The impact of building orientation and discount rates on a Portuguese reference building refurbishment decision

Energy Policy 91 (2016) 329–340

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Energy Policy journal homepage: www.elsevier.com/locate/enpol

The impact of building orientation and discount rates on a Portuguese reference building refurbishment decision Ana Brandão de Vasconcelos a, António Cabaço a, Manuel Duarte Pinheiro b,n, Armando Manso a a

Buildings Department, National Laboratory for Civil Engineering (LNEC), Av. do Brasil 101, 1700-066 Lisbon, Portugal Department of Civil Engineering, Architecture and Georesources, Instituto Superior Técnico – Universidade de Lisboa, Av. Rovisco Pais 1, 1049-001 Lisbon, Portugal

b

H I G H L I G H T S







Building refurbishment decision based on technical and economic points of view. 35.000 Packages of thermal rehabilitation solutions considered. Building orientation and discount rate impact on the cost-optimal package of solutions. Portuguese reference building case base.

art ic l e i nf o

a b s t r a c t

Article history: Received 28 July 2015 Received in revised form 14 January 2016 Accepted 18 January 2016 Available online 25 January 2016

Refurbishment, as part of the construction industry, has a strong global impact, not only from the viewpoint of economies but also from social and energy-efficiency perspectives. A thermal refurbishment process, in particular, involves numerous decisions and choices; the decision-makers being ultimately confronted with two major questions: which criterion should be adopted in the choice of the refurbishment construction solutions and which refurbishment construction solutions should be chosen? In this paper, a criterion based on technical and economic points of view is proposed, aiming to identify the cost-optimal package of energy efficient solutions from among a set of possible refurbishment measures, within the life cycle of buildings. Sensitivity analyses are also performed so that the results may help the decision-maker choose the appropriate refurbishment solutions to be adopted when different discount rates and building orientations are taken into consideration. A total of seven scenarios, for a macroeconomic perspective, and nine, for a financial perspective, are performed. The costoptimal methodology adopted, following the Directive 2010/31/EU (2010) recommendations, is applied to a Portuguese reference building. The analysis carried out allows obtaining low global life cycle costs solutions and points towards nearly Zero Energy Building (nZEB) concept. The results are important for drawing national political instruments on buildings energy efficiency. & 2016 Elsevier Ltd. All rights reserved.

Keywords: Refurbishment Cost-optimal methodology Decision-making Discount rate Building orientation

1. Introduction In 2014, refurbishment was the prevailing segment within EU's housing construction market, accounting for 61.2% of the total, with the balance being represented by new housing construction. These proportions are in contrast with the situation that prevailed during the peak period (2007) when new constructions Abbreviations: COP, Coefficient of Performance; EER, Energy Efficiency Rate; EPBD, Energy Performance of Buildings Directive; GHG, Global Greenhouse Gas; RB, Reference Building; SA, Sensitivity Analysis; nZEB, nearly Zero Energy Buildings n Corresponding author. E-mail address: [email protected] (M.D. Pinheiro). http://dx.doi.org/10.1016/j.enpol.2016.01.021 0301-4215/& 2016 Elsevier Ltd. All rights reserved.

represented over half (51.2%) of the total housing construction output when compared with refurbishment, which accounted for 48.8% (Euroconstruct, 2014). Refurbishment relies on the making of numerous decisions and choices. Therefore, life-cycle perspectives are being increasingly considered in the decision-making process and involving participants with different interests (Hernandez and Kenny, 2011; Sartori and Hestnes, 2007). Indeed, on the one hand, owners want to minimise the likely costs of the project, but they also want to achieve the highest acceptable quality standards and satisfy the technological, architectural and comfort requirements. On the other hand, designers and contractors are interested in maximising profits, being also concerned with other aspects such as

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company growth, market share, and the state institutions' interests (Banaitiene et al., 2008). As part of the construction industry, refurbishment has a strong global impact, not only from the viewpoint of economies, but also from social and energy-efficiency perspectives (Comstock et al., 2012; Ferreira et al., 2013; Keivani et al., 2010). Globally, buildings represent 40% of the world's energy consumption and one third of the global greenhouse gas (GHG) emissions (Graham, 2010). As urbanisation increases in the world's most populated countries, building sustainability is more and more seen as a key factor in achieving sustainable development. As a result of these energy efficiency challenges, the European Energy Performance of Building Directive (EPBD) (Directive 2010/ 31/EU, 2010) recast, which aims to ensure energy savings and CO2 emission reduction, required the Member States to establish a comparative methodology framework for calculating cost-optimal levels of minimum energy performance requirements for buildings and building elements. Higher energy performance buildings (Hernandez and Kenny, 2010; Marszal et al., 2011), like nearly Zero Energy Buildings (nZEB), should also be economically feasible. Thus, within a building refurbishment process, and taking into account those requirements, decision-makers are ultimately confronted with these two questions: 1) Which criterion should be adopted in the choice of the refurbishment construction solutions? 2) Which refurbishment construction solutions should be chosen? Following these EU Directives' recommendations, the authors propose a criterion based on technical and economic points of view, with a view to identify the cost-optimal package of energy efficient solutions from among a set of possible refurbishment construction solutions (Brandão de Vasconcelos et al., 2015a, 2015b, 2015c, 2014), within the life cycle of buildings. Other recent studies have also used the cost-optimal energy performance of buildings methodology, in line with the EPBD recast, to identify the cost-efficient set of solutions (Corrado et al., 2014; Ferrara et al., 2014; Ganiç and Yılmaz, 2014; Hamdy et al., 2013; Kurnitski et al., 2011; Pikas et al., 2014). Different authors have assessed the influence of base parameters on the calculation of the cost-optimal package of solutions, by performing Sensitivity Analysis (SA) on the results (Baglivo et al., 2015; Ferrara et al., 2014; Ferreira et al., 2014; Ganiç and Yılmaz, 2014; Hamdy et al., 2013; Morrissey et al., 2013; Stojiljković et al., 2015; Tol, 2012). All these studies provided approaches to the calculation framework at national levels. For the Portuguese context, an adaptation is required in order to consider specific national factors. This paper aims to describe in detail the cost-optimal methodology applied to the Portuguese context and to evaluate how different circumstances, based on different discount rates and building orientation, may affect the decision on which the refurbishment construction solutions to be chosen should be based. This evaluation is made through SA in order to assess the impact on the cost-optimal results of the parameters chosen for the model as input data. The methodology established considers both financial and macroeconomic perspectives applicable to the whole life cycle of buildings and takes into account the national reference standards. In the introduction (Section 1), this paper sets out the main objectives of the research work. Section 2 proceeds with the application of the cost-optimal methodology to a Reference Building (RB) representative of the Portuguese residential building stock. In Section 3, SA is carried out for the discount rate and building orientation parameters from macroeconomic and financial calculation perspectives. In Section 4 the influence of those parameters on the choice of the cost-optimal package of solutions for the RB

