Climatic Zoning for Building Construction in a Temperate Climate

Sustainable Cities and Society 40 (2018) 352–364

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Sustainable Cities and Society

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Climatic zoning for building construction in a temperate climate of Chile T ⁎ Konstantin Vericheva,b, Manuel Carpioc, a Institute of Civil Engineering, Faculty of Engineering Sciences, Universidad Austral de Chile, Valdivia, Chile b Department of Civil Engineering, Universidad de Granada, Granada, Spain c Department of Construction Engineering and Management, School of Engineering, Pontiﬁcia Universidad Católica de Chile, Santiago, Chile

ARTICLE INFO ABSTRACT

Keywords: In Chile, the official document that defines energy efficiency for building construction is the General Ordinance Building climatology of Urban Planning and Construction which defines seven thermal zones based on the annual average values of Thermal zoning heating degree-days (base temperature of 15 °C) calculated in 1999. In the context of climate change, the ob- Degree-Days method solete meteorological data must be updated. In the present study, we assessed three regions in the south of Chile Climatic zoning (La Araucanía, Los Ríos, and Los Lagos); updated annual average values of the heating degree-days using data Severity Climate Indexes from the meteorological observations for the past decade and updated the thermal zones. The results obtained Chile shows that the 20% of the municipalities were different from the thermal zones of the General Ordinance of Urban Planning and Construction. In addition, we considered the possibility of the climate severity index method application for climatic zoning in the study area. Due to this method, we identified the relative differences of energy demand for heating and cooling for the same building in different climatic conditions. The climatic zones were identifying based on the Technical Building Code of Spain. As a result, we detect three climatic zones for this regions in Chile and it was found that they were similar to the regions of northwest Spain. And finally, there was an analysis of the spatial distribution of the thermal and climatic zones and a comparison of the construction recommendations for each one of them.

1. Introduction (General Ordinance of Urban Planning and Construction) of the Ministry of Housing and Urban Planning of Chile provided the building Climatic zoning data is used in many areas of economic activity. The standards for the country. One of these standards is the Thermal correct definition of climatic zones helps to increase agricultural pro- Regulation of the OGUC that is directly related to energy efficiency of ductivity, use appropriate building materials, and design houses with buildings. This standard defines seven thermal zones with different the maximum energy efficiency, among other uses (de Rosa, Bianco, conditions for housing construction (Bustamante, 2009; Chile, 2009). Scarpa, & Tagliafico, 2015; Falasca, Ulberich, & Ulberich, 2012; The average annual values of heating degree-days (HDD) were used to Moradchelleh, 2011; Rakoto-Joseph, Garde, David, Adelard, & determine these zones. This zoning is not considered alongside the Randriamanantany, 2009). other climatological parameters. The classification of energy efficiency in housing is defined as the On the other hand, in Chile there is a standard NCh 1079-2008 costs of energy needed to maintain comfortable housing conditions in “Architectonic and construction – Climatic zoning for dwellings for Chile and different seasons of the year. In addition, energy efficiency in housing recommendations for architectural design” (Chile, 2008; Palme & Vásquez, depends on architectonic, building characteristics and thermal systems 2015). The standard NCh 1079–2008 divides the country into 9 climatic (Carpio, Zamorano, & Costa, 2013; Carpio, Garcia-Maraver, Ruiz, & zones and is based on various meteorological parameters (extreme and Martin-Morales, 2014), climatic parameters of the regions where the average temperatures, solar radiation, thermal oscillation, cloudiness, buildings are located (Carpio, Jódar, Rodríguez, & Zamorano, 2015) humidity, precipitation, vegetation, etc.) (Bustamante, Cepeda, and building recommendations that are regulated by the standards of Martínez, & Santa María, 2009). The main idea of this standard is to each country (Carpio, Garcia-Maraver, Ruiz, Martinez, & Zamorano, promote proper architectural design (Chile, 2008). However, this 2014). standard is only recommendatory and is not the main document that The Ordenanza General de Urbanismo y Construcciones (OGUC) regulates energy-efficient construction in Chile (Bustamante, 2009;

⁎ Corresponding author. E-mail address: [email protected] (M. Carpio). https://doi.org/10.1016/j.scs.2018.04.020 Received 7 September 2017; Received in revised form 7 March 2018; Accepted 14 April 2018 Available online 19 April 2018 2210-6707/ © 2018 Elsevier Ltd. All rights reserved. K. Verichev, M. Carpio Sustainable Cities and Society 40 (2018) 352–364

