combines these criteria to cover people who are in at least 1 of the following situations

• at risk of poverty – people with an equivalised disposable income (after social transfers) below the at-risk-of-poverty threshold, which is set at 60% of the national median equivalised disposable income
• facing severe material and social deprivation – people unable to afford at least 7 out of 13 deprivation items (6 related to the individual and 7 related to the household) that are considered desirable – or even necessary – to have an adequate quality of life
• living in a household with very low work intensity – where working-age adults (aged 18–64, excluding students aged 18–24 and those who are retired) worked for 20% or less of their combined potential working time during the previous 12 months.

In 2023, more than 1 in 5 (21.4%) of the EU’s population was at risk of poverty or social exclusion. Map 1 shows the regional distribution of people at risk of poverty or social exclusion across NUTS level 2 regions. In 2023, the regional distribution of this indicator was somewhat skewed, as close to 40% of all EU regions (101 out of the 241 for which data are available) recorded shares of people at risk of poverty or social exclusion that were higher than the EU average.

The highest risks of poverty or social exclusion were typically observed in southern, eastern and outermost regions of the EU. At the top end of the distribution, there were 19 NUTS level 2 regions that recorded shares of at least 35.0% in 2023; they are shown by the darkest shade of blue in Map 1. Guyane in France (49.5%; 2022 data) and Calabria in southern Italy (48.6%) had the highest regional shares of people at risk of poverty or social exclusion. They were followed by Sud-Est in Romania (45.3%), Campania in southern Italy (44.4%) and La Réunion in France (43.2%; 2022 data). These were the only regions in the EU where the share of people at risk of poverty or social exclusion was more than twice as high as the EU average (21.4%).

At the other end of the distribution, there were 5 NUTS level 2 regions where less than 10.0% of the population was at risk of poverty or social exclusion in 2023; they are shown in a yellow shade in Map 1. This group included

• 2 regions from northern Italy – Provincia Autonoma di Bolzano/Bozen (5.8%; the lowest regional share in the EU) and Emilia-Romagna (7.4%)
• 2 regions from Czechia(2022 data) – Střední Čechy (8.7%) which surrounds the capital region of Praha (8.9%)
• the Polish capital region of Warszawski stołeczny (8.9%).

Figure 1 identifies the NUTS level 2 regions that had the biggest changes in their respective shares of people at risk of poverty or social exclusion between 2022 and 2023. There was a modest reduction across the EU, as this share fell 0.2 percentage points from 21.6% to 21.4%. Among the 203 regions for which data are available (at the time of the data extraction, there was no information for 2023 for Czechia, France and Slovakia), the share of people at risk of poverty or social exclusion rose in 88 regions, remained unchanged in 8 regions and fell in 107 regions.

Most of the regions with the biggest falls in their respective shares of people at risk of poverty or social exclusion were in eastern and southern EU countries. Between 2022 and 2023, the biggest decrease in the share of people at risk of poverty or social exclusion was recorded in the southern Italian region of Molise, down 12.4 percentage points (from 37.2% to 24.8%). There were 6 other regions that reported falls of more than 5.0 points

• Sterea Elláda in Greece (down 9.0 points)
• the Romanian capital region of Bucureşti-Ilfov (down 6.9 points)
• Abruzzo (down 6.7 points), Liguria (down 6.6 points) and Provincia Autonoma di Bolzano/Bozen (down 5.9 points) in Italy
• the Irish region of Northern and Western (down 5.6 points).

Figure 1: People at risk of poverty or social exclusion, 2023
(by NUTS 2 regions)
Source: Eurostat (ilc_peps11n) and (ilc_peps01n)

People at risk of poverty

More about the data: at-risk-of-poverty rate

The at-risk-of-poverty rate identifies the proportion of the population who live in a household with an annual equivalised disposable income that is below 60% of the national median. While the threshold is the same for all EU countries in percentage terms (60%), it varies in monetary terms as national median incomes differ between countries.

The at-risk-of-poverty rate before social transfers measures a hypothetical situation where social transfers are absent; pensions, such as old-age and survivors’ (widows’ and widowers’) benefits, are counted as income (before social transfers) and not as social transfers. It is possible to assess the impact and redistributive effects of welfare policies by comparing at-risk-of-poverty rates before and after social transfers. Such transfers cover assistance that is given by central, state or local institutional units and include, among other types of transfers, unemployment benefits, sickness and invalidity benefits, housing allowances, social assistance and tax rebates.

Map 2 shows the at-risk-of-poverty rate for NUTS level 2 regions. In 2023, the regional distribution of this rate was relatively skewed: there were 89 regions (just over a third of the total) that recorded a rate equal to or above the EU average of 16.2%, while the remaining 152 regions had lower than average rates.

The French outermost region of Guyane recorded the highest at-risk-of-poverty rate among NUTS level 2 regions, at 42.0% (2022 data). In 2023, the highest rates were observed in the southern Italian regions of Calabria (40.6%), Sicilia (38.0%) and Campania (36.1%). By contrast, at the other end of the distribution the lowest risk was recorded in the Romanian capital region of Bucureşti-Ilfov (2.1%).

There was a considerable degree of inter-regional variation among at-risk-of-poverty rates across the regions of Belgium, Italy and Romania

• the rate in the Belgian capital Région de Bruxelles-Capitale/Brussels Hoofdstedelijk Gewest was 5.1 times as high as that recorded in Prov. Oost-Vlaanderen
• the rate in the southern Italian region of Calabria was 10.4 times as high as that recorded in northern region of Provincia Autonoma di Bolzano/Bozen
• the rate in Sud-Vest Oltenia was 14.9 times as high as that recorded in the Romanian capital region of Bucureşti-Ilfov.

Figure 2 shows the redistributive impact of social transfers and the extent to which they reduce the risk of monetary poverty, reflecting, among other influences, historical, political, economic and cultural factors. In 2023, the EU’s at-risk-of-poverty rate before social transfers was 24.8%. It was reduced by 8.6 percentage points to 16.2% after social transfers. Social transfers had a high impact on reducing the risk of poverty across many regions of Belgium, Denmark, Ireland, southern Italy and Poland.

Prior to social transfers, there were 4 NUTS level 2 regions that recorded considerably higher rates than in any other region of the EU, with upwards of 40.0% of their populations facing the risk of monetary poverty in 2023: the southern Italian regions of Calabria (51.9%), Campania (51.7%) and Sicilia (49.1%) and the Belgian capital Région de Bruxelles-Capitale/Brussels Hoofdstedelijk Gewest (47.1%). At the lower end of the distribution, there were 3 EU regions where less than 10.0% of the population faced the risk of monetary poverty: the Romanian capital region of Bucureşti-Ilfov (4.8%), the northern Italian region of Provincia Autonoma di Bolzano/Bozen (8.2%) and the Slovak capital region of Bratislavský kraj (9.0%).

Having taken account of the redistributive impact of social transfers, only Calabria continued to report that more than 40.0% of its population was at risk of monetary poverty. Sicilia and Campania were the only other regions in the EU where the risk of monetary poverty after social transfers was more than twice as high as the EU average (16.2%).

Figure 2: At-risk-of-poverty rate before and after social transfers, 2023
(%, by NUTS 2 regions)
Source: Eurostat (ilc_li10_r), (ilc_li41), (ilc_li10) and (ilc_li02)

Severe material and social deprivation

The severe material and social deprivation rate provides information on people experiencing an enforced lack of items that are necessary and desirable to lead an adequate life (individuals who can’t afford a certain good, service or social activity). It is 1 of 3 criteria used to identify people at risk of poverty or social exclusion and is defined as the share of people who are unable to afford at least 7 out of 13 items (6 related to the individual and 7 related to the household) that are considered desirable – or even necessary – to lead an adequate quality of life.

In 2023, there were 29.3 million people across the EU that were facing severe material and social deprivation; this was equivalent to 6.8% of the total population. The severe material and social deprivation rate had previously stood at 6.3% in 2021 but increased by 0.4 percentage points in 2022 and by a further 0.1 points in 2023; these recent rises may be linked, at least in part, to the cost-of-living crisis.

Figure 3 shows the regional distribution of severe material and social deprivation rates. Many of the highest rates were observed in the south-eastern part of the EU, while the lowest rates tended to be concentrated in Czechia, northern/central Italy, the Netherlands, Austria and Poland.

In 2023, the highest regional share of people experiencing severe material and social deprivation was recorded in Sud-Est in Romania (30.8%). There were 8 other regions in the EU where more than 20.0% of the population faced severe material and social deprivation

• Severen tsentralen (25.0%), Yuzhen tsentralen (23.9%) and Yugoiztochen (22.9%) in Bulgaria
• Sud-Vest Oltenia (24.8%) and Sud-Muntenia (23.7%) in Romania
• Észak-Magyarország (21.4%) in Hungary
• Calabria (20.7%) in Italy
• Dytiki Elláda (20.2%) in Greece.