studied is discussed and, finally, in Section 5, the main conclusions are presented.

2. Cost-optimal decision-making methodology A cost-optimal methodology is proposed in this paper as a basis for a decision-making criterion as regards the choice of refurbishment construction solutions. This methodology phasing is fully described in Brandão de Vasconcelos et al. (2015a, 2014) and allows establishing a relationship between the performance and the correspondent costs of energy refurbishment solutions, thus enabling to determine the most cost-efficient package of solutions throughout the life cycle, which is called the cost-optimal level. In the following paragraphs, the application of the proposed methodology to the RB considered is described in detail. 2.1. Phase 1 – definition of a Portuguese residential reference building The first phase of the methodology involves the definition of a RB. The option to chose a RB representative of the Portuguese building stock rather than considering different RBs is based on the objective set for this paper to present in detail all research issues that are likely to be useful at national or international level for cost-optimal methodologies and for the decision on refurbishment construction solutions considering different circumstances. Therefore, the RB selected is representative of the Portuguese residential building stock in terms of construction solutions and its configuration is representative of Lisbon's building typologies in the 1960–1990 construction period. The RB characterisation took into consideration, among other aspects, the fact that 50% of the total housing stock in Portugal was built between 1960 and 1990 (INE [Statistics Portugal], 2012) and more than 85% of the buildings constructed before 1990 have been marked as C or less energy classification (ADENE, 2011). By combining these and other aspects, the RB adopted is mainly characterized as shown in Table 1. These characteristics make it nationally representative in terms of construction solutions and its configuration makes it representative of Lisbon's building typologies, in the 1960–1990 construction period. This RB is fully characterised in Brandão de Vasconcelos et al., (2015a). 2.2. Phase 2 – identification of the energy efficiency measures for the RB The building envelope has been reported by several authors (Florides et al., 2002; IEA, 2013; Ramesh et al., 2010; Sadineni et al., 2011) as playing a key role in determining levels of comfort, natural lighting and ventilation; its energy performance (including external walls, floors, roofs, ceilings, windows and doors) being critical in determining how much energy is required for heating and cooling. Therefore, the energy efficiency measures selected to be applied to the RB are within the group of thermal refurbishment solutions of the building envelope (Brandão de Vasconcelos et al., 2015b), which is focused on the reduction of the building's energy consumption through the reinforcement of the protection of opaque elements (external walls, roofs and floors) and windows. Table 2 lists the thermal refurbishment measures chosen to be applied to the RB envelope. For the determination of the costoptimal level, the measures listed were combined so as to create 35.000 packages of solutions. 2.3. Phase 3 – calculating the primary energy consumption for each

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Table 1 Main characteristics of the RB. Main characteristics

Unit RB solution

Net internal floor area Clear height Type of structure Location Orientation Building configuration Number of rooms Number of floors Number of floors of the dwelling Number of dwellings/floor Number of façades Roof Total gross area Vertical envelop Façade width Façade total area Area of the opaque exterior envelop Share of window area of total building envelope External walls Construction solution

m2 m – – – – – – – m2 m m2 m2 % –

Roof

Construction solution

–

Ground floor

Construction solution

–

External windows

Construction solution Solar shading Internal walls for room separation

– – –

Internal walls

Internal walls for dwelling separation – –

Internal floors

Internal walls for circulation area separation Construction solution

Ventilation

Natural/Mechanical

–

Solar thermal collectors Heating system Cooling system Heating energy source Cooling energy source

