Influence of the Population Density of Cities on Energy Consumption of Their Households

sustainability Article Influence of the Population Density of Cities on Energy Consumption of Their Households Pedro J. Zarco-Periñán *, Irene M. Zarco-Soto and Fco. Javier Zarco-Soto   Citation: Zarco-Periñán, P.J.; Zarco-Soto, I.M.; Zarco-Soto, F..J. Influence of the Population Density of Cities on Energy Consumption of Their Households. Sustainability 2021, 13, 7542. https://doi.org/10.3390/ su13147542 Academic Editor: JoséAlberto Molina Received: 31 May 2021 Accepted: 2 July 2021 Published: 6 July 2021 Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). Departamento de Ingeniería Eléctrica, Escuela Superior de Ingeniería, Universidad de Sevilla, Camino de los Descubrimientos, s/n, 41092 Sevilla, Spain; [email protected] (I.M.Z.-S.); [email protected] (F.J.Z.-S.) *Correspondence: pzar[email protected] Abstract: 36% of the energy consumed and 40% of emissions are due to buildings in the residential and tertiary sectors. These antecedents have forced governments to focus on saving energy and reducing emissions in this sector. To help government decision-making and facilitate energy planning for utilities, this work analyzes the energy consumption that occurs in city buildings. The information used to carry it out is publicly accessible. The study is carried out from the point of view of the population density of the cities, and these are analyzed individually. Furthermore, the area actually occupied by the city has been considered. The results are studied by inhabitant and household. The proposed method has been applied to the case of Spanish cities with more than 50,000 inhabitants. The results show that the higher the population density, the higher the energy consumption. This occurs both per inhabitant and per household. Furthermore, the consumption of electrical energy is inelastic, which is not the case with the consumption of thermal origin. Keywords: population density; energy consumption; population behaviors; cities; buildings; Spain 1. Introduction Energy is responsible for more than 80% of greenhouse gas (GHG) emissions, with transport corresponding to only a third [ 1 ]. Thirty six percent of the energy consumed and 40% of emissions are due to buildings in the residential and tertiary sectors [ 2 ]. In them, the usual form of energy consumption is through electricity and natural gas for thermal consumption [3]. Therefore, cities are the most important centers for the consumption of energy and the production of polluting emissions. Being aware of this, the European Union created the Covenant of Mayors. Subsequently, it changed its name to Climate & Energy to integrate mayors from 8000 cities from 53 countries around the world. Among its objectives is to achieve access to affordable and sustainable energy for all citizens [4]. Currently, and because cities have been the main areas affected by the COVID-19 pandemic [ 5 ], the European Union has launched a EUR 750 billion recovery plan for COVID-19 [6] with six fields of action, one of which is construction and buildings [7]. For all the above, cities in general and their buildings in particular take a leading role for governments and utilities. In the case of the former, to establish laws that favor the reduction of consumption and emissions; in the latter, to plan the infrastructures that allow the growth of energy consumption, if possible, through renewable energy sources. Therefore, it is essential to know the relationship between energy and urbanization to achieve sustainable cities. For this reason, this paper studies the energy consumption of buildings. All the buildings have been considered, and their consumption has been distributed among their inhabitants, including non-residential ones. This is so because non-residential buildings are used by the inhabitants of a city and exist in greater or lesser numbers depending on the population of it. Sustainability 2021,13, 7542. https://doi.org/10.3390/su13147542 https://www.mdpi.com/journal/sustainability Sustainability 2021,13, 7542 2 of 15 The methodology used in the study, based on statistical analysis, is similar to others that, although classic, are still being used recently and use information from statistical databases [ 8 – 12 ] and on others that are based on the creation of synthetic populations [ 13 ]. Thus, the population of cities is represented in a simplified way from aggregated public data. The main contributions of this paper are: analyze energy consumption of city buildings based on population density; study the behavior of the cities of a country separately, and not in an aggregate way; analyze the results by household and by inhabitant; and apply the method to the case of Spanish cities with more than 50,000 inhabitants. To the authors’ knowledge, a similar investigation has not been carried out previously. With all this, it is intended that both utilities and governments have detailed knowledge of the behavior of cities based on their population density. The article is structured as follows: Section 2presents studies that relate energy in cities with the population density; Section 3describes the proposed method, based on the use of public information; the application to the case of Spanish cities is presented in Section 4; the results, per inhabitant and household, are presented and discussed in Section 5; finally, Section 6summarizes the findings of the study. 