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

Departamento de Ingeniería Eléctrica, Escuela Superior de Ingeniería, Universidad de Sevilla, Camino de los Descubrimientos, s/n, 41092 Sevilla, ; [email protected] (I.M.Z.-S.); [email protected] (F.J.Z.-S.) * Correspondence: [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 Citation: Zarco-Periñán, P.J.; Zarco-Soto, I.M.; Zarco-Soto, F..J. Influence of the Population Density of Cities on Energy Consumption of 1. Introduction Their Households. Sustainability 2021, Energy is responsible for more than 80% of greenhouse gas (GHG) emissions, with 13, 7542. https://doi.org/10.3390/ transport corresponding to only a third [1]. Thirty six percent of the energy consumed and su13147542 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 Academic Editor: José Alberto Molina consumption [3]. Therefore, cities are the most important centers for the consumption of energy and the Received: 31 May 2021 production of polluting emissions. Being aware of this, the European Union created the Accepted: 2 July 2021 Published: 6 July 2021 Covenant of Mayors. Subsequently, it changed its name to & Energy to integrate mayors from 8000 cities from 53 countries around the world. Among its objectives is to

Publisher’s Note: MDPI stays neutral achieve access to affordable and sustainable energy for all citizens [4]. with regard to jurisdictional claims in Currently, and because cities have been the main areas affected by the COVID-19 published maps and institutional affil- pandemic [5], the European Union has launched a EUR 750 billion recovery plan for iations. 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 sources. Copyright: © 2021 by the authors. Licensee MDPI, Basel, Switzerland. Therefore, it is essential to know the relationship between energy and urbanization to This article is an open access article achieve sustainable cities. distributed under the terms and For this reason, this paper studies the energy consumption of buildings. All the conditions of the Creative Commons buildings have been considered, and their consumption has been distributed among their Attribution (CC BY) license (https:// inhabitants, including non-residential ones. This is so because non-residential buildings creativecommons.org/licenses/by/ are used by the inhabitants of a city and exist in greater or lesser numbers depending on 4.0/). 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 pub- lic 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: Section2 presents studies that relate energy in cities with the population density; Section3 describes the proposed method, based on the use of public information; the application to the case of Spanish cities is presented in Section4; the results, per inhabitant and household, are presented and discussed in Section5; finally, Section6 summarizes 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, 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 Sustainability 2021, 13, 7542 specific sector. Thus, in the electricity consumed in the residential sector, it increases3 of 15 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]. Depend- specificallying on the analyzed, urban density, despite beingthe energy one of theconsumption main consumers increases of energy up andto a producers certain value, of and emissionsfrom there [33 it]. hardly has any influence. In the specific case of the study carried out in 29 provincesRegarding of China, the works this thatvalue analyze is 808 energy inhabitants consumption per square in buildings, kilometer. they In focus addition, on other a specific sector. Thus, in the electricity consumed in the residential sector, it increases variables were used, such as economic development or urbanization. In the case of this when they do household income and number of rooms. In the study carried out in Malysia onlast a variable, sample of the 620 urbanization urban households, rate increased the average above consumption 55.31%; below was determined this value, [34 residential]. Dependingenergy consumption on the urban decreased density, the [35]. energy In the consumption service sector, increases consumption up to a certain per value, inhabitant is andlower from as theredensity it hardly increases. has any This influence. efficiency In the is specific justified case by of the the studyhigher carried factor out productivity in 29[36]. provinces of China, this value is 808 inhabitants per square kilometer. In addition, other variablesAt the were country used, such level, as economicin Kenya development the possible or drivers urbanization. of energy In the consumption case of this last have been variable,studied. the Among urbanization them are rate population increased above density 55.31%; and below urbanization. this value, In residential this case, energy while popu- consumptionlation density decreased and urbanization [35]. In the servicereduce sector, energy consumption consumption, per inhabitant electricity is consumption lower as in- densitycreases increases.[37]. Something This efficiency similar is happens justified byin theChina: higher as factorpopulation productivity density [36 increases,]. energy At the country level, in Kenya the possible drivers of energy consumption have consumption increases, while just the opposite occurs with urbanization [38]. However, been studied. Among them are population density and urbanization. In this case, while populationin Canada densitythe opposite and urbanization is true. The reduce electricity energy consumption consumption, of electricity all sectors, consumption except industrial, increasesis analyzed [37]. and Something six predictors similar happens are used. in China: Amon asg population them, population density increases, density energy is one of the consumptiondetermining increases, factors. As while a conclusion, just the opposite it is occurs obtained with that urbanization when the [38 population]. However, indensity is Canadahigher, thethe oppositeelectricity is true.consumption The electricity per consumptioncapita is lower of all [39]. sectors, In addition, except industrial, in a study of 93 iscountries, analyzed the and results six predictors were found are used. to be Among comple them,tely different population from density country is one to of country the [40]. determiningTherefore, factors. of the As studies a conclusion, that analyze it is obtained energy that consumption, when the population there are density very few that isrelate higher, energy the electricity consumption consumption in buildings per capita with is population lower [39]. Indensity. addition, Not in only a study that, of but they 93 countries, the results were found to be completely different from country to country [40]. also do not even consider a very important energy source, natural gas. Hence, the need to Therefore, of the studies that analyze energy consumption, there are very few that relateknow energy more consumptionprecisely the in influence buildings that with popu populationlation density.density Nothas onlyon energy that, but consumption, they alsoin the do case not even of this consider article, a veryby applying important the energy proposed source, method natural gas.to the Hence, specific the needcase toof Spain. know more precisely the influence that population density has on energy consumption, in the3. Materials case of this and article, Methods by applying the proposed method to the specific case of Spain.