Bustamante et al., 2009; Ossio, Veas, & Herde, 2012): the main docu- approximation and interpolation of parameters to obtain maps of cli- ment is the Thermal Regulation of OGUC. matic and thermal zones; (d) determining climatic and thermal zones The main disadvantage of the zoning of OGUC is accounting spe- for the capital cities of the municipalities; and (e) comparison of the cifically for winter conditions for buildings, the other disadvantage is recommendations and construction standards provided by the CTE and the low standards of thermal transmission for the structural elements of by the OGUC for study area. buildings in some regions (Bustamante, 2009). Bustamante considers two cities in the same thermal zone of OGUC (the cities of Calama and 2. Material and methods Valparaiso) and defines that energy demand for heating in Calama is 65% more than in Valparaiso for the same building. Significant differ- 2.1. Methods for determining climatic zones ences of the energy demand for heating in these cities is related to the inaccuracy in the determination of the thermal zones of OGUC 2.1.1. Calculation of heating and cooling degree-days (Bustamante et al., 2009). Simulation of thermal conditions inside these Two parameters were used, to identify the climatic zones, namely: buildings, that were built based on standards of the OGUC for all (a) cooling degree-days (CDD); and (b) heating degree-days (HDD). thermal zones, showed a discrepancy between simulated temperatures Degree-days is a universal climatic indicator used to calculate energy and the comfortable thermal conditions in various regions of Chile consumption of housing and emission of greenhouse gases resulting (Vasco, Muñoz-Mejías, Pino-Sepúlveda, Ortega-Aguilera, & García- from the heating and cooling of dwellings (Carpio et al., 2015). Herrera, 2017). There are different methods to reconstruct and calculate CDD and The method of the degree-days is used for thermal zoning in Chile HDD values. Some methods are based on daily average temperature and for climatic zoning in others countries of the world (ECBC, 2006; values and their statistical characteristics (Walsh & Miller, 1983). Other Owen, 2013; Walsh, Cóstola, & Labaki, 2017). This method has proven methods use minimum and maximum daytime temperatures to calcu- to be effective for analysing the influence of climatic conditions on the late these parameters (CIBSE, 2006; Matzarakis & Balafoutis, 2004). In energy consumption of buildings (CIBSE, 2006). Currently, there are addition, to restore HDD values, used monthly (Erbs, Klien, & Beckman, many methods and models for the calculation of degree-days (Borah, 1983) and annual (Mourshed, 2012) average temperature values. Singh, & Mahapatra, 2015); however, the most accurate method always Indeed, these two parameters (CDD and HDD) are dependent on uses hourly data of temperature measurements collected at weather environmental temperature and have their own climatic trends stations (Carpio et al., 2015), therefore we will use this type of data in (Castañeda & Claus, 2013; Lam, Tsang, & Li, 2004). That is why it is this work. important to update and renew information about these parameters. Another method for climate zoning to be consider in this work, is In order to reconstruct the CDD and HDD parameters in the present the climate severity index method (Markus, 1982). This method ad- study, we used data of the hourly temperature measurements. Daily ditionally, helps to take into account effects of solar radiation on HDD and CDD are obtained by Eqs. (1) and (2), respectively (Mourshed, buildings in climatic zoning. The climate severity index method reflects 2012): the relationship between the energy requirement of a building and i=1 climatic features based on ́severitý of the climate. The climate severity ⎡ +⎤ 1 HDDd = ∑ () Tbi− T ⎢ ⎥ 24 index for some regions, is calculated on the basis of the simulation of ⎣ 24 ⎦ (1) energy consumption of building types, common in this region in the i=1 whole range of constructive and architectural scenarios in average cli- ⎡ +⎤ 1 CDDd = ∑ () Tib− T matic conditions (Makhmalbaf, Srivastava, & Wang, 2013). The divi- ⎢ ⎥ 24 ⎣ 24 ⎦ (2) sion of climate severity index for the winter severity index (WSC) and summer severity index (SCS) allows for the analysis of energy con- where Ti – hourly temperature measured at the i-th hour of the day; sumptions of buildings for heating and cooling. Good correlation be- index (+) means that it is only necessary to calculate positive differ- tween the WSC and SCS indexes and climatic parameters (degrees-days ences between the base temperature (Tb) and Ti. Daily CDD and HDD and total solar radiation) makes it possible to calculate the values of values are used to calculate monthly, quarterly, and annual values. these indexes in other regions where simulation of energy consumption To correctly calculate energy efficiency in housing, it is very im- of buildings was not carried out (de la Flor, Lissén, & Domínguez, 2006; portant to use adequate base temperature for different weather condi- Makhmalbaf et al., 2013). tions (Lindelöf, 2016), but in our situation in conditions of insignificant The main advantage of this method is the possibility of comparing variation of climates in this study area we will use fixed values of base the energy consumption of certain buildings in different climatic zones temperature. The American Society of Heating determined HDD with a relative to the reference point (Markus, 1982; Salmerón, Álvarez, base temperature of approximately 18 °C (Owen, 2013). On the other Molina, Ruiz, & Sánchez, 2013). In this study, the method described in hand, the European Standard EN ISO 15927-6 recommends using a base Código Técnico de la Edificación (CTE) (Technical Building Code) has temperature of 12 °C. been used for the calculation of the WSC and SCS indexes (de la Flor Spain and Portugal use the same base temperature of 20 °C to cal- et al., 2006; Spain, 2006). This document, defines the norms for the culate HDD and CDD (Portugal, 2006; Spain, 2006). In Chile, the base proper characterization of energy efficiency in buildings in Spain temperature of 15 °C is used to calculate HDD (Chile, 2009). (Spain, 2006). In CTE, combinations of WCS and SCS indexes define climatic zones of Spain. 2.1.2. Method of technical building code of Spain The main goals of the present study were to update the HDD cli- We used the CTE of Spain to determine the climatic zones. In this matic values from hourly measured data of temperature for the studied document, the climatic zones depend on two indexes: winter climatic area, and on the basis of this update, improve thermal zones of OGUC; severity (WCS) and summer climatic severity (SCS). Data of global solar determinate the climatic zones for buildings in the south of Chile with radiation, HDD, and CDD is necessary to calculate those two indexes. the climate severity index method; compare the spatial distribution of CSaRadbDGcRadDGdRadeDGf=× +× +× × +×()22 +× + ; climatic zones of CTE and thermal zones of OGUC in the study area; and to determinate areas of equal energy consumption of buildings in Chile (3) and Spain. The following steps to achieve the main goals of the study CS here refers to WCS or SCS. For the case of WCS: DG is the monthly were performed: (a) defining the methods for identifying climatic and average HDD with base temperature of 20 °C for winter months (June, thermal zones; (b) using actual data to determine the climatic and July, and August), and Rad [kWh/m2] is the monthly average accu- thermal zones in all the meteorological stations of the study area; (c) mulated global radiation incident upon a horizontal surface for the

353 K. Verichev, M. Carpio Sustainable Cities and Society 40 (2018) 352–364

Table 1 Coeﬃcients values to calculate WSC and SCS according to the CTE.

abcd e f

− − − − − − WCS −8.35 10 3 3.72 10 3 −8.62 10 6 4.88 10 5 7.15 10 7 −6.81 10 2 − − − − − − SCS 3.724 10 3 1.409 10 2 −1.869 10 5 −2.053 10 6 −1.389 10 5 −5.434 10 1

Table 2 Climatic zones according to the CTE.