2. Literature Review Utilities and governments are paying increasing attention to cities in general, and their buildings in particular, as focuses to reduce energy consumption. Therefore, this study investigates from the point of view of population density. Despite the importance that population density is acquiring in cities, this approach has been little analyzed [ 14 ]. Instead, the buildings have been analyzed individually: hotels [ 15 ], houses [ 16 ]; or the urban heat island generated [ 17 ]; or the relationship between transport and population density from the point of view of energy consumption [18]. Studies that analyze the population of cities have been carried out taking into account urbanization or population density. The most numerous are the first. They analyze the percentage of urban population with respect to the total national population. These give a general idea of the influence of migration from rural to urban areas. In addition, they usually refer to large areas, as is the case in the country-level analysis: Brazil [ 19 ], the USA [ 20 ], CIVETS countries, namely, Colombia, Indonesia, Vietnam, Egypt, Turkey, and South Africa [ 21 ], or 72 countries [ 22 ]. However, they do not provide information at the city level. In general, the published works that analyze energy consumption focus on calculating the forecast of electricity demand at the country level, as is the case of Turkey [ 23 ], Spain [ 24 ], or Greece [ 25 ]; or at the level of the residential sector in some countries [ 26 ]. Studies that take natural gas into account usually also predict demand. This is the case of Pakistan [ 27 ], Bangladesh [ 28 ], or Bahrain, Saudi Arabia, Syria, and the United Arab Emirates [ 29 ]; or also at the residential level [30]. Using population density as a study variable, information can be obtained from a more specific area. This variable considers people by land area. In this way, it can be analyzed in more detail from a country [ 31 ] to a city [ 32 ] and is more appropriate for smaller areas. However, studies usually include the area occupied by the entire municipality and not just the area occupied by the populated area. Therefore, the population density that is calculated is that corresponding to the inhabitants who live in a certain city with respect to the entire area of the municipality, although a significant part of that area is neither inhabited nor has services for its inhabitants. However, from the authors’ point of view, this is not valid for a detailed study of the influence of population density on certain magnitudes such as those analyzed in this study. On the contrary, the area considered must be that actually occupied by population. The works that analyze the influence of population density do so considering the total energy. Therefore, they also include transport, so the influence of buildings is not Sustainability 2021,13, 7542 3 of 15 specifically analyzed, despite being one of the main consumers of energy and producers of emissions [33]. Regarding the works that analyze energy consumption in buildings, they focus on a specific sector. Thus, in the electricity consumed in the residential sector, it increases when they do household income and number of rooms. In the study carried out in Malysia on a sample of 620 urban households, the average consumption was determined [ 34 ]. Depending on the urban density, the energy consumption increases up to a certain value, and from there it hardly has any influence. In the specific case of the study carried out in 29 provinces of China, this value is 808 inhabitants per square kilometer. In addition, other variables were used, such as economic development or urbanization. In the case of this last variable, the urbanization rate increased above 55.31%; below this value, residential energy consumption decreased [ 35 ]. In the service sector, consumption per inhabitant is lower as density increases. This efficiency is justified by the higher factor productivity [36]. At the country level, in Kenya the possible drivers of energy consumption have been studied. Among them are population density and urbanization. In this case, while population density and urbanization reduce energy consumption, electricity consumption increases [ 37 ]. Something similar happens in China: as population density increases, energy consumption increases, while just the opposite occurs with urbanization [ 38 ]. However, in Canada the opposite is true. The electricity consumption of all sectors, except industrial, is analyzed and six predictors are used. Among them, population density is one of the determining factors. As a conclusion, it is obtained that when the population density is higher, the electricity consumption per capita is lower [ 39 ]. In addition, in a study of 93 countries, the results were found to be completely different from country to country [ 40 ]. Therefore, of the studies that analyze energy consumption, there are very few that relate energy consumption in buildings with population density. Not only that, but they also do not even consider a very important energy source, natural gas. Hence, the need to know more precisely the influence that population density has on energy consumption, in the case of this article, by applying the proposed method to the specific case of Spain. 