3. MaterialsThe phases and Methods of the proposed method are as follows: first, the study area must be de- fined; second, the criteria for selecting the cities in that area are defined; third, cities must The phases of the proposed method are as follows: first, the study area must be defined;be classified second, according the criteria to density for selecting of inhabitants; the cities in and that fourth, area are the defined; consumption third, cities per inhab- mustitant beand classified per household according in tothe density buildings of inhabitants; must be obtained. and fourth, the consumption per inhabitantThe data and perused household for the study in the buildingsshould come must from be obtained. public databases and, whenever pos- sible,The should data be used of forgovernment the study origin. should All come this from information public databases must be and, properly whenever processed to possible,obtain the should desired be of results. government In this origin. way, All with this informationthe information must beon properly the energy processed consumed, it towill obtain be possible the desired to results.implement In this specific way, with measures the information that favor on thethe energyreduction consumed, of consumption it willin each be possible city and to implement implement specific renewable measures energy that sources favor the that reduction cover ofthe consumption growth in demand in in eacheach citycity and and implement reduce their renewable emissions. energy A meth sourcesodological that cover approach the growth of the in demand proposed in method each city and reduce their emissions. A methodological approach of the proposed method is shown in Figure 1. is shown in Figure1.

FigureFigure 1. 1.Methodological Methodological approach. 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 = ∑ 1 (1) j

∑j Eij mean : Ei = (2) ni v u 2 u E − E  t ∑ij ij i Standard deviation : si = (3) (ni − 1) h i ni+1 Median : Mediani = 2 th term if the total number of the elements is an ni ni (4) ( 2 )th term +( 2 +1)th term odd number, otherwise Mediani = 2  Maximum : Ei max = max Eij (5)  Minimum : Ei min = min Eij (6)

where ni is the number of cities that belong to group i; Ei is the mean energy consumed in group i; Eij is the energy consumption of city j, which is located in group i; si 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 i and 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 activités économiques dans la Communauté européenne”) 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. Table1 shows the segmentation of the cities ordered alphabetically. 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.

Sustainability 2021, 13, 7542 Table 1. Classification of Spanish cities by density. 6 of 15

