In the year 1500, the share of Western Europe's population living in urban areas was just six percent, but this rose to 31 percent by the end of the 19th century. Despite this drastic change, development was quite slow between 1500 and 1800, and it was not until the industrial revolution when there was a spike in urbanization. As Britain was the first region to undergo the industrial revolution, from around the 1760s until the 1840s, these areas were the most urbanized in Europe by 1890. The Low Countries Prior to the 19th century, Belgium and the Netherlands had been the most urbanized regions due to the legacy of their proto-industrial areas in the medieval period, and then the growth of their port cities during the Netherlands' empirical expansion (Belgium was a part of the Netherlands until the 1830s). Belgium was also quick to industrialize in the 1800s, and saw faster development than its larger, more economically powerful neighbors, France and Germany. Least-urban areas Ireland was the only Western European region with virtually no urbanization in the 16th and 17th century, but the industrial growth of Belfast and Dublin (then major port cities of the British Empire) saw this change by the late-1800s. The region of Scandinavia was the least-urbanized area in Western Europe by 1890, but it saw rapid economic growth in Europe during the first half of the following century.

This is the replication package for the following paper: Railways, Growth, and Industrialization in a Developing German Economy, 1829-1910. The paper studies the average and heterogeneous effects of railway access on parish-level population, income, and industrialization in Württemberg during the Industrial Revolution. The package contains data and code replicating the paper's tables and figures.

Although European economic history provides essentially no support for the view that education of the general population has a positive causal effect on economic growth, a recent paper by Becker, Hornung and Woessmann (Education and catch-up in the Industrial Revolution, 2011) claims that such education had a significant impact on Prussian industrialisation. I show that the instrumental variable they use to identify the causal effect of education is correlated with variables that influenced industrialisation but were omitted from their regression models. Once this specification error is corrected, the evidence shows that education of the general population had, if anything, a negative causal impact on industrialisation in Prussia.

Genetic variation is fundamental to population fitness and adaptation to environmental change. Human activities are driving declines in many wild populations and could have similar effects on genetic variation. Despite the importance of estimating such declines, no global estimate of the magnitude of ongoing genetic variation loss has been conducted across species. By combining studies that quantified recent changes in genetic variation across a mean of 27 generations for 91 species, we conservatively estimate a 5.4-6.5% decline in within-population genetic diversity of wild organisms since the industrial revolution. This loss has been most severe for island species, which show a 30% average decline. We identified taxonomic and geographic gaps in temporal studies that must be urgently addressed. Our results are consistent with single time-point meta-analyses, which indicated that genetic variation is likely declining. However, our results represent the first confirmation of a global decline, and provide an estimate of the magnitude of the genetic variation lost from wild populations.

The Anthropogenic Biomes of the World, Version 2: 1800 data set describes anthropogenic transformations within the terrestrial biosphere caused by sustained direct human interaction with ecosystems, including agriculture and urbanization c. 1800. Potential natural vegetation, biomes, such as tropical rainforests or grasslands, are based on global vegetation patterns related to climate and geology. Anthropogenic transformation within each biome is approximated using population density, agricultural intensity (cropland and pasture) and urbanization. This data set is part of a time series for the years 1800, 1800, 1900, and 2000 that provides global patterns of historical transformation of the terrestrial biosphere during the Industrial Revolution.

2007 marked the first year where more of the world's population lived in an urban setting than a rural setting. In 1960, roughly a third of the world lived in an urban setting; it is expected that this figure will reach two thirds by 2050. Urbanization is a fairly new phenomenon; for the vast majority of human history, fewer than five percent of the world lived in urban areas, due to the dependency on subsistence agriculture. Advancements in agricultural practices and technology then coincided with the beginning of the industrial revolution in Europe in the late 19th century, which resulted in waves of urbanization to meet the demands of emerging manufacturing industries. This trend was replicated across the rest of the world as it industrialized over the following two centuries, and the most significant increase coincided with the industrialization of the most populous countries in Asia. In more developed economies, urbanization remains high even as economies de-industrialize, due to a variety of factors such as housing availability, labor demands in service industries, and social trends.