At the other end of the distribution, every region in Czechia, Ireland, Croatia, Lithuania, the Netherlands, Poland, Slovenia, Finland and Sweden had a severe material and social deprivation rate in 2023 that was less than the EU average of 6.8%; this was also the case in Estonia, Cyprus, Latvia, Luxembourg and Malta.

Figure 3: Severe material and social deprivation rate, 2023
(%, by NUTS 2 regions)
Source: Eurostat (ilc_mdsd18) and (ilc_mdsd11)

As noted above, the EU’s severe material and social deprivation rate was 0.1 percentage points higher in 2023 than in 2022, with the rate increasing in 122 out of the 215 regions for which data are available. Figure 4 shows that by far the biggest increase was observed in the southern Italian region of Calabria (up 8.9 percentage points). The next highest increases were recorded in the Greek region of Dytiki Makedonia (up 4.8 points) and the Hungarian regions of Észak-Magyarország (up 4.5 points) and Dél-Dunántúl (up 4.1 points).

The largest fall for the severe material and social deprivation rate between 2022 and 2023 was reported in the Greek region of Sterea Elláda, where the rate fell from 15.4% to 9.1% (down 6.3 percentage points).

Figure 4: Severe material and social deprivation rate, 2023
(by NUTS 2 regions)
Source: Eurostat (ilc_mdsd18) and (ilc_mdsd11)

People living in a household with very low work intensity

More about the data: very low work intensity

Working-age adults with low work intensity are defined as people aged 18–64 (excluding students aged 18–24 and those who are retired) who worked for 20% or less of their combined potential working time during the previous 12 months. Households composed only of children, of students aged less than 25 and/or of people aged 65 or more are excluded from the calculation of this indicator.

In 2023, there were 26.5 million people (aged 0–64) in the EU living in a household with very low work intensity, this equated to 8.0% of this subpopulation. Figure 5 shows there was a relatively high degree of regional variation for the share of people living in households with very low work intensity. Across multi-regional EU countries, the difference between the highest and lowest shares – as measured in percentage point terms – peaked in France (at 20.3 points; 2022 data), while relatively large regional variations were also observed across Italy (18.9 points), Germany (18.2 points), Belgium (17.7 points) and Spain (15.5 points).

Figure 5: People living in a household with very low work intensity, 2023
(%, by NUTS 2 regions)
Source: Eurostat (ilc_lvhl21n) and (ilc_lvhl11n)

In 2023, the highest share of people living in a household with very low work intensity was recorded in the French outermost region of Guyane (28.1%; 2022 data), while there were 7 other regions across the EU with shares of more than 20.0% (see the first chart in Figure 6)

• the French outermost regions of La Réunion (23.1%; 2022 data) and Guadeloupe (22.6%; 2022 data)
• Bremen (21.8%) in Germany
• Prov. Hainaut (21.5%) in Belgium
• Campania (21.2%) and Calabria (20.9%) in southern Italy
• the autonomous Spanish region of Ciudad de Melilla (20.3%).

At the lower end of the distribution, there were 10 NUTS level 2 regions where the share of people living in a household with very low work intensity was no more than 2.5% in 2023. This group was concentrated in Austria (3 regions), Romania and Italy (both 2 regions), while it also included single regions from each of Slovakia, Hungary and Poland. The Romanian capital region of Bucureşti-Ilfov (0.7%) and the Austrian region of Salzburg (0.8%) had the lowest values; they were the only regions in the EU where the share of people living in a household with very low work intensity was less than 1.0%.

Across the EU, the share of people living in a household with very low work intensity fell 0.3 percentage points between 2022 and 2023 (see the second chart in Figure 6), with a fall reported in more than half (120 out of 215) of the NUTS level 2 regions for which data are available. The largest fall was recorded in the Spanish autonomous region of Ciudad de Ceuta (down 10.8 percentage points), followed, at some distance, by the Austrian regions of Vorarlberg (down 5.4 points) and Tirol (down 4.6 points) and the Dutch region of Groningen (also down 4.6 points).

Among the 92 NUTS level 2 regions that reported a rising share of people living in a household with very low work intensity between 2022 and 2023, the highest increases were recorded in the Romanian regions of Sud-Est (up 7.9 percentage points) and Vest (up 6.9 points) and the German regions of Sachsen-Anhalt (up 5.7 points) and Münster (up 4.3 points).

Figure 6: People living in a household with very low work intensity, 2023
(by NUTS 2 regions)
Source: Eurostat (ilc_lvhl21n) and (ilc_lvhl11n)

Goal 2 – end hunger, achieve food security and improved nutrition and promote sustainable agriculture

SDG 2 seeks to end hunger and malnutrition and ensure access to safe, nutritious and sufficient food. Achieving this goal will largely depend on promoting sustainable production systems and increasing investment in rural infrastructure and agricultural research and development.

Healthy diets and productive and sustainable agricultural systems are essential for a healthy food system that is good for people and the planet. Farms across the EU play a crucial role in supplying safe, affordable food. Farm managers are increasingly encouraged to manage the countryside for the public good. This shift towards sustainability – alongside a rise in health-conscious consumers – has spurred rapid growth in organic farming. The infographic below illustrates that organic farming (defined here as fully converted land and land under conversion) accounted for 8.3% of the EU’s utilised agricultural area in 2020.

Source: Eurostat (ef_lus_main)

Organic farming

Farming can have a considerable environmental impact. Among other issues, it can lead to an increase in greenhouse gas emissions and soil erosion, or result in habitat and biodiversity loss, deforestation or the contamination of waters. Recent years have seen an increasing number of EU farmers embracing organic farming methods.

More about the data: promoting EU agriculture through organic policy measures

A sustainable food system is at the heart of the European Green Deal. Under the Farm to Fork strategy, the European Commission has set a target to have ‘at least 25% of the EU’s agricultural land under organic farming and a significant increase in organic aquaculture by 2030’.

In March 2021, the European Commission introduced an Action plan to promote organic production within the EU. It is structured according to 3 axes and focuses on boosting consumer demand, stimulating production and processing, and enhancing environmental sustainability.

The EU’s monitoring framework for the 8th Environment Action Programme (8th EAP), unveiled in 2022, includes measures to speed-up the transition to a greener economy and safeguard the environment. This programme is aligned with the United Nations 2030 Agenda and its sustainable development goals. Under a heading for ‘environmental and climate pressures related to EU production and consumption’, a key target to track progress is the above-mentioned European Green Deal target to have 25% of the EU’s agricultural land organically farmed by 2030.

In 2020, the EU’s organic area covered 13.1 million hectares (equivalent to 131 000 km²). To put these figures into context, the EU’s organic area accounted for 8.3% of its utilised agricultural area. This organic area encompasses both fully converted land and land currently under conversion to organic farming.

The relative importance of organic farming shows considerable variations, both across EU countries and among NUTS level 2 regions. For instance, the share of utilised agricultural area that was under organic farming exceeded the EU average of 8.3% in every region of Austria, Slovenia, Finland and Sweden in 2020; the share was also above the EU average in Estonia and Lativa. Conversely, this share was lower than the EU average in every region of Bulgaria, Ireland, Greece, Hungary (incomplete data) and Romania; the share was also below the EU average in Cyprus, Luxembourg and Malta.

Among the 240 NUTS level 2 regions for which data are available for 2020, there were 24 regions – predominantly located in Poland, Belgium and Romania – where less than 1.5% of the utilised agricultural area was given over to organic farming. By contrast, there were 11 regions with more than 25.0% of their utilised agricultural area under organic farming (they are shown by the darkest shade of blue in Map 3).

The Austrian region of Salzburg recorded the highest regional share in 2020, with over half (56.9%) of its utilised agricultural area under organic farming. There were 3 other NUTS level 2 regions where organic farming accounted for at least 33.3% of the utilised agricultural area in 2020: Burgenland in eastern Austria (38.2%), Calabria in southern Italy (33.6%) and Severozápad in north-west Czechia (33.3%).

Figure 7 shows the regions with the highest shares of the utilised agricultural area given over to organic farming and it also presents information for developments over time. Between 2010 and 2020, the area dedicated to organic farming in the EU rose from 3.8% to 8.3% of the utilised agricultural area. Salzburg recorded the largest increase among NUTS level 2 regions (in percentage point terms), as the relative importance of organic farming increased from 32.7% to 56.9% of its utilised agricultural area (up 24.2 points). The next highest increases were recorded in 2 central Italian regions: the share of utilised agricultural area under organic farming rose 21.5 points in Toscana (from 5.5% to 27.0%) and 18.2 points in Marche (from 5.5% to 23.6%), respectively.

In absolute terms and among NUTS level 2 regions, the southern Spanish region of Andalucía had, by far, the biggest area under organic farming (812 000 hectares in 2020, or 6.2% of the EU total). The area used for organic farming was also very large in the central Spanish region of Castilla-La Mancha (412 400 hectares), the south-western French region of Midi-Pyrénées (326 900 hectares) and the Italian island region of Sicilia (304 600 hectares).