Inhabitants/Hectare Cities

Albacete,Table Alcalá 1. Classification de Guadaíra, of Spanish Alcoy/Alcoi, cities by density. /Alacant, Aranjuez, Arganda del Rey, Arona, Ávila, Badajoz, Benalmádena, Benidorm, Boadilla del Monte, Cáceres, Cartagena, Castellón de la Plana, Chiclana de la Frontera, Inhabitants/Hectare Cities , Collado Villalba, Córdoba, Elche/Elx, Elda, Estepona, Ferrol, Jerez de la Frontera, Linares, Línea de , Alcalá de Guadaíra, Alcoy/Alcoi, Alicante/Alacant, Aranjuez, Arganda del Rey, la ConcepciónArona, Á vila,(La), Badajoz, Lorca, Benalm Lugo,ádena, Marbella, Benidorm, Mérida, Boadilla del Mijas, Monte, , Cáceres, Cartagena,Orihuela, , Paterna, Ponferrada, Ponte- Group 1: density < 100 vedra, PozueloCastellón dede la Alarcón, Plana, Chiclana Puerto de la de Frontera, Santa Ciudad María, Real, Rivas-Vaciamadrid, Collado Villalba, Córdoba, Rozas de (Las), Rubí, Sagunto/Sa- Elche/Elx, Elda, Estepona, Ferrol, Jerez de la Frontera, Linares, Línea de la Concepción (La), gunt, SanLorca, Cristóbal Lugo, Marbella, de la MLaguna,érida, Mijas, San Murcia, Sebastián Orihuela, de Ourense, los Reyes, Paterna, San Ponferrada, Vicente del Raspeig, Sanlúcar de Barrameda, Group 1: density < 100 Sant CugatPontevedra, del Vallès, Pozuelo Santiago de Alarcón, de Puerto Compostela, de Santa Mar Talaveraía, Rivas-Vaciamadrid, de la Reina, Rozas Toledo, de Torrelavega, Torrevieja, Utrera, Vé- Madrid (Las), Rubí, Sagunto/Sagunt, San Cristóbal de la Laguna, San Sebastián de los lez-Málaga,Reyes, , San Vicente Vila-Real del Raspeig, Sanlúcar de Barrameda, Sant Cugat del Vallès, Santiago de Alcobendas,Compostela, , Talavera Almería, de la Reina, Arrecife, Toledo, Torrelavega, Avilés, Torrevieja,Burgos, Utrera,Castelldefels, Vélez-Málaga, Cerdanyola del Vallès, Coslada, Cuenca, Vigo, Vila-Real Dos Hermanas, Ejido (El), Fuengirola, Gandía, Getxo, Gijón, Girona, , Granollers, Guadalajara, Huesca, Alcobendas, Algeciras, Almería, Arrecife, Avilés, Burgos, Castelldefels, Cerdanyola del Irún, Jaén, , León, Lleida, Logroño, Majadahonda, Málaga, Manresa, Molina de Segura, Motril, Group 2: 100 ≤ density < 200 Vallès, Coslada, Cuenca, Dos Hermanas, Ejido (El), Fuengirola, Gandía, Getxo, Gijón, ,Girona, Palencia, Granada, Palma Granollers, de Mallorca, Guadalajara, Pi Huesca,nto, Reus, Irún, JaRoquetasén, Las Palmas, de Mar, León, Lleida,, San Bartolomé de Tirajana, San Logroño, Majadahonda, Málaga, Manresa, Molina de Segura, Motril, Oviedo, Palencia, Group 2: 100 ≤ density < 200 Sebastián/Donostia,Palma de Mallorca, Santa Pinto, Cruz Reus, Roquetasde , de Mar, Santa Salamanca, Lucía San de Bartolom Tirajana,é de Tirajana, Santander, , Siero, Tarragona, Telde, Terrassa,San Torremolinos, Sebastián/Donostia, Valdemoro, Santa Cruz de Va Tenerife,lladolid, Santa Vilanova Lucía de Tirajana, i la Geltrú, Santander, Vitoria/Gasteiz, Zamora, Segovia, Siero, Tarragona, Telde, Terrassa, Torremolinos, Valdemoro, , Vilanova i A Coruña, Alcalá de Henares, Alcorcón, Barakaldo, Ceuta, Getafe, Leganés, Madrid, Mataró, Melilla, Mollet del Group 3: 200 ≤ density < 300 la Geltrú, Vitoria/Gasteiz, Zamora, Zaragoza Vallès, Móstoles,A Coruña, Alcal Pamplona/Iruña,á de Henares, Alcorc Sabaón, Barakaldo,dell, San Ceuta, Fernando, Getafe, Legan Santés, Boi Madrid, de Llobregat, Sevilla, , Viladecans Group 4: 300Group ≤ density 3: 200 ≤

tionedAlthough that the the influence climate of external is one factors of has those not been that eliminated, may be it must of begreater men- importance. That is why, to tionedhave that a vision the climate of is the one oftypes those that of mayclimates be of greater in whic importance.h cities That are is why, located, to Figure 2 shows the types have a vision of the types of in which cities are located, Figure2 shows the types ofof climates climates in Spain in and Spain the number and ofthe cities number studied that of are citi in eaches studied of them [41 ].that are in each of them [41].

FigureFigure 2. Number 2. Number of cities by of type cities of climate by oftype Spain. of climate of Spain. 4.2. Thermal and Electric Energy Consumption To obtain the consumption of thermal and electrical energy, information from the Ministry4.2. Thermal of Economic and Affairs Electric and Digital Energy Transformation Consumption and the Ministry for Ecological TransitionTo and obtain Demographic the consumption Challenge has been used:of thermal Spanish National and Statisticselectrical Insti- 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- 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 house- holds, 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 Sustainability 2021, 13, 7542 7 of 15

tute [46], National Commission on Markets and Competition [47], Secretary of State for Sustainability 2021, 13, x FOR PEER REVIEWEnergy [48 ]. 7 of 15