Medieval European urbanization presents a line of continuity between earlier cities and modern European urban systems. Yet, many of the spatial, political and economic features of medieval European cities were particular to the Middle Ages, and subsequently changed over the Early Modern Period and Industrial Revolution. There is a long tradition of demographic studies estimating the population sizes of medieval European cities, and comparative analyses of these data have shed much light on the long-term evolution of urban systems. However, the next step—to systematically relate the population size of these cities to their spatial and socioeconomic characteristics—has seldom been taken. This raises a series of interesting questions, as both modern and ancient cities have been observed to obey area-population relationships predicted by settlement scaling theory. To address these questions, we analyze a new dataset for the settled area and population of 173 European cities from the early fourteenth century to determine the relationship between population and settled area. To interpret this data, we develop two related models that lead to differing predictions regarding the quantitative form of the population-area relationship, depending on the level of social mixing present in these cities. Our empirical estimates of model parameters show a strong densification of cities with city population size, consistent with patterns in contemporary cities. Although social life in medieval Europe was orchestrated by hierarchical institutions (e.g., guilds, church, municipal organizations), our results show no statistically significant influence of these institutions on agglomeration effects. The similarities between the empirical patterns of settlement relating area to population observed here support the hypothesis that cities throughout history share common principles of organization that self-consistently relate their socioeconomic networks to structured urban spaces.

The Anthropogenic Biomes of the World, Version 2: 1900 data set describes anthropogenic transformations within the terrestrial biosphere caused by sustained direct human interaction with ecosystems, including agriculture and urbanization c. 1900. Potential natural vegetation, biomes, such as tropical rainforests or grasslands, are based on global vegetation patterns related to climate and geology. Anthropogenic transformation within each biome is approximated using population density, agricultural intensity (cropland and pasture) and urbanization. This data set is part of a time series for the years 1900, 1900, 1900, and 2000 that provides global patterns of historical transformation of the terrestrial biosphere during the Industrial Revolution.

Uruguay National: ISIC Rev 4: Manufacturing data was reported at 10.800 % in Sep 2018. This records an increase from the previous number of 9.800 % for Aug 2018. Uruguay National: ISIC Rev 4: Manufacturing data is updated monthly, averaging 11.500 % from Jan 2011 (Median) to Sep 2018, with 93 observations. The data reached an all-time high of 13.600 % in Jun 2013 and a record low of 9.700 % in Jan 2018. Uruguay National: ISIC Rev 4: Manufacturing data remains active status in CEIC and is reported by National Institute of Statistics. The data is categorized under Global Database’s Uruguay – Table UY.G004: Distribution of Working Population.

In the year 1800, approximately five percent of the world's population lived in urban areas of 10,000 people or more. At this time, the world's population was just under one billion people, and the industrial revolution was in its early stages in Western Europe and North America. As industrialization spread across the world, urbanization rates rose accordingly. In 2021, the global urbanization rate was approximately 56 percent.

The available data are intended to show the distribution of the economically active population of the cities and districts in the individual economic sectors in North Rhine-Westphalia. The development of the working population in the territory of North Rhine-Westphalia is reported primarily with the help of the characteristic values, which are not available annually in the official statistics but only at periods of comprehensive occupational censuses since 1871. Due to the extensive territorial changes in the 120-year period under review, which thus also cover a period prior to the state´s existence, the comments are of particular importance. Due to the considerable scope of the annotations on territorial changes they are not listed in the table header but they are available as a downloadable PDF file.
The data can be found in HISTAT under the topic Population and refer to the following administrative districts with their city districts, independent cities and rural districts:01 Administrative district of Aachen02 Arnsberg administrative district03 Düsseldorf administrative district 04 Cologne administrative district 05 Minden or Detmold administrative district 06 Münster administrative district 07 Total area or NRW In the censuses of the years 1882, 1895 and 1907 the term ´Berufspersonen´, i.e. ´working persons in a learned profession´, was still used. In the censuses of the years 1925, 1939, 1950 and 1961 the term ´Erwerbspersonen´, i.e. ´occupation persons, labour force, working population´ was used. In the 1970 census, the term “Erwerbstätige”, i.e. ´employed, employed person´ was used. The censuses from 1882 to 1907 were purely occupational censuses that were conducted independently of the population censuses. The primary occupation of the population was surveyed, but not the commercial branch of the enterprise in which the respondent was employed. Temporarily unemployed persons were also classified according to their last occupation. In contrast, family helpers were only incompletely included in the censuses. The initial figures for the female occupational population and in particular the women´s rate of 1882 are therefore too low in comparison with later data. The correlation between occupation and gainful employment that still applies to the first surveys is being lost more and more as the Industrial Revolution progresses (i.e. in the later period not all employed persons had a job in their learned profession or in a company belonging to the branch of the learned profession). From 1925 onwards, the primary focus was on employment in a particular economic branch, covered by the economic classification, but temporary unemployed persons continued to be included, so that not only the actual working population, but all the labour force were covered. It was only in 1970 that the unemployed were not included. The four economic sectors from 1970 are decisive for the allocation of all counting results from 1882 onwards to the economic departments, as the terms of this economic classification make historical comparability possible.