SCS ≤ 0.6 0.6 < SCS≤0.9 0.9 < SCS≤1.25 SCS > 1.25

WCS ≤ 0.3 A1 A2 A3 A4 0.3 < WCS≤0.6 B1 B2 B3 B4 0.6 < WCS≤0.95 C1 C2 C3 C4 0.95 < WCS≤1.3 D1 D2 D3 D4 WCS > 1.3 E1 E2 E3 E4

Table 3 similar amount of energy for heating, and SCS provides the values of Thermals zones of Chile according to the OGUC. energy consumption to cooling the houses. Climatic severity is deﬁned as the ratio between the energy de- Zone Value of annual HDD (base 15 °C) mands of a dwelling in any given location and the same dwelling in a 1 ≤500 reference point location. In the case of Spain, the reference point is 2 > 500 ≤750 Madrid. This way, the climatic severity in Madrid is 1.0 unit for SCS and ≤ 3 > 750 1000 WSC (Carpio et al., 2015). 4 > 1000 ≤1250 5 > 1250 ≤1500 The new descriptive document of the Reference Climates of the 6 > 1500 ≤2000 Ministry of Public Works and Transport of Spain, July 2015 (Spain, 7 > 2000 2015), presents the following new formula for calculating SCS: SCS=× a GD +× b GD2 + c (4) where GD is the sum of the summer degree-days with a base temperature of 20 °C for the summer months (December, January, February and March in southern hemisphere); a = 2.990E-3; b = 1.1597E-07; and c = 1.713E-1. In this work, we calculate the SCS index with two methods: from solar radiation and CDD (Eq. (3)); and only from CDD (Eq. (4)). The possibility of using Eq. (4) is based on the fact that in summer the temperature is a function directly dependent on solar radiation.

2.1.3. Method of general ordinance of urban planning and construction of Chile Decree No. 192 of 11th November 2005, which amended Decree No. 47 of the OGUC (Chile, 2009), incorporated provisions for thermal insulation requirements in dwellings, in accordance with zoning ex- clusively based on the required heating temperature for habitable comfort in Chile. The OGUC Application Manual of Thermal Regulation (Chile, 2009) determines seven thermal zones in Chile (Table 3). This Fig. 1. Boxplot of climatic data of the global solar radiation and boxplot of table shows the values of heating degree-days, which is the sum of climatic data of the average maximum temperature for summer period and the degree-days throughout the year. average minimum temperature for winter period for 50 cities of Spain and for In the zoning established by Decree No. 192, the required HDD to 44 meteorological stations in study area of Chile. achieve thermal comfort with a base temperature of 15 °C, should increase in colder zones. This fact explains that zoning considers less HDD same months. For the case of SCS: DG is the monthly average CDD with in zone 1 of the north of Chile (≤500) and greater HDD in zone 7 of the base temperature of 20 °C for summer months (December, January, southern tip (> 2000) (Bustamante, 2009). These values have only February, and March), and Rad [kWh/m2] is the monthly average ac- been calculated for 1999, which, from the climatology point of view, is cumulated global radiation incident upon a horizontal surface for the not enough to obtain adequate thermal zoning. same months. Two types of DG are calculated from hourly temperature measurements (Eqs. (1) and (2)). Coefficients a, b, c, d, e, and f are 2.2. Database shown in Table 1. Depending on WCS and SCS values, it is possible to determine five In the present study, direct-access data of hourly temperature and climatic zones (A, B, C, D, and E) for winter and four zones (1, 2, 3, and global solar radiation from different sources of various agencies were 4) for summer, as shown in Table 2, according to the corresponding used. intervals. Hourly temperature and global radiation measured by: Combinations of values of the two indexes can characterise up to 20 climatic zones (Table 2). The concept of this climatology is that two (a) Ministry of Agriculture – National Agroclimatic Network (35 sta- similar houses located in two places with the same WCS consume a tions) (Agromet, 2017);

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Fig. 2. Dependence between WCS and SCS calculated from simulation data of solar radiation and from measurement data.

area is located in a temperate climatic zone (Kottek, Grieser, Beck, Rudolf, & Rubel, 2006), based on the new climatic zoning of the continental part of Chile (Sarricolea, Herrera-Ossandon, & Meseguer-Ruiz, 2016). The three regions of study were: 1. La Araucanía. Parts of the central and northern areas of the region have a Mediterranean climate. The Pacific coast has a Mediterranean climate (warm summer) influenced by the ocean [Csb´] (Puerto Saavedra). Temuco, the capital city of the region, has a Mediterranean climate (warm summer) [Csb]. The lower ranges of the Andes Mountains have a Mediterranean climate (warm summer) influenced by the mountains [Csb(h)], and a Mediterranean climate (mild summer) [Csc] (Sarricolea et al., 2016). 2. Los Ríos. This region is characterised by a marine west coast climate. Valdivia, the capital city of the region, is located in an area of marine west coast climate (warm and dry summer) influenced by the ocean [Cfb´(s)]. The central part of the region is characterised by a marine west coast climate (warm and dry summer) [Cfb(s)]. The lower ranges of the Andes Mountains have a Mediterranean climate (warm summer) influenced by the mountains [Csb(h)], and a Mediterranean climate (mild summer) [Csc] (Sarricolea et al., 2016). 3. Los Lagos. This region is entirely located in a marine west coast climate, with the exception of the mountain areas. Osorno has a marine west coast climate (warm and dry summer) [Cfb(s)]. On the other hand, the capital city Puerto Montt, has a marine west coast climate (warm Fig. 3. Scheme of calculation methodology of WCS and SCS. summer) influenced by the ocean [Cfb´]. The south of Puerto Montt has a marine west coast climate (warm summer) [Cfb] (Sarricolea et al., (b) Ministry of the Environment – National Air Quality Information 2016). System (4 stations) (SINCA, 2017); In general terms, the three regions have temperate (97.5%) and (c) Directorate General of Civil Aviation, Meteorological Directorate of tundra (2.5%) climates in the mountainous areas (Sarricolea et al., Chile (5 stations) (DMC, 2017). 2016). Temperate marine west coast climates prevail from 39°32′ Sto 43° S. The reduction in the height of the Andes Mountains in this part of Modelled global radiation data: Chile, the impact of western transfer of air masses, high rainfall, and the influence of the ocean, determine the climatic conditions in this region. (a) Solar Energy Explorer. Programme of the School of Physical In Valdivia, the average temperatures of the coldest and warmest Sciences and Mathematics of the University of Chile (ExSol, 2017). months are +6.7 °C and +16.2 °C, respectively, and annual rainfall is 1734 mm. In Puerto Montt, the average temperatures of the coldest and warmest months are +6.2 °C and +14.3 °C, respectively, and annual 2.3. Study area rainfall is 1569 mm (DMC, 2017). In La Araucanía, due to increased solar radiation and reduced The present study focused on three regions in southern Chile, rainfall, the climatic zones change to a Mediterranean climate. For this namely: La Araucanía; Los Ríos; and Los Lagos. The three regions to- reason, it can be affirmed that this region has the coldest Mediterranean gether have a total area of 98,855 km2 and a total population of ap- climate of Chile. In Temuco, the average temperatures of the coldest proximately 2 million inhabitants (INE, 2016). This area of study was and warmest months are +6.9 °C and +16.1 °C, respectively, with an chosen to carry out a direct comparison with areas of Spain where the annual rainfall of 1103 mm (data of the Chilean Meteorological same climate condition occurs, and compare two methods of climate Department for 1986–2015) (ExClim, 2017). zoning and the standards of housing construction in the two countries. According to the Köppen-Geiger climate classification, the study