Sustainability 2021, 13, x FOR PEER REVIEW5. Results and Discussion 7 of 15

5.1. Sample of Study The energy consumption in the buildings of the 145 Spanish cities with more than 50,000from inhabitants official havesources, been studied. although The buildings properly are those processed. corresponding The to households,cities have been segmented into governmentfromfive groups official agencies, accordingsources, and tertiary although to sectors.Table properly Consumption1. processed. is that usually The used citi ines buildings: have been segmented into thermalfive groupsFigure in the form according 3 presents of natural gasto the Table and number electricity. 1. of The cities data used in areeach public group. and from The official most numerous groups are sources, although properly processed. The cities have been segmented into five groups accordingthe twoFigure to with Table 3 presents1the. lowest the population number of citiesdensity. in each Each group. of them The represents most numerous almost groups 40% of are cities. theThe Figuretwo rest with3 presentsof the the thegroupslowest number population only of cities represent in each density. group. 22% TheEach and most of numerousas them the represents density groups are increases, almost 40% the of number cities. of the two with the lowest population density. Each of them represents almost 40% of cities. Thecities rest decreases. of the groups Thus, onlythe grourepresentp of cities 22% andwith as the the highest density density increases, barely the numberrepresents of 3%. Thecities rest decreases. of the groups onlyThus, represent the grou 22% andp of as cities the density with increases, the highest the number density of cities barely represents 3%. decreases.However, Thus, of the the group number of cities with of the inhabitants, highest density barelyGrou representsp 2 is the 3%. However,largest, with 32% of the total. However, of the number of inhabitants, Group 2 is the largest, with 32% of the total. ofGroups the number 3 and of inhabitants, 1 follow Group with 2more is the largest,than 25%. with 32% The of one the total. with Groups the lowest 3 and number of inhabitants 1Groups follow with 3 and more 1 thanfollow 25%. with The one more with than the lowest 25%. number The one of inhabitants with the islowest Group 5,number of inhabitants is Group 5, with only 2% (Figure 4). withis Group only 2% 5, (Figure with4 ).only 2% (Figure 4).

FigureFigure 3. Number 3.3. Number Number of cities of of of cities eachcities group.of of each each group. group.

FigureFigure 4. Population4. Population of each of group each of group cities. of cities. FigureTable 4.2 showsPopulation the main of statistical each group data of theof cities. households and population of each group. The firstTable column 2 showsshows each the of themain groups statistical into which data the analysis of the has households been divided, and population of each eachgroup. ofTable its The rows 2 containsfirst shows column its statisticalthe showsmain data. statisticaleach The conclusions of the data gr areoups of similar theinto to households thosewhich indicated. the analysisand population has been ofdi- each vided,group. and The each first of column its rows showscontains each its statistical of the gr data.oups The into co whichnclusions the are analysis similar hasto those been di- indicated.vided, 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.

Table 2.POPULATION Statistical data by population and household of each NUMBEROF group of HOUSEHOLDS cities. Population Total Mean Std. Dev. Median Maximum Minimum Total Mean Std. Dev. Median Maximum Minimum Density POPULATION NUMBEROF HOUSEHOLDS Population Group 1 6,132,394Total 107,586Mean Std.79,857 Dev. Median79,878 Maximum443,243 Minimum 50,334 2,280,611 Total 40,011 Mean 29,113 Std. Dev.29,727 Median 154,421 Maximum 15,434 Minimum DensityGroup 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 GroupGroup 1 3 6,132,394 6,938,864 107,586365,203 710,04579,857 178,28879,878 3,182,981443,243 51,128 50,334 2,684,0332,280,611 141,26540,011 282,31829,113 67,11329,727 1,262,282154,421 18,967 15,434 GroupGroup 2 4 7,888,999 2,957,407 140,875328,601 491,187123,196 145,11590,730 1,620,809664,938 63,897 50,442 1,167,2603,060,916 129,69654,659 204,15948,525 54,95233,872 666,143269,347 23,831 18,160 GroupGroup 3 5 6,938,864 542,186 365,203 135,547 710,045 82,802 102,104 178,288 257,349 3,182,981 80,630 51,128 201,649 2,684,033 50,412141,265 31,580 282,318 37,685 67,113 97,044 1,262,282 29,235 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 5.2. TotalTable Energy 3 shows, Consumption 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 almostTable identical 3 shows, consumptions, in each of itseven rows, though the statis Grouptical 2 hasdata almost of the 15%total more consumption inhabitants. of each Theygroup, are in followed MWh per by year. Group The 1 highest with a 36%consumpt lowerions consumption, are produced although in Groups its number 2 and 3,of with inhabitantsalmost identical is only consumptions, 11% lower. Group even 5 isthough the one Group with the 2 has lowest almost consumption. 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. Sustainability 2021, 13, 7542 8 of 15

Table 2. Statistical data by population and household of each group of cities.

