This statistic depicts a projection of the global population aged 65 and over between 2010 and 2050, sorted by geographic area. In 2025, there will be some *** million people aged 65 and over in Europe. That would be some ** percent of the total European population.

The industrial and energy sectors in Asia demanded approximately 316,000 cubic meters of water only in 2010, and this figure is expected to double by 2050, when the water consumption from these sectors reaches some 760,000 cubic meters annually.

The Groundswell Spatial Population and Migration Projections at One-Eighth Degree According to SSPs and RCPs, 2010-2050, data set provides a baseline population distribution for 2010 and projections from 2020 to 2050, in ten-year increments, of population distribution and internal climate-related and other migration. The projections are produced using the NCAR-CIDR Spatial Population Downscaling Model developed by the CUNY Institute for Demographic Research (CIDR) and the National Center for Atmospheric Research (NCAR). The model incorporates assumptions based on future development scenarios (Shared Socioeconomic Pathways or SSPs) and emissions trajectories (Representative Concentration Pathways or RCPs). The SSPs include SSP2, representing a middle-of-the road future, and SSP4, representing an unequal development future. Climate models using low and high emissions scenarios, RCP2.6 and RCP8.5, then drive climate impact models on crop productivity and water availability from the Inter-Sectoral Impacts Model Intercomparison Project (ISIMIP). Sea-level rise impacts in the coastal zone are estimated to be 1 meter under RCP2.6 and 2 meters under RCP8.5, to account for potential storm surge or coastal flooding. Three scenarios are generated, a pessimistic reference scenario combining SSP4 and RCP8.5, a more climate-friendly scenario combining SSP4 and RCP2.6, and a more inclusive development scenario combining SSP2 and RCP8.5, and each scenario represents an ensemble of four model runs combining different climate impact models. The modeling work was funded and developed jointly with The World Bank, and covers most World Bank client countries, with reports released in 2018 and 2021 that address different regions and provide full methodological details.

This statistic displays a timeline with estimations of the total population in Chile from 2010 to 2050, broken down by gender. By 2050, the source projected a total male population of 10.3 million people in the South American country.

Modelled average travel distances in 2010 and 2050 according to LUISA projections and a spatial interaction model (unit:meters). The results are based on a number of simulation-specific assumptions but are instrumental in informing the relative potential for sustainable urban transport.

A model which allows users to create alternative pathways for the UK from 2010 to 2050 and see the consequences for energy demand, supply and greenhouse gas emissions.

This statistic depicts the projected average annual growth in Medicare enrollment in the United States from 2010 to 2050. For the period 2010-2020, the average annual growth is expected to be three percent.

Analysis of ‘UDP - Urban proportion by metro regions, 2010 and 2050 (JRC LUISA Trend Scenario 2016)’ provided by Analyst-2 (analyst-2.ai), based on source dataset retrieved from http://data.europa.eu/88u/dataset/jrc-luisa-udp-urbanprop-trend-2016 on 17 January 2022.

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

Urban population proportion. Proportion of the population living in Local Administrative Units - 2 (LAU2s) classified as cities, towns and suburbs. Classification of LAU2s as cities, towns and suburbs is based on the LUISA degree of urbanization projections. The population that live in cities, towns and suburbs is calculated based on total LAU2 populations, not the population of grids.

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

These data provide decadal estimates of port areas required based on future predictions of trade to 2050 under four climate-related policy scenarios. Also included are projections of relative sea-level rise and cost estimates for (i) adaptation to the anticipated sea-level rise under each scenario, and (ii) construction of any new port area required. The resilience of shipping infrastructure and trade to future climate impacts has implications for shipping globally and locally. As a service to other sectors, it will need to adjust to new patterns of economic growth whilst, at the same time, dealing with its own climate challenges. Key among sector concerns is the provision of suitable port infrastructure capable of handling the transfer of sea-borne trade to land based transport systems.

Our vision is to create an enduring, multidisciplinary and independent research community strongly linked to industry and capable of informing the policy making process by developing new knowledge and understanding on the subject of the shipping system, its energy efficiency and emissions, and its transition to a low carbon, more resilient future. Shipping in Changing Climates (SCC) is the embodiment of that vision: a multi-university, multi-disciplinary consortium of leading UK academic institutions focused on addressing the interconnected research questions that arise from considering shipping's possible response over the next few decades due to changes in: - climate (sea level rise, storm frequency) - regulatory climate (mitigation and adaptation policy) - macroeconomic climate (increased trade, differing trade patterns, higher energy prices) Building on RCUK Energy programme's substantial (~2.25m) investment in this area: Low Carbon Shipping and High Seas projects, this research will provide crucial input into long-term strategic planning (commercial and policy) for shipping, in order to enable the sector to transition the next few decades with minimum disruption of the essential global services (trade, transport, economic growth, food and fuel security) that it provides.

This dataset is a raster of predicted suitable bioclimate using statistical correlations between known habitat and current climate (1950-1999 average) , and then projecting that niche into the future. The future timeslices used are 2020s, which is an average of 2020-2029, and 2050s which is 2050-2059. The Values 1-6 show the degree of model agreement (For example: areas with a value of 1 is where only 1 GCM predicted suitability; pixels with a value of 6 are where 6 GCMs predicted suitability, ect). *see Maxent output pdfs for more details about model inputs and settings.

