The world population surpassed eight billion people in 2022, having doubled from its figure less than 50 years previously. Looking forward, it is projected that the world population will reach nine billion in 2038, and 10 billion in 2060, but it will peak around 10.3 billion in the 2080s before it then goes into decline. Regional variations The global population has seen rapid growth since the early 1800s, due to advances in areas such as food production, healthcare, water safety, education, and infrastructure, however, these changes did not occur at a uniform time or pace across the world. Broadly speaking, the first regions to undergo their demographic transitions were Europe, North America, and Oceania, followed by Latin America and Asia (although Asia's development saw the greatest variation due to its size), while Africa was the last continent to undergo this transformation. Because of these differences, many so-called "advanced" countries are now experiencing population decline, particularly in Europe and East Asia, while the fastest population growth rates are found in Sub-Saharan Africa. In fact, the roughly two billion difference in population between now and the 2080s' peak will be found in Sub-Saharan Africa, which will rise from 1.2 billion to 3.2 billion in this time (although populations in other continents will also fluctuate). Changing projections The United Nations releases their World Population Prospects report every 1-2 years, and this is widely considered the foremost demographic dataset in the world. However, recent years have seen a notable decline in projections when the global population will peak, and at what number. Previous reports in the 2010s had suggested a peak of over 11 billion people, and that population growth would continue into the 2100s, however a sooner and shorter peak is now projected. Reasons for this include a more rapid population decline in East Asia and Europe, particularly China, as well as a prolonged development arc in Sub-Saharan Africa.

General Information

The Pop-AUT database was developed for the DISCC-AT project, which required subnational population projections for Austria consistent with the updated Shared Socio-Economic Pathways (SSPs). For this database, the most recent version of the nationwide SSP population projections (IIASA-WiC POP 2023) are spatially downscaled, offering a detailed perspective at the subnational level in Austria. Recognizing the relevance of this information for a wider audience, the data has been made publicly accessible through an interactive dashboard. There, users are invited to explore how the Austrian population is projected to evolve under different SSP scenarios until the end of this century.

Methodology

The downscaling process of the nationwide Shared Socioeconomic Pathways (SSP) population projections is a four-step procedure developed to obtain subnational demographic projections for Austria. In the first step, population potential surfaces for Austria are derived. These indicate the attractiveness of a location in terms of habitability and are obtained using machine learning techniques, specifically random forest models, along with geospatial information such as land use, roads, elevation, distance to cities, and elevation (see, e.g., Wang et al. 2023).

The population potential surfaces play a crucial role in distributing the Austrian population effectively across the country. Calculations are based on the 1×1 km spatial resolution database provided by Wang et al. (2023), covering all SSPs in 5-year intervals from 2020 to 2100.

Moving to the second step, the updated nationwide SSP population projections for Austria (IIASA-WiC POP 2023) are distributed to all 1×1 km grid cells within the country. This distribution is guided by the previously computed grid cell-level population potential surfaces, ensuring a more granular representation of demographic trends.

The base year for all scenarios is 2015, obtained by downscaling the UN World Population Prospects 2015 count for Austria using the WorldPop (2015) 1×1 km population count raster.

In the third step, the 1×1 km population projections are temporally interpolated to obtain yearly projections for all SSP scenarios spanning the period from 2015 to 2100.

The final step involves the spatial aggregation of the gridded SSP-consistent population projections to the administrative levels of provinces (Bundesländer), districts (Bezirke), and municipalities (Gemeinden).

Dashboard

The data can be explored interactively through a dashboard.

Data Inputs

Updated nationwide SSP population projections: IIASA-WiC POP (2023) (https://zenodo.org/records/7921989)

Population potential surfaces: Wang, X., Meng, X., & Long, Y. (2022). Projecting 1 km-grid population distributions from 2020 to 2100 globally under shared socioeconomic pathways. Scientific Data, 9(1), 563.

Shapefiles: data.gv.at

WorldPop 2015: WorldPop (www.worldpop.org - School of Geography and Environmental Science, University of Southampton; Department of Geography and Geosciences, University of Louisville; Departement de Geographie, Universite de Namur) and Center for International Earth Science Information Network (CIESIN), Columbia University (2018). Global High Resolution Population Denominators Project - Funded by The Bill and Melinda Gates Foundation (OPP1134076). https://dx.doi.org/10.5258/SOTON/WP00647

Version

This is version 1.0, built upon the Review-Phase 2 version of the updated nationwide SSP population projections (IIASA-WiC POP 2023). Once these projections are revised, this dataset will be accordingly updated.