Sustainability 2021, 13, x FOR PEER REVIEWPOPULATION NUMBEROF HOUSEHOLDS 9 of 15

Population Total Mean Std. Dev. Median Maximum Minimum Total Mean Std. Dev. Median Maximum Minimum Density 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 From the point of view of electricity consumption, the behavior is similar. However, 5.2.the Total consumption Energy Consumption of Group 2 is 12% higher than that of Group 3, even though the total consumptionTable3 shows, inof each both of its rows,groups the statistical was almost data of the identical. total consumption Regarding of each thermal consumption, group, in MWh per year. The highest consumptions are produced in Groups 2 and 3, with almostGroups identical 2 and consumptions, 3 have a even behavior though Group contrary 2 has almost to that 15% morepresented inhabitants. in electricity consumption: TheyGroup are followed3 is the by one Group with 1 with the a 36% highest lower consumption, consumpt althoughion, followed its number by of Group 2. The rest of the inhabitants is only 11% lower. Group 5 is the one with the lowest consumption. groupsFrom thefollow point ofa viewsimilar of electricity behavior. consumption, the behavior is similar. However, the consumptionGraphically, of Group Figure 2 is 12% 5 higher presents than that the of Group total, 3, eventhermal though and the total electrical con- consumption of each sumptiongroup in of bothGWh groups per was year. almost The identical. consumptions Regarding thermal that consumption, a group of Groups average 2 values would present and 3 have a behavior contrary to that presented in electricity consumption: Group 3 is the oneare with also the shown. highest consumption, It can be observed followed by Groupthat, 2.at The the rest level of the of groups total follow consumption, a Groups 2 and 3 similarhave behavior.higher consumption than the average value, while Groups 4 and 5 have lower con- Graphically, Figure5 presents the total, thermal and electrical consumption of each groupsumption; in GWh perGroup year. The1 has consumptions a total consumption that a group of average almo valuesst identical would present to the average value. There- arefore, also when shown. analyzing It can be observed this that,figure at the and level relating of total consumption, it to Figure Groups 3; Figure 2 and 4 of the number of cities 3 have higher consumption than the average value, while Groups 4 and 5 have lower consumption;and inhabitants Group 1per has agroup total consumption respectively, almost it identical is not topossible the average to value. draw a conclusion about the Therefore,trend that when exists analyzing in the this figureglobal and consumption relating it to Figure of3; Figureeach4 group.of the number Global consumption does not offollow cities and a trend inhabitants proportional per group respectively, to the number it is not possible of cities to draw per agroup conclusion or of inhabitants. Regarding about the trend that exists in the global consumption of each group. Global consumption doeselectrical not follow and a trend thermal proportional consumption, to the number the of cities behavi per groupor is or ofsimilar inhabitants. to that described, except in RegardingGroup 1, electrical which and in thermalthe case consumption, of electrical the behavior consumption is similar to is that above described, the average value and in the except in Group 1, which in the case of electrical consumption is above the average value andcase in of the thermal, case of thermal, below. below.

Figure 5. Thermal,5. Thermal, electric, electric, and total mean and energy total consumption mean energy of each consumption group of cities. 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 con- sumption 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 Std. Std. Std. Mean Median Max. Min. Mean Median Max. Min. Mean Median Max. Min. Density dev. Dev. Dev. 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 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 Std. Std. Std. Total Mean Median Max. Min. Total Mean Median Max. Min. Total Mean Median Max. Min. Density Dev. Dev. Dev. 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 Sustainability 2021, 13, 7542 10 of 15

5.3. Energy Consumptions per Household Table4 and Figure6 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 Std. Std. Std. Mean Median Max. Min. Mean Median Max. Min. Mean Median Max. Min. Density Dev. Dev. Dev. 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 Sustainability Group2021, 3 13, x 11.88FOR PEER 3.67 REVIEW 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 10 of 15 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

FigureFigure 6. Thermal, 6. Thermal, electric, and electric, total mean and energy total consumption mean perenergy household co ofnsumption each group of cities.per household of each group of cities.Thermal consumption follows a similar behavior, although not identical. The main difference is that the second group with the highest consumption is not the densest cities, Group 5, but Group 3, although with similar values between them. The group with the highestThermal consumption consumption is 42% higher than follows the average, a similar while the behavior, group with thealthough lowest not identical. The main thermaldifference consumption is that is 30%the lower. second Therefore, group the differenceswith the between highest the consumption extreme groups is not the densest cities, are much more pronounced than in the case of the comparison in total consumption. In fact,Group among 5, the but less Group dense groups 3, althou the differencegh with that existssimilar is almost values 40%. Onlybetween Group 1them. The group with the hashighest a lower valueconsumption than the value is of 42% the mean higher group. than the average, while the group with the lowest thermalRegarding consumption electricity consumption, is 30% lower. it is the leastTherefore, dense group the that differences has the highest between the extreme groups consumption, and Group 3 that has the lowest, with the consumption of the rest of the groupsare much being almostmore identical. pronounced However, than the difference in the between case of the the maximum comparison and mini- in total consumption. In mumfact, consumption among the is only less 3%. dense Therefore, groups the electrical the differenc consumptione presentsthat exists an inelastic is almost 40%. Only Group 1 behavior. In addition, now the opposite occurs, and only Group 1 is the one with a higher-than-averagehas a lower value consumption. than the value of the mean group. TheRegardingDVI index defined electricity in Equation consumption, (7) has been used to it easily is the analyze least the variationsdense ingroup that has the highest consumption between groups. Figure7 shows the index for the three types of consumption. Totalconsumption, consumption increases and Group as population 3 that density has increases, the lowest, except inwith the group the ofconsumption most of the rest of the groups being almost identical. However, the difference between the maximum and mini- mum consumption is only 3%. Therefore, the electrical consumption presents an inelastic behavior. In addition, now the opposite occurs, and only Group 1 is the one with a higher- than-average consumption. The DVI index defined in Equation 7 has been used to easily analyze the variations in consumption between groups. Figure 7 shows the index for the three types of consump- tion. Total consumption increases as population density increases, except in the group of most populated cities, in which it decreases slightly. Furthermore, this increase is rela- tively mild. In the case of thermal consumption, the behavior of consumption is similar to the total. However, the differences are much more pronounced, reaching 70% between the extremes. Regarding electricity consumption, it is similar in all groups, with a minimal difference between all of them. As conclusion: the higher the population density in the cities, the higher the con- sumption, except in the four cities with the highest density, in which it decreases slightly; and the electrical consumption is almost inelastic, whereas the thermal one is not. Fur- thermore, although the increase in total consumption between groups is approximately homogeneous, the growth in thermal consumption is not. In fact, a very significant in- crease occurs among the groups with the lowest density. Sustainability 2021, 13, 7542 11 of 15