3. Materials and Methods The phases of the proposed method are as follows: first, the study area must be defined; second, the criteria for selecting the cities in that area are defined; third, cities must be classified according to density of inhabitants; and fourth, the consumption per inhabitant and per household in the buildings must be obtained. The data used for the study should come from public databases and, whenever possible, should be of government origin. All this information must be properly processed to obtain the desired results. In this way, with the information on the energy consumed, it will be possible to implement specific measures that favor the reduction of consumption in each city and implement renewable energy sources that cover the growth in demand in each city and reduce their emissions. A methodological approach of the proposed method is shown in Figure 1. Sustainability 2021, 13, x FOR PEER REVIEW 3 of 15 specifically analyzed, despite being one of the main consumers of energy and producers of emissions [33]. Regarding the works that analyze energy consumption in buildings, they focus on a specific sector. Thus, in the electricity consumed in the residential sector, it increases when they do household income and number of rooms. In the study carried out in Malysia on a sample of 620 urban households, the average consumption was determined [34]. Depending on the urban density, the energy consumption increases up to a certain value, and from there it hardly has any influence. In the specific case of the study carried out in 29 provinces of China, this value is 808 inhabitants per square kilometer. In addition, other variables were used, such as economic development or urbanization. In the case of this last variable, the urbanization rate increased above 55.31%; below this value, residential energy consumption decreased [35]. In the service sector, consumption per inhabitant is lower as density increases. This efficiency is justified by the higher factor productivity [36]. At the country level, in Kenya the possible drivers of energy consumption have been studied. Among them are population density and urbanization. In this case, while population density and urbanization reduce energy consumption, electricity consumption increases [37]. Something similar happens in China: as population density increases, energy consumption increases, while just the opposite occurs with urbanization [38]. However, in Canada the opposite is true. The electricity consumption of all sectors, except industrial, is analyzed and six predictors are used. Among them, population density is one of the determining factors. As a conclusion, it is obtained that when the population density is higher, the electricity consumption per capita is lower [39]. In addition, in a study of 93 countries, the results were found to be completely different from country to country [40]. Therefore, of the studies that analyze energy consumption, there are very few that relate energy consumption in buildings with population density. Not only that, but they also do not even consider a very important energy source, natural gas. Hence, the need to know more precisely the influence that population density has on energy consumption, in the case of this article, by applying the proposed method to the specific case of Spain. 3. Materials and Methods The phases of the proposed method are as follows: first, the study area must be defined; second, the criteria for selecting the cities in that area are defined; third, cities must be classified according to density of inhabitants; and fourth, the consumption per inhabitant and per household in the buildings must be obtained. The data used for the study should come from public databases and, whenever possible, should be of government origin. All this information must be properly processed to obtain the desired results. In this way, with the information on the energy consumed, it will be possible to implement specific measures that favor the reduction of consumption in each city and implement renewable energy sources that cover the growth in demand in each city and reduce their emissions. A methodological approach of the proposed method is shown in Figure 1. Figure 1. Methodological approach. Figure 1. Methodological approach. Sustainability 2021,13, 7542 4 of 15 Certain factors can influence energy consumption in cities. For example, the type of housing, the age of its construction, its orientation, the orographic characteristics of its surroundings, the climatic zone in which it is located, etc. However, their elimination is beyond the scope of this study. Therefore, the possible influence that they could have remains within the study. 