File Organization

The SSP-consistent population projections for Austria are accessible in two formats: .csv files for administrative units (provinces = Bundesländer, districts = Politische Bezirke, municipalities = Gemeinden) and 1×1 km raster files in GeoTIFF and NetCDF formats. All files encompass annual population counts spanning from 2015 to 2100.

EUROPOP2019 are the latest Eurostat population projections produced at national and subnational levels for 31 countries: all 27 European Union (EU) Member States and four European Free Trade Association (EFTA) countries, covering the time horizon from 2019 to 2100.

Population projections are 'what-if scenario' that aim to show the hypothetically developments of the population size and its structure based on a sets of assumptions for fertility, mortality and net migration; they are presented for a long time period that covers more than a half-century (50 years).

The datasets at national level are composed by the baseline population projections and five sensitivity tests, namely:

• no migration – it is assumed that the net migration is set to zero in each year of the entire horizon of projections;
• lower migration – it is assumed that the net migration is 33% lower than in the baseline assumptions, in each year of the entire horizon of projections;
• higher migration – it is assumed that the net migration is 33% higher than in the baseline assumptions, in each year of the entire horizon of projections;
• lower fertility - it is assumed that the fertility rates are lower 20% than in the baseline assumptions, in each year of the entire horizon of projections;
• lower mortality - it is assumed that the mortality rates are decreased such that the life expectancy at birth will increase of about two years by 2070 when compared with the baseline assumptions.

Data are available by single year time interval, as follows:

• Projected population on 1 January by age and sex;
• Assumptions on future age-specific fertility rates, probabilities of dying and net migration levels;
• Projected life expectancy by age (in completed years) and sex.

Moreover, the demographic balances and indicators are available for the baseline projections and the five sensitive variants:

• Total numbers of the projected live births and deaths;
• Projected population structure indicators: proportions of broad age groups in total population, age dependency ratios and median ages of the population (for each sex component).

The dataset at regional level is composed by the baseline population projections and covers all 1169 regions classified as NUTS level 3 corresponding to the NUTS-2016 classification (the Nomenclature of Territorial Units for Statistics) and the 47 Statistical Regions (SR) agreed between European Commission and EFTA countries. Statistical regions are defined according to principles similar to those used in the establishment of the NUTS classification.

For all 1216 regions NUTS-3 level, data are available by single year time interval as follows:

• Projected population on 1 January by age and sex;
• Assumptions on future age-specific fertility rates, probabilities of dying and net migration levels;
• Projected deaths by age and sex;
• Projected life expectancy by age (reached during the year) and sex, which is computed according to the method described in the https://ec.europa.eu/eurostat/cache/metadata/Annexes/proj_19n_esms_an_24.pdf" target="_self">Technical note - Alternative life table (with annex)

In addition to the baseline projections, datasets on projected population at regional level are available for two sensitivity tests:

• no migration - it is assumed that migration is zero for both international and internal components in each year of the entire horizon of projections;
• no inter-regional migration - it is assumed that only internal migration is zero in each year of the entire horizon of projections.

Moreover, the demographic balances and indicators are available for the baseline projections and the two sensitive variants:

• Total numbers of the projected live births by sex and deaths;
• Projected population structure indicators: proportions of broad age groups in total population, age dependency ratios and median ages of the population (for each sex component).

The additional dataset called ‘Short-term update of the projected population (2022-2032)’ [proj_stp22] was published on 28 September 2022. While EUROPOP2019 remain the main set of reference for population projections, this new dataset includes updates of baseline projections for the total population, population in the age group 15 to 74 years (considered as the population in the working-age group), and its share in the total population. In addition, two sensitivity tests are carried out – high and very high number of refugees – by introducing in the baseline projections a shock due to the mass-influx of refugees fleeing the war in Ukraine, and who have received temporary protection in the EU countries.

The updated EUROPOP2019 projections were constructed from cumulative sums of weighted averages of annual population changes of two series: the original EUROPOP2019 projection and a new short-term population projection computed from the latest available data over the period of 10 years.

