## 4 Urban Population and Urban PV Generation vs. Energy Sustainability
### Energy Trilemma Index and Urban Population in the Period 2014-2017  
Using the results of the ETI during the period 2014-2017, and data from the United Nations [3] on the percentage of urban population, Figure 8 was constructed to analyze the relationship between these two variables. The positions one to 125 of the ETI ranking, organized into five segments of 25 countries, run along the horizontal axis. The vertical axis on the left shows the percentage of  
Figure 7: Effectiveness of the energy dimension of smart cities to achieve energy sustainability in urban areas and countries. population concentration (UP) and the results of ETI standardized between 0-100, while the vertical axis on the right shows the urban population of the five segments. The results obtained are described below. There is a positive correlation between the best results in energy sustainability and the UP of the 125 countries classified in the ETI 2017, as well as with each of its three pillars: From greatest to least, this correlation (\(r\)) between the UP and EQR, ETI, ESR, and EMR is 0.73, 0.68, 0.33, and 0.23, respectively. The first three of the five country segments (positions 1-75) on average have an UP of above 73% (segments one to three, respectively: 77.4%, 75.86%, and 73.16%). Despite the fourth segment (positions 76-100) having an average UP of 54.17%, it has the highest urban population value (1.56 billion) of all segments and it is almost the sum of the first three segments. As for the fifth segment (positions 101-125), it has the lowest average UP (38.53%) and the lowest value of urban population. Figure 8: Correlation between the percentage of urban population and the ETI during the period 2014–2017. Source: Created by authors using data from [3; 12; 71; 72; 73; 74]. The first 25 countries in the ETI ranking are rich countries in Europe with the highest %UP, over 75%, and the final segment is mostly made up of countries of the Group-IV and have an %UP of below 25%. The second segment is made up of countries from the groups Groups-GDP II and III of Europe, Asia, and MENA. The third segment has a more balanced distribution between countries in Europe, LAC, and MENA of the Groups-GDP I, II, and III. In the fourth segment, the largest in urban population, it is made up of Asian, LAC, and countries of the sub-Saharan region. Most of the latter are found in the fifth segment. To analyze these results in depth, Figure 9 was constructed, which shows the variation of the 125 countries in their ranking positions and the percentage of urban population (%UP) from 2014 to 2017. This variation is plotted in the four quadrants of a Cartesian axis, in which the horizontal axis represents the UP (growth in the positive axis and decrease in the negative) and the vertical axis represents the variation of the position in the ETI ranking (the higher positions on the positive axis and a lower position on the negative). Each of these four axes is divided into segments of positive correlations (\(0.5>\mathrm{r}\leq 1\) and \(0\geq\mathrm{r}\leq 0.5\)) and negative correlations (\(-0.5\geq\mathrm{r}<0\) and \(-1\geq\mathrm{r}>-0.5\)). The table on the right shows the percentage of countries in each quadrant in relation to the total number of countries, distributed in each region and Group-GDP. In 110 of these countries, the urban population percentage increases and, of these, 48% move higher up in the ETI and the remaining 52% go down. There is a large number of countries (57) in the fourth quadrant (Q4) that go down in the ETI rankings but increase their UP; 42 of these countries have a negative correlation between \(-1\) and \(-0.5\) (mainly countries from the regions of Europe and Sub-Saharan), which places them close to the first quadrant (Q1). This quadrant is in second position by number of countries (53), which have gone up in the ETI rankings as well as  
Figure 9: Variation of the 125 countries in the ETI ranking and the percentage of urban population (%UP) from 2014 to 2017. Source: Created by authors using data from [3; 71; 72; 73; 12].