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rising from 90 m now to 110 m for 2030 and 2070 (see online Supplementary Information for more detail). Only areas with average wind speeds below this cut-off in four out of four quarters were excluded.

2.1.3. From suitable to available area The exclusions above yielded the suitable area for solar and wind power. To assess the area which will likely actually be available for electricity production we used a geographically nonspeciﬁc availability factor (see Table 2). This can be interpreted as representing the average share of the suitable area in a given grid cell, region, or country, which is likely to be actually available for a PV, CSP or wind power park in the given period. Because this availability factor is highly uncertain but has a large bearing on the overall potential, we spanned a range of possible values in our assumptions, denoted Low, Medium, High and varied the factor for the High case between industrialised and developing countries, and different land types. For solar electricity, availability factors were based on Trieb et al. (2009) for the Medium case and variations around this number for the Low and High cases. For on-shore wind, we tried to derive availability factors from case studies in Germany, Denmark and the Netherlands. We estimated currently installed wind power capacities to cover around 1–2% of suitable area in these countries (see Supplementary Information for the calculation behind these numbers). Given that these countries are not, on average, at the limit of their wind power density (although individual regions within the countries may be reaching the limits acceptable to the local population), we have assumed that this represents around 20–30% of the possible maximum available area, resulting in an availability factor of 5–6%. This is in line with another European study (EEA, 2009) postulating 4–5% availability. Based on these considerations, we used a range of 3–10% for our three scenarios and a much lower availability for forests. Since availability for offshore wind parks is today primarily impacted by competing use and perceived visual impact, the availability factor was varied by distance from shore (see Table 2). The factors were based on the following considerations: � Social acceptance is only expected to play a role <50 km from shore as wind farms at higher distances are not visible, therefore availability has been heavily restricted for distances <50 km from shore. Table 2 Availability factor for technologies on land (Ind. = industrialised, Dev. = developing country). Technology

Wind on-shore

Land class or distance from shore class

Forest

Availability (by case and country type) Low

Med.

Ind./Dev.

Ind./Dev.

Ind.

High Dev.

0.5%

1%

2%

2%

3%

6%

10%

20%

0.1%

0.5%

2%

5%

Agriculture Desert Grassland Barren land PV/CSP

Agriculture

� The Low case is based on the values used in another study (EEA, 2009), but leads to a more restricted area since that study started with a much larger (less constrained) suitable area. � The Medium and High cases assume full availability (100%) minus an (upper) estimate of areas for protection (Medium Case) or protection and shipping (High Case) which we did not have sufﬁcient data for to exclude above.

2.1.4. Resource cut-offs Although this study is not attempting to calculate economic potentials, it is instructive to translate the resource intensity cutoffs into approximate production cost values at least for our base year and 2030. These are shown in Table 3 with inputs derived from literature (Teske et al., 2011; Schlo¨mer et al., 2014) and assuming a lifetime of 20 years and a weighted cost of capital of 10%. Note that these approximate costs are higher than typical current costs, as they represent costs for low resource intensity areas and that actual production costs would be minimised on a project-by-project basis. 2.1.5. Building-based solar resource A GIS approach for assessing roof and fac¸ade area would carry a large uncertainty as the global GIS dataset only identiﬁes artiﬁcial surfaces at a 1 km Â 1 km scale, not differentiating between roofs on buildings and other structures. Instead we have used ﬂoor space to derive the roof and fac¸ade area suitable for solar resources as shown in Eq. (3). Aroof; faHade ð p; cÞ ¼ Pop ð p; c; uÞ Á

Afloor ð p; c; uÞ Pop

Â Ã Á F roof ðb; uÞ Á Sroof þ F faHade ðb; u; oÞ Á SfaHade

(3)

where Aroof = area of building roofs suitable for energy harvesting using PV; Afac¸ade = area of building fac¸ades suitable for energy harvesting using PV; Pop = population for each country per period and urbanisation level (United Nations, 2009); p = the study period (2010, 2030, 2070); c = country; u = urbanisation level; Aﬂoor/ Pop = ﬂoor area per capita for each country per period and urbanisation level; Froof = roof to ﬂoor ratio, dependent on building type and urbanisation level; Ffac¸ade = fac¸ade to ﬂoor ratio, dependent on building type, urbanisation level and orientiation; b = building type; o = orientation; Sroof/fac¸ade = suitability factor on roofs/fac¸ades, i.e. share of full roof/fac¸ade deemed suitable and available for energy harvesting. 2.1.5.1. Floor area. We calculated ﬂoor area for each country based on the ﬂoor area per capita and the population per country. The ﬂoor area per capita was ﬁrst estimated for ten reference countries and all other countries were mapped to these ten reference countries based on several characteristics (region, climate zone, GDP per population). The mapping is shown in the Supplementary Information online.

Table 3 Estimated production costs for the medium term at the resource cut-offs used here.

Grassland 0.5%

1%

3%

5%

Desert

2%

5%

8%

15%

0–10 km

4%

5%

5%

10–50 km

10%

30%

40%

50–200 km

25%

60%

80%

Barren land Wind off-shore

For more information about how these factors were established, see the Supplementary Information online.

Technology

Resource cut-off

Wind on-shore Wind off-shore CSP PV

6 m/s at hub height 8 m/s at hub height 1900 kWh/m2/a DNI [$800 kWh/m2/a GHI]

Approximate levelised costs in EUR2012/kWh 2010

2030

0.08–0.12 0.10–0.18 0.24–0.68 0.53–0.80

0.05–0.08 0.07–0.14 0.12–0.33 0.11–0.21