–

– – – – –

78 2.7 Reinforced concrete Latitude: 38.73°; Longitude:  9.15°; Elevation: 71 m N–S 2 7 1 2 2 215.3 16.3 684.6 458.56 15% Single walls of hollow ceramic brick of 30  20  22 mm without thermal insulation, plastered and painted Sloped roof without thermal insulation with a horizontal solid reinforced concrete slab, 0.23 m thick, with ceramic roof tiles Ground floor without thermal insulation with a solid reinforced structure slab, 0.23 thick, and application of wooden blocks coating directly on the screed Aluminium window frames (no thermal break) with single clear glass 6 mm thick Outdoor clear plastic blinds Single walls of hollow ceramic brick of 30  20  11 mm without thermal insulation, plastered and painted Single walls of hollow ceramic brick of 30  20  15 mm without thermal insulation, plastered and painted Reinforced concrete wall, 0.30 thick Internal floor without thermal insulation with a solid reinforced structure slab, 0.23 m thick, and application of wooden blocks coating directly on the screed Natural Air change rates: 0.6/h for dwellings; 2/h for the ventilated roof; 1.65/h for the staircase Not installed Split (COP: 3..4) Split (EER: 3.0) Electricity Electricity

package of measures

financial perspective is therefore calculated using formula (1):

The energy needs for heating and cooling, associated to the 35.000 packages of measures mentioned in Section 3.2, were calculated (Coelho et al., 2015) following the EPBD procedure and using the EnergyPlus software. The parameters considered in the calculation were based on the Portuguese EPBD thermal regulations for Residential Buildings – REH, 2013 (Decreto-Lei No. 118/ 2013, 2013).

cg (τ ) = ct +

2.4. Phase 4 – calculating the global costs of each package of measures The cost classification considered for calculating the cost-optimal levels takes into consideration the Guidelines accompanying the Commission Delegated Regulation (EU) No. 244/2012, which are based on standard EN 15459 (2007). Two perspectives, regarding the type of individual viewpoint and expectations concerning the investment to be made, are adopted for the calculation: the macroeconomic perspective or the financial one (Aggerholm et al., 2011; Guidelines Regulation No. 244, 2012). 2.4.1. Financial perspective In the financial perspective, only the immediate costs and benefits from the investment decision are taken into account. Thus, the global cost of each package of solutions corresponds to the price paid by the end consumer, including taxes, such as VAT, and all applicable subsidies and incentives. The global cost for the

⎡

τ

⎤

∑ ⎢ ∑ (C m, i(j) × Rd(i) + Cs, i(j) × Rd(i) + Ce, i(j) × Rd(i)) − vf , τ(j)⎥ j

⎢⎣ i = 1

⎥⎦

(1)

where τ is the calculation period, Cg (τ ) the global cost referring to the starting year ( τ0 ) over the calculation period, Ct the initial investment costs per measure or set of measures j, Cm,i(j ), Cs,i(j ) and Ce,i(j ) maintenance, replacement and energy costs, respectively, during year i per measure or set of measures j, Vf, τ(j ) the residual value per measure or set of measures j at the end of the calculation period (discounting the starting year) and R d(i ) the discount factor for year i. The discount factor is calculated using formula (2), where p means the number of years since the starting period and r means the real discount rate:

⎛ ⎞p 1 Rd(p) = ⎜ ⎟ ⎝ 1 + r /100 ⎠

(2)

The discount rate adopted in this perspective is 6%. This value was established in accordance with the discount rates considered in the Portuguese energy private investment studies (Ferreira et al., 2014) and in other cost-optimal reports published by EU countries (Department for Communities and Local Government, 2013; European Commission, 2015). 2.4.2. Macroeconomic perspective The macroeconomic perspective is used when the justification for introducing energy performance regulations is to make

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Table 2 Thermal refurbishment measures applied to the RB. Measure ID

