Population of Europe: Difference between revisions

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==Result==
==Result==
The current result is based on data obtained from IC. Not final version, though.


{{resultlink}}
{{resultlink}}

Revision as of 13:45, 12 July 2010


Population of Europe estimates the size of the population in Europe in 2000-2050.D↷

Scope

What is the the number of people in the countries of the European Union and on the 50x50 km Emep grid, for the years 2000, 2010, 2020, 2030, 2050, disaggregated by age (5 year age groups), gender and spatial location of residence?

Definition

Data

Data available:


Surveys were performed as a basis for the population data sources applied in the assessment (for past estimations).

Data used: Data sources applied are: a) CIESIN/SEDAC data (http://sedac.ciesin.columbia.edu/gpw/global.jsp) b) UN data (http://esa.un.org/unpp/index.asp); c) high resolution data provided by Danielle from IC; d) Eurostat data.

Ad a) Data is available for the years 1990-2015 in 5 year steps. Numbers are given as total number per grid cell (not stratified). An extrapolation of the current population growth to 2015 was undertaken to result in a projection of the population in the year 2015. Data is available on a grid with the following grid sizes: 1°, 0.5°, 0.25°, and 2.5'. Ad b) Data is available for the years 1950-2050 in 5 year steps. It is available for all countries. Data is stratified by 5 year age groups and gender. Three different growth rates are available. Ad c) ... .

Causality

  • The number of people living in a grid cell, or country, is dependent on the birth rate, the mortality rate and the migration rate.

Unit

#

Formula

Alternative 1 is used.

Alternative 1

This alternative uses existing IIASA data.

  • Analytica model for computations: IIASA World Population Program.ANA.
  • The data comes directly from IIASA population in Europe by country.
  • Problem: The ready-made estimates are only for years 2007 and 2030. Solution: Ignore, start with those two years.
  • Problem: IIASA has also population projections for 2008-2100 for each year, but this is only at the level of "Western Europe". This could be scaled somehow. Western Europe is smaller than EU-30, because some Eastern Europe countries belong to the latter. Therefore, the totals do not match. In addition, the population trends are different in different countries, so that it is not good to just apply the same trend in each country. Some fuzzy algorithm could be used, but that takes time because it is not readily available. Maybe we should develop a simple, generic fuzzy algorithm for combining conflicting data? Solution: Ignore time trend data.

Alternative 2

  • For national data the UN data is used directly.
  • For the gridded data the CIESIN/SEDAC data is used, which is on the grid. The UN growth rates from the UN data are applied to the gridded data. For the subgroup stratification source c) is applied. For gridded data the following steps are performed:
    • Step 1: The Gridded World Population (GWP) data for 2000 is taken as basis for each 50x50 km Emep grid cell.
    • Step 2: In a next step, if necessary, it is scaled to fit the country totals GWP of 2000 with those of the 2000 UN data.
    • Step 3: Then, the fine resolution data souce c) \wichtig{include source} , which is based on the year 2001, is used to calculate the shares of each subgroup (age and gender), specifically for each single grid cell!
    • Step 4: Now the growth rates for future years are estimated: Growth rates (per country) of the UN data from 2000 to 2010, 2020, 2030 and 2050 are calculated for each population sub group separately (to allow for shifts in the percentages of the subgroups instead of using the growth rate for the total population).
    • Step 5: The growth rates are now applied, for each year, to the sub groups of the base year.

Given the numbers for the sub groups and years, the percentages for age groups, the percentages for working/non-working status:

Let the following.

  • Country is the index for European countries. There should be a row "Sea" for sea areas.
  • Year is the index for years considered (selected years between 2000-2050)
  • Sex is the index for sex (Male or Female)
  • EMEP is the index for EMEP grid identifiers (1 - ca. 3000)
  • Age is the index for 5-year age groups of the population.
  • Population_by_country is the total population in Europe, indexed by country, age group, and year.
  • Country_emep is an indicator (indexed by EMEP and Country), which tells the fraction of each EMEP grid cell that belongs to the specified country. This sums up to 1 when summed up over Country.
  • Population_emep is the current population disaggregated into the EMEP grid.
  • Population_ic is the disaggregated population data for 2001. This should be first aggregated to EMEP grid (if that's what we want). This is indexed by age and sex.

The Analytica code for disaggretagion could look like this D↷:

<anacode> var a:= population_emep*country_emep; a:= a/sum(a,emep); a:= a*population_by_country </anacode>


See also

Result

The current result is based on data obtained from IC. Not final version, though.

{{#opasnet_base_link:Op_en3017}}


See also

References

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