populated cities, in which it decreases slightly. Furthermore, this increase is relatively mild. In the case of thermal consumption, the behavior of consumption is similar to the total. Sustainability 2021, 13, x FOR PEER REVIEW 11 of 15 However, the differences are much more pronounced, reaching 70% between the extremes. Regarding electricity consumption, it is similar in all groups, with a minimal difference between all of them.

FigureFigure 7. Variation 7. Variation of the DVI ofindex the DVI for energy index consumptions for energy per householdconsumptions of each group per of household cities. of each group of cities. As conclusion: the higher the population density in the cities, the higher the consump- tion,5.4. exceptEnergy in the Consumptions four cities with the per highest Inhabitant density, in which it decreases slightly; and the electrical consumption is almost inelastic, whereas the thermal one is not. Furthermore, althoughTable the increase 5 shows in total the consumption statistical between data groups of the is approximately consumption homogeneous, per inhabitant and Figure 8 the themean growth values in thermal of consumptioneach group is not.and In the fact, mean a very significant consumption increase occurs of all among the groups, in MWh per year. the groups with the lowest density. As density increases, per capita consumption increases, up to a density of between 300 5.4.and Energy 400 Consumptions inhabitants/hectare, per Inhabitant Group 4. The four cities that make up the group with the Table5 shows the statistical data of the consumption per inhabitant and Figure8 the meanhighest values density, of each group Group and the 5, mean have consumption consumption of all the identical groups, in MWh to Group per year. 3. The greatest difference Asin densityconsumption increases, per between capita consumption groups occurs increases, between up to a density the ofone between corresponding 300 to the lowest den- and 400 inhabitants/hectare, Group 4. The four cities that make up the group with the highestsity group, density, GroupGroup 5, have 1, and consumption the next, identical reaching to Group 15 3. The%. greatestAmong difference the rest in of the groups, the differ- consumptionence in consumption between groups occursonly betweenoscillates the one 5%. corresponding The only togroup the lowest with density a value lower than the mean group,value Group is Group 1, and the 1. next, reaching 15%. Among the rest of the groups, the difference in consumption only oscillates 5%. The only group with a value lower than the mean value is Group 1. Thermal consumption is similar to total consumption. Group 4 is the one with the highest consumption, with Group 3 being the next. However, the difference between the three densest groups is barely 5%. The one with the lowest consumption is Group 1, which is also the only one that has a value lower than the average of the groups. In this case, the differences in consumption between groups are more pronounced. Thus, the difference between the extreme groups reaches over 70%. The greatest difference occurs between Groups 1 and 2, being greater than 45%. However, the difference from the rest of the groups is just over 20%. Sustainability 2021, 13, x FOR PEER REVIEW 12 of 15

Table 5. Statistical data of energy consumptions per inhabitant of each group of cities.

TOTAL (MWh/year) THERMAL (MWh/year) ELECTRIC (MWh/year) Population Std. Std. Std. Mean Median Max. Min. Mean Median Max. Min. Mean Median Max. Min. Density Dev. Dev. Dev. Group 1 3.69 1.05 3.33 5.78 2.40 0.94 0.91 0.56 2.82 0.00 2.75 0.32 2.74 3.57 2.25 Group 2 4.33 1.19 4.53 6.47 2.40 1.57 1.11 1.93 3.76 0.00 2.76 0.34 2.71 3.86 2.25 Group 3 4.48 1.45 4.79 6.35 1.67 1.84 1.12 2.13 3.45 0.00 2.64 0.38 2.66 2.96 1.67 Group 4 4.56 1.27 4.79 6.35 2.43 1.90 1.07 2.13 3.45 0.18 2.66 0.23 2.66 2.96 2.25 Group 5 4.48 1.07 4.79 5.78 2.62 1.80 0.92 2.13 2.82 0.19 2.68 0.18 2.66 2.96 2.43

