This statistic shows the total population of the European Union from 2010 to 2023. The population is based on data from the most recent census adjusted by the components of population change produced since the last census, or based on population registers. At the beginning of 2023, the total population of the European Union amounted to approximately 448.38 million inhabitants. See figures for the total population by continent here. The global population The global population is rapidly increasing. Between 1990 and 2015, the global population has increased by around 2 billion people, and it is estimated to have increased by another 1 billion people by 2030. Asia is the continent in the world with the largest population, followed by Africa and Europe. Asia has the two most populous nations in the world: China and India. In 2014, the combined population in China and India amounted to more than 2.6 billion people. The total population in Europe is around 741 million people. As of 2014, about 10.2 percent of the global population lived in Europe. Europe is the continent with the second highest life expectancy at birth in the world. Born in 2013, the average European was estimated to live for around 78 years. Stable economies as well as developing and emerging markets in Europe provide for good living conditions for foreign nationals; seven of the top twenty countries in the world with the largest gross domestic product in 2024 are located in Europe.

The population of Europe was estimated to be 745 million in 2024, an increase of around 4 million when compared with 2012. Over 35 years between 1950 and 1985, the population of Europe grew by approximately 157.8 million. But 35 years after 1985 it was estimated to have only increased by around 38.7 million. Since the 1960s, population growth in Europe has fallen quite significantly and was even negative during the mid-1990s. While population growth has increased slightly since the low of -0.07 percent in 1998, the growth rate for 2020 was just 0.04 percent. Which European country has the biggest population? As of 2024, the population of Russia was estimated to be approximately 144.8 million and was by far Europe's largest country in terms of population, with Turkey being the second-largest at over 87 million. While these two countries both have territory in Europe, however, they are both only partially in Europe, with the majority of their landmasses being in Asia. In terms of countries wholly located on the European continent, Germany had the highest population at 84.5 million, and was followed by the United Kingdom and France at 69.1 million and 66.5 million respectively. Characteristics of Europe's population There are approximately 384.6 million females in Europe, compared with 359.5 million males, a difference of around 25 million. In 1950, however, the male population has grown faster than the female one, with the male population growing by 104.7 million, and the female one by 93.6 million. As of 2024, the single year of age with the highest population was 37, at 10.6 million, while in the same year there were estimated to be around 136 thousand people aged 100 or over.

This statistic illustrates the distribution of working age (15-64 years) populations in selected European countries in 2015. In this year, almost two thirds of the population of Spain were of working age. This was followed by Germany and Norway.

This dataset is copied from Eurostat and visualizes the NUTS3 areas as of 2021. It includes information about wether or not the areas are metropolitan areas.

The province of South-Holland also analyzed the population data from Eurostat at Nuts 3 level from 2015 to 2022. We identified areas where the population grew, stayed stable of declined. This information is added to each area.

Created for the Mapping METREX GIS-viewer, hosted by province South-Holland. Link to the viewer: https://experience.arcgis.com/experience/2a24effbf2a1495aa0d20966f4b70886.

OBSOLETE RELEASE Get the latest release at https://ghsl.jrc.ec.europa.eu/download.php

The Global Human Settlement Layer (GHSL) project is supported by European Commission, Joint Research Center and Directorate-General for Regional and Urban Policy. The GHSL produces new global spatial information, evidence-based analytics, and knowledge describing the human presence in the planet.

The GHSL relies on the design and implementation of new spatial data mining technologies allowing to process automatically and extract analytics and knowledge from large amount of heterogeneous data including: global, fine-scale satellite image data streams, census data, and crowd sources or volunteering geographic information sources. Spatial data reporting objectively and systematically about the presence of population and built-up infrastructures are necessary for any evidence-based modelling or assessing of i) human and physical exposure to threats as environmental contamination and degradation, natural disasters and conflicts, ii) impact of human activities on ecosystems, and iii) access to resources.

This spatial raster dataset depicts the distribution and density of population, expressed as the number of people per cell. Residential population estimates for target years 1975, 1990, 2000 and 2015 provided by CIESIN GPWv4 were disaggregated from census or administrative units to grid cells, informed by the distribution and density of built-up as mapped in the Global Human Settlement Layer (GHSL) global layer per corresponding epoch.