Figure 7: Area under organic farming, 2010 and 2020
(% of utilised agricultural area, by NUTS 2 regions)
Source: Eurostat (ef_lus_main)

Goal 4 – ensure inclusive and equitable quality education and promote lifelong learning opportunities for all

SDG 4 seeks to ensure access for all to quality education through all stages of life, as well as to increase the number of young people and adults who have the relevant skills for employment, decent jobs and entrepreneurship.

Early leavers from education and training

Within the EU, education policy seeks to ensure that all people in the EU (irrespective of age) have the skills, knowledge and capabilities to develop their careers. The transition from education into work may prove particularly difficult for people with low levels of literacy and numeracy, those who leave education at an early age, and people coming from disadvantaged backgrounds. A particular area of concern is the proportion of early leavers from education and training. These are individuals aged 18–24 who have at most a lower secondary level of educational attainment (as defined by the [[Glossary:International_standard_classification_of_education_(ISCED)|international standard classification of education] (ISCED levels 0–2)) and who weren’t engaged in any further education and training (during the 4 weeks preceding the labour force survey). As well as being included as an indicator for monitoring SDGs, the share of early leavers is also 1 of 7 key targets outlined in the strategic framework for European cooperation in education and training towards the European Education Area and beyond (2021–30); the EU has set a goal to reduce the proportion of early leavers to less than 9% by 2030.

Over the last 2 decades, the share of early leavers from education and training declined across the EU. From a peak of 16.9% in 2002 (the start of the time series), this share fell each and every year through to 10.5% by 2017. Having remained unchanged in 2018, there were further falls in the following 5 years. By 2023, the share of young people in the EU who had at most a lower secondary level of educational attainment and who weren’t engaged in any further education and training was 9.5%; as such, it stood 0.5 percentage points higher than the policy target set for 2030.

There is both a spatial and a gender dimension to the issue of early leavers from education and training.

• The proportion of early leavers tends to be higher in rural and sparsely-populated regions of the EU, as well as in regions characterised as former industrial heartlands. Among other reasons, this pattern may be a reflection of fewer educational opportunities and weak local labour markets, which may discourage people from staying longer in education and also act as a ‘push factor’ to encourage people with higher levels of educational attainment to move away.
• For the gender dimension, a higher proportion of young men (compared with young women) tend to be early leavers. Across the EU in 2023, the share of early leavers from education and training was 11.3% among young men, which was 3.6 percentage points higher than the corresponding share among young women (7.7%).

In 2023, the share of early leavers from education and training was already less than the 9.0% policy target in more than 50% (106 out of 204) of the NUTS level 2 regions for which data are available – as shown by 3 shades of teal in Map 4. These regions were widely dispersed across the EU. Looking in more detail, the share of early leavers from education and training was less than 9.0% for every region (for which data are available) of Belgium, Ireland, Croatia, Lithuania, the Netherlands, Slovenia and Sweden; shares of less than 9.0% were recorded in Cyprus, Latvia and Luxembourg too.

At the other end of the range, there were 7 NUTS level 2 regions where the share of early leavers from education and training in 2023 was at least 20.0%; they are denoted by the darkest shade of gold in Map 4. This group included several sparsely populated, island and/or peripheral regions (it is likely that a disproportionately high share of students from some island and/or peripheral regions have to leave home if they wish to follow a particular course or programme, leaving behind a higher concentration of early leavers).

Figure 8 highlights the NUTS level 2 regions with the highest and lowest regional shares of early leavers from education and training in 2023. At the top end of the distribution, the Romanian region of Sud-Est had the highest share, with 24.6% of its individuals aged 18–24 classified as early leavers. Shares of more than 20.0% were also recorded in the French regions of Guyane (21.7%) and Corse (21.5%), the Portuguese Região Autónoma dos Açores (21.7%), the Spanish autonomous regions of Ciudad de Ceuta (21.2%) and Ciudad de Melilla (20.4%), as well as an additional region from Romania – Centru (21.0%).

At the lower end of the distribution, there were 21 NUTS level 2 regions where the share of early leavers from education and training among people aged 18 to 24 was less than 5.0% in 2023. These regions were often grouped together, with clusters of regions with low shares in Ireland, south-west France, Belgium, Czechia, Croatia and Greece. The lowest shares of early leavers from education and training were recorded in

• the Czech capital region of Praha (1.7%)
• the Greek region of Kentriki Makedonia (1.3%)
• the Croatian coastal region of Jadranska Hrvatska (also 1.3%; 2022 data).

Figure 8: Early leavers from education and training, 2023
(% of people aged 18–24, by NUTS 2 regions)
Source: Eurostat (edat_lfse_16)

People with a tertiary level of educational attainment

Education has the potential to drive socioeconomic development forward: this is particularly the case in a globalised world where a highly skilled workforce can be an advantage in terms of productivity, innovation and competitiveness.

The infographic below provides information for the 10 NUTS level 2 regions across the EU that recorded the highest shares of people (aged 25–34) with a tertiary level of educational attainment. In 2023, several of the highest shares were recorded in capital regions. This was the case in the Lithuanian capital region, where 72.3% of people aged 25–34 had a tertiary level of educational attainment, while the Polish, French, Irish, Swedish, Belgian and Dutch capital regions also recorded high shares, as did Cyprus.

Source: Eurostat (edat_lfse_04)

Map 5 shows the regional distribution of tertiary (or higher) educational attainment in 2023. It is based on attainment levels for people aged 25–34 years, by when the vast majority of the population have completed their education. Within the strategic framework for European cooperation in education and training, the EU has a target that, by 2030, the share of people aged 25–34 with a tertiary educational attainment should be at least 45%.

In 2023, 43.1% of the EU population aged 25–34 had a tertiary level of educational attainment; some people within this age group might still be studying. Of the 240 NUTS level 2 regions for which data are available, 80 had already reached or surpassed the EU’s policy target of 45.0% (as shown by 3 shades of teal in Map 5).

At the top end of the distribution, there were 17 regions where at least 60.0% of young people aged 25–34 had a tertiary level of educational attainment in 2023. Many of these regions appear to act as a magnet for highly qualified people, exerting considerable ‘pull effects’ through the varied educational, employment and social/lifestyle opportunities that they offer. This group included the capital regions of Belgium, Czechia, Denmark, Ireland, Spain, France, Lithuania, Hungary, the Netherlands, Poland and Sweden; it also included Cyprus and Luxembourg. The remaining 4 regions with high shares were specialised in research and innovation activities and/or high-technology manufacturing

• Prov. Brabant Wallon in Belgium
• the northern Spanish regions of País Vasco and Cantabria
• Utrecht in the Netherlands.

At the bottom end of the distribution, there were 20 NUTS level 2 regions where fewer than 25% of all people aged 25–34 had a tertiary level of educational attainment in 2023 (as shown by the darkest shade of gold). Many of these regions were characterised as rural/isolated regions that had relatively large agricultural sectors, with a low level of opportunities for highly skilled employment. Others were characterised by their relatively high specialisation in vocational educational programmes, with students moving into the labour market through apprenticeships and training schemes rather than as a result of obtaining tertiary level qualifications. This group of 20 regions was concentrated in eastern and southern EU countries. The lowest regional shares were recorded in the Hungarian region of Észak-Magyarország (16.3%) and the Romanian regions of Sud-Est (16.5%) and Sud-Muntenia (14.7%).

Participation in early childhood education

More about the data: statistics on early childhood education and care

Within the strategic framework for European cooperation in education and training, a key policy target concerns the share of children aged between 3 years and the starting age of compulsory primary education who are participating in early childhood education and care. Eurostat data on early childhood education (ISCED level 0) are used to measure progress towards the goal of having at least 96% of children in this age group participating in early childhood education and care by 2030.

Research has shown that early experiences of children are often critical for their long-term development. Early childhood education programmes are typically designed to introduce young children to organised instruction outside of the family context. Programmes have an intentional education component and target children below the age of entry into primary education (ISCED level 1). These programmes constitute the 1st level of education and training systems and play a key role in redressing ‘unequal’ life chances, tackling inequalities by preventing the formation of early skills gaps.

Based on the latest available data, there were an estimated 15.5 million children (of any age) enrolled in early childhood education across the EU in 2022 (data for Belgium, Greece and Malta only cover pre-primary education). Map 6 shows a more detailed picture for 209 NUTS level 2 regions, it covers pupils between the age of 3 and the starting age of compulsory education at primary level. There were considerable differences in regional participation rates in early childhood education, with the highest rates generally recorded in the westernmost regions of the EU and lower rates across most eastern regions. Capital regions had higher than average participation rates in some EU countries (for example, Bulgaria or Poland), whereas in others they recorded lower than average rates (for example, Ireland, Portugal or Sweden).

