Sustainable development goals (SDGs) and EU regions - prosperity

Data extracted in spring/summer 2024.

Planned article update: September 2025.

Highlights

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 – and in many of the EU’s capital regions.

The capital regions of Warszawski stołeczny and Bratislavský kraj had the highest regional employment rates in the EU.

This article looks at sustainable development indicators from a regional perspective – it covers Goal 8 - Decent work and economic growth, Goal 9 – Industry, innovation and infrastructure, Goal 10 – Reduced inequalities, and Goal 11 – Sustainable cities and communities. 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.

Goal 8 – decent work and economic growth

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 1).

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.

Map 1: GDP per inhabitant, 2022
(PPS, by NUTS 2 regions)
Source: Eurostat (nama_10r_2gdp)

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

Within the European Pillar of Social Rights Action Plan, the EU set a policy target whereby the share of young people (aged 15–29) who are neither in employment nor in education and training (NEET) should fall to less than 9% by 2030. Having peaked at 16.1% in 2013, the NEET 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, see Map 2. 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). Among these, there were 9 regions where the NEET rate was less than 5.0%. 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.

Map 2: 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)

Figure 1 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 1: 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

The EU’s employment rate target is to have, by 2030, at least 78% of the population aged 20–64 years 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 3 shows the employment rate in 2023 for NUTS level 2 regions. In 2023, approximately 45% of EU regions (109 out of the 241 for which data are available) had already reached or surpassed the EU target of 78.0%. 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 also included Estonia, Cyprus and Malta.

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. 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%).

Map 3: Employment rate, 2023
(%, people aged 20–64, by NUTS 2 regions)
Source: Eurostat (lfst_r_lfe2emprtn)

Goal 9 – industry, innovation and infrastructure

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%, see Map 4. 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%).

Map 4: R&D intensity, 2021
(%, based on gross domestic expenditure on R&D (GERD) relative to gross domestic product (GDP), by NUTS 2 regions)
Source: Eurostat (rd_e_gerdreg)

Goal 10 – reduced inequalities

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 2 presents information on regional disparities in GDP per inhabitant. The coefficient of variation is used as a measure of disparity across regions: a higher number means greater disparity within the EU country being analysed.

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 2: 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 income quintile share ratio (S80/S20) is used to measure the inequality of income distribution. In 2023, the EU’s this 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 5 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. 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).

Map 5: Income quintile share ratio (S80/S20), 2023
(by NUTS 2 regions)
Source: Eurostat (ilc_di11_r) and (ilc_di11)

Goal 11 – sustainable cities and communities

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. The EU has set itself the goal of cutting in half the number of road fatalities and serious injuries by 2030, and committed to reduce the number of fatalities on its roads to almost zero by 2050.

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 6 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. 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. 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).

Between 2012 and 2022, most EU regions saw a reduction in their number of and their incidence of road fatalities. There were several regions in Poland, Austria and Sweden where the incidence of road fatalities decreased by more than 50%; this was also the case for Prov. Brabant wallon in Belgium, Ipeiros in Greece, Åland in Finland, as well as Lithuania. At the other end of the range, the incidence of road fatalities in Malta almost doubled during the period under consideration, with the next highest increases recorded in 2 more island regions, namely, Voreio Aigaio in Greece and Região Autónoma dos Açores in Portugal.

Map 6: Number of road fatalities, 2022
(per million inhabitants, by NUTS 2 regions)
Source: Eurostat (tran_r_acci) and (tran_sf_roadus)

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. The definition of fine particulate matter covers particles with a diameter of 2.5 micrometres or less (otherwise referred to as PM_2.5). The European Commission has set a goal to reduce by at least 55% between 2005 and 2030 the number of premature deaths in the EU resulting from exposure to air pollution. 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.

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 per 100 000 inhabitants, see Map 7. 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 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.

Map 7: Premature deaths attributed to exposure to fine particulate matter (PM_2.5), 2021
(per 100 000 inhabitants, by NUTS 3 regions)
Source: European Environment Agency (EEA)

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 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 United Nations framework for sustainable development

In September 2015, the United Nations General Assembly 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 (January 2025), the SDG indicator framework consists of 231 indicators.

The 2030 Agenda provided the European 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 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 a quantitative assessment of the EU’s progress towards the SDGs using a set of 102 indicators that have been adapted to the EU context. The EU SDG indicator set is structured according to the 17 SDGs – each goal has 6 indicators attributed to it.

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.

Regional statistics, structured by SDG, offer a detailed territorial view of the current socioeconomic situation in areas such as living conditions, health, education, equality, economic growth or climate action. These regional statistics make it possible to pinpoint areas that require targeted interventions, address disparities between regions, and ensure that no one is left behind.

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

Global and EU targets for air quality

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.

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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

Publications

Paper and PDF publications

Online publications

Methodology

Manuals and further methodological information

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

Visualisation