The two sensitivity tests were built on the following assumptions:

• High number of refugees sensitivity test – assumes that the influx of refugees occurs during 2022 only, and is followed by annual returns at a constant rate such that at the end of 2031 the remaining number of refugees is 10% of the total influx in 2022;
• Very high number of refugees sensitivity test – assumes that the influx of refugees occurs during 2022 and 2023, and is followed by annual returns at a constant rate such that at the end of 2031 the remaining number of refugees is 15% of the cumulated influx in 2022 and 2023.

EUROPOP2019 are the latest Eurostat population projections produced at national and subnational levels for 31 countries: all 27 European Union (EU) Member States and four European Free Trade Association (EFTA) countries, covering the time horizon from 2019 to 2100.

Population projections are 'what-if scenario' that aim to show the hypothetically developments of the population size and its structure based on a sets of assumptions for fertility, mortality and net migration; they are presented for a long time period that covers more than a half-century (50 years).

The datasets at national level are composed by the baseline population projections and five sensitivity tests, namely:

• no migration – it is assumed that the net migration is set to zero in each year of the entire horizon of projections;
• lower migration – it is assumed that the net migration is 33% lower than in the baseline assumptions, in each year of the entire horizon of projections;
• higher migration – it is assumed that the net migration is 33% higher than in the baseline assumptions, in each year of the entire horizon of projections;
• lower fertility - it is assumed that the fertility rates are lower 20% than in the baseline assumptions, in each year of the entire horizon of projections;
• lower mortality - it is assumed that the mortality rates are decreased such that the life expectancy at birth will increase of about two years by 2070 when compared with the baseline assumptions.

Data are available by single year time interval, as follows:

• Projected population on 1 January by age and sex;
• Assumptions on future age-specific fertility rates, probabilities of dying and net migration levels;
• Projected life expectancy by age (in completed years) and sex.

Moreover, the demographic balances and indicators are available for the baseline projections and the five sensitive variants:

• Total numbers of the projected live births and deaths;
• Projected population structure indicators: proportions of broad age groups in total population, age dependency ratios and median ages of the population (for each sex component).

The dataset at regional level is composed by the baseline population projections and covers all 1169 regions classified as NUTS level 3 corresponding to the NUTS-2016 classification (the Nomenclature of Territorial Units for Statistics) and the 47 Statistical Regions (SR) agreed between European Commission and EFTA countries. Statistical regions are defined according to principles similar to those used in the establishment of the NUTS classification.

For all 1216 regions NUTS-3 level, data are available by single year time interval as follows:

• Projected population on 1 January by age and sex;
• Assumptions on future age-specific fertility rates, probabilities of dying and net migration levels;
• Projected deaths by age and sex;
• Projected life expectancy by age (reached during the year) and sex, which is computed according to the method described in the https://ec.europa.eu/eurostat/cache/metadata/Annexes/proj_19n_esms_an_24.pdf" target="_self">Technical note - Alternative life table (with annex)

In addition to the baseline projections, datasets on projected population at regional level are available for two sensitivity tests:

• no migration - it is assumed that migration is zero for both international and internal components in each year of the entire horizon of projections;
• no inter-regional migration - it is assumed that only internal migration is zero in each year of the entire horizon of projections.

Moreover, the demographic balances and indicators are available for the baseline projections and the two sensitive variants:

• Total numbers of the projected live births by sex and deaths;
• Projected population structure indicators: proportions of broad age groups in total population, age dependency ratios and median ages of the population (for each sex component).

The additional dataset called ‘Short-term update of the projected population (2022-2032)’ [proj_stp22] was published on 28 September 2022. While EUROPOP2019 remain the main set of reference for population projections, this new dataset includes updates of baseline projections for the total population, population in the age group 15 to 74 years (considered as the population in the working-age group), and its share in the total population. In addition, two sensitivity tests are carried out – high and very high number of refugees – by introducing in the baseline projections a shock due to the mass-influx of refugees fleeing the war in Ukraine, and who have received temporary protection in the EU countries.

The updated EUROPOP2019 projections were constructed from cumulative sums of weighted averages of annual population changes of two series: the original EUROPOP2019 projection and a new short-term population projection computed from the latest available data over the period of 10 years.