Population density 2015 (inhabitants per km²), Lorraine: 2013 Territorial entities: arrondissements (Wallonie), zones d'emploi (Lorraine), cantons (Luxembourg), Kreise (Saarland, Rheinland-Pfalz) Statistical data sources: INSEE Grand Est; SPF Economie; STATEC; Statistisches Landesamt Rheinland-Pfalz; Statistisches Amt Saarland. Harmonization: IBA / OIE 2016 Geodata sources: EuroGeographics EuroRegionalMap v3.0 - 2010. Harmonization: SIG-GR / GIS-GR 2016 Link to interactive map: https://map.gis-gr.eu/theme/main?version=3&zoom=8&X=708580&Y=6429642&lang=fr&rotation=0&layers=1732&opacities=1&bgLayer=basemap_2015_global Link to Geocatalog: https://geocatalogue.gis-gr.eu/geonetwork/srv/eng/catalog.search#/metadata/4f71026c-4ab0-4153-a00d-2a5d34aae307 This dataset is published in the view service (WMS) available at: https://ws.geoportail.lu/wss/service/GR_Pop_density_WMS/guest with layer name(s): -Pop_density_2015

Italy - Population as a % of EU population was 13.10% in December of 2024, according to the EUROSTAT. Trading Economics provides the current actual value, an historical data chart and related indicators for Italy - Population as a % of EU population - last updated from the EUROSTAT on June of 2025. Historically, Italy - Population as a % of EU population reached a record high of 13.60% in December of 2015 and a record low of 13.10% in December of 2024.

Change in total population 2000-2015 (zones d'emploi Lorraine: 1999-2013) Territorial entities: arrondissements (Wallonie), zones d'emploi (Lorraine), cantons (Luxembourg), Kreise (Saarland, Rheinland-Pfalz) Statistical data sources: INSEE Grand Est; SPF Economie; STATEC; Statistisches Landesamt Rheinland-Pfalz; Statistisches Amt Saarland. Calculations: IBA / OIE 2016 Geodata sources: EuroGeographics EuroRegionalMap v9.1 - 2016. Harmonization: SIG-GR / GIS-GR 2016 Link to interactive map: https://map.gis-gr.eu/theme/main?version=3&zoom=8&X=708580&Y=6429642&lang=fr&rotation=0&layers=1723&opacities=1&bgLayer=basemap_2015_global Link to Geocatalog: https://geocatalogue.gis-gr.eu/geonetwork/srv/eng/catalog.search#/metadata/b4e5ef37-42f7-4a53-a6a9-a418f8628636 This dataset is published in the view service (WMS) available at: https://ws.geoportail.lu/wss/service/GR_Population_change_WMS/guest with layer name(s): -Pop_change_2000_2015

In 2024, Germany was the leading EU country in terms of population, with around 85 million inhabitants. In 2050, approximately 89.2 million people will live in Germany, according to the forecast. See the total EU population figures for more information. The global population The global population is rapidly increasing. Between 1990 and 2015, it increased by around 2 billion people. Furthermore, it is estimated that the global population will have increased by another 1 billion by 2030. Asia is the continent with the largest population, followed by Africa and Europe. In Asia,the two most populous nations worldwide are located, China and India. In 2014, the combined population in China and India alone amounted to more than 2.6 billion people. for comparison, the total population in the whole continent of Europe is at around 741 million people. As of 2014, about 60 percent of the global population was living in Asia, with only approximately 10 percent in Europe and even less in the United States. Europe is the continent with the second-highest life expectancy at birth in the world, only barely surpassed by Northern America. In 2013, the life expectancy at birth in Europe was around 78 years. Stable economies and developing and emerging markets in European countries provide for good living conditions. Seven of the top twenty countries in the world with the largest gross domestic product in 2015 are located in Europe.

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Data and Documentation section...Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau''s Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities and towns and estimates of housing units for states and counties..Explanation of Symbols:An ''**'' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An ''-'' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An ''-'' following a median estimate means the median falls in the lowest interval of an open-ended distribution..An ''+'' following a median estimate means the median falls in the upper interval of an open-ended distribution..An ''***'' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An ''*****'' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An ''N'' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An ''(X)'' means that the estimate is not applicable or not available..Estimates of urban and rural population, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2015 American Community Survey (ACS) data generally reflect the February 2013 Office of Management and Budget (OMB) definitions of metropolitan and micropolitan statistical areas; in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB definitions due to differences in the effective dates of the geographic entities..Occupation codes are 4-digit codes and are based on Standard Occupational Classification 2010..Industry codes are 4-digit codes and are based on the North American Industry Classification System 2012. The Industry categories adhere to the guidelines issued in Clarification Memorandum No. 2, "NAICS Alternate Aggregation Structure for Use By U.S. Statistical Agencies," issued by the Office of Management and Budget..Due to methodological changes to data collection that began in data year 2013, comparisons of language estimates from that point to estimates from 2013 forward should be made with caution. For more information, see: Language User Note..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2015 American Community Survey 1-Year Estimates