355 K. Verichev, M. Carpio Sustainable Cities and Society 40 (2018) 352–364

Table 4 Comprehensive information about meteorological stations and calculated values of WCS and SCS for these stations.

Number of Name of station Region Lat. Long. Alt. WCS SCS station Value Years of % of data Value Years of % of data New SCS measurements measurements

1 Carillanca Araucanía −38.69 −72.42 200 1.01 7 99% 0.32 7 98% 0.11 2 Tranapuente Araucanía −38.69 −73.35 64 0.86 7 99% 0.10 7 100% −0.15 3 Quiripio Araucanía −38.64 −73.24 332 0.94 7 100% 0.10 7 100% −0.14 4 La Providencia Araucanía −38.29 −72.64 254 0.97 7 100% 0.38 7 92% 0.15 5 San Luis Araucanía −38.40 −71.90 549 1.12 7 99% 0.35 6 99% 0.12 6 Dominguez Araucanía −38.92 −73.24 93 0.87 7 100% 0.10 7 100% −0.15 7 C.Llollinco Araucanía −38.98 −73.00 24 0.99 7 100% 0.18 7 100% −0.06 8 Cuarta Faja Araucanía −39.12 −72.61 115 1.00 7 100% 0.33 7 100% 0.13 9 Sta. Adela Araucanía −38.76 −72.89 50 0.95 7 100% 0.31 6 100% 0.09 10 Lago Verde Los Ríos −40.17 −72.63 248 1.12 6 100% 0.14 5 100% −0.03 11 Remehue Los Lagos −40.52 −73.06 73 1.11 7 100% 0.19 7 98% 0.09 12 Los Canelos Los Lagos −41.48 −73.47 105 1.11 7 99% 0.03 7 100% −0.12 13 La Pampa Los Lagos −40.86 −73.16 96 1.11 7 97% 0.15 7 93% 0.05 14 Octay Los Lagos −40.96 −72.89 178 1.10 7 98% 0.06 5 100% −0.10 15 El Cardal Los Ríos −40.39 −72.92 80 1.09 6 100% 0.23 5 100% 0.14 16 Huyar Alto Los Lagos −42.40 −73.57 155 1.20 7 100% 0.01 7 100% −0.13 17 Butalcura Los Lagos −42.26 −73.65 148 1.20 7 100% 0.03 7 100% −0.07 18 Tara Los Lagos −42.70 −73.79 145 1.21 6 100% 0.00 6 91% −0.09 19 Polizones Los Lagos −41.12 −73.38 137 1.12 6 100% 0.15 5 100% 0.03 20 Colegual Los Lagos −41.22 −73.26 177 1.16 5 100% 0.10 5 100% −0.03 21 Las Lomas Los Ríos −39.70 −73.01 22 1.04 4 100% 0.36 3 100% 0.28 22 Santa Carla Los Ríos −39.68 −72.61 264 1.19 4 100% 0.18 3 100% 0.06 23 Palermo Los Ríos −40.26 −73.11 78 1.00 3 100% 0.29 3 100% 0.20 24 Est. Exp. Austral Los Ríos −39.79 −73.23 15 0.94 2 96% 0.29 1 100% 0.16 25 Desague Rupanco Los Lagos −40.75 −72.66 272 1.10 4 91% 0.10 3 100% −0.03 26 Ensenada Los Lagos −41.23 −72.52 76 1.05 4 91% 0.15 3 100% 0.01 27 Quilacahuin Los Lagos −40.35 −73.31 17 1.00 3 100% 0.36 2 100% 0.30 28 Sta Ines Araucanía −38.50 −72.34 263 0.99 2 100% 0.37 1 100% 0.28 29 Surco y Semilla Araucanía −38.03 −72.29 379 0.97 2 97% 0.52 1 100% 0.46 30 Las Palmas Araucanía −39.23 −72.27 388 1.05 2 99% 0.45 1 100% 0.41 31 San Fabian Araucanía −38.45 −72.85 197 0.99 2 100% 0.37 1 100% 0.23 32 Perales Araucanía −38.66 −72.81 55 0.93 2 100% 0.33 1 100% 0.20 33 Huiscapi Araucanía −39.26 −72.40 266 1.02 2 98% 0.33 1 100% 0.23 34 El Membrillo Araucanía −38.83 −71.68 527 0.96 2 96% 0.46 1 100% 0.40 35 Marimenuco Araucanía −38.73 −71.14 1084 1.44 2 99% 0.44 1 100% 0.29 36 Valdivia MMA Los Ríos −39.83 −73.23 8 1.01 4 89% 0.30 3 86% 0.15 37 Las Encias Temuco Araucanía −38.75 −72.62 106 0.83 4 82% 0.21 4 79% 0.06 MMA 38 Osorno MMA Los Lagos −40.58 −73.12 52 0.99 4 90% 0.24 5 89% 0.07 39 Pto. Montt MMA Los Lagos −41.48 −72.97 104 0.72 6 92% 0.16 3 75% −0.17 40 La Araucanía Araucanía −38.93 −72.65 96 0.98 2 100% 0.33 2 94% 0.12 41 Pichoy Los Ríos −39.65 −73.08 21 1.02 2 97% 0.35 2 90% 0.14 42 Lonquimay Araucanía −38.46 −71.36 912 1.35 3 63% 0.54 3 66% 0.31 43 Ancud Los Lagos −41.87 −73.82 31 0.96 2 98% 0.03 2 91% −0.15 44 Nueva Chaiten Los Lagos −42.79 −72.78 10 1.12 2 77% −0.05 2 78% −0.17