Looking in more detail, by 2022 the share of children between the age of 3 years and the age for starting compulsory primary education participating in early childhood education had already reached the EU’s strategic target of 96.0% in more than 1 out of 3 EU regions for which data are available (78 out of 209 regions); they are shaded using 3 different teal tones in Map 6. These 78 regions already at or above the target made up a large proportion of the regions in Belgium, Denmark, Spain, France, Croatia, Lithuania, Portugal and Sweden. At the very top end of the distribution, there were 18 regions in the EU where practically every child (100.0%) between the age of 3 years and the age for starting compulsory primary education participated in early childhood education (as shown by the darkest shade of teal). Half of this group of 18 regions was concentrated in France (9 regions), with a further 5 regions located in neighbouring Belgium.

In Map 6, the regions with participation rates below the strategic target of 96.0% are shaded using 4 different golden tones. In 2022, the share of young children participating in early childhood education was less than 75.0% in 13 out of the 209 EU regions for which data are available. These regions with relatively low participation rates (as shown by the 2nd darkest shade of gold) were concentrated in Greece (8 regions; 2019 data) and Romania (3 regions), but also included Východné Slovensko in Slovakia and Åland in Finland. The lowest rate was recorded in the Greek region of Voreio Aigaio (55.0%; 2019 data).

Adult education and training

Lifelong learning seeks to improve an individual’s knowledge, skills, competences and/or qualifications for personal, social and/or professional reasons. For many occupations, it is increasingly important for the labour force to develop existing skills and learn new ones that are relevant to a specific job or which provide opportunities for new career paths. Some jobs/occupations will likely cease to exist in the future as a result of technological change.

During the last 2 decades, the proportion of adults (aged 25–64) in the EU participating in education and training has more than doubled. At the start of the time series in 2002, around 1 in 20 people participated in education and training during the 4 weeks prior to the (labour force) survey, with the participation rate standing at 5.3%. The rate increased gradually and by 2019 had reached 10.8%. However, following the onset of the COVID-19 crisis, it fell back to 9.1% in 2020, before subsequently rebounding to 10.8% in 2021. Thereafter, the EU’s adult participation rate for education and training continued to increase, growing at a relatively rapid pace, reaching 11.9% in 2022 and 12.7% in 2023.

The regional distribution of participation rates in education and training among people aged 25–64 was somewhat skewed insofar as almost 60% of NUTS level 2 regions – or 139 out of 241 regions – reported a rate in 2023 that was below the EU average (see Map 7).

Map 7 shows participation rates in education and training for people aged 25–64 for 2023. The regional distribution of adult participation rates was relatively homogeneous within individual EU countries, at least in part reflecting national rather than regional education and training initiatives. There were 20 NUTS level 2 regions that had participation rates that were equal to or above 25.0% (as shown by the darkest shade of blue); this group included every region of Denmark and Sweden, as well as 4 Dutch regions and 3 Finnish ones. The 8 highest regional participation rates in education and training were recorded in Sweden. The Swedish capital region of Stockholm had the highest participation rate, at 41.3%, followed by Västsverige, Sydsverige and Östra Mellansverige (all within the range of 38.0–38.9%). The Danish capital region of Hovedstaden had the highest participation rate outside of Sweden (35.2%).

There were 25 NUTS level 2 regions where the participation rate for adult education and training was below 5.0% in 2023 (they are indicated by the yellow shade in Map 7). This group was principally concentrated in south-eastern Europe. At the bottom end of the range, the lowest rates were recorded in the Bulgarian regions of Severoiztochen (1.1%), Severozapaden (1.0%) and Severen tsentralen (0.9%).

Goal 5 – achieve gender equality and empower all women and girls

SDG 5 aims to achieve gender equality by ending all forms of discrimination, violence and any harmful practices against women and girls. It also calls for the full participation of women and equal opportunities for leadership at all levels of decision-making.

Gender employment gap

Ending all forms of discrimination against women and girls and empowering women are crucial to accelerating sustainable development in the EU. Long-standing challenges linked to female participation in the labour force are illustrated by persistent gender gaps for employment and pay. These gaps between the sexes exist for a variety of reasons, among which

• women often bear a disproportionate share of unpaid care and household chores that may limit their availability for paid employment
• gender bias and discrimination when hiring, promoting and paying women
• fewer women in leadership positions to draw attention to gender-related policies or mentor more junior female staff
• a lack of affordable childcare and support for working parents
• disincentives in tax and benefit systems that can lead to 2nd earners bearing a higher tax burden when they participate in the labour market
• occupational segregation, with women often concentrated in specific activities that are characterised by lower wages and/or fewer opportunities for career development.

In 2023, the EU’s gender employment gap was 10.2 percentage points: this gap is defined as the difference between the employment rates of men and women aged 20-64. The European Pillar of Social Rights Action Plan set a subgoal of halving the EU’s gender employment gap, as part of its overall target to increase the employment rate to 78% by 2030. The subgoal envisages the gender employment gap narrowing to 5.6 percentage points by 2030, equivalent to an average fall of 0.5 points each year (over the period 2019–30).

In 2023, 52 out of 241 NUTS level 2 regions for which data are available reported a gender employment gap that was already 5.6 percentage points or narrower; they are shown in different shades of gold in Map 8. This group of 52 regions was mainly concentrated in France (13 regions), Germany (7 regions), Sweden (7 out of 8 regions) and Finland (all 5 regions). Those regions with relatively narrow gender employment gaps were often characterised by high overall employment rates.

In 2023, there were only 3 regions within the EU that reported a higher employment rate for women (than for men): Åland, Etelä-Suomi and Pohjois- ja Itä-Suomi (all in Finland). In the Slovak capital region of Bratislavský kraj, there was no difference in employment rates between the sexes.

Despite some progress, female employment rates still lag behind male rates in the vast majority of EU regions. The European Commission’s Gender Equality Strategy 2020–25 is designed, among other goals, to counter gender stereotypes and promote women’s participation in decision-making, while closing gender gaps in the labour market.

EU regions with relatively wide gender employment gaps were often characterised by higher unemployment rates and levels of women outside the labour force. In 2023, there were 24 NUTS level 2 regions that had gaps of at least 17.5 percentage points (as shown by the darkest shade of teal in Map 8). This group was concentrated in Greece (11 out of 13 regions), central/southern Italy (8 regions) and Romania (4 regions); the other region was Střední Čechy in Czechia. The Italian regions of Campania and Puglia (both 29.5 points) and the Greek region of Sterea Elláda (29.3 points) had the widest gender employment gaps in the EU.

Goal 8 – promote sustained, inclusive and sustainable economic growth, full and productive employment and decent work for all

SDG 8 recognises the importance of sustained economic growth and high levels of economic productivity for the creation of well-paid quality jobs and calls for opportunities for full employment and decent work for all.

GDP per inhabitant is calculated as the ratio of GDP to the average population in a specific year. These data are expressed in purchasing power standard (PPS) terms, which represent a common currency that eliminates differences in price levels between countries to allow meaningful volume comparisons of GDP.

In 2022, GDP per inhabitant averaged 35 400 PPS across the EU. Some of the highest levels of GDP per inhabitant were clustered in western EU countries, with particularly high levels in Ireland, the Benelux countries, Germany and Austria. There were also high levels recorded in many of the EU’s capital regions (see Map 9).

The Irish region of Southern had the highest level of GDP per inhabitant in 2022, at 101 200 PPS. It was followed by Luxembourg (90 900 PPS), the Irish capital region of Eastern and Midland (87 600 PPS) and the Czech capital region of Praha (73 400 PPS). There were 10 other capital regions across the EU where GDP per inhabitant was higher than 50 000 PPS.

For more information on regional disparities in GDP per inhabitant, please refer to SDG 10 below, where the focus is on reducing inequalities within and among countries.

Young people who are neither in employment nor in education and training (NEET)

More about the data: young people who are neither in employment nor in education and training (NEET)

The share of young people (aged 15–29) who are neither in employment nor in education and training (NEET) provides a useful measure for studying the vulnerability of young people in terms of their labour market participation and social exclusion.

The NEET rate is expressed relative to the total population of the same age (15–29); the numerator includes not only young people who are unemployed but also young people who are outside the labour force for reasons other than education or training (for example, because they are caring for family members, volunteering or travelling, or unable to work for health reasons).

Within the European Pillar of Social Rights Action Plan, the EU set a policy target whereby the NEET rate should fall to less than 9% by 2030. Having peaked at 16.1% in 2013, the rate subsequently fell during 6 consecutive years. With the onset of the COVID-19 pandemic, it climbed to 13.8% in 2020, after which a downward trend returned. In 2023, the EU’s NEET rate stood at 11.2%.

Economic crises tend to hit young people disproportionately hard, as young people are more likely to work with temporary and other forms of atypical contracts that are easier to terminate. The NEET rate can be used to investigate the share of young people who haven’t transitioned from education/training to employment. It is generally considered a more comprehensive measure than the unemployment rate, insofar as it is more closely linked to young people’s risk of social and labour market exclusion.