3.1. Classification of Cities by Population Density First, the area to study must be defined. Its size will depend on the scope of the study to be carried out. Next, the cities in that area must be selected. The selection will be made depending on the criteria of interest. These criteria can be the number of inhabitants, the energy consumed, the saturation of its infrastructure, its emissions, its growth rate, or any other that is of interest. From there, each city is represented by its population density and a segmentation can be defined. To perform the analysis, the main statistical data of electric, thermal, and total energy consumptions for each group of cities are studied: Number of cities : ni=∑ j 1 (1) mean : Ei=∑jEij ni (2) Standard deviation : si=v u u t ∑ijEij −Ei2 (ni−1)(3) Median : Mediani=hni+1 2ith term if the total number of the elements is an odd number, otherwise Mediani=(ni 2)th term +(ni 2+1)th term 2 (4) Maximum : Ei max =maxEij(5) Minimum : Ei min =minEij(6) where n i is the number of cities that belong to group i; Ei is the mean energy consumed in group i;E ij is the energy consumption of city j, which is located in group i;s i is the standard deviation of the energy consumed in the cities of group i; the energy consumed will be thermal, electric or total depending on the case study; and cities consumptions should be listed in ascending order to calculate the median. An index analogous to that defined in [ 41 ] is used to analyze the energy consumption of cities. The density variation index (DVI) is defined as: DVIi=Ei/E(7) where DVIi is the index of the group of cities that have size i, Ei is the energy consumption mean value of group iand E is the mean energy consumption of all cities (of all groups). With it, the consumption of the groups can be easily compared. 3.2. Population Density of Cities To calculate the population density, it is necessary to identify the study area. One criterion is to consider the one that corresponds to the entire municipality of the city (this is the commonly used criterion). However, according to the authors, this is not the appropriate option. In certain cases, the city occupies the entire land area of the municipality; this usually happens in those highly populated cities with very little land area. However, usually the area of the municipality is greater than what the population occupies. Therefore, the whole area of the city municipality should not be considered, but only that which is actually populated. To do this, only the area occupied by buildings must Sustainability 2021,13, 7542 5 of 15 be considered and not the rest. This surface can be continuous or discontinuous (depending on their housing scheme: single family houses or high-rise dwelling, city center of suburb). This is the criterion that will be followed in the study: only the surface occupied by buildings will be considered, and this can be continuous or discontinuous. Therefore, the area considered is that occupied by continuous and discontinuous urban fabric [42]. 3.3. Electric and Thermal Energy Consumption To analyze energy consumption in cities, only that corresponding to buildings has been considered. That of industries has not been considered, nor that of means of transport. However, not only energy consumption in residential buildings has been considered, but also that of tertiary sector buildings. This is due to a double reason: on the one hand, the official data provided does not usually distinguish between whether the supply points correspond to residential, commercial, or administrative offices; and on the other, the rest of non-residential buildings in a city exist to serve its inhabitants, and their number is greater or lesser depending on the number of its inhabitants. For this reason, the study is carried out considering the energy consumption of all these buildings and is distributed among the inhabitants of each city. Population and consumption data by city are used to calculate thermal and electrical consumption. In addition, they must be disaggregated from the information usually provided by public bodies. For electricity consumption, the classification of the Statistical Classification of Economic Activities in the European Community, commonly referred to as NACE (for the French term “nomenclature statistique des activitéséconomiques dans la Communautéeuropéenne”) is used [ 43 ]. The following items have been considered: 36 to 39, 53, 60, 61, 72, 84 to 88 (exc. 85.5 and 85.6), 91, 99, 45 to 47, 58.2, 59, 62 to 71, 73 to 75, 77 to 82, 85.5, 85.6, 90, 92 to 98. It should be noted that electricity consumption does not only include that corresponding to lighting. It also covers the consumption of air conditioning in buildings and other uses that are made of electricity in them. For thermal consumption, the information corresponding to supply points with a pressure equal to or less than 4 bar and a consumption between 5000 and 50,000 kWh per year is used. These points are those that usually correspond to homes, stores, public administrations, and services. 