Background information on the IPCC population scenarios
The IPCC (2000) 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) (http://www.iiasa.ac.at/Research/POP/index.html) (Table 1).
Table 1: The IPCC SRES population scenarios
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SRES
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Data source
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http://www.iiasa.ac.at/Research/<stockticker>POP</stockticker>/index.html
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A1
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IIASA .rapid demographic transition model
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Population growth was assumed to be low (~ 6.5 billion in 2100) because of the importance of development in bringing about the demographic transition from high to low fertility in developing countries with fertility currently above replacement level. Low mortality is assumed to correlate with the low fertility
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A2
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IIASA .slow demographic transition model
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Population growth in A2 is high (15 billion by 2100) because of the reduced financial resources available to address human welfare, child and reproductive health and education. The relatively higher fertility rates in this scenario are assumed to correlate with higher mortality rates
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B1
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IIASA .rapid. demographic model
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Population growth is again low
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B2
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UN 1998 Medium Long Range Projection (based on 1996 revision)
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Population growth is considered to be medium in this scenario (10.3 billion in 2100). For this case the SRES used the UN 1998 medium long-range projection as described. This is the only SRES scenario using a medium population growth projection with replacement level fertility in the long-run.
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NOTE: The SRES OECD region includes Canada, Guam, Puerto Rico, United States of America, Virgin Islands, Andorra, Austria, Azores, Belgium, Canary Islands, Channel Islands, Cyprus, Denmark, Faeroe Islands, Finland, France, Germany, Gibraltar, Greece, Greenland, Iceland, Ireland, Isle of Man, Italy, Liechtenstein, Luxembourg, Madeira, Malta, Monaco, the Netherlands, Norway, Portugal, Spain, Sweden, Switzerland, Turkey
Baseline population data
Baseline population data are available from:
- London: Office of National Statistics (ONS)
- Rome: the National Institute of Statistics, Italy (ISTAT)
- Helsinki: City of Helsinki Urban Facts
WP3.7 Methodology: downscaling SRES-population scenarios from OECD-level to the city-level
Figure 1 provides an illustration of our methodology.
A). First, we obtained the SRES population projections and the UN Population Prospects 2006 Revision’s projections for the OECD region.
- The SRES OECD projections are available for total population and 4 different scenarios (A1, A2, B1 and B2). The time horizon is 2100.
- The UN 2006 population projections provide population data for both sexes and 5-year age groups, for each year up to 2050, and for several variants such as medium, high and low population.
B). For each SRES population scenario for the OECD region (2050), the United Nations variant (medium, high or low) that was the closest to the SRES scenario was chosen as the starting point for the population downscaling:
- SRES- A1 (A1B Illustrative Marker with model AIM) was matched withthe UN 2006 medium variant. According to this UN-variant the OECD population in 2050 will be 1.08 billion whereas the SRES A1 scenario ( (estimated that population will be 1.08 7 billion in 2050 (UN 2006 medium variant= 100% *A1).
- SRES-A2(A2 Illustrative Marker with model ASF) was matched withthe UN 2006 high variant, as A2 is characterized by high population growth. According to this UN-variant, the OECD population in 2050 will be 1.25 billions where as the A2 scenario gives a population of 1.13 billion 2050. (UN 2006 high variant= 109% *A2).
- SRES-B1 (B1 Illustrative Marker with model IMAGE) was matched with UN 2006 medium variant. According to this UN variant the OECD population (minus Turkey and Cyprus) in 2050 will be 0.98 billion whereas the SRES B1 scenario estimated that population will be 1.00 billion in 2050 (UN 2006 medium variant= 98% *B1). We accounted fro the fact that the IMAGE model placed Turkey and Cyprus in the Middle East region, as opposed to OECD, as is typical with the other SRES marker models
Please note that the CIESIN made the same decisions based on the UN 2002 population revision data. Center for International Earth Science Information Network (CIESIN), 2002. Country-level Population and Downscaled Projections based on the B2 Scenario, 1990-2100, [digital version]. Palisades, NY: CIESIN, Columbia University. http://www.ciesin.columbia.edu/datasets/downscaled.
C). For each city, we have accordingly translated the selected UN national population scenarios (UN Population Prospects 2006 Revision) to city-level population projections (2030, 2050) in the following steps:
- Step 1: Linking the selected UN 2006 projections with available national projections
- We identified available population projections provided by national institutes.
- For each UN 2006 scenario (national level), the national projection that was closest to the UN projection was identified.
- Step 2: Linking/downscaling selected national projections with/to city level population projections
- We identified relevant - population projections (preferably city level).
- For each national projection selected in step 1, we either a) selected the associated city-level projection (if available), or b) downscaled the associated sub-national projection to city level. Assuming that the population ratio of city\sub-national area remains the same to baseline year 2001.
The WP3.7-UVR full assessment report provides worksheets describing how this methodology has been applied to each of the three case studies (London, Rome, Helsinki).
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