In 15 out of the 237 NUTS level 2 regions for which data are available, at least 20.0% of all young people aged 15–29 were neither in employment, nor in education or training in 2023 (these regions are shaded in the darkest shade of teal in Map 10). Some of the highest NEET rates were recorded in predominantly rural regions located in southern and eastern EU countries, as well as the outermost regions of France. More narrowly, there were 7 regions where more than 25.0% of all young people were neither in employment, nor in education or training

• 3 of these were located in Italy – Campania (26.9%), Calabria (27.2%) and Sicilia (27.9%)
• 3 were located in Romania – Centru (25.5%), Sud-Est (26.8%) and Sud-Vest Oltenia (27.7%)
• however, the highest NEET rate was recorded in the French outermost region of Guyane, where 29.7% of all young people were neither in employment, nor in education or training.

In 2023, there were 84 NUTS level 2 regions that reported a NEET rate that was already below the EU’s policy target of 9.0% (to be reached by 2030); they are shown in golden shades within Map 10. Among these, there were 9 regions where the NEET rate was less than 5.0% (as shown by the darkest shade of gold). A majority of these were located in the Netherlands. They were joined by 2 regions from Sweden and the capital regions of Hungary and Poland. The lowest NEET rates were recorded in Småland med öarna in Sweden (3.7%) and Overijssel in the Netherlands (3.9%).

Capital regions generally recorded lower than (national) average shares of young people who were neither in employment nor in education or training. In 2023, the only exceptions – among multi-regional EU countries – were in Austria, Germany, Belgium and the Netherlands; the difference in the latter was minimal.

Figure 9 confirms that, among NUTS level 2 regions in 2023, the NEET rate ranged from a high of 29.7% in the French outermost region of Guyane down to a low of 3.7% in the south-eastern Swedish region of Småland med öarna. It also shows that some but not all regions characterised by high NEET rates displayed considerable gender differences, with NEET rates generally higher for females (than males).

In the EU, the share of young females aged 15–29 who were neither in employment nor in education and training was 12.5% in 2023. This figure was 2.4 percentage points higher than the corresponding figure for young males, which stood at 10.1%. Across NUTS level 2 regions, it was more common to find higher NEET rates for young females (than for young males). This gender gap was most pronounced in regions located in eastern EU countries and Greece, where cultural, economic and societal factors may play a role in acting as barriers for young females to enter the workforce.

Figure 9: Share of young people neither in employment nor in education and training (NEET), 2023
(%, people aged 15–29, by NUTS 2 regions)
Source: Eurostat (edat_lfse_22)

The employment rate

More about the data: employment rates

The employment rate is the percentage of employed people (of a given age) relative to the total population (of the same age).

Increasing the number and share of people in work is a principal policy objective for the EU. This goal is included as an indicator in the social scoreboard which is used to monitor the implementation of the European Pillar of Social Rights. The EU’s employment rate target is to have, by 2030, at least 78% of the population aged 20–64 in work. The choice of this age range reflects the growing proportion of young people who remain within education into their late teens (and beyond), potentially restricting their participation in the labour market.

Prior to the onset of the COVID-19 crisis, the EU’s employment rate for the core working-age population (20–64 years) had increased for 6 consecutive years, reaching 73.1% by 2019. This pattern came to an abrupt end in 2020 as the rate fell 0.9 percentage points . However, almost all of the losses during the initial stages of the pandemic were recovered in 2021. The EU’s employment rate continued to increase in 2022 and 2023, rising 1.6 and 0.7 points, respectively, to stand at an historical high of 75.3% in 2023.

Map 11 shows the employment rate in 2023 for NUTS level 2 regions: regions with rates already equal to or above the EU target of 78.0% are shown in shades of teal. In 2023, approximately 45% of EU regions (109 out of the 241 for which data are available) had already reached or surpassed this level. These regions were mainly concentrated in Czechia (all 8 regions), Denmark (all 5 regions), Germany (35 out of 38 regions; the exceptions being Berlin, Düsseldorf and Bremen), Hungary (6 out of 8 regions), the Netherlands (all 12 regions), Slovakia (3 out of 4 regions) and Sweden (all 8 regions); the group included Estonia, Cyprus and Malta too.

In 2023, the Polish capital region of Warszawski stołeczny had the highest employment rate among NUTS level 2 regions of the EU, at 86.5%. The 2nd highest rate was also recorded in a capital region, Bratislavský kraj in Slovakia (85.8%). The 3rd highest rate was observed in the western German region of Trier (85.4%), where a relatively high proportion of people commute across a national border to work in Luxembourg.

Many of the regions with relatively low employment rates were characterised as rural, sparsely-populated, or peripheral regions. This pattern was particularly apparent in southern regions of Spain and Italy, much of Greece, some regions in Romania, and the outermost regions of France. These areas typically suffered from limited employment opportunities, especially for individuals with intermediate and high skill levels. Another group of regions characterised by relatively low employment rates are former industrial heartlands that haven’t adapted economically. Some of these have witnessed the negative impact of globalisation on traditional sectors of their economies (such as coal mining, steel or textiles manufacturing). Examples include a band of regions running from north-east France into the Région wallonne (Belgium).

Approximately a quarter (65 out of the 241 regions for which data are available) of all EU regions had an employment rate that was below 72.5% in 2023 (as shown by the 2 darkest shades of gold in Map 11). This group included the capital regions of Belgium, Italy, Greece and Austria, as well as 3 regions in southern Italy where less than half of the core working-age population was employed: Calabria (48.4%), Campania (48.4%) and Sicilia (48.7%).

Goal 9 – build resilient infrastructure, promote inclusive and sustainable industrialisation and foster innovation

SDG 9 calls for building resilient and sustainable infrastructure and promotes inclusive and sustainable industrialisation. It also recognises the importance of research and innovation for finding solutions to social, economic and environmental challenges.

R&D intensity

Gross domestic expenditure on R&D (GERD) includes research expenditure made by businesses, higher education institutions, governments and private non-profit organisations. In 2021, the EU’s GERD was valued at €331.0 billion; this is the latest year for which regional statistics are available.

R&D intensity is frequently used as a measure to determine an economy’s creative/innovative capacity; it is the ratio of R&D expenditure to GDP. Despite modest annual increases over the last couple of decades, R&D intensity in the EU remains below a long-established target of 3.00%. Having increased somewhat during the COVID-19 crisis – reflecting a larger downturn in GDP than R&D expenditure – R&D intensity returned to its pre-pandemic levels, with ratios of 2.27% in 2021 and 2.24% in 2022.

The regional distribution of R&D intensity was heavily skewed: in 2021, fewer than a quarter (53 out of 225) of all regions for which data are available had an intensity ratio above the EU average of 2.27%. There were 23 NUTS level 2 regions within the EU that recorded R&D intensity of at least 3.30% – as shown by the darkest shade of blue in Map 12. They were concentrated exclusively in western and Nordic EU countries: Germany (11 regions), Belgium (4 regions), Austria and Sweden (both 3 regions), with single regions located in each of France and Finland. There were 4 capital regions within this group of 23, namely: Wien in Austria (4.04%), Helsinki-Uusimaa in Finland (3.77%), Stockholm in Sweden (3.57%) and Berlin in Germany (3.37%).

In 2021, the highest ratio of R&D intensity among NUTS level 2 regions was recorded in the Belgian region of Prov. Brabant Wallon (11.39%); its research activities are centred on pharmaceuticals, university research, life sciences, medical imagery, computing and telecommunications. The next highest ratios were recorded in 3 German regions: Stuttgart (6.81%), Braunschweig (6.09%) and Tübingen (5.47%).

Goal 10 – reduce inequality within and among countries

SDG 10 addresses inequalities within and among countries. It calls for nations to reduce inequalities in income as well as those based on age, sex, disability, race, ethnicity, origin, religion, and economic or other status within a country. The goal also addresses inequalities among countries and calls for support for safe migration and the mobility of people.

Regional disparities for GDP per inhabitant

Figure 10 presents information on regional disparities in GDP per inhabitant. The coefficient of variation is defined, for a particular dataset, as the ratio of the standard deviation divided by the mean; a higher ratio indicates a greater degree of dispersion.

In 2022, there were considerable regional disparities for GDP per inhabitant across 3 eastern EU countries: Romania, Czechia and Hungary. They each had coefficients of variation that were greater than 50.0%. Their coefficients of variation reflected particularly high levels of GDP per inhabitant in capital regions that could be contrasted with the remainder of the territory where GDP per inhabitant was lower than the EU average. By contrast, GDP per inhabitant was much more uniformly distributed across the regions of Portugal, Austria, Finland and Sweden, where the coefficient of variation was within the range of 16.5–18.0%.

During the period 2012 to 2022, regional disparities for GDP per inhabitant fell in Hungary, Finland, Portugal and Poland, where the coefficient of variation was at least 2.5 percentage points lower at the end of the period under consideration. This narrowing of regional disparities reflected faster than average growth in several relatively ‘poor’ regions that were ‘catching-up’ or converging with relatively ‘wealthier’ regions.