Measure location Solution

Existing solution Wind 00 Roof 00 Floor 00

Window Roof Ground floor

Wall 00 External wall Proposed measures Wind 01 – Wind 03 Window

Wind 04 – Wind 06 Window

Wind 07 – Wind 09 Window

Roof 01 – Roof 06

Roof

Floor 01 – Floor 07

Ground floor

Floor 08 – Floor 13

Ground floor

Floor 14 – Floor 19

Ground floor

Wall 01 – Wall 06

External wall

Wall 07 – Wall 12

External wall

Wall 13 – Wall 18

External wall

Wall 19 – Wall 24

Exterior wall

Aluminium window frames (no thermal break) with single clear glass, 6 mm thick Sloped roof without thermal insulation, with a horizontal solid reinforced concrete slab, 0.23 m thick, with ceramic roof tiles Ground floor without thermal insulation with a solid reinforced structure slab, 0.23 thick, and application of wooden blocks coating directly on the screed Single walls of hollow ceramic brick of 30  20  22 mm without thermal insulation, plastered and painted Replacement of the existing window by an aluminium window frame (no thermal break): with double clear glass (4 mmþ 6 mm thick) and 6 mm air space (Wind 01), with double clear glass (4 mmþ 6 mm thick) and 16 mm air space (Wind 02) and with double low emissivity clear glass (4 mmþ 6 mm low-e thick) and 16 mm air space (Wind 03) Replacement of the existing window by a PVC window frame: with double clear glass (4 mm þ6 mm thick) and 6 mm air space (Wind 04), with double clear glass (4 mm þ 6 mm thick) and 16 mm air space (Wind 05) and with double low emissivity clear glass (4 mm þ6 mm low-e thick) and 16 mm air space (Wind 06) Replacement of the existing window by an aluminium window frame (thermal break): with double clear glass (4 mm þ 6 mm thick) and 6 mm air space (Wind 07), with double clear glass (4 mmþ 6 mm thick) and 16 mm air space (Wind 08) and with double low emissivity clear glass (4 mmþ 6 mm low-e thick) and 16 mm air space (Wind 09) Application of EPS, with the thicknesses as follows: 20 mm (Roof 01), 30 mm (Roof 02), 40 mm (Roof 03), 60 mm (Roof 04), 80 mm (Roof 05), 100 mm (Roof 06), over the concrete slab Application of vinyl floor coating without thermal insulation (Floor 01), over EPS with the thicknesses as follows: 20 mm (Floor 02), 30 mm (Floor 03), 40 mm (Floor 04), 60 mm (Floor 05), 80 mm (Floor 06), and 100 mm (Floor 07) Application of marble natural stone over EPS with the thicknesses as follows: 20 mm (Floor 08), 30 mm (Floor 09), 40 mm (Floor 10), 60 mm (Floor 11), 80 mm (Floor 12), and 100 mm (Floor 13) Application of pine wood parquet (on wooden intermediate support structure) over EPS with the thickness as follows: 20 mm (Floor 14), 30 mm (Floor 15), 40 mm (Floor 16), 60 mm (Floor 17), 80 mm (Floor 18), and 100 mm (Floor 19) Application of ETICS with 20 mm of EPS (Wall 01), 30 mm of EPS (Wall 02), 40 mm of EPS (Wall 03), 60 mm of EPS (Wall 04), 80 mm of EPS (Wall 05), and with100 mm of EPS (Wall 06), from the outside of the existing external wall Ventilated façade of metal plates over EPS with the thicknesses as follows: 20 mm (Wall 07), 30 mm (Wall 08), 40 mm (Wall 09), 60 mm (Wall 10), 80 mm (Wall 11), and 100 mm (Wall 12) Construction of a drywall (with metallic intermediate support structure) from the inside of the existing external wall over EPS with the thicknesses as follows: 20 mm (Wall 13), 30 mm (Wall 14), 40 mm (Wall 15), 60 mm (Wall 16), 80 mm (Wall 17), and 100 mm (Wall 18) Construction of a 7 cm brick wall from the inside of the existing external wall over EPS with the thicknesses as follows: 20 mm (Wall 19), 30 mm (Wall 20), 40 mm (Wall 21), 60 mm (Wall 22), 80 mm (Wall 23), and 100 mm (Wall 24)

organisations or individuals to take actions that do not reflect their own direct interests (and are therefore unattractive as investments) but that can prove to be beneficial to society as a whole (Aggerholm et al., 2011). This macroperspective includes benefits and costs of “externalities”, such as damages from climate changes associated with carbon dioxide emissions. Following strictly the EPBD meaning for this perspective, the global cost of each package of solutions corresponds to the price paid by the end consumer, excluding all applicable taxes, subsidies and incentives, and including the cost of global greenhouse gas (GHG) emissions – Cc,i(j ), as indicated in formula (3): Cg (τ ) = Ct +

⎡

τ

∑ ⎢ ∑ (C m, i(j) × Rd(i) + Cs, i(j) × Rd(i) + Ce, i(j) × Rd(i j

⎢⎣ i + 1

⎤ + Cc , i(j ) × R d(i )) − Vf , τ(j ))⎥ ⎥⎦

(3)

The discount rate adopted in the macroeconomic perspective should give emphasis to political priorities rather than to the financial context and to the mortgage credit conditions in the country. The value adopted is 3% and corresponds to one of the two values (3% and 4%) most cited in studies (Department for Communities and Local Government, 2013; European Commission, 2015; Ferreira et al., 2014; Regulation No. 244, 2012). 2.4.3. Cost calculation For both perspectives, the investment costs, the maintenance costs and the replacement costs are obtained from the ProNIC (Protocol for Technical Information Standardisation in Construction) database (Monteiro et al., 2014) and are complemented by prices taken from standard offers of construction companies and from LNEC's database on construction prices (Manso et al., 2004). The residual value of each measure is calculated on the basis of the

remaining lifetime of the last replacement of the measure until the end of the calculation period, assuming a straight-line depreciation over its lifetime. For the macroperspective, the GHG emission costs are calculated according to the Portuguese information on GHG emission allowances (DGEG (Direção Geral de Energia e Geologia), 2013). As this information covers only a period until 2030, the data for the remaining years (until the end of the calculation period, 2043) is obtained by interpolation. The conversion factors of primary energy to GHG emissions are based on the Portuguese decree-law (Despacho (extrato) No. 15793-D/2013, 2013). The definition of the maintenance activities, periodicity and lifespan of each construction element and solutions, are obtained from the information included in preventive maintenance plans and scientific publications (Abate et al., 2009; Albano, 2005; Housing Association Property Mutual – HAPM, 2003; Institut de Tecnologia de la Construcció de Catalunya, 1991; Silva, 2011; Viegas, 2006). The energy costs are directly calculated from the energy needs for heating and cooling the building (obtained in Phase 3), multiplied by the Portuguese annual energy costs (DGEG (Direção Geral de Energia e Geologia), 2014). For the first year of calculation (year 0), the energy cost values adopted are 0.1243 €/ kW h (macroeconomic perspective – excluding taxes) and 0.2131 €/kW h (financial perspective – including taxes), both corresponding to 2013 second semester data values. The energy cost forecasts followed the EU's trends for domestic electricity (European Commission, 2014). The primary energy factor for electricity is 2.5 kW hPE/kW h and it is also based on the Portuguese decreelaw (Despacho (extrato) No. 15793-D/2013, 2013). This factor is assumed to remain constant over the years. The different types of costs considered (initial investment costs, maintenance costs, operational costs, energy costs, greenhouse gas emission costs, and disposal costs) (EN 15459, 2007; Guidelines