4. Application of the Method to the Case of Spain An example of application of the proposed method is presented in this section. As a study area, the whole of Spain is considered. In it, cities with more than 50,000 inhabitants have been selected. They represent more than 50% (24.5 million) of the 46.5 million inhabitants it has. The data used correspond to 2016. The results of the study will allow detailed knowledge of energy consumption, which will favor decision-making and the assessment of infrastructures that allow supplying energy demand and its growth. 4.1. Classification of Spanish Cities To carry out the classification of cities according to their density, it is necessary to know the population [44] and the area of each one of them [45]. The number of cities that meet the criteria of having more than 50,000 inhabitants is 145. From the public information available, their density, electricity and thermal consumption in the form of natural gas in their buildings and their emissions have been calculated. Based on density, cities have been segmented into five groups. For this, the number of inhabitants per hectare has been calculated, being 1 hectare 10,000 square meter. Group 1 is made up of cities with a density lower than 100 inhabitants/hectare; Group 2, for those whose density is greater than or equal to 100 and less than 200; Group 3, for cities with a density greater than 200 and less than 300 inhabitants/hectare; Group 4 has a density between 300 and 400; and Group 5 is made up of cities with a density greater than 400 inhabitants/hectare. Table 1shows the segmentation of the cities ordered alphabetically. Sustainability 2021,13, 7542 6 of 15 Table 1. Classification of Spanish cities by density. Inhabitants/Hectare Cities Group 1: density < 100 Albacete, Alcaláde Guadaíra, Alcoy/Alcoi, Alicante/Alacant, Aranjuez, Arganda del Rey, Arona, Ávila, Badajoz, Benalmádena, Benidorm, Boadilla del Monte, Cáceres, Cartagena, Castellón de la Plana, Chiclana de la Frontera, Ciudad Real, Collado Villalba, Córdoba, Elche/Elx, Elda, Estepona, Ferrol, Jerez de la Frontera, Linares, Línea de la Concepción (La), Lorca, Lugo, Marbella, Mérida, Mijas, Murcia, Orihuela, Ourense, Paterna, Ponferrada, Pontevedra, Pozuelo de Alarcón, Puerto de Santa María, Rivas-Vaciamadrid, Rozas de Madrid (Las), Rubí, Sagunto/Sagunt, San Cristóbal de la Laguna, San Sebastián de los Reyes, San Vicente del Raspeig, Sanlúcar de Barrameda, Sant Cugat del Vallès, Santiago de Compostela, Talavera de la Reina, Toledo, Torrelavega, Torrevieja, Utrera, Vélez-Málaga, Vigo, Vila-Real Group 2: 100 ≤density < 200 Alcobendas, Algeciras, Almería, Arrecife, Avilés, Burgos, Castelldefels, Cerdanyola del Vallès, Coslada, Cuenca, Dos Hermanas, Ejido (El), Fuengirola, Gandía, Getxo, Gijón, Girona, Granada, Granollers, Guadalajara, Huesca, Irún, Jaén, Las Palmas, León, Lleida, Logroño, Majadahonda, Málaga, Manresa, Molina de Segura, Motril, Oviedo, Palencia, Palma de Mallorca, Pinto, Reus, Roquetas de Mar, Salamanca, San Bartoloméde Tirajana, San Sebastián/Donostia, Santa Cruz de Tenerife, Santa Lucía de Tirajana, Santander, Segovia, Siero, Tarragona, Telde, Terrassa, Torremolinos, Valdemoro, Valladolid, Vilanova i la Geltrú, Vitoria/Gasteiz, Zamora, Zaragoza Group 3: 200 ≤density < 300 A Coruña, Alcaláde Henares, Alcorcón, Barakaldo, Ceuta, Getafe, Leganés, Madrid, Mataró, Melilla, Mollet del Vallès, Móstoles, Pamplona/Iruña, Sabadell, San Fernando, Sant Boi de Llobregat, Sevilla, Valencia, Viladecans Group 4: 300 ≤density < 400 Badalona, Barcelona, Bilbao, Cádiz, Fuenlabrada, Huelva, Parla, Prat de Llobregat (El), Torrejón de Ardoz Group 5: 400 ≤density Cornellàde Llobregat, L’Hospitalet de Llobregat, Santa Coloma de Gramenet, Torrent Although the influence of external factors has not been eliminated, it must be mentioned that the climate is one of those that may be of greater importance. That is why, to have a vision of the types of climates in which cities are located, Figure 2shows the types of climates in Spain and the number of cities studied that are in each of them [41]. Sustainability 2021, 13, x FOR PEER REVIEW 6 of 15 between 300 and 400; and Group 5 is made up of cities with a density greater than 400 inhabitants/hectare. Table 1 shows the segmentation of the cities ordered alphabetically. Table 1. Classification of Spanish cities by density. Inhabitants/Hectare Cities Group 1: density < 100 Albacete, Alcalá de Guadaíra, Alcoy/Alcoi, Alicante/Alacant, Aranjuez, Arganda del Rey, Arona, Ávila, Badajoz, Benalmádena, Benidorm, Boadilla del Monte, Cáceres, Cartagena, Castellón de la Plana, Chiclana de la Frontera, Ciudad Real, Collado Villalba, Córdoba, Elche/Elx, Elda, Estepona, Ferrol, Jerez de la Frontera, Linares, Línea de la Concepción (La), Lorca, Lugo, Marbella, Mérida, Mijas, Murcia, Orihuela, Ourense, Paterna, Ponferrada, Pontevedra, Pozuelo de Alarcón, Puerto de Santa María, Rivas-Vaciamadrid, Rozas de Madrid (Las), Rubí, Sagunto/Sagunt, San Cristóbal de la Laguna, San Sebastián de los Reyes, San Vicente del Raspeig, Sanlúcar de Barrameda, Sant Cugat del Vallès, Santiago de Compostela, Talavera de la Reina, Toledo, Torrelavega, Torrevieja, Utrera, Vélez-Málaga, Vigo, Vila-Real Group 2: 100 ≤ density < 200 Alcobendas, Algeciras, Almería, Arrecife, Avilés, Burgos, Castelldefels, Cerdanyola