In 2019, the world and regional situation is forecasted to continue to be complicated and unpredictable. The world economy continues to recover growth, trade wars between major countries, the 4th Industrial Revolution is having a strong impact on many aspects, along with population growth and demand. The consumption of agricultural products in the world is expected to increase along with quality and food safety requirements.

The available data are intended to show the distribution of the economically active population of the cities and districts in the individual economic sectors in North Rhine-Westphalia. The development of the working population in the territory of North Rhine-Westphalia is reported primarily with the help of the characteristic values, which are not available annually in the official statistics but only at periods of comprehensive occupational censuses since 1871. Due to the extensive territorial changes in the 120-year period under review, which thus also cover a period prior to the state´s existence, the comments are of particular importance. Due to the considerable scope of the annotations on territorial changes they are not listed in the table header but they are available as a downloadable PDF file.

The data can be found in HISTAT under the topic Population and refer to the following administrative districts with their city districts, independent cities and rural districts: 01 Administrative district of Aachen 02 Arnsberg administrative district 03 Düsseldorf administrative district
04 Cologne administrative district
05 Minden or Detmold administrative district
06 Münster administrative district
07 Total area or NRW

In the censuses of the years 1882, 1895 and 1907 the term ´Berufspersonen´, i.e. ´working persons in a learned profession´, was still used. In the censuses of the years 1925, 1939, 1950 and 1961 the term ´Erwerbspersonen´, i.e. ´occupation persons, labour force, working population´ was used. In the 1970 census, the term “Erwerbstätige”, i.e. ´employed, employed person´ was used.

The censuses from 1882 to 1907 were purely occupational censuses that were conducted independently of the population censuses. The primary occupation of the population was surveyed, but not the commercial branch of the enterprise in which the respondent was employed. Temporarily unemployed persons were also classified according to their last occupation. In contrast, family helpers were only incompletely included in the censuses. The initial figures for the female occupational population and in particular the women´s rate of 1882 are therefore too low in comparison with later data.

The correlation between occupation and gainful employment that still applies to the first surveys is being lost more and more as the Industrial Revolution progresses (i.e. in the later period not all employed persons had a job in their learned profession or in a company belonging to the branch of the learned profession). From 1925 onwards, the primary focus was on employment in a particular economic branch, covered by the economic classification, but temporary unemployed persons continued to be included, so that not only the actual working population, but all the labour force were covered. It was only in 1970 that the unemployed were not included.

The four economic sectors from 1970 are decisive for the allocation of all counting results from 1882 onwards to the economic departments, as the terms of this economic classification make historical comparability possible.

It is estimated that Europe had an urbanization rate of approximately 8.5 percent in the year 1800. The Netherlands and Belgium were some of the most heavily urbanized regions, due the growth of port cities such as Rotterdam and Antwerp during Netherlands' empirical expansion, and the legacy of urbanization in the region, which stems from its wool and craft industries in medieval times. Additionally, the decline of their agricultural sectors and smaller territories contributed to a lower rural population. Scotland and England had also become more urban throughout the British Empire's growth, although the agricultural revolution of the previous two centuries, along with the first industrial revolution, then led to more rapid urbanization during the 19th century. In contrast, there was a large imbalance between the east and west of the continent; the two largest empires, Austria and Russia, had the lowest levels of urbanization in Europe in 1800, due to their vast territories, lower maritime presence, and lack of industrial development.