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Regulation No. 244, 2012) are calculated in reference to the starting year by applying the selected discount rate. The calculation period adopted is 30 years, as proposed in the EPBD. A cost scenario and the details of the values regarding the measures applied to the RB are presented in Brandão de Vasconcelos et al. (2016). 2.5. Phase 5 – determination of a cost-optimal level of energy performance In this last phase, the cost-optimal level of the energy performance is determined. It is based on the calculations of primary energy use (phase 3) and on global costs (phase 4) associated with the different measures (phase 2) assessed for the defined RB (phase 1). Graphs can be drawn representing the primary energy use (x-axis) and the global costs (y-axis) of the different measures. A full description of the procedure followed to obtain the costoptimal curve can be found in Brandão de Vasconcelos et al. (2016). Fig. 1 shows the cost-optimal curve that is found when assessing all the combinations of measures of the RB from a macroeconomic perspective. The lowest point of the curve (red point) corresponds to the package of solutions with the lowest global cost (Wind 01/Wall 24/Roof 04/Floor 02). This package consists of the procedures as follows: replacement of the existing window by an aluminium window frame (no thermal break) with double clear glass (4 mm þ6 mm thick) and 6 mm air space, construction of a 7 cm brick wall from the inside of the existing external wall over a 100 mm thick EPS, application of a 60 mm thick EPS over the roof concrete slab and application of vinyl floor coating over a 20 mm thick EPS. The cost-optimal level of packages with the same or similar costs corresponds to the one with the lower primary energy use (circle dots with different color levels in Fig. 1). Once these packages are close to the cost-optimal point, they also are considered as likely cost-efficient measures. The part of the curve to the right of the cost-optimal level represents the solutions that underperform in both aspects (environmental and financial). The left part of the curve, starting at the cost-optimal level, represents the cost-optimal energy-performance levels for both low and nZEB. The shadowed zone illustrated in Fig. 1 includes the thermal refurbishment packages of solutions having less primary energy

333

consumption and less global costs than the ones assigned to the RB base package of solutions. Therefore, from the cost-optimal point of view, it is more advantageous to proceed with any thermal refurbishment package of measures located inside the shadowed zone rather than doing nothing on the RB considered. The cost-optimal package of solutions found in the financial perspective is exactly the same as the one obtained for the macroperspective. The graphics for both perspectives have the same shape, differing only as refers to the position of the dots cloud. The dots cloud, in the financial perspective, is located above (on y-axis) the macroeconomical one, which means that the global costs assigned to the first are higher than the latter.

3. Sensitivity analysis 3.1. Aims and scope In the Section 2, the cost-optimal package of solutions has been determined based on some conditions and parameters. SA on the results achieved makes it possible to perform changes in the model inputs and assumptions/parameters and to determine how the cost-optimal package of solutions may vary. To achieve that, combinations of deterministic values for the input parameters can be performed and their results assessed (Aksoy and Inalli, 2006; Calleja Rodríguez et al., 2013; Depecker et al., 2001; Gratia and De Herde, 2003; Hemsath and Bandhosseini, 2015; Ourghi et al., 2007; Pacheco et al., 2012), or probabilistic distributions can be assigned to each parameter and a probability value is therefore associated to the results (Das et al., 2014; Fürbringer and Roulet, 1995; Heiselberg et al., 2009; Ioannou and Itard, 2015; Pudleiner and Colton, 2015; Shen and Tzempelikos, 2013). Most studies follow the first approach (deterministic values), the other (probability value), which basically corresponds to physical behaviour parameters – e.g. the thermal transmission coefficient of windows, the solar factor of glasses, the walls conductivity, the lighting controls, the amount of ventilation during winter –, is followed by only a few. The deterministic SA approach has been followed in the present study, as the main purpose was to create scenarios within a decision-making process and not so much to study the probabilities of occurrences. The parameters chosen to be analysed were the discount rate and the building orientation: the first is

Fig. 1. Cost-optimal level from the macroeconomic perspective (base parameters).