3. Results For the analysis of the thermal conditions in Spain and Chile climatological data of average maximum temperatures for summer period 3.1. Winter and summer climatic severity indexes and average minimum temperatures for winter period were used (AEmet, 2011; Castillo, 2001). The Fig. 1 shows that the amplitude of 3.1.1. Winter and summer climatic severity indexes per meteorological temperatures observed in La Araucanía, Los Ríos, and Los Lagos regions stations is included within the range of temperatures observed in Spain for The climatic severity index method was developed based on cli- winter period. In summer period 60% of the amplitude of climatological matic values of air temperature and solar radiation in 50 cities of Spain. values of maximum temperatures in Chile is included within the in- We analysed climatic values of solar radiation in 50 cities of Spain and terval of Spain. Therefore, we can conﬁdently use this method to cal- in 44 meteorological stations of the study area for summer and winter culate WCS index in study area. In the case of calculation SCS index, periods (ExSol, 2017; Sancho, Riesco, & Jiménez, 2012). The Fig. 1 errors can occur in the cold climates of study area. shows the results of this analysis where it can be seen the intervals of Data of the temperatures measurements and global solar radiation climatic values of solar radiation in Spain for which Eq. (3) was de- in each station to calculate WCS and SCS (Eq. (3)) were used; even veloped. Global solar radiation has latitudinal dependence, and also though the meteorological stations did not always have information depends on cloud cover, elevation above the sea level, and the com- about global radiation. For this reason, ﬁrstly the instrumental data of position of gases and aerosols in the atmosphere (IPCC, 2013). Three global radiation measurements on a horizontal surface were replaced regions of Chile are located between 37°35′ S and 44°04′ S, and main- with data from the atmospheric radiation model (Solar Energy Ex- land Spain is located between 36°01′ N and 43°48′ N. As a result, we plorer) (ExSol, 2017). The calculation of WCS and SCS was made for all have almost the same climatic values of solar radiation in two parts of periods that present parallel measurements of temperature and global the world. radiation. In addition, WCS and SCS indexes were calculated in relation

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Fig. 4. Map of meteorological stations in the south of Chile. The serial number of each station corresponds to the “Number of station” in Table 4. to temperature measurements and modelled global radiation. The measurements and capacity data of measurements in percentages for graph of Fig. 2 illustrates the dependence between WCS and SCS cal- WCS between June and August, and for SCS between December and culated from measurements and modelling of global radiation in 44 March. Eq. (3) (correlation between WCS and SCS indexes and me- meteorological stations. Nearly all stations had WCS indexes calculated teorological parameters) was determined based on the simulation of the by two types of solar radiation data with less than 10% of errors (blue energy demand for heating and cooling in 50 cities of Spain. This cor- lines). In the case of the SCS index, there were augmentation errors relation was obtained for an interval of the WCS index [0.2;1.75] and together with decreased values of this index. In general terms, it is for an interval of the SCS index [0.05;1.70] (de la Flor et al., 2006). In possible to aﬃrm that the use of modelled global radiation was ap- our study, for meteorological stations, the values of the WCS and SCS propriate for our situation. The scheme of calculation WCS and SCS indexes were recalculated for the intervals [0.72;1.44] and indexes is shown in Fig. 3. [−0.05;0.54], respectively (Table 4). Based on the similarity of climatic Table 4 presents the information of meteorological stations and the conditions in the study area and in Spain, is possible to conﬁrm the results obtained for WCS and SCS, with information from years of adequacy of the use of the CTE method for the calculation of WCS and

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Fig. 5. Dependence between SCS and WCS in the meteorological stations. The serial number of each station corresponds to the “Number of station” in Table 4.

Fig. 6. Maps of spatial distribution of WCS and SCS.

SCS indexes. because Lonquimay (WCS = 1.35; SCS = 0.54) and Marimenuco In addition, this table presents values of the SCS index calculated (WCS = 1.44; SCS = 0.44) stations are located far away from the ocean using Eq. (4). It can be observed that, to our study area, SCS from two and have maximum WCS and SCS values for study area. Therefore, equations only determined one type of climate, i.e., colder climate these places had colder winters and hotter summers. On the other hand, number 1 for summer. The map of Fig. 4 illustrates the meteorological Quiripo (WCS = 0.94 ± 0.06; SCS = 0.10 ± 0.01), Tranapuente stations indicated in Table 4 to demonstrate the spatial coverage of (WCS = 0.86 ± 0.10; SCS = 0.06 ± 0.01) and Domínguez meteorological observations. (WCS = 0.87 ± 0.10; SCS = 0.04 ± 0.007) stations are located near The graphs of Fig. 5 illustrate the dependence between SCS and the coast of the Paciﬁc Ocean and, therefore, have warmer climatic WCS in meteorological stations of La Araucanía, Los Ríos, and Los conditions in the winter and cooler in the summer in La Araucanía. Lagos. In La Araucanía was observed more continental type of climate, La Providencia (WCS = 0.97 ± 0.11), Sta. Adela

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Table 5 Comparison of HDD values from measurements and data of the OGUC relating to diﬀerent cities of Chile.