del Vallès, Coslada, Cuenca, Dos Hermanas, Ejido (El), Fuengirola, Gandía, Getxo, Gijón, Girona, Granada, Granollers, Guadalajara, Huesca, Irún, Jaén, Las Palmas, León, Lleida, Logroño, Majadahonda, Málaga, Manresa, Molina de Segura, Motril, Oviedo, Palencia, Palma de Mallorca, Pinto, Reus, Roquetas de Mar, Salamanca, San Bartolomé de Tirajana, San Sebastián/Donostia, Santa Cruz de Tenerife, Santa Lucía de Tirajana, Santander, Segovia, Siero, Tarragona, Telde, Terrassa, Torremolinos, Valdemoro, Valladolid, Vilanova i la Geltrú, Vitoria/Gasteiz, Zamora, Zaragoza Group 3: 200 ≤ density < 300 A Coruña, Alcalá de Henares, Alcorcón, Barakaldo, Ceuta, Getafe, Leganés, Madrid, Mataró, Melilla, Mollet del Vallès, Móstoles, Pamplona/Iruña, Sabadell, San Fernando, Sant Boi de Llobregat, Sevilla, Valencia, Viladecans Group 4: 300 ≤ density < 400 Badalona, Barcelona, Bilbao, Cádiz, Fuenlabrada, Huelva, Parla, Prat de Llobregat (El), Torrejón de Ardoz Group 5: 400 ≤ density Cornellà de Llobregat, L’Hospitalet de Llobregat, Santa Coloma de Gramenet, Torrent Although the influence of external factors has not been eliminated, it must be mentioned that the climate is one of those that may be of greater importance. That is why, to have a vision of the types of climates in which cities are located, Figure 2 shows the types of climates in Spain and the number of cities studied that are in each of them [41]. Figure 2. Number of cities by type of climate of Spain. 4.2. Thermal and Electric Energy Consumption To obtain the consumption of thermal and electrical energy, information from the Ministry of Economic Affairs and Digital Transformation and the Ministry for Ecological Transition and Demographic Challenge has been used: Spanish National Statistics Institute [46], National Commission on Markets and Competition [47], Secretary of State for Energy [48]. 5. Results and Discussion 5.1. Sample of Study The energy consumption in the buildings of the 145 Spanish cities with more than 50,000 inhabitants have been studied. The buildings are those corresponding to households, government agencies, and tertiary sectors. Consumption is that usually used in buildings: thermal in the form of natural gas and electricity. The data used are public and Figure 2. Number of cities by type of climate of Spain. 4.2. Thermal and Electric Energy Consumption To obtain the consumption of thermal and electrical energy, information from the Ministry of Economic Affairs and Digital Transformation and the Ministry for Ecological Transition and Demographic Challenge has been used: Spanish National Statistics Insti- Sustainability 2021,13, 7542 7 of 15 tute [ 46 ], National Commission on Markets and Competition [ 47 ], Secretary of State for Energy [48]. 5. Results and Discussion 5.1. Sample of Study The energy consumption in the buildings of the 145 Spanish cities with more than 50,000 inhabitants have been studied. The buildings are those corresponding to households, government agencies, and tertiary sectors. Consumption is that usually used in buildings: thermal in the form of natural gas and electricity. The data used are public and from official sources, although properly processed. The cities have been segmented into five groups according to Table 1. Figure 3presents the number of cities in each group. The most numerous groups are the two with the lowest population density. Each of them represents almost 40% of cities. The rest of the groups only represent 22% and as the density increases, the number of cities decreases. Thus, the group of cities with the highest density barely represents 3%. However, of the number of inhabitants, Group 2 is the largest, with 32% of the total. Groups 3 and 1 follow with more than 25%. The one with the lowest number of inhabitants is Group 5, with only 2% (Figure 4). Sustainability 2021, 13, x FOR PEER REVIEW 7 of 15 from official sources, although properly processed. The cities have been segmented into five groups according to Table 1. Figure 3 presents the number of cities in each group. The most numerous groups are the two with the lowest population density. Each of them represents almost 40% of cities. The rest of the groups only represent 22% and as the density increases, the number of cities decreases. Thus, the group of cities with the highest density barely represents 3%. However, of the number of inhabitants, Group 2 is the largest, with 32% of the total. Groups 3 and 1 follow with more than 25%. The one with the lowest number of inhabitants is Group 5, with only 2% (Figure 4). Figure 3. Number of cities of each group. Figure 4. Population of each group of cities. Table 2 shows the main statistical data of the households and population of each group. The first column shows each of the groups into which the analysis has been divided, and each of its rows contains its statistical data. The conclusions are similar to those indicated. Table 2. Statistical data by population and household of each group of cities. POPULATION NUMBEROF HOUSEHOLDS Population Density Total Mean Std. Dev. Median Maximum Minimum Total Mean Std. Dev. Median Maximum Minimum Group 1 6,132,394 107,586 79,857 79,878 443,243 