Sustainability 2021, 13, x FOR PEER REVIEW 12 of 15

Sustainability 2021, 13, 7542 12 of 15

Table 5. Statistical data of energy consumptions per inhabitant of each group of cities. Table 5. Statistical data of energy consumptions per inhabitant of each group of cities. TOTAL (MWh/year) THERMAL (MWh/year) ELECTRIC (MWh/year) TOTAL (MWh/year) THERMAL (MWh/year) ELECTRIC (MWh/year) Population Std. Std. Std. Population Std. Std. Std. MeanMean MedianMedian Max.Max. Min.Min. Mean Mean Median Max.Median Min. Max. Mean Min. MedianMean Max. Min.Median Max. Min. DensityDensity Dev. Dev. Dev. Dev. Dev. Dev. Group 1 3.69 1.05 3.33 5.78 2.40 0.94 0.91 0.56 2.82 0.00 2.75 0.32 2.74 3.57 2.25 Group 1 3.69 1.05 3.33 5.78 2.40 0.94 0.91 0.56 2.82 0.00 2.75 0.32 2.74 3.57 2.25 GroupGroup 2 2 4.33 4.33 1.19 1.19 4.53 4.53 6.47 6.47 2.40 2.40 1.57 1.571.11 1.93 1.11 3.76 1.93 0.00 3.76 2.76 0.34 0.00 2.71 2.76 3.86 0.34 2.25 2.71 3.86 2.25 GroupGroup 3 3 4.48 4.48 1.45 1.45 4.79 4.79 6.35 6.35 1.67 1.67 1.84 1.841.12 2.13 1.12 3.45 2.13 0.00 3.45 2.64 0.38 0.00 2.66 2.64 2.96 0.38 1.67 2.66 2.96 1.67 GroupGroup 4 4 4.56 4.56 1.27 1.27 4.79 4.79 6.35 6.35 2.43 2.43 1.90 1.901.07 2.13 1.07 3.45 2.13 0.18 3.45 2.66 0.23 0.18 2.66 2.66 2.96 0.23 2.25 2.66 2.96 2.25 Group 5 4.48 1.07 4.79 5.78 2.62 1.80 0.92 2.13 2.82 0.19 2.68 0.18 2.66 2.96 2.43 Group 5 4.48 1.07 4.79Figure 5.788. Thermal, 2.62 electric, 1.80 and 0.92 total 2.13mean energy 2.82 cons 0.19 umption 2.68 per 0.18 inhabitant 2.66 of 2.96each group 2.43 of cities.

Thermal consumption is similar to total consumption. Group 4 is the one with the highest consumption, with Group 3 being the next. However, the difference between the three densest groups is barely 5%. The one with the lowest consumption is Group 1, which is also the only one that has a value lower than the average of the groups. In this case, the differences in consumption between groups are more pronounced. Thus, the difference between the extreme groups reaches over 70%. The greatest difference occurs between Groups 1 and 2, being greater than 45%. However, the difference from the rest of the groups is just over 20%. Regarding electricity consumption, this is similar in all groups, oscillating only 4% among all. However, here it is Groups 1 and 2 that have a higher consumption than the FigureFigure 8. Thermal,8. Thermal, electric, electric, and total mean and energy total consumption mean energy per inhabitant consumption of each group per of inhabitant cities. of each group of mean, although this is minimal. cities.Regarding electricity consumption, this is similar in all groups, oscillating only 4% amongThe all. However,variation here of itthe is Groups DVI index 1 and 2for that all have consumptions a higher consumption per inhabitant than the is shown in Figure mean,9. Total althoughThermal consumption this consumption is minimal. increases is similar with increasing to total co populationnsumption. density, Group except 4 is the in onethe groupwith the of fourThe cities variation with of thetheDVI highestindex for density. all consumptions Furtherm per inhabitantore, except is shown in in GroupFigure9 . 1, the variation that Totalhighest consumption consumption, increases with with increasing Group population 3 being density, the next. except However, in the group the of four difference between the citiesoccursthree with densest among the highest groups the density. other is barely Furthermore,groups 5%. is 5%.The except However,one in Groupwith 1,the from the lowest variation Group consumption that 1 to occurs 2 there is is Group a difference 1, which of among15%.is also the the other only groups one is that 5%.However, has a value from Grouplower 1 than to 2 there the is average a difference of of the 15%. groups. In this case, the differences in consumption between groups are more pronounced. Thus, the difference between the extreme groups reaches over 70%. The greatest difference occurs between Groups 1 and 2, being greater than 45%. However, the difference from the rest of the groups is just over 20%. Regarding electricity consumption, this is similar in all groups, oscillating only 4% among all. However, here it is Groups 1 and 2 that have a higher consumption than the mean, although this is minimal. The variation of the DVI index for all consumptions per inhabitant is shown in Figure 9. Total consumption increases with increasing population density, except in the group of four cities with the highest density. Furthermore, except in Group 1, the variation that occurs among the other groups is 5%. However, from Group 1 to 2 there is a difference of 15%.