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much influenced by economical conditions and the latter has a strong influence on the overall building energy consumption. The decision to choose these two parameters is two folded: on the one hand, it is aimed to analyse the influence of the discount rate on the cost-optimal package results; and on the other hand, it is intended to verify if those results are much influenced by a physical characteristic that was predefined for the RB and did not result from the statistical data collected for its definition – the building orientation. Furthermore, different studies have shown that this building characteristic is relevant for the building total energy demand (Aksoy and Inalli, 2006; Hemsath and Bandhosseini, 2015; Pacheco et al., 2012). For the determination of the cost-optimal packages of solutions associated to each parameter studied, two types of calculations were performed, according to different perspectives –macroeconomic and financial, respectively –, as described in Section 2.4. Table 3 shows the parameter values studied in the SA. These parameters were firstly considered to vary independently, one by one, and afterwards by combining each discount rate value with each building orientation – both situations being analysed from the macroeconomic and the financial perspectives. A total of seven combinations, for the macroeconomic perspective, and nine, for the financial perspective, were performed. For each combination/ scenario, the correspondent cost-optimal package of solutions was determined and then compared with the one achieved for the RB base parameters (N–S orientation, 3% and 6% macroeconomic and financial discount rates). The first two rates, selected for the macroeconomic perspective (2% and 4%), are to reflect variations of one percentage point around the 3% base discount rate considered, while the 6% discount rate corresponds to the same percentage rate value adopted in the financial perspective. In the financial perspective, the 3% discount rate enables a direct comparison between the two perspectives with the same discount rate, the 5% and 7% rates aim to reflect variations of one percentage point around the base discount rate considered and the 10% rate is also considered to attain higher rate values used in other cost-optimal studies (Department for Communities and Local Government, 2013; European Commission, 2015). As to the building orientation, apart from the N–S one already considered as a base parameter, the E–W orientation is also studied as it represents a totally different solar/thermal incidence on the RB, which is also representative within Lisbon's housing stock.

different discount rates analysed. These curves coincide with the lower boundary line of each dot cloud and have marked the costoptimal package of solutions. The cost-optimal packages of solutions determined with 2% and 3% discount rates (low discount rates) are the same and correspond also to the cost-optimal base package: Wind 01/Wall 24/ Roof 04/Floor 02. By increasing the discount rate, the cost-optimal packages of solutions change into less thermal efficiency ones. In detail, the cost-optimal window solution becomes the aluminium without thermal break and single clear 6 mm thick glass, the costoptimal floor solution no longer includes thermal insulation, the cost-optimal roof solution decreases the EPS insulation thickness to 40 mm and the cost-optimal wall solution remains the same construction solution as the RB without thermal insulation (Wall 00). It is also noticed that the biggest variations found in the thermal insulation thickness of the building envelope elements for the different discount rates correspond to the wall solutions as follows: 100 mm thick EPS for 2% and 3% discount rates, 80 mm thick EPS for 4% discount rate and no need whatsoever for thermal insulation for the 6% discount rate.

3.2. Discount rates

3.3. Building orientation

3.2.1. Macroeconomic perspective Fig. 2 illustrates the results obtained with the application of the four discount rates, including the 3% base discount rate, for the N– S RB orientation, in the macroeconomic perspective. The different curves represent the packages of solutions having the lowest global cost for each value of primary energy consumption, for the

3.3.1. Macroeconomic and financial perspectives The macroeconomic and financial perspectives are presented together, provided that the cost-optimal package of solutions found in the RB E–W orientation is the same for both perspectives and the correspondent dot clouds are also equivalent but with different global costs. Fig. 4 illustrates the results obtained for the E–W RB orientation and from the macroeconomic perspective. The cost-optimal package of solutions found corresponds to Wind 03/Wall 24/Roof 04/Floor 01, consisting of the procedures as follows: replacement of the existing window by an aluminium window frame without thermal break with double low emissivity clear glass (4 mm þ 6 mm low-e thick) and 16 mm air space; construction of a 7 cm brick wall from the inside of the existing exterior wall over a 100 mm thick EPS; application of a 60 mm thick EPS over the roof concrete slab; and application of a vinyl coating without thermal insulation on the ground floor. Fig. 5 shows the results obtained for both building orientations (N–S and E–W), in the macroeconomic perspective (same results

Table 3 Parameters studied in the SA. Parameters

Discount rate Macroeconomic perspective

RB base parameters 3% SA parameters for combination

2%, 3%, 4%, 6%

Building orientation Financial perspective 6%

North–South (N–S) 3%, 5%, 6%, 7% e North–South 10% (N–S) East–West (E– W)

3.2.2. Financial perspective Fig. 3 shows the results obtained with the application of the five discount rates, including the 6% base discount rate, for the N–S RB orientation, in the financial perspective. The different curves are represented in the same way as described for the macroeconomic perspective. It is observed that the cost-optimal packages of solutions for the discount rates of 5% and 6% match the base cost-optimal one (Wind 01/Wall 24/Roof 04/Floor 02). For 3% and 7% discount rates, the cost-optimal packages of solutions slightly change, corresponding to a higher thermal insulation thickness on the roof for a discount rate of 3% (80 mm thick EPS instead of 60 mm thick EPS) and to a lower thermal insulation thickness on the external wall for a discount rate of 7% (80 mm thick EPS instead of 100 mm thick EPS). The biggest variation in the cost-optimal package of solutions is achieved with the 10% discount rate. The corresponding package consists of maintaining the RB window base solution, of the replacement of the existing floor solution by a vinyl coating one without thermal insulation, of the application of a 40 mm and a 60 mm thick EPS thermal insulation over the roof concrete slab and on the external wall, respectively.

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Fig. 2. Discount rate SA (macroeconomic perspective and N–S RB orientation).