According with the enviroGRIDS scenarios, we analyze the UN projection variants for population, and we propose a methodology for the downscaling from national to regional level (NUTS2). Results include urban and total population trends over the period 2010-2050 for the 214 enviroGRIDS regions, consistent with BS HOT, BS ALONE, BS COOP and BS COOL scenarios. Data sources: Demographic data (total population both male and female sexes, for urban and rural areas) were collected from international organisations (UN and Eurostat), national statistical offices, and by partners contribution (Deliverable 3.1, 3.5). http://www.envirogrids.net/index.php?option=com_content&view=article&id=23&Itemid=40

This statistic displays the projected Muslim population of Europe from 2010 to 2050, compared with that of non-Muslims. For the 2050 projections, three different scenarios are presented, one for zero migration to Europe, one for medium migration and the last for a high level of immigration. In the scenario where zero-migration occurs the total non-Muslim population of Europe would actually decrease from ****** million people to ****** million people. In the high migration scenario, Muslims are predicted to number ***** million people, in which the total non-Muslim population of Europe is ****** million.

Annual projections of habitat suitability for Komodo dragons: 2010 to 2050.https://doi.org/10.1002/ece3.6705

🇬🇧 영국 English A model which allows users to create alternative pathways for the UK from 2010 to 2050 and see the consequences for energy demand, supply and greenhouse gas emissions.

This dataset is a raster of predicted suitable bioclimate using statistical correlations between known habitat and current climate (1950-1999 average) , and then projecting that niche into the future. The future timeslices used are 2020s, which is an average of 2020-2029, and 2050s which is 2050-2059. The Values 1-6 show the degree of model agreement (For example: areas with a value of 1 is where only 1 GCM predicted suitability; pixels with a value of 6 are where 6 GCMs predicted suitability, ect). *see Maxent output pdfs for more details about model inputs and settings.

This dataset is a raster of predicted suitable bioclimate using statistical correlations between known habitat and current climate (1950-1999 average) , and then projecting that niche into the future. The future timeslices used are 2020s, which is an average of 2020-2029, and 2050s which is 2050-2059. The Values 1-6 show the degree of model agreement (For example: areas with a value of 1 is where only 1 GCM predicted suitability; pixels with a value of 6 are where 6 GCMs predicted suitability, ect). *see Maxent output pdfs for more details about model inputs and settings.

This dataset is a set of 24 gridded netcdf files, each including data describing a total of 14,400 widespread flooding events across mainland GB, with event selection based on a peaks-over-threshold approach. The data describes peak river flow in m3/s and the associated annual probability of exceedance for each 1km grid-square on the GB river network. The data is extracted from daily time series data from the Grid-to-Grid model, using UKCP18 12km regional projections from 12 members of a perturbed parameter ensemble, over the periods Dec 1980 – Nov 2010 and Dec 2050 – Nov 2080 (based on 360-day years). Multi-day events were summarised by taking cell-wise flow maxima. This data was generated for use in analysis of risk through catastrophe modelling using the Future Flows Explorer. It was generated and interpreted by UKCEH, working with Sayers & Partners Consultancy, as part of the AquaCAT project, part of the UK Climate Resilience Programme.

By applying Supply-demand Balance Analysis, the water resource supply and demand of the whole river basin and each county or district were calculated, based on which the vulnerability of the water resources system of the basin was evaluated. The IPAT equation was used to set a future water resource demand scenario, setting variables such as future population growth rate, economic growth rate, and unit GDP water consumption to establish the scenario. By taking 2005 as the base year and using assorted forecasting data of population size and economic scale, the future water demand scenarios of various counties and cities from 2010 to 2050 were forecast. By applying the basic structure of the HBV conceptual hydrological model of the Swedish Hydrometeorological Institute, a model of the variation tendency of the basin under climate change was designed. The glacial melting scenario was used as the model input to construct the runoff scenario under climate change. According to the national regulations of the water resources allocation of the basin, a water distribution plan was set up to calculate the water supply comprehensively. Considering of the supply and demand situation, the water resource system vulnerability was evaluated by the water shortage rate. By calculating the (grain production) land pressure index of the major counties and cities in the basin, the balance of supply and demand of land resources under the climate change, glacial melt and population growth scenarios was analyzed, and the vulnerability of the agricultural system was evaluated. The Miami formula and HANPP model were used to calculate the human appropriation of net primary biomass and primary biomass in the major counties and cities for the future, and the vulnerability of ecosystems from the perspective of supply and demand balance was assessed.

This statistic represents the projected capital costs of a typical nuclear power plant in the United States in 2008, 2010 and 2050. In 2008, the capital costs of a nuclear power plant amounted to around 6,230 U.S. dollars per kilowatt hour.

Total Jobs by Industry, Historic 2010 to 2020 and Projected 2025 to 2050 in Maryland by Industry and by Place of Work.