FigureFigure 9. Variation9. Variation of the DVIof theindex DVI for index energy consumptionsfor energy consumptions per inhabitant of each per group inhabitant of cities. of each group of cities.

Figure 9. Variation of the DVI index for energy consumptions per inhabitant of each group of cities. Sustainability 2021, 13, 7542 13 of 15

Regarding thermal consumption, the behavior is similar, but here the differences are again more pronounced. These differences are greater between Group 1 and 2 (reach- ing 45%), and between 2 and 3 (reaching 20%). Regarding electricity consumption, the behavior is almost identical in all groups. There is only a 3% variation between all of them. The conclusions are similar to those obtained when studying households: the higher the population density, the higher the consumption, except in the cities with the highest density, where there is a slight decrease; in addition, the thermal consumption is elastic, with the electrical being practically inelastic. In addition, the differences between groups are more pronounced than those presented in consumption per household, mainly in relation to thermal consumption.

6. Conclusions

Eighty percent of GHG emissions correspond to CO2. 40% of the emissions are due to buildings in the residential and tertiary sectors. In addition, they consume 36% of the energy. Against this background, governments consider cities in general, and buildings in particular, priority centers for reducing energy consumption and emissions. Considering also that the COVID-19 pandemic has mainly affected cities, the concern of governments is evident. For all this, Covenant of Mayors and the COVID-19 recovery plan have been created. To help governments make decisions and utilities to plan their infrastructures correctly, this paper has analyzed the energy consumption of buildings in cities. Electricity and thermal consumption in the form of natural gas have been considered. These are the forms of energy commonly consumed in buildings. The study has been carried out from the point of view of the population density of the cities. For this, the area that the city actually occupies has been considered, and not the area covered by the municipality, which always has large uninhabited areas. In addition, the energy consumption of all buildings has been considered, both for residential and tertiary use. The results have been analyzed per inhabitant and per household. Therefore, the consumption of non-residential buildings has been distributed among the inhabitants and households of the city. This has been done because cities have a greater or lesser number of tertiary sector buildings to serve their inhabitants, and they exist insofar as they are necessary for them. For ease of analysis, an index has been introduced. Information of public access has been used for the study. The case of the 145 Spanish cities with more than 50,000 inhabitants has been presented as an application of the proposed method. The results of the total consumption of the groups do not show a relationship with respect to the number of cities in each group or with the number of inhabitants of each one of them. The findings obtained on consumption per household show that the higher the popu- lation density in the city, the higher the consumption. However, there is an exception in the four cities with the highest density, in which consumption decreases slightly compared to the previous group. Furthermore, while total consumption has an approximately homoge- neous growth among the different groups, in the case of thermal consumption such growth is very marked. Regarding electricity consumption, it hardly changes as a consequence of the variation in the density of cities. Thus, electrical consumption is almost inelastic, while thermal is quite elastic. Regarding consumption per inhabitant, the conclusions are similar to those obtained per household. Thus, the higher the population density in the city, the higher the con- sumption, except in the four densest cities. The fact that electricity consumption is inelastic is also represented. However, thermal consumption is elastic and even with variations between groups much more pronounced than in the case of consumption per household. These conclusions will allow utilities and governments to have a detailed understand- ing of the behavior of energy consumption in cities as a function of their density. In this way, utilities will be able to adequately plan their infrastructures and governments will issue laws that help optimize energy use in buildings. Sustainability 2021, 13, 7542 14 of 15

Author Contributions: Conceptualization, I.M.Z.-S. and P.J.Z.-P.; methodology, I.M.Z.-S. and P.J.Z.-P.; validation, I.M.Z.-S., F.J.Z.-S. and P.J.Z.-P.; formal analysis, I.M.Z.-S., F.J.Z.-S. and P.J.Z.-P.; investiga- tion, I.M.Z.-S. and P.J.Z.-P.; data curation, I.M.Z.-S. and F.J.Z.-S.; writing—original draft preparation, P.J.Z.-P.; writing—review and editing, I.M.Z.-S., F.J.Z.-S. and P.J.Z.-P.; visualization, I.M.Z.-S.; supervi- sion, P.J.Z.-P.; project administration, P.J.Z.-P.; funding acquisition, P.J.Z.-P. All authors have read and agreed to the published version of the manuscript. Funding: This research received no external funding. Institutional Review Board Statement: Not applicable. Informed Consent statement: Not applicable. Data Availability Statement: Not applicable. Acknowledgments: The authors would like to thank eCitySevilla project for providing facilities to conduct the research. Conflicts of Interest: The authors declare no conflict of interest.

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