50,334 2,280,611 40,011 29,113 29,727 154,421 15,434 Group 2 7,888,999 140,875 123,196 90,730 664,938 50,442 3,060,916 54,659 48,525 33,872 269,347 18,160 Group 3 6,938,864 365,203 710,045 178,288 3,182,981 51,128 2,684,033 141,265 282,318 67,113 1,262,282 18,967 Group 4 2,957,407 328,601 491,187 145,115 1,620,809 63,897 1,167,260 129,696 204,159 54,952 666,143 23,831 Group 5 542,186 135,547 82,802 102,104 257,349 80,630 201,649 50,412 31,580 37,685 97,044 29,235 5.2. Total Energy Consumption Table 3 shows, in each of its rows, the statistical data of the total consumption of each group, in MWh per year. The highest consumptions are produced in Groups 2 and 3, with almost identical consumptions, even though Group 2 has almost 15% more inhabitants. They are followed by Group 1 with a 36% lower consumption, although its number of inhabitants is only 11% lower. Group 5 is the one with the lowest consumption. Figure 3. Number of cities of each group. Sustainability 2021, 13, x FOR PEER REVIEW 7 of 15 from official sources, although properly processed. The cities have been segmented into five groups according to Table 1. Figure 3 presents the number of cities in each group. The most numerous groups are the two with the lowest population density. Each of them represents almost 40% of cities. The rest of the groups only represent 22% and as the density increases, the number of cities decreases. Thus, the group of cities with the highest density barely represents 3%. However, of the number of inhabitants, Group 2 is the largest, with 32% of the total. Groups 3 and 1 follow with more than 25%. The one with the lowest number of inhabitants is Group 5, with only 2% (Figure 4). Figure 3. Number of cities of each group. Figure 4. Population of each group of cities. Table 2 shows the main statistical data of the households and population of each group. The first column shows each of the groups into which the analysis has been divided, and each of its rows contains its statistical data. The conclusions are similar to those indicated. Table 2. Statistical data by population and household of each group of cities. POPULATION NUMBEROF HOUSEHOLDS Population Density Total Mean Std. Dev. Median Maximum Minimum Total Mean Std. Dev. Median Maximum Minimum Group 1 6,132,394 107,586 79,857 79,878 443,243 50,334 2,280,611 40,011 29,113 29,727 154,421 15,434 Group 2 7,888,999 140,875 123,196 90,730 664,938 50,442 3,060,916 54,659 48,525 33,872 269,347 18,160 Group 3 6,938,864 365,203 710,045 178,288 3,182,981 51,128 2,684,033 141,265 282,318 67,113 1,262,282 18,967 Group 4 2,957,407 328,601 491,187 145,115 1,620,809 63,897 1,167,260 129,696 204,159 54,952 666,143 23,831 Group 5 542,186 135,547 82,802 102,104 257,349 80,630 201,649 50,412 31,580 37,685 97,044 29,235 5.2. Total Energy Consumption Table 3 shows, in each of its rows, the statistical data of the total consumption of each group, in MWh per year. The highest consumptions are produced in Groups 2 and 3, with almost identical consumptions, even though Group 2 has almost 15% more inhabitants. They are followed by Group 1 with a 36% lower consumption, although its number of inhabitants is only 11% lower. Group 5 is the one with the lowest consumption. Figure 4. Population of each group of cities. Table 2shows the main statistical data of the households and population of each group. The first column shows each of the groups into which the analysis has been divided, and each of its rows contains its statistical data. The conclusions are similar to those indicated. Sustainability 2021,13, 7542 8 of 15 Table 2. Statistical data by population and household of each group of cities. POPULATION NUMBEROF HOUSEHOLDS Population Density Total Mean Std. Dev. Median Maximum Minimum Total Mean Std. Dev. Median Maximum Minimum Group 1 6,132,394 107,586 79,857 79,878 443,243 50,334 2,280,611 40,011 29,113 29,727 154,421 15,434 Group 2 7,888,999 140,875 123,196 90,730 664,938 50,442 3,060,916 54,659 48,525 33,872 269,347 18,160 Group 3 6,938,864 365,203 710,045 178,288 3,182,981 51,128 2,684,033 141,265 282,318 67,113 1,262,282 18,967 Group 4 2,957,407 328,601 491,187 145,115 1,620,809 63,897 1,167,260 129,696 204,159 54,952 666,143 23,831 Group 5 542,186 135,547 82,802 102,104 257,349 80,630 201,649 50,412 31,580 37,685 97,044 29,235 5.2. Total Energy Consumption Table 3shows, in each of its rows, the statistical data of the total consumption of each group, in MWh per year. The highest consumptions are produced in Groups 2 and 3, with almost identical consumptions, even though Group 2 has almost 15% more inhabitants. They are followed by Group 1 with a 36% lower consumption, although its number of inhabitants is only 11% lower. Group 5 is the one with the lowest consumption. From the point of view of electricity consumption, the behavior is similar. However, the consumption of Group 2 is 12% higher than that of Group 3, even though the total consumption of both groups was almost identical. Regarding thermal consumption, Groups 2 and 3 have a behavior contrary to that presented in electricity consumption: Group 3 is the one with the highest consumption, followed by Group 2. The rest of the