By contrast, there were 5 EU countries where the coefficient of variation rose between 2012 and 2022. The largest increases were observed in Denmark and Czechia, up 11.0 and 4.6 percentage points, respectively, to 33.2% and 53.2%. The widening of regional disparities in Denmark and Czechia reflected faster than average growth in their capital regions of Hovedstaden and Praha.

Figure 10: Regional disparities in GDP per inhabitant, 2012 and 2022
(coefficient of variation in %, by NUTS 2 regions)
Source: Eurostat (nama_10r_2gdp)

Income distribution

Although GDP per inhabitant has traditionally been used to assess regional divergence/convergence in overall living standards, this measure doesn’t account for income paid/received across national or regional borders, nor does it capture the distribution of income within a population. Consequently, social scientists are increasingly using alternative/broader measures in their quest to gain a more comprehensive and nuanced understanding of economic and societal developments.

The unequal distribution of income/wealth has gained increasing importance in political and socioeconomic discussions since the global financial and economic crisis and, more recently, during the cost-of-living-crisis. It is also a key issue when examining regions that have been ‘left behind’.

More about the data: income inequality

The income quintile share ratio (S80/S20) measures the inequality of income distribution. It is calculated as the ratio between the share of income received by the 20% of the population with the highest income (the top quintile) and the share of income received by the 20% of the population with the lowest income (the bottom quintile). High values for this ratio suggest that there are considerable disparities in the distribution of income between upper and lower income groups. The reference period for statistics on income refers to the calendar year before the year in which the survey took place.

In 2023, the EU’s income quintile share ratio was 4.7 – in other words, the combined income received by the 20% of people with the highest incomes was 4.7 times as high as the combined income received by the 20% with the lowest incomes.

Map 13 shows the regional distribution of the income quintile share ratio. In 2023, its regional distribution was skewed: 83 out of 124 regions for which data are available had a ratio that was below the EU average, while there were 3 regions that had the same ratio and 38 regions that reported income disparities that were greater than the EU average.

At the top end of the distribution, there were 12 NUTS level 2 regions where the income quintile share ratio was at least 6.0 in 2023 (as shown by the darkest shade of blue in Map 13). The highest ratios were concentrated in Bulgaria, Italy, the northern EU countries and Romania, with a peak registered in the southern Italian region of Calabria (where the income of the top 20% of earners was 8.5 times as high as the income of the bottom 20% of earners). The next highest ratios were observed in the Romanian region of Sud-Vest Oltenia (7.4) and the Bulgarian capital region of Yugozapaden (7.0).

In 2023, the lowest income quintile share ratio was recorded in the Slovak capital region of Bratislavský kraj, where the share of total income held by the highest earning 20% of the population was 2.7 times as high as the share held by the lowest earning 20% of the population.

Within multi-regional EU countries, the distribution of income often had a different pattern in the capital region when compared with the rest of each territory. In 2023, it was commonplace to find that the capital region had the highest income quintile share ratio. This was the case in Belgium (4.6; NUTS level 1), Bulgaria (7.0), Ireland (3.9), Lithuania (6.8), the Netherlands (4.3; NUTS level 1), Poland (5.0), Slovenia (3.4) and Finland (4.2). By contrast, this pattern was reversed in Romania and Slovakia, where the lowest income quintile share ratios were recorded in the capital regions of Bucureşti-Ilfov (3.8) and Bratislavský kraj (2.7).

Goal 11 – make cities and human settlements inclusive, safe, resilient and sustainable

SDG 11 aims to renew and plan cities and other human settlements in a way that offers opportunities for all, with access to basic services, energy, housing, transport and green public spaces, while reducing resource use and environmental impact.

Around 332 million people, or almost 3 out of 4 within the EU’s population live in urban areas — cities, towns and suburbs. With the share of Europe’s urban population projected to rise, sustainable cities, towns and suburbs are essential for citizens’ well-being and quality of life.

Road fatalities

The EU’s roads are among the safest in the world. While transport mobility brings many benefits, it isn’t without environmental and societal costs: these include greenhouse gas emissions, other pollution, congestion, as well as accidents – all of which affect our health and well-being.

The European Parliament adopted a resolution in October 2021 on an EU Road Safety Policy Framework 2021–30 – Recommendations on next steps towards ‘Vision Zero’ (2021/2014), which reaffirmed the EU’s commitment to reduce the number of deaths on its roads to almost zero by 2050. The strategy set an initial goal of cutting in half the number of road fatalities and serious injuries by 2030.

Within a statistical context, the number of road fatalities concerns people who were killed immediately in a traffic accident or who died within 30 days as a result of an injury sustained in a road accident.

In 2022, there were 46 road fatalities per million inhabitants in the EU. These fatalities were quite evenly distributed insofar as 129 out of 242 NUTS level 2 regions (or 53.3% of all regions) recorded an incidence of road fatalities that was above the EU average, while 108 had a value that was below; there were 5 regions that had the same number of road fatalities per million inhabitants as the EU average.

Map 14 confirms that some of the highest incidence rates for road fatalities were recorded in rural regions of the EU. In 2022, there were 13 NUTS level 2 regions with at least 100 road fatalities per million inhabitants (as shown by the 2 darkest shades of blue in the map). This group was quite widely dispersed, with 3 outermost/island regions of France, 3 regions in Greece, 2 regions from each of Belgium, Bulgaria and Romania, and a single region from Portugal. The 3 highest ratios were recorded in regions with high tourism intensity, namely the southern Portuguese region of Alentejo (149 road fatalities per million inhabitants) and the Greek island regions of Notio Aigaio (131) and Ionia Nisia (127).

By contrast, urban and capital regions tended to report much lower incidences of road fatalities. Among other factors, this may be linked to more extensive public transport networks, lower motorisation rates and lower average speeds – there may be lower speed limits in built-up areas, while motorway networks in and around major conurbations are often congested. There were 21 NUTS level 2 regions where the incidence of road fatalities was less than 25 deaths per million inhabitants in 2022 (as shown by the yellow shade in Map 14). A majority of regions in this group were characterised as urban areas, including 10 that were capital regions. Particularly low incidence rates were recorded in the Swedish capital region of Stockholm (7), the Austrian capital region of Wien (9) and the German capital region of Berlin (also 9).

Air quality

Air pollution is a major cause of disease and premature death in the EU, with fine particulate matter deemed to have the most severe impact. Some of the most common causes of both illness and premature death attributed to air pollution include heart disease, stroke, lung disease, lung cancer and asthma; these illnesses also have an associated economic cost through lost working days and healthcare expenditure.

Human activities can lead to a considerable deterioration in air quality, for example, through industrial processes (including electricity generation), the burning of solid fuels, transport, agriculture and the generation or treatment of waste. Naturally occurring air pollution can result, among other sources, from volcanic eruptions, desert dust or forest fires.

More about the data: air quality guidelines, commitments and targets

Fine particulate matter covers particles with a diameter of 2.5 micrometres or less (otherwise referred to as PM_2.5). In September 2021, the World Health Organization (WHO) established global air quality guidelines, emphasising the need to safeguard public health: an annual average of 5 µg/m³ for PM_2.5, reflecting emerging scientific insights that even low concentrations of air pollution pose significant risks to human health.

To achieve the EU’s ambitious vision of zero pollution by 2050, the European Commission has outlined key targets and initiatives. Among these, an intermediate goal to reduce premature deaths resulting from exposure to air pollution by at least 55% between 2005 and 2030. Additionally, the European Commission has proposed a revision (COM(2022) 542 final) of its air quality standards to align these more closely to the WHO’s recommendations.

Directive (2016/2284/EU) on the reduction of national emissions of certain atmospheric pollutants sets emission reduction commitments for 5 air pollutants, including fine particulate matter. They are designed to reduce the health impacts of air pollution by 50% compared with 2005. The directive also requires EU countries to draw up national air pollution control programmes.

The European Environment Agency (EEA) estimates that around 253 000 premature deaths in the EU could be attributed to the impact of fine particulate matter in 2021; this equates to an average of 57.2 deaths per 100 000 inhabitants. The regional distribution was skewed, as the number of premature deaths attributable to air pollution per 100 000 inhabitants was below the EU average in 817 out of 1 152 – or 70.9% – of NUTS level 3 regions for which data are available.

Unsurprisingly, the highest absolute numbers of premature deaths associated with fine particulate matter were observed in some of the most populous NUTS level 3 regions; they were concentrated in southern and eastern EU countries and included many predominantly urban regions. The northern Italian region of Milano (3 917) recorded the highest number of premature deaths attributed to fine particulate matter in 2021. There were also high counts in Roma (2 819) and Barcelona (2 808), while 7 more regions in the EU had more than 2 000 premature deaths attributed to air pollution. Among these, 6 were capital regions: Miasto Warszawa in Poland, Bucureşti in Romania, Madrid in Spain, Berlin in Germany, Sofia (stolitsa) in Bulgaria and Budapest in Hungary; the other region was Torino in Italy.