City Data from measurements OGUC

Period % of data Value of annual HDD (base 15 °C) Standard deviation Thermal zone Value of annual HDD (base 15 °C)

Iquique 2011–2015 99.5% 21 20 1 ≤500 Calama 2011–2015 96.0% 1242 83 2 500–750 Antofagasta 2011–2015 99.7% 162 71 1 ≤500 La Serena 2011–2015 99.5% 697 103 1 ≤500 Pudahuel 2011–2015 99.6% 1019 102 3 750–1000 Concepción 2011–2015 99.6% 1069 87 4 1000–1250 Puerto Montt 2011–2015 99.6% 1851 93 6 1500–2000 Balmaceda 2011–2015 98.0% 2946 84 7 > 2000 Punta Arenas 2011–2015 99.6% 3145 86 7 > 2000

Table 6 interval of WCS, greater than that of SCS for annual averages obtained Results of calculation of heating degree-days values in 35 meteorological sta- with more than 5-years of measurements). Narrow confidence intervals tions and comparison with values from the OGUC. of SCS are linked to not very high absolute values of SCS and the sen- Number of Name of station HDD (base 15 °C) sitivity of Eq. (3) from the input parameters. station Finally, WCS and SCS were calculated for all meteorological sta- OGUC Measurements data tions, but for create maps of spatial distribution of these two indexes, approximation and interpolation methods will be use (Carpio et al., average minimum maximum 2015). 1 Carillanca 1250–1500 1365 1165 1489 2 Tranapuente 1250–1500 1369 1129 1568 3.1.2. Reconstruction of winter and summer climatic severity indexes – 3 Quiripio 1250 1500 1507 1324 1795 The analysis of the results for WCS in the meteorological stations 4 La Providencia 1250–1500 1270 1184 1421 5 San Luis 1250–1500 1773 1615 2074 indicated that this index was a function that depended on latitude and 6 Dominguez 1250–1500 1299 1141 1452 elevation above sea level. In addition, it was found that SCS was a factor 7 C.Llollinco 1250–1500 1396 1274 1541 that depended on latitude, altitude, and distance between the meteor- – 8 Cuarta Faja 1250 1500 1225 1096 1530 ological stations and the ocean. 9 Sta. Adela 1250–1500 1167 1073 1221 In these regions, the most important climatic factor of the summer 10 Lago Verde 1250–1500 1525 1401 1630 11 Remehue 1250–1500 1501 1391 1663 was the distance to the ocean. This distance defined the continentality 12 Los Canelos 1500–2000 1665 1504 1783 of the climate at each location. Obviously, greater distances defined 13 La Pampa 1500–2000 1564 1314 1723 warmer places with higher SCS values. However, this spatial depen- – 14 Octay 1500 2000 1496 1357 1587 dence only occurred up to some altitudes. In our situation, we could 15 El Cardal 1250–1500 1325 1221 1394 16 Huyar Alto 1500–2000 1904 1634 2336 calculate SCS in places that were located up to 1000 meters above sea 17 Butalcura 1500–2000 1897 1750 2134 level. 18 Tara 1500–2000 1814 1697 1896 The dependence of WCS and SCS values on geographical parameters 19 Polizones 1500–2000 1579 1544 1622 was obtained and a geographical relief model of 305 sites for the three 20 Colegual 1500–2000 1746 1687 1809 regions using geographical coordinates, altitude of the sites, and the 21 Las Lomas 1250–1500 1260 1179 1308 22 Santa Carla 1250–1500 1622 1547 1725 shortest distance to the ocean was built. 23 Palermo 1250–1500 1206 1174 1238 Subsequently, the approximation equations used to calculate WCS 24 Est. Exp. Austral 1250–1500 1123 1123 1123 and SCS values in 305 sites of the relief model. Finally, through the use – 25 Desague 1500 2000 1636 1514 1783 of ArcGIS (ArcGIS, 2017) and the Kriging method (Oliver & Webster, Rupanco 26 Ensenada 1500–2000 1556 1479 1691 1990), maps with the spatial distribution of WCS and SCS in the study 27 Quilacahuin 1250–1500 1107 1040 1173 area were created. 28 Sta Ines 1250–1500 1384 1384 1384 – 29 Surco y Semilla 1250 1500 1217 1217 1217 3.1.3. Final results of winter and summer climatic severity indexes 30 Las Palmas 1250–1500 1400 1400 1400 31 San Fabian 1250–1500 1251 1251 1251 Maps with the spatial distribution of WCS and SCS in the three as- 32 Perales 1250 –1500 1181 1181 1181 sessed regions are presented in Fig. 6. The minimum WCS values are 33 Huiscapi 1250–1500 1317 1317 1317 observed in the northwest part of La Araucanía close to the Pacific coast 34 El Membrillo 1500–2000 1254 1254 1254 (WCS = 0.85–0.95) and in the city of Puerto Montt (WCS < 0.75). The 35 Marimenuco 1500–2000 2315 2315 2315 minimum value of this index characterised milder climatic conditions for winter in the three regions. The change in axis of the index WCS (WCS = 0.95 ± 0.06), and Quiripo (WCS = 0.94 ± 0.06) stations are went from the northwest to the southeast of the study area. The max- located in La Araucanía. According to Table 2, there may be a problem imum value of this index is observed in the southeast of Los Lagos, of correct identification of the climatic zone, because the values of which is characterised by colder and more extreme climatic conditions index WCS of these stations were located on the border between climate of the three regions (WCS > 1.60). types C and D. In the case of the spatial distribution of SCS, it was observed the In Los Lagos, the stations are located in the south of the region, i.e., opposite situation. The maximum values were observed in the northeast Butalcura (WCS = 1.20 ± 0.04; SCS = 0.04 ± 0.03) and Huyar Alto part of La Araucanía (SCS > 0.50), and the minimum values in the (WCS = 1.20 ± 0.10; SCS = 0.005 ± 0.017) observe colder climates southwest part of Los Lagos. Maximum values of SCS determined cli- in the whole region, which is reflected in the extreme values of WCS mate with the warmest summers in the three regions and maximum of and SCS. It is possible to observe that the change in amplitude of WCS dwelling energy consumption for cooling. fi was greater than the change in amplitude of SCS (95% confidence This spatial distribution of the indexes was de ned in winter due to the climatic effect of ocean warming, and in summer due to the climatic