The two sensitivity tests were built on the following assumptions:

• High number of refugees sensitivity test – assumes that the influx of refugees occurs during 2022 only, and is followed by annual returns at a constant rate such that at the end of 2031 the remaining number of refugees is 10% of the total influx in 2022;
• Very high number of refugees sensitivity test – assumes that the influx of refugees occurs during 2022 and 2023, and is followed by annual returns at a constant rate such that at the end of 2031 the remaining number of refugees is 15% of the cumulated influx in 2022 and 2023.

The region of present-day China has historically been the most populous region in the world; however, its population development has fluctuated throughout history. In 2022, China was overtaken as the most populous country in the world, and current projections suggest its population is heading for a rapid decline in the coming decades. Transitions of power lead to mortality The source suggests that conflict, and the diseases brought with it, were the major obstacles to population growth throughout most of the Common Era, particularly during transitions of power between various dynasties and rulers. It estimates that the total population fell by approximately 30 million people during the 14th century due to the impact of Mongol invasions, which inflicted heavy losses on the northern population through conflict, enslavement, food instability, and the introduction of bubonic plague. Between 1850 and 1870, the total population fell once more, by more than 50 million people, through further conflict, famine and disease; the most notable of these was the Taiping Rebellion, although the Miao an Panthay Rebellions, and the Dungan Revolt, also had large death tolls. The third plague pandemic also originated in Yunnan in 1855, which killed approximately two million people in China. 20th and 21st centuries There were additional conflicts at the turn of the 20th century, which had significant geopolitical consequences for China, but did not result in the same high levels of mortality seen previously. It was not until the overlapping Chinese Civil War (1927-1949) and Second World War (1937-1945) where the death tolls reached approximately 10 and 20 million respectively. Additionally, as China attempted to industrialize during the Great Leap Forward (1958-1962), economic and agricultural mismanagement resulted in the deaths of tens of millions (possibly as many as 55 million) in less than four years, during the Great Chinese Famine. This mortality is not observable on the given dataset, due to the rapidity of China's demographic transition over the entire period; this saw improvements in healthcare, sanitation, and infrastructure result in sweeping changes across the population. The early 2020s marked some significant milestones in China's demographics, where it was overtaken by India as the world's most populous country, and its population also went into decline. Current projections suggest that China is heading for a "demographic disaster", as its rapidly aging population is placing significant burdens on China's economy, government, and society. In stark contrast to the restrictive "one-child policy" of the past, the government has introduced a series of pro-fertility incentives for couples to have larger families, although the impact of these policies are yet to materialize. If these current projections come true, then China's population may be around half its current size by the end of the century.

Climate and land-use change are major components of global environmental change with feedbacks between these components. The consequences of these interactions show that land use may exacerbate or alleviate climate change effects. Based on these findings it is important to use land-use scenarios that are consistent with the specific assumptions underlying climate-change scenarios. The Integrated Climate and Land-Use Scenarios (ICLUS) project developed land-use outputs that are based on a downscaled version of the Intergovernmental Panel on Climate Change (IPCC) Special Report on Emissions Scenarios (SRES) social, economic, and demographic storylines. ICLUS outputs are derived from a pair of models. A demographic model generates county-level population estimates that are distributed by a spatial allocation model (SERGoM v3) as housing density across the landscape. Land-use outputs were developed for the four main SRES storylines and a baseline ("base case"). The model is run for the conterminous USA and output is available for each scenario by decade to 2100. In addition to housing density at a 1 hectare spatial resolution, this project also generated estimates of impervious surface at a resolution of 1 square kilometer. This shapefile holds population data for all counties of the conterminous USA for all decades (2010-2100) and SRES population growth scenarios (A1, A2, B1, B2), as well as a 'base case' (BC) scenario, for use in the Integrated Climate and Land Use Scenarios (ICLUS) project.

About this dataset

Context

The dataset tabulates the Wrangell population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Wrangell across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of Wrangell was 2,070, a 1.43% decrease year-by-year from 2021. Previously, in 2021, Wrangell population was 2,100, a decline of 1.27% compared to a population of 2,127 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Wrangell decreased by 365. In this period, the peak population was 2,521 in the year 2018. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the Wrangell is shown in this column.
• Year on Year Change: This column displays the change in Wrangell population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Wrangell Population by Year. You can refer the same here