While the absolute number of premature deaths attributed to exposure to fine particulate matter was highest in some of the most populous NUTS level 3 regions of the EU, the most significant impacts of air pollution (when normalised relative to population size) were generally observed in eastern EU countries. In 2021, there were 156 NUTS level 3 regions within the EU where the number of premature deaths attributable to air pollution was at least 100.0 per 100 000 inhabitants (these regions are shown in the 2 darkest shades of blue in Map 15). Vidin in north-west Bulgaria and Miasto Kraków in southern Poland were the only regions to record more than 200 premature deaths per 100 000 inhabitants attributable to air pollution. There were 22 other regions where the number of premature deaths per 100 000 inhabitants attributable to air pollution was in the range of 150–200. This group was composed of 10 more regions from each of Bulgaria and Poland, as well as a single region from each of Romania and Hungary.

At the other end of the range, there were 106 NUTS level 3 regions where the number of premature deaths attributed to exposure to fine particulate matter was less than 15.0 per 100 000 inhabitants in 2021. This group – where this type of air pollution had a relatively low impact on human health – included every region of Estonia, Ireland and Finland and almost every region in Sweden; the only exception was Västra Götalands län.

Goal 13 – take urgent action to combat climate change and its impacts

SDG 13 seeks to achieve a climate-neutral world by mid-century and to limit global warming to well below 2°C – with an aim of 1.5°C – compared with pre-industrial times. It aims to strengthen countries’ climate resilience and adaptive capacity, with a special focus on supporting least-developed countries.

Climate change mitigation

Since the industrial revolution, the presence of greenhouse gases in the Earth’s atmosphere has increased at a rapid pace. Some of the principal man-made causes of greenhouse gas emissions include burning fossil fuels, deforestation and intensive livestock farming. Climate change and environmental degradation are interconnected: climate change affects biodiversity and triggers a range of environmental consequences, while healthy ecosystems provide services that are critical for climate change mitigation (carbon sinks and stocks) and adaptation (water retention, protection against floods and desertification, urban heat reduction, protection against air pollution, and so on).

Source: EDGAR_GHG_NUTS2_v2.0. GHG emissions at subnational level, European Commission (Joint Research Centre), see https://edgar.jrc.ec.europa.eu/dataset_ghg80_nuts2

The Paris Agreement is a legally binding international treaty on climate change. It was adopted by 196 parties at the UN Climate Change Conference (COP21) in December 2015 and set forth an ambitious global goal ‘to limit the temperature increase to 1.5°C above pre-industrial levels’. Without decisive action to curtail greenhouse gas emissions, it’s likely the world will experience more frequent and extreme weather events, such as heatwaves, droughts and flooding. According to the UN, this will put the lives of over 3 billion people at risk.

The European Green Deal aims to reduce EU greenhouse gas emissions by at least 55% by 2030 (compared with 1990 levels). Such a reduction will require profound and transformative changes, for example, to energy and transport systems, industrial processes and agriculture, as well as increased carbon removal by ecosystems.

Map 16 shows the progress made towards this target, with emissions in the EU falling 26.8% between 1990 and 2022. There were 191 NUTS level 2 regions across the EU that recorded a fall in greenhouse gas emissions between 1990 and 2022, 50 regions where emissions increased and a single region where there was no change. Every region of Bulgaria, Czechia, Germany, Croatia, Lithuania, Romania, Slovenia, Slovakia, Finland and Sweden recorded a fall in emissions during the period under consideration; this was the case in Estonia, Latvia, Luxembourg and Malta too. At the bottom end of the distribution, there were 14 regions in the EU where greenhouse gas emissions had already fallen by more than 55.0% between 1990 and 2022 (they are shown in the darkest shade of teal in Map 16), including

• Centru, Sud-Est, Bucureşti-Ilfov (the capital region) and Vest in Romania
• Hovedstaden (the capital region) and Sjælland in Denmark
• Sostinės regionas, the capital region of Lithuania – which recorded the biggest overall fall (down 75.0%)
• the neighbouring Baltic countries of Estonia and Latvia
• Moravskoslezsko in Czechia, Rheinhessen-Pfalz in Germany, Dytiki Makedonia in Greece, Liguria in Italy and Közép-Dunántúl in Hungary.

Greenhouse gas emissions increased between 1990 and 2022 in a majority of the NUTS level 2 regions in Ireland, Spain and Portugal; this was also the case in Cyprus. At the top end of the distribution, the biggest increases were recorded in 2 of the French outermost regions, Mayotte (up 223.7%) and La Réunion (up 166.5%). Región de Murcia and La Rioja – both in Spain – were the only other regions to report that their greenhouse gas emissions more than doubled during the period under consideration.

Goal 15 – protect, restore and promote sustainable use of terrestrial ecosystems, sustainably manage forests, combat desertification, and halt and reverse land degradation and halt biodiversity loss

SDG 15 seeks to protect, restore and promote the conservation and sustainable use of terrestrial ecosystems. This includes efforts to manage forests sustainably and halt deforestation, combat desertification, restore degraded land and soil, halt biodiversity loss and protect threatened species. In the EU, this goal ensures that the health and functioning of terrestrial ecosystems and the delivery of ecosystem services remain a priority, especially in the face of global developments such as population growth, accelerating urbanisation and an increasing need for natural resources as well as climate change impacts.

Drought impact

Most regions of the EU have sufficient water resources: however, water scarcity and drought are becoming increasingly frequent and widespread phenomena. Severe and frequent droughts may, among other impacts, lead to a reduction in water resources, reduce agricultural output, accelerate the process of soil erosion and cut carbon sequestration. Droughts can also impact biodiversity and the restoration of nature through habitat loss, the migration of species and the spread of invasive alien species.

Information on drought impacts can be used to determine the start and duration of drought conditions. These conditions arise when soil moisture availability to plants drops to such a level that it adversely affects crop yields and therefore agricultural production. Monitoring vegetation response to water deficits makes it possible for policymakers to introduce measures that aim to increase the resilience of ecosystems in line with the EU’s Nature Restoration Law – a key element of the EU’s biodiversity strategy for 2030.

During the period 2000–22, the average area of drought impact on vegetation productivity in the EU was approximately 167 000 km². Relatively large areas of land were under drought impact during 4 of the last 5 years for which data are available, the exception being 2021.

In 2022, the EU experienced its hottest summer and 2nd warmest year on record. The area of drought impact on vegetation was approximately 631 000 km², which was equivalent to 15.4% of the total land area and 3.8 times as high as the average for the period 2000–22. A majority of the impacted area was composed of cropland (51.9%), while forest and woodland (24.1%) and grassland (14.9%) also accounted for relatively high shares.

Map 17 shows that large parts of Belgium, Germany, France, Croatia, Luxembourg, Portugal and Slovenia were severely impacted by drought in 2022. There were 145 NUTS level 3 regions where at least 45.0% of all land was impacted by drought in 2022 (as shown by the darkest shade of brown in Map 17). The central Slovenian region of Zasavska recorded the highest share (97.2%). It was followed by 3 regions in north-western Belgium – Arr. Tielt, Arr. Aalst and Arr. Oudenaarde – each with shares in the range of 85.4–87.5%.

The SDG indicator for severe erosion by water measures the area of land affected by significant soil loss due to water-driven processes. It reflects environmental health, influencing agricultural productivity, ecosystem stability and human well-being. Monitoring this indicator is crucial for sustainable land management and combating land degradation.

This indicator estimates the area at risk of severe erosion by water – such as rain splash, sheet-wash and rills (soil loss greater than 10 tonnes per hectare and year). The area at risk is expressed as a percentage of the total non-artificial erodible area, with estimates made using soil erosion susceptibility models that were provided by the European Commission’s Joint Research Centre.

Some 196 850 square kilometres (km²) of the EU’s non-artificial erodible area were considered to be at risk of severe soil erosion by water in 2016, equivalent to 5.3% of the total non-artificial erodible area. Unsurprisingly, the risk of severe soil erosion by water was concentrated in some of the most southerly regions of the EU, where the dry season can lead to soil desiccation, making the soil more prone to erosion if heavy rains arrives in the autumn/winter. Furthermore, when rain does occur in these regions, it often comes in the form of intense storms/downpours that may quickly overwhelm the soil’s capacity to absorb water. Finally, much of southern Europe is relatively mountainous or hilly, with steep slopes that can exacerbate the speed and volume of water runoff.

In absolute terms, the largest areas in the EU that were at risk of severe soil erosion by water in 2016 included

• the southern Spanish region of Andalucía (19 650 km²)
• the southern Italian regions of Sicilia (10 450 km²) and Calabria (5 720 km²)
• the mountainous, northern Italian region of Piemonte (5 540 km²).