Population Employed: NENE: ISIC Rev. 4: Manufacturing data was reported at 900.959 Person th in Oct 2025. This records a decrease from the previous number of 909.843 Person th for Sep 2025. Population Employed: NENE: ISIC Rev. 4: Manufacturing data is updated monthly, averaging 874.810 Person th from Mar 2013 (Median) to Oct 2025, with 152 observations. The data reached an all-time high of 959.785 Person th in Nov 2017 and a record low of 744.755 Person th in Jul 2020. Population Employed: NENE: ISIC Rev. 4: Manufacturing data remains active status in CEIC and is reported by National Institute of Statistics. The data is categorized under Global Database’s Chile – Table CL.G: Employment: by Industry: NENE.

Lake and river ice seasonality (dates of ice freeze and breakup) responds sensitively to climatic change and variability. We analyzed climate-related changes using direct human observations of ice freeze dates (1443-2014) for Lake Suwa, Japan, and of ice breakup dates (1693-2013) for Torne River, Finland. We found a rich array of changes in ice seasonality of two inland waters from geographically distant regions: namely a shift towards later ice formation for Suwa and earlier spring melt for Torne, increasing frequencies of years with warm extremes, changing inter-annual variability, waning of dominant inter-decadal quasi-periodic dynamics, and stronger correlations of ice seasonality with atmospheric CO2 concentration and air temperature after the start of the Industrial Revolution. Although local factors, including human population growth, land use change, and water management influence Suwa and Torne, the general patterns of ice seasonality are similar for both systems, suggesting that global processes including climate change and variability are driving the long-term changes in ice seasonality.

Influence of industrial robot application on the employment of the floating population in universities or above.

Humans have exploited the earth's metal resources for thousands of years leaving behind a legacy of toxic metal contamination and poor water quality. The southwest of England provides a well-defined example, with a rich history of metal mining dating to the Bronze Age. Mine water washout continues to negatively impact water quality across the region where brown trout (Salmo trutta L.) populations exist in both metal-impacted and relatively clean rivers. We used microsatellites to assess the genetic impact of mining practices on trout populations in this region. Our analyses demonstrated that metal-impacted trout populations have low genetic diversity and have experienced severe population declines. Metal-river trout populations are genetically distinct from clean-river populations, and also from one another, despite being geographically proximate. Using approximate Bayesian computation (ABC), we dated the origins of these genetic patterns to periods of intensive mining activity. The historical split of contemporary metal-impacted populations from clean-river fish dated to the Medieval period. Moreover, we observed two distinct genetic populations of trout within a single catchment and dated their divergence to the Industrial Revolution. Our investigation thus provides an evaluation of contemporary population genetics in showing how human-altered landscapes can change the genetic makeup of a species.

Lake and river ice seasonality (dates of ice freeze and breakup) responds sensitively to climatic change and variability. We analyzed climate-related changes using direct human observations of ice freeze dates (1443–2014) for Lake Suwa, Japan, and of ice breakup dates (1693–2013) for Torne River, Finland. We found a rich array of changes in ice seasonality of two inland waters from geographically distant regions: namely a shift towards later ice formation for Suwa and earlier spring melt for Torne, increasing frequencies of years with warm extremes, changing inter-annual variability, waning of dominant inter-decadal quasi-periodic dynamics, and stronger correlations of ice seasonality with atmospheric CO2 concentration and air temperature after the start of the Industrial Revolution. Although local factors, including human population growth, land use change, and water management influence Suwa and Torne, the general patterns of ice seasonality are similar for both systems, suggesting that global processes including climate change and variability are driving the long-term changes in ice seasonality.

The earliest point where scientists can make reasonable estimates for the population of global regions is around 10,000 years before the Common Era (or 12,000 years ago). Estimates suggest that Asia has consistently been the most populated continent, and the least populated continent has generally been Oceania (although it was more heavily populated than areas such as North America in very early years). Population growth was very slow, but an increase can be observed between most of the given time periods. There were, however, dips in population due to pandemics, the most notable of these being the impact of plague in Eurasia in the 14th century, and the impact of European contact with the indigenous populations of the Americas after 1492, where it took almost four centuries for the population of Latin America to return to its pre-1500 level. The world's population first reached one billion people in 1803, which also coincided with a spike in population growth, due to the onset of the demographic transition. This wave of growth first spread across the most industrially developed countries in the 19th century, and the correlation between demographic development and industrial or economic maturity continued until today, with Africa being the final major region to begin its transition in the late-1900s.