Fig. 3. Discount rate SA (financial perspective and N–S RB orientation).

are achieved in the financial perspective). The dot cloud for the E– W orientation is much more spread than the N–S one and corresponds to packages of solutions that lead to higher primary energy consumptions. The differences in the primary energy consumptions are originated by the increase of around 15% in the heating energy needs and of about 100% in the cooling energy needs occurring in the E–W orientation when compared to the N– S one. For this reason, the E–W cost-optimal package of solutions includes windows with low emissivity glasses that reduce the internal solar gains and floors without thermal insulation to take advantage of the lower ground temperatures, allowing therefore a reduction in the cooling energy needs. The roof and external wall solutions remain the same for both orientations, i.e. equal to the correspondent base cost-optimal solutions. 3.4. Discount rates and E–W building orientation In this section, the discount rate parameters considered for both macroeconomic and financial calculation perspectives are combined with the E–W building orientation parameter.

3.4.1. Macroeconomic perspective Fig. 6 illustrates the results obtained with the application of the four discount rates, including the 3% base discount rate, for the E– W RB orientation, in the macroeconomic perspective. None of the cost-optimal packages of solutions found correspond to the cost-optimal base package. The cost-optimal packages of solutions correspondent to the macroeconomic discount rates of 2% and 3% for the E–W orientation are the same as the one found for the E–W orientation, when SA was performed considering only the building orientation parameter (Fig. 6): Wind 03/ Wall 24/Roof 04/Floor 01. By increasing the discount rate, the cost-optimal packages of solutions change into less thermally efficient ones, as observed in the N–S orientation. In detail, the cost-optimal window solution becomes the aluminium without thermal break and double clear glass (4 mm þ6 mm thick) and 6 mm air space, and the cost-optimal roof solution decreases the EPS insulation thickness to 40 mm, while the cost-optimal wall and floor solutions remain the same (Wall 24, Floor 01). It is also noticed that as regards the macroeconomic discount

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Fig. 4. Cost-optimal level from the macroeconomic perspective and E–W RB.

Fig. 5. Building orientation SA (macroeconomic perspective and 3% discount rate).

rate of 6%, for the N–S orientation, the cost-optimal package of solutions only considers a thermal insulation over the roof concrete slab, by keeping the window and wall RB solutions (no insulation). In the case of the E–W orientation using a macroeconomic discount rate of 6%, the cost-optimal package of solutions includes a maximum thermal insulation thickness on the external wall (Wall 24 – 100 mm thick) and a double clear glass on windows (Wind 01 – 4 mm þ6 mm thick and 6 mm air space), by keeping the roof and pavement solutions achieved with the N–S orientation for the same discount rate. 3.4.2. Financial perspective Fig. 7 illustrates the results obtained with the application of the five discount rates, including the 6% base discount rate, for the E– W RB orientation, in the financial perspective. As noticed before for the macroeconomic perspective, none of the cost-optimal packages of solutions found correspond to the cost-optimal base package. With the 5% and 6% financial discount rates for the E–W orientation, the cost-optimal package of solutions corresponds to the one found for the E–W orientation when SA was performed

considering only the building orientation parameter (Fig. 4): Wind 03/Wall 24/Roof 04/Floor 01. With the 3% financial discount rate, the cost-optimal package of solutions comprises a 20 mm thickness increase in the roof thermal insulation (Roof 05). By increasing the financial discount rate by 6%, the low-e glass window solution is replaced by the double clear glass (for a 7% discount rate) and the roof thermal insulation thickness decreases to 40 mm (for a 10% discount rate). As mentioned for the macroeconomic perspective, the costoptimal package of solutions for the highest discount rate includes improvements in the thermal performance of the window and external wall solutions, which were not contemplated in the N–S orientation.

4. Discussion of results The methodology phasing proposed allows the decision-makers to choose the cost-optimal packages of solutions to be applied to their building. For the Portuguese RB, some conclusions can be

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Fig. 6. Discount rates and E–W orientation SA (macroeconomic perspective).

Fig. 7. Discount rates and E–W orientation SA (financial perspective).

drawn regarding the influence of discount rates and building orientation parameters on the choice of the cost-efficient solutions to be considered. From the possible packages of solutions listed, the one having the lowest global cost (the cost-optimal package of solutions) – Wind 01/Wall 24/Roof 04/Floor 02 package – consists of the procedures as follows: replacement of the existing RB window by an aluminium window frame (no thermal break) with a double clear glass (4 mm þ 6 mm thick) and a 6mm air space; construction of a 7 cm brick wall from the inside of the existing external wall over a 100 mm thick EPS; application of a 60 mm thick EPS over the roof concrete slab; and application of a vinyl floor coating over a 20 mm thick EPS. This solution was determined on the basis of the base parameters considered, i.e., macroeconomic perspective, 3% discount rate and N–S building orientation. However, it is important to take into account that, within a decision making process, other aspects can be considered, which might influence or even change the cost-optimal package. Examples of these aspects are the structure, the accessibility and the conservation building characteristics, as well as the behavioural users' patterns, among

others. This cost-optimal base package remains without any changes in its solutions for the discount rates of 2% and 3%, in the macroeconomic perspective, and for the discount rates of 5% and 6%, in the financial perspective, as refers to the N–S orientation. For the E–W orientation, none of the cost-optimal packages of solutions found correspond to the cost-optimal base package. However, the cost-optimal packages of solutions correspondent to the macroeconomic discount rates of 2% and 3% and to the financial discount rates of 5% and 6% are the same as the one found for the E–W orientation (Fig. 4). The SA discount rates also show that the cost-optimal packages, for both building orientations, are the same considering the discount rates of 4% (macroeconomic perspective) and 7% (financial perspective), but different than the cost-optimal base package. The same happens when considering the discount rate of 6% (macroeconomic perspective) and 10% (financial perspective) for the E–W orientation. Considering all the discount rates for both macroeconomic and financial perspectives and the two building orientations, the