In 2016, there were 7 NUTS level 2 regions across the EU where more than a third of the non-artificial erodible area was estimated to be at risk of severe soil erosion by water (seeMap 18). The highest shares were recorded in the Italian regions of Marche (47.6%) and Sicilia (43.9%), while this group also included 4 more regions from Italy – Calabria, Campania, Molise and Valle d’Aosta/Vallée d’Aoste. The only other region with a share of more than a third was the Greek island region of Ionia Nisia (37.4%).

Goal 16 – promote peaceful and inclusive societies for sustainable development, provide access to justice for all, and build effective, accountable and inclusive institutions at all levels

SDG 16 calls for peaceful and inclusive societies based on respect for human rights, protection of the most vulnerable, the rule of law and good governance at all levels. It also envisions transparent, effective and accountable institutions. Peace, security, democracy, the rule of law and respect for fundamental rights are also founding values of the EU.

This SDG indicator tracks the number of deaths due to homicide and injuries inflicted by another person with the intent to injure or kill by any means, as defined by the (International Classification of Diseases (ICD) codes X85 to Y09 and Y87.1. The data are presented as standardised death rates, meaning they are adjusted to a standard European age distribution to measure death rates independently of the population age structure in individual EU regions; they are expressed as a ratio per 100 000 inhabitants.

Within the EU in 2021, there were 0.65 deaths due to homicide per 100 000 inhabitants. Some of the highest rates were recorded in a band of regions running down the easternmost edge of the EU from Finland, through the Baltic countries to Romania, Bulgaria, Greece and Cyprus. There were also very high death rates in a number of the EU’s outermost regions, including the French regions of Guadeloupe (5.45 deaths due to homicide per 100 000 inhabitants) and Guyane (4.68 deaths per 100 000 inhabitants), which had the 2 highest rates in the EU across NUTS level 2 regions. They were followed by Latvia (3.55 deaths per 100 000 inhabitants), while Martinique in France, Sostinės regionas in Lithuania, Nord-Est in Romania and Estonia were the only other regions where the standardised death rate due to homicide was at least 2.00 deaths per 100 000 inhabitants.

Source data for figures and maps

Sustainable development indicators (SDGs) – regional analyses

Data sources

All of the data presented in this article can be found on Eurostat’s database. The bulk of the information was collected through the European Statistical System (ESS). However, a number of alternative data sources have been used, including data from the European Commission’s Joint Research Centre and the European Environment Agency. Specific details concerning the sources used are provided under each infographic, map or figure.

The data presented within this article concern regional statistics for the EU and European Free Trade Association (EFTA) countries, as well as EU candidate countries. The classification of territorial units for statistics – known as NUTS – is at the heart of the EU’s regional statistics. It is a classification based on a hierarchy, subdividing each EU country into regions. These are classified according to NUTS levels 1, 2 and 3, from larger to smaller regions. The 2021 version of the NUTS classification provides the basis for classifying regional information in this article. For EFTA and candidate countries – the concept of ‘statistical regions’ is used instead of NUTS. This applies the same principles as those used in the establishment of the NUTS classification but is based on bilateral agreements between the countries concerned and Eurostat.

For further information concerning metadata and data sources, please refer to the links that are provided at the end of each section in the main article above.

Context

The EU’s approach to implementing the SDGs

Several major policy documents have shaped the EU’s approach to implementing the SDGs. A communication, Next steps for a sustainable European future: European action for sustainability (COM(2016) 739 final highlighted the integration of the SDGs into the EU’s policy framework.

The EU’s approach for implementing the 2030 Agenda is described in detail within Delivering on the UN’s Sustainable Development Goals — A comprehensive approach. For a complete overview of the European Commission’s activities, see the EU’s ‘whole of government’ approach to implementing the 2030 Agenda.

EU policies that help towards the implementation of the 2030 Agenda

The European Green Deal, adopted in December 2019, is the EU’s growth strategy. It aims to transform the EU into a climate-neutral society while leaving no one behind, creating a modern, resource-efficient, competitive and fair economy where there are no net emissions of greenhouse gases by 2050 and where economic growth is decoupled from resource use. The European Green Deal is an integral part of the European Commission’s strategy to implement the 2030 Agenda and the SDGs.

Cohesion policy in the EU is strongly aligned with the SDGs. It contributes to strengthening economic, social and territorial cohesion and correcting imbalances between countries and regions. It delivers on the EU’s political priorities, especially the green and digital transitions.

These are just 2 examples of a wide range of EU policies that highlight the EU’s comprehensive approach to implementing the 2030 Agenda. Below is a non-exhaustive list of some other policies that contribute towards delivering on the 2030 Agenda

• Biodiversity Strategy
• Circular Economy Action Plan
• EU Climate Law
• European Pillar of Social Rights
• European Semester
• Farm to Fork Strategy
• Gender Equality Strategy
• NextGenerationEU Recovery Plan
• Urban Agenda.

Monitoring progress towards implementing the SDGs across the EU

Monitoring progress towards the SDGs takes place at various levels: global, supranational, national, regional, local and thematic. The 2030 Agenda encourages UN members to conduct voluntary national reviews.

The EU is fully committed to delivering on the 2030 Agenda, and the SDGs form an intrinsic part of the European Commission’s work programme. Eurostat supports this approach through regular monitoring and reporting on progress towards the SDGs in an EU context. Eurostat provides a quantitative assessment of the EU’s progress towards reaching the SDGs, based on the EU SDG indicator set, which is aligned as far as appropriate with the UN list of global indicators; this allows the EU dataset to focus on monitoring EU policies and on phenomena particularly relevant in a European context.

The EU SDG indicator set comprises 102 indicators that are structured according to the 17 SDGs – each goal has 6 indicators attributed to it. There are 34 multipurpose indicators, meaning they are used to monitor more than a single SDG.

Eurostat has prepared annual reports monitoring the progress towards the SDGs in the EU context since 2017. These monitoring reports are a key tool for facilitating the coordination of SDG-related policies within the EU. They promote the on-going assessment and progress made towards implementing the SDGs, as well as highlighting their cross-cutting nature.

Explore further

Other articles

• All articles on regions and cities
• All articles on sustainable development goals

Database

• Regional statistics by NUTS classification (reg), see

Regional agriculture statistics (reg_agr)

Regional demographic statistics (reg_dem)

Regional economic accounts (reg_eco10)

Regional science and technology statistics (reg_sct)

Regional structural business statistics (reg_sbs)

Regional business demography (reg_bd)

Regional health statistics (reg_hlth)

Regional tourism statistics (reg_tour)

Regional transport statistics (reg_tran)

Regional labour market statistics (reg_lmk)

Regional labour costs statistics (reg_lcs)

Regional digital economy and society (reg_isoc)

Regional environmental and energy statistics (reg_env)

Regional poverty and social exclusion statistics (reg_ilc)

Regional crime statistics (reg_crim)

• Sustainable development indicators (sdg), see

Goal 1 - No poverty (sdg_01)

Goal 2 - Zero hunger (sdg_02)

Goal 3 - Good health and well-being (sdg_03)

Goal 4 - Quality education (sdg_04)

Goal 5 - Gender equality (sdg_05)

Goal 6 - Clean water and sanitation (sdg_06)

Goal 7 - Affordable and clean energy (sdg_07)

Goal 8 - Decent work and economic growth (sdg_08)

Goal 9 - Industry, innovation and infrastructure (sdg_09)

Goal 10 - Reduced inequalities (sdg_10)

Goal 11 - Sustainable cities and communities (sdg_11)

Goal 12 - Responsible consumption and production (sdg_12)

Goal 13 - Climate action (sdg_13)

Goal 14 - Life below water (sdg_14)

Goal 15 - Life on land (sdg_15)

Goal 16 - Peace, justice and strong institutions (sdg_16)

Goal 17 - Partnerships for the goals (sdg_17)

Thematic section

• Regions and cities
• Sustainable development goals

Publications

Paper and PDF publications

• Eurostat regional yearbook – 2024 edition
• Sustainable development in the European Union: monitoring report on progress towards the SDGs in an EU context – 2024 edition
• Sustainable development in the European Union: overview of progress towards the SDGs in an EU context – 2024 edition

Online publications

• Eurostat Regional Yearbook
• Sustainable development in the European Union

Methodology

Manuals and further methodological information

• Methodological manual on territorial typologies
• Statistical regions in the European Union and partner countries: NUTS and statistical regions 2021 – 2022 edition
• Assessment of indicator trends against SDG-related EU objectives and targets
• Methodology for assessing the EU Member States status and progress towards SDGs

External links

• European Commission – Sustainable development goals, see
  • The EU and the United Nations – common goals for a sustainable future
  • Voluntary reviews of SDG implementation

• United Nations – Sustainable development goals, see
  • The 17 goals
  • The Sustainable Development Goals Report 2024
  • Transforming our world: the 2030 Agenda for Sustainable Development

Visualisation

• Eurostat statistical atlas
• Regional statistics illustrated
• Progress of SDGs in the EU
• SDG country overview
• SDGs and me