The methodology used to produce these projections differs from ICLUS v2.0 (https://cfpub.epa.gov/ncea/iclus/recordisplay.cfm?deid=322479). The demographic components of change (i.e., rates of fertility and mortality) for ICLUS v2.1 were taken directly from the Wittgenstein Centre Data Explorer (http://witt.null2.net/shiny/wic/). These projections were produced more recently than the Census projections used in ICLUS v2.0, and incorporate more recent observations of population change. SSP2 is a “middle-of-the-road” projection, where social, economic and technological trends do not shift markedly from historical patterns, resulting in a U.S. population of 455 million people by 2100. Domestic migration trends remain largely consistent with the recent past, however the amenity value of local climate (average precipitation and temperature for summer and winter) is used in ICLUS v2.1.1 to influence migration patterns. The name of the climate model used as the source of future climate patterns is included at the end of the file name (e.g., "GISS-E2-R" or "HadGEM2-ES"). The approach for incorporating climate change into the migration model is described in the ICLUS v2.0 documentation. The SSP5 narrative describes a rapidly growing and flourishing global economy that remains heavily dependent on fossil fuels, and a U.S. population that exceeds 730 million by 2100. ICLUS v2.1 land use projections under SSP5 result in a considerably larger expansion of developed lands relative to SSP2. The the amenity value of local climate (average precipitation and temperature for summer and winter) is used in ICLUS v2.1.1 to influence migration patterns. The name of the climate model used as the source of future climate patterns is included at the end of the file name (e.g., "GISS-E2-R" or "HadGEM2-ES"). The approach for incorporating climate change into the migration model is described in the ICLUS v2.0 documentation. RCP4.5 assumes that global greenhoue gas emissions increase into the latter part of the century, before leveling off and eventually stabilizing by 2100 as a result of various climate change policies. RCP8.5 assumes that global greenhoue gas emissions increase through the year 2100.

About this dataset

Context

The dataset tabulates the Weatherby Lake population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Weatherby Lake across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of Weatherby Lake was 2,100, a 0.77% increase year-by-year from 2021. Previously, in 2021, Weatherby Lake population was 2,084, an increase of 0.14% compared to a population of 2,081 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Weatherby Lake increased by 239. In this period, the peak population was 2,100 in the year 2022. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the Weatherby Lake is shown in this column.
• Year on Year Change: This column displays the change in Weatherby Lake population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Weatherby Lake Population by Year. You can refer the same here

EUROPOP2019 are the latest Eurostat population projections produced at national and subnational levels for 31 countries: all 27 European Union (EU) Member States and four European Free Trade Association (EFTA) countries, covering the time horizon from 2019 to 2100.

Population projections are 'what-if scenario' that aim to show the hypothetically developments of the population size and its structure based on a sets of assumptions for fertility, mortality and net migration; they are presented for a long time period that covers more than a half-century (50 years).

The datasets at national level are composed by the baseline population projections and five sensitivity tests, namely:

• no migration – it is assumed that the net migration is set to zero in each year of the entire horizon of projections;
• lower migration – it is assumed that the net migration is 33% lower than in the baseline assumptions, in each year of the entire horizon of projections;
• higher migration – it is assumed that the net migration is 33% higher than in the baseline assumptions, in each year of the entire horizon of projections;
• lower fertility - it is assumed that the fertility rates are lower 20% than in the baseline assumptions, in each year of the entire horizon of projections;
• lower mortality - it is assumed that the mortality rates are decreased such that the life expectancy at birth will increase of about two years by 2070 when compared with the baseline assumptions.

Data are available by single year time interval, as follows:

• Projected population on 1 January by age and sex;
• Assumptions on future age-specific fertility rates, probabilities of dying and net migration levels;
• Projected life expectancy by age (in completed years) and sex.

Moreover, the demographic balances and indicators are available for the baseline projections and the five sensitive variants:

• Total numbers of the projected live births and deaths;
• Projected population structure indicators: proportions of broad age groups in total population, age dependency ratios and median ages of the population (for each sex component).

The dataset at regional level is composed by the baseline population projections and covers all 1169 regions classified as NUTS level 3 corresponding to the NUTS-2016 classification (the Nomenclature of Territorial Units for Statistics) and the 47 Statistical Regions (SR) agreed between European Commission and EFTA countries. Statistical regions are defined according to principles similar to those used in the establishment of the NUTS classification.