Supporting documentation on code lists, subject definitions, data accuracy, and statistical testing can be found on the American Community Survey website in the Data and Documentation section...Sample size and data quality measures (including coverage rates, allocation rates, and response rates) can be found on the American Community Survey website in the Methodology section..Tell us what you think. Provide feedback to help make American Community Survey data more useful for you..Although the American Community Survey (ACS) produces population, demographic and housing unit estimates, it is the Census Bureau''s Population Estimates Program that produces and disseminates the official estimates of the population for the nation, states, counties, cities and towns and estimates of housing units for states and counties..Explanation of Symbols:An ''**'' entry in the margin of error column indicates that either no sample observations or too few sample observations were available to compute a standard error and thus the margin of error. A statistical test is not appropriate..An ''-'' entry in the estimate column indicates that either no sample observations or too few sample observations were available to compute an estimate, or a ratio of medians cannot be calculated because one or both of the median estimates falls in the lowest interval or upper interval of an open-ended distribution..An ''-'' following a median estimate means the median falls in the lowest interval of an open-ended distribution..An ''+'' following a median estimate means the median falls in the upper interval of an open-ended distribution..An ''***'' entry in the margin of error column indicates that the median falls in the lowest interval or upper interval of an open-ended distribution. A statistical test is not appropriate..An ''*****'' entry in the margin of error column indicates that the estimate is controlled. A statistical test for sampling variability is not appropriate. .An ''N'' entry in the estimate and margin of error columns indicates that data for this geographic area cannot be displayed because the number of sample cases is too small..An ''(X)'' means that the estimate is not applicable or not available..Estimates of urban and rural population, housing units, and characteristics reflect boundaries of urban areas defined based on Census 2010 data. As a result, data for urban and rural areas from the ACS do not necessarily reflect the results of ongoing urbanization..While the 2011-2015 American Community Survey (ACS) data generally reflect the February 2013 Office of Management and Budget (OMB) definitions of metropolitan and micropolitan statistical areas; in certain instances the names, codes, and boundaries of the principal cities shown in ACS tables may differ from the OMB definitions due to differences in the effective dates of the geographic entities..Telephone service data are not available for certain geographic areas due to problems with data collection. See Errata Note #93 for details. ..Industry codes are 4-digit codes and are based on the North American Industry Classification System (NAICS). The Census industry codes for 2013 and later years are based on the 2012 revision of the NAICS. To allow for the creation of 2011-2015 tables, industry data in the multiyear files (2011-2015) were recoded to 2013 Census industry codes. We recommend using caution when comparing data coded using 2013 Census industry codes with data coded using Census industry codes prior to 2013. For more information on the Census industry code changes, please visit our website at https://www.census.gov/people/io/methodology/..Occupation codes are 4-digit codes and are based on Standard Occupational Classification 2010..Methodological changes to data collection in 2013 may have affected language data for 2013. Users should be aware of these changes when using multi-year data containing data from 2013. For more information, see: Language User Note..Data are based on a sample and are subject to sampling variability. The degree of uncertainty for an estimate arising from sampling variability is represented through the use of a margin of error. The value shown here is the 90 percent margin of error. The margin of error can be interpreted roughly as providing a 90 percent probability that the interval defined by the estimate minus the margin of error and the estimate plus the margin of error (the lower and upper confidence bounds) contains the true value. In addition to sampling variability, the ACS estimates are subject to nonsampling error (for a discussion of nonsampling variability, see Accuracy of the Data). The effect of nonsampling error is not represented in these tables..Source: U.S. Census Bureau, 2011-2015 American Community Survey 5-Year Estimates

Analysis of ‘Population (MD_3.4e) 2015-31.12. (OD_Population): from district, main resident, gender, German/foreign’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/4517 on 13 January 2022.