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financial discount rate of 3% is the one that leads to a cost-optimal package of solutions with the best energy performance (less Uvalue of solutions). It is also possible to conclude that higher discount rates for the E–W orientation demand more energy efficient packages of solutions than for the N–S orientation. It is also shown, for both calculation perspectives, that the higher the discount rates (r) the lesser the discount factor (Rd) and consequently the lesser the global cost. Thus, associated to a higher discount rate there is a decreased investment global cost, while the investment cost of each package is maintained. So, in this context, a quicker and more commercial attitude in investment is privileged, which leads to the adoption of a cheaper package of solutions. In the decision-making process as refers to the thermal refurbishment to perform, an agreement on a lower discount rate, based on sustainability principles, would mean giving priority to environmental benefit projects. For example, in the case of a residential thermal efficiency and for the N–S orientation, macroeconomic discount rates of 4% or financial discount rates of 7% or less would promote the investments that could maximise the reduction in energy use. On the other hand, the macroeconomic discount rate of 6% or the financial discount rate of 10% may become prohibitive under policies aimed to energy use rationalisation or to GHG emission reduction. As for the SA on building orientation parameters (N–S or E–W), the results presented may lead us to conclude that the N–S orientation is the one that leads to less primary energy consumption (especially in terms of cooling energy needs), and consequently to decreased overall costs. Thus, E–W orientation requires more efficient glazing (low emissivity clear glass) and no thermal insulation on the ground floor. When setting refurbishment policies in Portugal, these findings allow obtaining a differentiation in the packages of solutions to be adopted in accordance with the building orientation. Generally speaking and taking into account different discount rates, a low emissivity clear glass is only needed for E–W orientated building, while roof and wall thermal insulations are needed for both buildings orientations.

5. Conclusion and policy implications In order to respond to the first question made by decisionmakers and mentioned in the introduction (Which criterion should be adopted in the choice of the refurbishment construction solutions?), a methodology has been proposed in this paper, which makes it possible to determine the cost-optimal package of solutions for buildings and their components, from a technical and economic perspective, following the requirements set out in EPBD Directive. The methodology was applied to a reference building (RB) representative of the Portuguese residential building stock, but it can be generalised and applied to other residential buildings in Portugal or in other countries, or even to other types of buildings. Regarding the second decision-makers' question (Which refurbishment construction solutions should be chosen?), an SA was carried out in order to clarify the importance and the influence of some key parameters (discount rates and building orientation) on the choice of the cost-optimal package of building refurbishment solutions for the Portuguese typical conditions. This approach assumes that, in a refurbishment process, building envelope measures (selective thermal insulation and fenestration) should be firstly contemplated in order to take full advantage of primary passive solutions potential. Therefore, neither the usage of energy systems and facilities nor the users' behaviour or management systems were considered, and will be further analysed in future research studies. The energy cost

evolution, the efficiency of the cooling and heating equipment, the Portuguese public incentives for building refurbishment and the carbon prices will also be addressed. In order to achieve sustainable development, political agreement on lower discount rates should be prioritised, with a view to promote the investments that could maximise the reduction in energy use. Greater discount rates (the macroeconomic discount rate of 6% or the financial discount rate of 10%) may become prohibitive under policies aimed to energy use rationalisation or to GHG emission reduction. Furthermore, the cost-benefit analysis (CBA) performed to support any energy efficient refurbishment decision should consider a cost premium as regards a future risk reduction in environmental impacts, such as for carbon related measures. Facing the EU requirements set on energy efficiency, energy savings and CO2 emission reduction – low discount rates policy –, the study done allows concluding that, for residential buildings constructed in Lisbon in the 1960–1990 period and having a N–S orientation, the cost-optimal package of solutions recommended to be applied is the Wind 01/Wall 24/Roof 04/Floor 02 package. For E–W building orientations, the cost-optimal package of solutions includes alternatively double low emissivity glazing (instead of double clear glass) in windows and no thermal insulation of the floor; therefore the Wind 03/Wall 24/Roof 04/Floor 01 package should be chosen. The study done also shows the way the discount rate – a parameter strongly affected by economic conditions – may influence the choice for the cost-optimal package of solutions, as well as how the building orientation – a physical building characteristic – affects the results: higher discount rates for the E–W orientation demand more energy efficient packages of solutions than for the N–S orientation. The cost-optimal packages of solutions mentioned, in each case, not only allow having low global life cycle costs but also point towards nZEB concept. According to EPBD recommendations, the results obtained are important for drawing national political instruments on buildings energy efficiency through the use of passive solutions, allowing the achievement of nZEB buildings with lower global costs during their life cycle. Guidelines and support mechanisms need to be included in the incentives and energy policies, so that passive solutions packages can be associated to different discount rates. This strategy leads both to the optimisation of the building thermal insulation needs and to the reduction of the building energy consumption, simultaneously promoting a long-term optimal cost, as intended by the EPBD.

Acknowledgements The authors wish to thank the three anonymous reviewers who contributed with excellent comments to an earlier version of the paper.

Appendix A. Supplementary material Supplementary data associated with this article can be found in the online version at http://dx.doi.org/10.1016/j.enpol.2016.01.021.

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