359 K. Verichev, M. Carpio Sustainable Cities and Society 40 (2018) 352–364

Fig. 7. Map of thermal zones according to the OGUC and updated composite map of thermal zones (right) (Determination of zones according to Table 3). effect of the underlying surface heating. In general terms, the dis- Webster, 1990). tribution of the indexes did not challenge the climatic logic of this region. In the first stage, the HDD values were calculated with data of the National Agroclimatic Network stations using Eq. (1). Table 6 shows the 3.2. Updated map of the general ordinance of urban planning and results of the calculation including the 35 stations of which 27 has more construction of Chile than two years of temperature measurements, while 7 stations has HDD values which not correspond to thermal zones of the OGUC. For ex- Firstly, the differences between HDD calculations for 2011–2015 ample, the Santa Carla station has a calculated value of 1622 HDD; with data from meteorological stations (DMC, 2017) and HDD calcu- however, according to OGUC zoning, this station was located in the lated by OGUC in 1999 for different cities of Chile (Table 5) were area with HDD between 1250 and 1500. showed. It can be observed that data from the period 2011–2015 In the second stage, the spatial distribution of HDD was calculated, showed that Calama had a range of 1242 HDD, which corresponds to after bioclimatic zoning as additional information to obtain updated the thermal zone 4; however, OGUC determined that this city belonged limits of thermal zones was used. As a result, we obtained a new to zone 2. This discrepancy of thermal zones in the Calama city, was composite map of thermal zones for the three regions (Fig. 7 right). also reflected in the study of Bustamante (Bustamante et al., 2009). The comparison between maps of the OGUC and new composite Another significant discrepancy is that La Serena had 697 HDD, and maps (Fig. 7) indicated that the climatic zone 4 moved to the south in OGUC considered this city as belonging to zone 1, with annual HDD the central part of La Araucanía, and there was insulation near Valdivia below 500. This mismatch of data indicates the need of continual up- in Los Ríos. This fact changed zone 5 to zone 4 in 11 cities of these two dating of thermal zoning and the use of data collected over long periods regions. In this area, there were also changes of bioclimatic zones, i.e., of time. the Mediterranean climate moved to the south, approximately to San Therefore, a recalculation for HDD for La Araucanía, Los Ríos, and José de la Mariquina in the northern area of Los Ríos (Sarricolea et al., Los Lagos was done, because the total energy consumption in the 2016). In older climatic publications, this region was characterised by southern regions of Chile is more dependent on the energy demands of another type of climate – temperate marine (Fuenzalida-Ponce, 1971). buildings for heating in winter period. In order to update the limits of In the northeast of La Araucanía, the climatic zone 6 moved to the thermal zones were used: west, and in Curacautín was observed the change from zone 5 to zone 6, which was in line with data from measurements collected at the San 1. Maps of thermal zones of OGUC (1999 year of data) (Chile, 2009) Luis station, where there were 1773 annual HDD (minimum of 1615 2. Bioclimatic zoning map of Chile (Sarricolea et al., 2016) and maximum of 2074) from 2009 to 2016. In Los Lagos, was observed 3. Interpolation of data from the National Agroclimatic Network using that zone 6 changed to zone 5 in Puerto Octay city. the Kriging method (Kumar, Maroju, & Bhat, 2007; Oliver & For this reason, the updating of degree-days data indicated a large