--- Dataset description provided by original source is as follows ---

Population (MD_3.4e) 2015-31.12. (OD_Population): from district, main resident, gender, German/foreign

--- Original source retains full ownership of the source dataset ---

Analysis of ‘Population (MD_3.1e) 2015-31.12. (OD_Population): from urban area, main inhabitants, age (years), (85 & older)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/4609 on 18 January 2022.

--- Dataset description provided by original source is as follows ---

Population (MD_3.1e) 2015-31.12. (OD_Population): from urban area, main inhabitants, age (years), (85 & older)

--- Original source retains full ownership of the source dataset ---

Population density [inhabitants/ha] on the basis of blocks and partial block areas on the map 1 : 5,000 (ISU5, spatial reference environmental atlas 2010).

This dataset contains annual urban population counts for Estonia and Portugal from 2015 to 2022. Each record specifies the country, ISO region code, year, total population count, and urban classification (“Urban”). The file provides time series data suitable for demographic analysis, urbanisation trends, and regional studies in Europe. No rural population data or additional socio-economic variables are included.

The most important key figures about population, households, birth, mortality, changes of residence, marriages, marriage dissolutions and change of nationality of the Dutch population.

Statistics Netherlands will reorganise the tables relating to statistics on population and households as of 2015. The aim is to reduce the number of tables while striving to preserve (much) needed information.

Data available from: 1899

Status of the figures: All data in this publication are final data.

Changes as from 29 December 2017: The final data of 2016 regarding 'Mortality by some causes of death' have been added.

Changes as from 18 October 2017: - The terms ‘People with a Dutch background’ (in Dutch: autochtoon) and ‘People with a foreign background’ (in Dutch: allochtoon) have been revised. They have been replaced by ‘Native Dutch people’ and ‘People with a migration background’ respectively. The terms in this table have been replaced as a result. - The underlying coding of classifications used in this table has been adjusted. It is now in line with the standard encoding defined by CBS. The structure and data of the table have not been adjusted.

Changes as from 10 October 2017: - The figure on the 'Population on 1 January, persons with Surinamese background' in 2015 has been corrected. This correction is due to a rounding error. The correction does not affect the remaining figures in the table. - Figures on the subject 'Mortality' and the selection 'Mortality by causes of death' have been corrected for the year 2014. These corrections are due to the fact that the correct average population was not taken as a basis. The corrections do not affect the remaining figures in the table.

When will the new figures be published? The following figures will be published in the fourth quarter of 2022: The figures on population dynamics concerning 2017 to 2021 and about the population on the 1st of January 2018 to 1st of January 2022.

This graph displays the total population size of citizens aged between 60 and 64 years old in Europe in 2015, by country. That year there were roughly **** million inhabitants of this age group in Germany, which was followed by France and Italy at **** million and **** million inhabitants, respectively.

Population density per pixel at 100 metre resolution. WorldPop provides estimates of numbers of people residing in each 100x100m grid cell for every low and middle income country. Through ingegrating cencus, survey, satellite and GIS datasets in a flexible machine-learning framework, high resolution maps of population counts and densities for 2000-2020 are produced, along with accompanying metadata.

DATASET: Alpha version 2010 and 2015 estimates of numbers of people per grid square, with national totals adjusted to match UN population division estimates (http://esa.un.org/wpp/) and remaining unadjusted.

REGION: Africa

SPATIAL RESOLUTION: 0.000833333 decimal degrees (approx 100m at the equator)

PROJECTION: Geographic, WGS84

UNITS: Estimated persons per grid square

MAPPING APPROACH: Land cover based, as described in: Linard, C., Gilbert, M., Snow, R.W., Noor, A.M. and Tatem, A.J., 2012, Population distribution, settlement patterns and accessibility across Africa in 2010, PLoS ONE, 7(2): e31743.

FORMAT: Geotiff (zipped using 7-zip (open access tool): www.7-zip.org)

FILENAMES: Example - AGO10adjv4.tif = Angola (AGO) population count map for 2010 (10) adjusted to match UN national estimates (adj), version 4 (v4). Population maps are updated to new versions when improved census or other input data become available.

Mali data available from WorldPop here.

Population age distribution in Europe. Map type: Charts. Spatial extent: Europe. Times: 1960, 1970, 1980, 1990, 2000, 2010, 2015, 2020. Distinction: 10-year class, 5-year class

The average for 2015 based on 27 countries was 11 percent. The highest value was in Luxembourg: 44 percent and the lowest value was in Bulgaria: 1 percent. The indicator is available from 1990 to 2015. Below is a chart for all countries where data are available.