For all 1216 regions NUTS-3 level, data are available by single year time interval as follows:

• Projected population on 1 January by age and sex;
• Assumptions on future age-specific fertility rates, probabilities of dying and net migration levels;
• Projected deaths by age and sex;
• Projected life expectancy by age (reached during the year) and sex, which is computed according to the method described in the https://ec.europa.eu/eurostat/cache/metadata/Annexes/proj_19n_esms_an_24.pdf" target="_self">Technical note - Alternative life table (with annex)

In addition to the baseline projections, datasets on projected population at regional level are available for two sensitivity tests:

• no migration - it is assumed that migration is zero for both international and internal components in each year of the entire horizon of projections;
• no inter-regional migration - it is assumed that only internal migration is zero in each year of the entire horizon of projections.

Moreover, the demographic balances and indicators are available for the baseline projections and the two sensitive variants:

• Total numbers of the projected live births by sex and deaths;
• Projected population structure indicators: proportions of broad age groups in total population, age dependency ratios and median ages of the population (for each sex component).

The additional dataset called ‘Short-term update of the projected population (2022-2032)’ [proj_stp22] was published on 28 September 2022. While EUROPOP2019 remain the main set of reference for population projections, this new dataset includes updates of baseline projections for the total population, population in the age group 15 to 74 years (considered as the population in the working-age group), and its share in the total population. In addition, two sensitivity tests are carried out – high and very high number of refugees – by introducing in the baseline projections a shock due to the mass-influx of refugees fleeing the war in Ukraine, and who have received temporary protection in the EU countries.

The updated EUROPOP2019 projections were constructed from cumulative sums of weighted averages of annual population changes of two series: the original EUROPOP2019 projection and a new short-term population projection computed from the latest available data over the period of 10 years.

The two sensitivity tests were built on the following assumptions:

• High number of refugees sensitivity test – assumes that the influx of refugees occurs during 2022 only, and is followed by annual returns at a constant rate such that at the end of 2031 the remaining number of refugees is 10% of the total influx in 2022;
• Very high number of refugees sensitivity test – assumes that the influx of refugees occurs during 2022 and 2023, and is followed by annual returns at a constant rate such that at the end of 2031 the remaining number of refugees is 15% of the cumulated influx in 2022 and 2023.

Computed prospective ages for 1950-2100 for all countries and regions based on 2017 Revision of the UN World Population Prospects.Content:1. codebook.pdf contains a brief overview of the dataset, its background and a description of the cases and variables.2. methods.pdf is a (draft but complete) write up of the calculations used to create the dataset.3. 2017_prospective-ages.csv is the human readable form of the prospective age dataset containing the calculated prospective old-age thresholds for 241 countries and regions, for the period 1950-2100, for men, women and both together, as well as the proportions of the population (male, female and total) over these thresholds.This figshare fileset is published directly from the github repository ProspectiveAgeData. For an application of this data see the factsheet on ageing in the Middle East and Northern Africa which will be published in Population Horizons journal.

About this dataset

Context

The dataset tabulates the Weatherby Lake population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Weatherby Lake across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of Weatherby Lake was 2,111, a 0.52% increase year-by-year from 2022. Previously, in 2022, Weatherby Lake population was 2,100, an increase of 0.77% compared to a population of 2,084 in 2021. Over the last 20 plus years, between 2000 and 2023, population of Weatherby Lake increased by 250. In this period, the peak population was 2,111 in the year 2023. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the Weatherby Lake is shown in this column.
• Year on Year Change: This column displays the change in Weatherby Lake population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Weatherby Lake Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the Herington population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Herington across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of Herington was 2,100, a 0.62% decrease year-by-year from 2021. Previously, in 2021, Herington population was 2,113, an increase of 0.33% compared to a population of 2,106 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Herington decreased by 451. In this period, the peak population was 2,551 in the year 2000. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the Herington is shown in this column.
• Year on Year Change: This column displays the change in Herington population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Herington Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the Pulaski township population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Pulaski township across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of Pulaski township was 1,884, a 0.26% decrease year-by-year from 2021. Previously, in 2021, Pulaski township population was 1,889, an increase of 0.11% compared to a population of 1,887 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Pulaski township decreased by 57. In this period, the peak population was 2,100 in the year 2019. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the Pulaski township is shown in this column.
• Year on Year Change: This column displays the change in Pulaski township population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Pulaski township Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the Buffalo population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of Buffalo across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of Buffalo was 1,821, a 1.39% increase year-by-year from 2021. Previously, in 2021, Buffalo population was 1,796, an increase of 1.58% compared to a population of 1,768 in 2020. Over the last 20 plus years, between 2000 and 2022, population of Buffalo decreased by 105. In this period, the peak population was 2,100 in the year 2009. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the Buffalo is shown in this column.
• Year on Year Change: This column displays the change in Buffalo population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for Buffalo Population by Year. You can refer the same here

