The IPCC SRES emissions scenarios (A1, A2, B1, B2) used population projections from both the United Nations (UN) and the International Institute for Applied Systems Analysis (IIASA).
General Background Information for the IIASA Population Projections
The SRES A1-B1 and A2 population scenarios for world regions were adopted in 2000 from population projections realized at IIASA in 1996 and published in Lutz (1996). The IPCC SRES A1 and B1 scenarios both used the same IIASA "rapid" fertility transition projection, which assumes low fertility and low mortality rates. The SRES A2 scenario used a corresponding IIASA "slow" fertility transition projection (high fertility and high mortality rates).
Both IIASA low and high projections are done for 13 world regions, which are: North Africa, Sub-Saharan Africa, China and Centrally Planned Asia, Pacific Asia, Pacific OECD, Central Asia, Middle East, South Asia, Eastern Europe, European part of the former Soviet Union, Western Europe, Latin America, North America. Detailed scenario description and results for those regions are available at: http://www.iiasa.ac.at/Research/POP/IPCC/index.html.
It is important to note that, since the SRES models generally had a different regional breakdown compared to the IIASA population projections, each model had to adapt the IIASA projections to their model regions, as best they could. This process probably introduced some small differences into the regional population totals from the SRES models as compared to the original IIASA data. This source of discrepancy will be seen in comparison tables between the SRES models and IIASA population totals.
Downscaling of SRES A1-B1 and A2 regional population projections to country-level population figures
In response to requests for country-level population projections, consistent with the IIASA regional projections used in SRES, the downscaling of the regional total population figures to national ones for the SRES projection period 1990-2100, and for scenarios A1-B1 and A2 was done. The downscaling from region to country level of the IIASA scenarios is based on the calculation of the fractional shares of each country into regions according to the latest country population estimates and projections for 1990-2050, from the United Nations 2000 Revision. For each SRES population scenario, the United Nations variant that was the closest to the SRES scenario was chosen as the starting point for the population downscaling. For scenario A2, the United Nations 2000 high variant was used. According to this variant, the world population in 2050 will be 10.9 billions where as the A2 scenario gives a population of 11.3 billion 2050. For scenarios A1 and B1 the United Nations medium variant was chosen: according to this variant the world population in 2050 will be 9.3 billion whereas the SRES A1/B1 scenarios estimated that population will be 8.7 billion in 2050.
The United Nations country age-specific populations were allocated into the 11 IIASA SRES regions (originally, there were 13 regions in the IIASA projections, but the former Soviet Union and Central Asia are brought together as well as Northern America and Middle East).Then, the IIASA population project calculated the fractional share of each age group (five-year age groups from 0 to 100+) for each country into the total of the region age structure reconstituted from United Nations 2000 in five-year period from 1990 to 2050. These shares were applied to the age structure of the population of the region in scenario A1-B1 and A2 from 1990 to 2050. After 2050, the shares of each country (by age groups) were kept constant at the 2050 level and applied to the regional population from 2050 to 2100.
We also added 1990 population estimates from the UN Statistics Division "Common Database".
Population Downscaling Discontinuities:
Artifacts arise with the present downscaling procedure. The problems occur because of the post-2050 transition to the uniform growth rate method. If a country is projected by the UN 2000 Revision to have a declining (or growing) population at 2050 but falls within a larger region that has a growing (or declining) population after 2050, a discontinuity will occur. For example, Cuba and Barbados are problematic in this regard and should not be used. Other countries may have a slower or faster projected growth rate at 2050 than the regional projection. In these cases, the population slope for such countries will show a discontinuity, post-2050.
If we attempt to remove these discontinuities on a case-by-case basis, such as by using additional country-specific information, or even deleting them from the database altogether, then the regional totals will likely develop discrepancies with those in the SRES report. Overall there are clear artifacts associated with the simplicity of the linear downscaling approach, and they can only be removed with more sophisticated treatments, or by relaxing constraints on consistency with the SRES report.
A1 Population Downscaling Compared with SRES Regional Totals: The percent differences between the A1 downscaling and the SRES regional population totals are shown on the accompanying online tab spreadsheet. As with B2, the differences are very small, but in a few cases rise to 1-2%. As noted above, the marker model for the A1 scenario (AIM model) has a different regional disaggregation than the IIASA population projection. In adapting the IIASA population totals to the AIM model, small differences in population probably were introduced and show up in our comparison.
B1 Population Downscaling Compared with SRES Regional Totals: The B1 population downscaling regional sums (shown on the accompanying online tab spreadsheet) show reasonable agreement with the SRES marker model (IMAGE from RIVM). It should be noted for this projection that IMAGE placed Turkey and Cyprus in the Middle East region, as opposed to OECD, as is typical with the other SRES marker models. When calculating the regional sums for B1 we therefore placed Turkey and Cyprus in the Middle East. For all the other population projections it was placed in OECD. The marker model for the B1 scenario (IMAGE model) has a different regional disaggregation than the IIASA population projection. In adapting the IIASA population projections to the RIVM model, small differences in population estimates were probably introduced.
A2 Population Downscaling Compared with SRES Regional Totals: The A2 population downscaling again compares generally well (shown on the accompanying online tab spreadsheet), but with some isolated years of discrepancies of 5-6%. This again is probably due to small differences introduced by the marker model in this case (ASF model), when it adapted the IIASA regional population projections to the different ASF model regions. In addition, the ASF model computed results in 25-year intervals so the errors shown may also be due to interpolation factors.
For further details on the country population results for scenarios A1-B1 and A2, check on IIASA's website.