groups follow a similar behavior. Graphically, Figure 5presents the total, thermal and electrical consumption of each group in GWh per year. The consumptions that a group of average values would present are also shown. It can be observed that, at the level of total consumption, Groups 2 and 3 have higher consumption than the average value, while Groups 4 and 5 have lower consumption; Group 1 has a total consumption almost identical to the average value. Therefore, when analyzing this figure and relating it to Figure 3; Figure 4of the number of cities and inhabitants per group respectively, it is not possible to draw a conclusion about the trend that exists in the global consumption of each group. Global consumption does not follow a trend proportional to the number of cities per group or of inhabitants. Regarding electrical and thermal consumption, the behavior is similar to that described, except in Group 1, which in the case of electrical consumption is above the average value and in the case of thermal, below. Sustainability 2021, 13, x FOR PEER REVIEW 9 of 15 From the point of view of electricity consumption, the behavior is similar. However, the consumption of Group 2 is 12% higher than that of Group 3, even though the total consumption of both groups was almost identical. Regarding thermal consumption, Groups 2 and 3 have a behavior contrary to that presented in electricity consumption: Group 3 is the one with the highest consumption, followed by Group 2. The rest of the groups follow a similar behavior. Graphically, Figure 5 presents the total, thermal and electrical consumption of each group in GWh per year. The consumptions that a group of average values would present are also shown. It can be observed that, at the level of total consumption, Groups 2 and 3 have higher consumption than the average value, while Groups 4 and 5 have lower consumption; Group 1 has a total consumption almost identical to the average value. Therefore, when analyzing this figure and relating it to Figure 3; Figure 4 of the number of cities and inhabitants per group respectively, it is not possible to draw a conclusion about the trend that exists in the global consumption of each group. Global consumption does not follow a trend proportional to the number of cities per group or of inhabitants. Regarding electrical and thermal consumption, the behavior is similar to that described, except in Group 1, which in the case of electrical consumption is above the average value and in the case of thermal, below. Figure 5. Thermal, electric, and total mean energy consumption of each group of cities. 5.3. Energy Consumptions per Household Table 4 and Figure 6 show the main statistical data and the average values of energy consumption per household, respectively. Total energy consumption increases as density increases, except between the two highest density groups, among which there is a small decrease of 2%. The group with the lowest density, Group 1, is the only one that has a lower value than the mean value of all the groups. While the group with the highest consumption presents a value 13% higher than the average value, the lowest is 8% below. In addition, the differences in consumption between groups are similar, none of them being much more pronounced than the rest. Table 4. Statistical data of energy consumptions per household of each group of cities. TOTAL (MWh/year) THERMAL (MWh/year) ELECTRIC (MWh/year) Population Density Mean Std. dev. Median Max. Min. Mean Std. Dev. Median Max. Min. Mean Std. Dev. Median Max. Min. Group 1 9.90 3.45 8.46 18.79 5.99 2.59 2.71 1.32 9.16 0.00 7.31 1.08 7.16 9.63 5.68 Group 2 11.17 3.14 11.21 18.44 6.04 4.01 2.87 4.54 8.99 0.00 7.16 1.14 7.03 9.64 5.30 Group 3 11.88 3.67 12.83 16.07 5.66 4.84 2.97 5.70 8.63 0.00 7.03 0.80 7.12 8.24 5.66 Group 4 12.31 4.13 12.63 17.28 6.26 5.17 3.03 5.62 8.43 0.46 7.15 1.24 7.02 8.86 5.74 Group 5 11.97 1.55 12.54 13.11 9.69 4.80 1.72 5.57 5.83 2.22 7.17 0.25 7.14 7.47 6.94 Figure 5. Thermal, electric, and total mean energy consumption of each group of cities. Sustainability 2021,13, 7542 9 of 15 Table 3. Statistical data of consumption of each group of cities. TOTAL (MWh/year) THERMAL (MWh/year) ELECTRIC (MWh/year) Population Density Total Mean Std. Dev. Median Max. Min. Total Mean Std. Dev. Median Max. Min. Total Mean Std. Dev. Median Max. Min. Group 1 21,669,891 380,174 260,575 303,694 1,516,830 140,786 4,769,859 83,682 72,436 56,765 267,920 0.00 16,900,032 296,492 229,752 210,365 1,340,879 120,861 Group 2 34,153,406 609,882 591,430 379,561 3,717,939 156,564 12,332,035 220,215 288,821 144,797 1,627,614 0.00 21,821,371 389,667 365,806 243,110 2,090,324 120,890 Group 3 34,147,099 1,797,216 4,073,759 972,005 18,400,465 143,830 14,703,803 773,884 1,997,447 268,310 8,969,965 0.00 19,443,297 1,023,331 2,099,678 528,230 9,430,500 135,908 Group 4 13,842,679 1,538,075 2,366,828 740,029 7,756,365 286,388 6,004,988 667,221 1,065,972 360,754 3,447,946 20,960 7,837,691 870,855 1,304,278 379,275 4,308,420 169,850 Group 5 2,495,895 623,974 420,414 488,615 1,231,541 287,123 1,047,692 261,923 205,067 217,205 547,458 65,824 1,448,203 362,051 218,586 271,411 684,083 221,299