About this dataset

Context

The dataset tabulates the St. Albans town population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of St. Albans town across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2023, the population of St. Albans town was 2,123, a 1.10% increase year-by-year from 2022. Previously, in 2022, St. Albans town population was 2,100, an increase of 1.45% compared to a population of 2,070 in 2021. Over the last 20 plus years, between 2000 and 2023, population of St. Albans town increased by 287. In this period, the peak population was 2,123 in the year 2023. The numbers suggest that the population has not reached its peak yet and is showing a trend of further growth. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2023

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2023)
• Population: The population for the specific year for the St. Albans town is shown in this column.
• Year on Year Change: This column displays the change in St. Albans town population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for St. Albans town Population by Year. You can refer the same here

EUROPOP2023 are the latest Eurostat long-term population projections produced at national level for 30 countries: all 27 European Union (EU) Member States and three European Free Trade Association (EFTA) countries (Iceland, Norway, and Switzerland), covering the time horizon from 2022 to 2100. Population projections are 'what-if scenario' that aim to show the hypothetically developments of the population size and structure based on a set of assumptions regarding fertility, mortality, and net migration. They are presented for a long time period that covers more than a half-century (50 years).

The datasets consist of the baseline population projections and five sensitivity tests, which are described as follows:

• no migration – it is assumed that net migration is zero for each year within the 2023-2100 time horizon;
• lower migration – it is assumed that the net migration is lower due to a 33% reduction in non-EU immigration flows for each year within the 2023-2100 time horizon;
• higher migration – it is assumed that the net migration is higher due to a 33% increase in non-EU immigration flows for each year within the 2023-2100 time horizon;
• lower fertility – it is assumed that the fertility rates are lower 20% than the baseline assumptions for each year within the 2023-2100 time horizon;
• lower mortality – it is assumed that the mortality rates are lower resulting in an increase of approximately two years in life expectancy at birth by 2070 compared to the baseline assumptions.

In each sensitivity test, the assumptions for the year 2022 were maintained as in the baseline projections. This is because, for that year, there is a combination of observed data (i.e. beneficiaries on temporary protections at the end of December 2022), information from the national authorities, and forecasting.

Data are available by single-year time interval, as detailed below:

• Projected population on 1 January by age and sex;
• Assumptions on future age-specific fertility rates, age-specific mortality rates and net migration levels;
• Projected life expectancy by age (in completed years) and sex.

Additionally, the demographic balances and indicators are available for the baseline projections and each of the five sensitive variants, including also:

• Total numbers of the projected live births and deaths;
• Projected population structure indicators including proportions of broad age groups in total population, age dependency ratios and median ages of the population (for each sex component).

STP2024 are the short-term population projections covering the time horizon from 2023 to 2050, and produced at national level for 30 countries: all 27 European Union (EU) Member States and three European Free Trade Association (EFTA) countries (Iceland, Norway, and Switzerland). Similar to long-term projections, these are 'what-if scenario' that aim to show the hypothetically developments of the population size and structure based on a set of assumptions regarding fertility, mortality and net migration. The latest demographic data published on Eurostat website, as of 06 September 2024, were used as input in building the assumptions, thereby including the published post-2021 census revisions and data related to the temporary protection granted to persons displaced from Ukraine due to Russia's invasion.

The dataset (proj_stp24) includes data by single-year time interval for two types of projections:

• Baseline projections:
  • Projected total population on 1 January, the working-age population (defined as persons aged from 15 to 74), and its share in the total population;
  • Assumptions on total fertility rates, life expectancy at birth by sex, and total net migration levels;
  • Total numbers of projected live births and deaths.

• No migration sensitivity test – it is assumed that the net migration is zero for each year within the 2024-2050 time horizon.
  • Projected total population on 1 January, the working-age population (defined as persons aged from 15to 74), and its share in the total population;
  • The 2023 net migration levels remain the same as in the baseline projections to reflect the nowcast data;
  • Total numbers of projected live births and deaths.