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Table 7 Table 7 (continued) Recalculated thermals zones according to the OGUC and recovered values of WSC and SCS for capital cities of the municipalities. Capital city of Thermal zone CTE municipality (OGUC) Capital city of Thermal zone CTE WCS SCS Climate zone municipality (OGUC) WCS SCS Climate zone Quellén 6 1.22 −0.06 D1 Quellón 6 1.23 −0.07 D1 La Araucanía Quemchi 6 1.14 0.02 D1 Angol 4 0.92 0.40 C1 Quínchao 6 1.20 0.005 D1 Carahue 5 0.94 0.09 C1 Rio Negro 6 1.11 0.15 D1 Cholchol 4 0.95 0.35 C1 San Juan de la Costa 6 1.07 0.21 D1 Collipulli 4 0.94 0.47 C1 San Pablo 5 1.09 0.23 D1 Cunco 5 1.04 0.35 D1 Curacautín 6 1.12 0.35 D1 Curarrehue 6 1.05 0.33 D1 number of inconsistencies in La Araucanía, which can be linked to Ercilla 4 0.97 0.52 D1 ff Freire 4 0.95 0.34 C1 global climate change and e ect of urban heat islands. This result is Galvarino 5 0.99 0.37 D1 explained by the fact that some stations were located in urban areas. Gorbea 4 1.00 0.33 D1 Lautaro 5 0.99 0.58 D1 Loncoche 5 1.09 0.28 D1 3.3. Complex results of municipalities Lonquimay 6 1.35 0.54 E1 Los Sauces 4 1.12 0.28 D1 By the end of the study, three climatic zones with climate types C1, Lumaco 5 1.02 0.27 D1 Melipeuco 5 0.96 0.46 D1 D1, and E1 were obtained (Table 7, Fig. 8). Climatic zones for 74 Nueva Imperial 5 0.94 0.47 C1 municipalities of the three regions were calculate and, finally, it was Padre Las Casas 4 0.86 0.27 C1 observing that the climatic zone C1 occurred in 19% of the munici- Perquenco 5 1.05 0.38 D1 palities, climatic zone D1 in 74%, and E1 in 7% of them. On the other Petrufquén 4 0.92 0.29 C1 hand, with the calculation of the amount of population in these three Pucón 5 0.97 0.29 D1 Purén 4 1.03 0.25 D1 regions, it was found that 47% of the population lived in zone C1, 50% Renaico 4 0.87 0.49 C1 in D1, and 3% in E1. That difference occurred because all large cities Saavedra 5 0.86 0.11 C1 (Valdivia, Temuco, and Puerto Montt) with urban heat island effects Temuco 4 0.83 0.21 C1 belonged to the climatic zone C1. Fig. 8 shows a map of climatic zones Teodoro Schmidt 5 0.99 0.18 D1 Toltén 5 1.03 0.17 D1 of the CTE for study area. Climatic zone E1 also covers mountainous Traiguén 5 0.97 0.38 D1 areas where there is no data on the SCS index (Fig. 6 right), because the Victoria 4 0.99 0.41 D1 mountainous areas are not characterised by the energy consumption of Vilcún 5 1.05 0.40 D1 buildings for cooling in the summer period. Villarrica 5 1.05 0.39 D1 According to the CTE (Spain, 2006), in Spain, climate type C1 are Los Ríos observed in the north and northwest part of the country, and this type Corral 5 1.02 0.19 D1 of climate is typical for the following cities: Pontevedra in the Auton- Futrono 6 1.04 0.23 D1 La Unión 4 0.99 0.29 D1 omous Community of Galicia; Oviedo in the Autonomous Community of Lago Ranco 6 1.05 0.20 D1 Asturias; and Bilbao and San Sebastian in the Autonomous Community Lanco 5 1.05 0.28 D1 of the Basque Country. Los Lagos 5 1.08 0.30 D1 Climate type D1 is typical for the following cities: Lugo (Galicia); Máfil 5 1.04 0.36 D1 Palencia (Castilla and León); and Pamplona (Navarra). On the other S.J. de la Mariquina 5 1.03 0.29 D1 Paillaco 5 1.04 0.25 D1 hand, climate type E1 is typical for the following cities: León (Castile- Panguipulli 5 1.05 0.32 D1 León); Burgos (Castile-Leon); and Soria (Castile-León). In the north and Rio Bueno 5 1.09 0.23 D1 northwest regions of the country there is a clear dependence, given for Valdivia 4 0.95 0.29 C1 coastal cities with climate C1, as distant cities from the sea with climate Los Lagos D1, and those far from the sea and above sea level has climate E1, such Ancud 6 0.96 0.04 D1 as Burgos (861 m above sea level) and Soria (984 m above sea level). Calbuco 6 1.02 0.05 D1 Important factors for determining the climate in the north and Castro 6 1.35 −0.05 E1 Chaitén 6 1.12 −0.05 D1 northwest of Spain are: the relative position of the ocean and the coast; Chonchi 6 1.29 −0.06 D1 effect of the Gulf Stream; terrain; and continentality. For this reason, Cocharnó 6 1.27 0.01 D1 the cities located near the coast have milder winters (climate type C1) − Curaco de Vélez 6 1.22 0.05 D1 In Spain, due to the heating effect of the Gulf Stream, there is cli- Dalcahue 6 1.20 0.005 D1 Fresia 6 1.15 0.12 D1 mate type C1 on the coast of the ocean (43°N). However, in Chile, there Frutillar 6 1.11 0.14 D1 was cooling effect caused by the Humboldt ocean current and, there- Futaleufú 7 1.75 – E1 fore, in the same longitude in Chile (between 42°S and 44°S) there was Hualaihué 6 1.5 −0.08 E1 climatic zone E1 on the ocean coast of Los Lagos region, which changed Llanquihue 6 1.02 0.14 D1 to D1 and then to C1 in the northern part of La Araucanía. The changes Los Muermos 6 1.11 0.03 D1 Maullín 6 0.99 0.04 D1 of climatic zones in the regions of Chile were linked to the latitudinal Osorno 5 0.99 0.24 D1 location of these regions (change of global solar radiation). On the other Palena 7 1.45 – E1 hand, in Spain, the regions with C1, D1, and E1 climate types have Puerto Montt 6 0.72 0.16 C1 longitudinal location and the change of climatic zones was linked to the Puerto Octay 5 1.10 0.07 D1 Puerto Varas 6 0.95 0.14 C1 altitude changes. Puqueldón 6 1.22 −0.06 D1 Table 7 shows that climatic zone C1 corresponded to thermal zone 4 Purranque 6 1.11 0.15 D1 in 64% of the municipalities, and climatic zone C1 corresponded to Puyehue 6 1.07 0.19 D1 thermal zones 5 and 6 in 44% and 45% of the municipalities, respectively. Table 8 presents the recommendations of thermal transmittance

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Fig. 8. Map of climatic zones according to the CTE. for roofs, walls, and floors for four thermal zones of the OGUC and three such as zone D1, with a thermal transmittance of 0.66 W/m2K for walls climatic zones of the CTE. It is possible to observe that the thermal which corresponds to thermal zones 5 and 6, with thermal transmit- transmittance interval for floors in the CTE [0.48–0.50 W/m2K] was tance of 1.60 and 1.10 W/m2K for walls, respectively. Thermal trans- within the interval of the MINVU [0.32–0.60 W/m2K]. For roofs, the mittance for windows and doors was nearly the same in the two CTE determines thermal transmittance for three climatic zones in the countries. Therefore, rules for construction of walls in Spain were ap- interval [0.35–0.41 W/m2K] and the OGUC for four thermal zones in proximately two times stricter than in Chile for climatic zones C1 and the interval [0.25–0.38 W/m2K]. However, the maximum difference D1 (corresponding in Chile to the thermal zones 4, 5, and 6). These was observed in the recommendations of thermal transmittance for differences in the recommendations for the thermal transmission of walls. building structural elements can be associated with different base In Spain, the CTE is defined within the interval [0.57–0.73 W/m2K], temperatures that determine indoor comfort in these two countries. which is in line with MINVU recommendations for the thermal zone 7 However, three regions in Chile are consider the leaders in the use [0.60 W/m2K]. There were great differences in other thermal zones, of wood for heating of buildings, which, in turn, generates high

362 K. Verichev, M. Carpio Sustainable Cities and Society 40 (2018) 352–364

Table 8 take into account the microclimatic eﬀects of urban heat islands. In Maximum thermal transmittance thresholds for building elements. addition, it is also necessary to upgrade the climatological data fre-

Thermal transmittance U[W/m2K] quently.

CTE Acknowledgment Rooﬁng Walls Floors Climate zone C1 0.41 0.73 0.50 This work was funded by the following research project: CONICYT Climate zone D1 0.38 0.66 0.49 Climate zone E1 0.35 0.57 0.48 FONDECYT11160524.

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