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Fig. 1. Logic used to classify grid cells as with or without infrastructure for the distance class grouping.

� An existing meta-analysis from 2008 published by REN21 was used to ﬁll gaps in the projected data for large hydropower (REN21, 2008) � The total size of water bodies in a country was used as a proxy to infer potential for small hydropower for countries without reported potentials (FAO, 2007). The numbers reported in the sources above at country level were combined with additional sources for individual countries (REN21, 2008; DLR, 2006; Fulton et al., 2011; SETIS, 2011) to arrive at estimates for the potential for hydroelectricity split into ‘large’ and ‘small’ hydroelectricity as follows: For large hydroelectricity potential: 1. We set the 2030 potential to the lower bound of the ‘mid-term projected output’ reported in the IHDW atlas. 2. We set the 2070 potential as the half-way point between this and the IHDWA ‘economic potential’. a. Where values from IHDWA 2007 and IEA 2007/9 differed for current production we have used the larger number. b. Where current (2007/9) production from IEA was larger than the IHDWA mid-term or economic potentials we have used the larger IEA number. For small hydroelectricity potential: 1. We have assumed that the reported potential was economically feasible (not technical) potential and have used this as our 2070 potential. This is a reasonable assumption given that this is estimated here at $1.6 EJ, whereas the global technical potential is estimated at 1.9–2.0 EJ in REN21. 2. We have set the 2030 potential as the point between the current (2009) capacity (zero for most countries due to underreporting) and the 2070 potential along a linear development path.

2.6.2. Geothermal electricity We analysed $30 different country-level studies, presentations and brieﬁng papers containing potential estimates for $100 different countries in a meta-study (GEA, 2010; IEA, 2010; Bertani, 2009a, 2009b, 2010; Brooks and Bala, 2010; Chandrasekharam,

2000; DECC, 2006; DLR, 2005, 2006; EBRD, 2009; Eliasson, 2008; Energy and Mineral Resources Ministry, 2010; IEA, 2006, 2011; Green and Nix, 2006; Goldstein et al., 2011; Jelic´ et al., 2000; Joseph, 2008; Krewitt et al., 2009; RECIPES, 2006; Richter, 2011; Sarmiento and Steingrimsson, 2007; Simsek et al., 2005; Teklemariam, 2006; Tester et al., 2006; USGS, 2008). We mapped the reported potentials at the most detailed geographic level reported to a common nomenclature as shown in Table 7, where we differentiate currently used conventional technology and enhanced geothermal systems which allow electricity production from a wider range of geographies. In case of inconsistencies between sources, the larger number was reported. In addition, if potential was reported in periods, but not in others, we extrapolated values, where possible, for the missing periods based on the available data. For EGS, which is less location-dependent, potentials were estimated for countries without data based on other countries. It must be noted that the range of values reported in the literature was very large and the extrapolations above were primarily designed to yield a gap-free regional data set. We acknowledge that a meta-study such as this is necessarily simplistic and yields results with very large uncertainties. The full range of resulting estimates is shown in Section 3. 3. Results 3.1. Large global potential even under strict constraints We assessed the renewable electricity potential for the most common solar and wind technologies (on- and offshore wind, Table 7 Category mapping for geothermal literature survey. Categories in this study 2010 2030 2070 Conventional vs. EGS All technologies

Categories from other studies grouped in this deﬁnition Actual production reported from GEA (2010) and IEA ETSAP (2010) ‘Short-term (economic)’ potential if reported ‘Long-term (economic)’ potential if reported If explicitly stated If no technology stated explicitly