STP2025 are the latest short-term population projections covering the time horizon from 2024 to 2050, produced at national level for 30 countries: all 27 European Union (EU) Member States and three European Free Trade Association (EFTA) countries (Iceland, Norway, and Switzerland). Similar to long-term projections, these are 'what-if scenario' that aim to show the hypothetically developments of the population size and structure based on a set of assumptions regarding fertility, mortality, and net migration. The latest demographic data published on Eurostat website as of 15 May 2025, were used as input in building the assumptions, thereby including the published post-2021 census revisions and data related to temporary protection granted to persons displaced from Ukraine due to Russia's invasion.

The dataset (proj_stp25) includes data by single-year time interval for two types of projections:

• Baseline projections:
  • Projected total population on 1 January, working-age population (15-74 years) and its share in the total population;
  • Assumptions on total fertility rates, life expectancy at birth by sex, and total net migration levels;
  • Total numbers of projected live births and deaths.

• No migration sensitivity test – it is assumed that the net migration is zero in each year of the 2025-2050 time horizon.
  • Projected total population on 1 January, working-age population (15-74 years) and its share in the total population;
  • The 2024 net migration levels remain as in the baseline projections to reflect the nowcast data;
  • Total numbers of projected live births and deaths.

The dataset includes Business As Usual (BAU) forecast of the world's global CO2 emissions per capita (CpC) for 2020-2100.

The CO2 emission forecast is from the publication “Dataset Global Warming Forecast using Acceleration Factors” [3]. According to this publication, the CO2 emissions without international transport will change from 33,803 MtCO2/y in 2020 to 70,191 MtCO2/y in 2100, a 108% increase.

The population forecast applies a parabolic trendline of the last 30 years. According to this calculation, the world population will change from 7,795 million in 2020 to 15,206 million in 2100, a 95% increase.

CO2 emissions per capita (CpC) are calculated by dividing the CO2 emissions per year by the population in the same year.

The world CpC was 4.3366 tCO2/y,cap in 2020. The CpC forecast for 2100 is 4.6160 tCO2/y,cap, 6.4% increase.

About this dataset

Context

The dataset tabulates the New Wilmington population over the last 20 plus years. It lists the population for each year, along with the year on year change in population, as well as the change in percentage terms for each year. The dataset can be utilized to understand the population change of New Wilmington across the last two decades. For example, using this dataset, we can identify if the population is declining or increasing. If there is a change, when the population peaked, or if it is still growing and has not reached its peak. We can also compare the trend with the overall trend of United States population over the same period of time.

Key observations

In 2022, the population of New Wilmington was 2,106, a 0.00% decrease year-by-year from 2021. Previously, in 2021, New Wilmington population was 2,106, an increase of 0.29% compared to a population of 2,100 in 2020. Over the last 20 plus years, between 2000 and 2022, population of New Wilmington decreased by 328. In this period, the peak population was 2,515 in the year 2002. The numbers suggest that the population has already reached its peak and is showing a trend of decline. Source: U.S. Census Bureau Population Estimates Program (PEP).

Content

When available, the data consists of estimates from the U.S. Census Bureau Population Estimates Program (PEP).

Data Coverage:

• From 2000 to 2022

Variables / Data Columns

• Year: This column displays the data year (Measured annually and for years 2000 to 2022)
• Population: The population for the specific year for the New Wilmington is shown in this column.
• Year on Year Change: This column displays the change in New Wilmington population for each year compared to the previous year.
• Change in Percent: This column displays the year on year change as a percentage. Please note that the sum of all percentages may not equal one due to rounding of values.

Good to know

Margin of Error

Data in the dataset are based on the estimates and are subject to sampling variability and thus a margin of error. Neilsberg Research recommends using caution when presening these estimates in your research.

Custom data

If you do need custom data for any of your research project, report or presentation, you can contact our research staff at research@neilsberg.com for a feasibility of a custom tabulation on a fee-for-service basis.

Inspiration

Neilsberg Research Team curates, analyze and publishes demographics and economic data from a variety of public and proprietary sources, each of which often includes multiple surveys and programs. The large majority of Neilsberg Research aggregated datasets and insights is made available for free download at https://www.neilsberg.com/research/.

Recommended for further research

This dataset is a part of the main dataset for New Wilmington Population by Year. You can refer the same here

Global population density from 1970 to 2100 per land grid cell. The data is licensed under CC-BY. The IMAGE-team would appreciate cooperation when data is used.