Quantification of economic benefits of renovation of apartment buildings as a basis for cost optimal 2030 energy efficiency strategies

Energy and Buildings 86 (2015) 151–160

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Energy and Buildings journal homepage: www.elsevier.com/locate/enbuild

Quantification of economic benefits of renovation of apartment buildings as a basis for cost optimal 2030 energy efficiency strategies E. Pikas a,b,∗ , J. Kurnitski c,1 , R. Liias c,2 , M. Thalfeldt c,3 a b c

Aalto University, School of Engineering, Otakaari 4, Aalto, 00076 Espoo, Finland Early Stage Researcher, Tallinn University of Technology, Faculty of Civil Engineering, Ehitajate tee 5, 19086 Tallinn, Estonia Tallinn University of Technology, Faculty of Civil Engineering, Ehitajate tee 5, 19086 Tallinn, Estonia

a r t i c l e

i n f o

Article history: Received 21 April 2014 Received in revised form 30 September 2014 Accepted 4 October 2014 Available online 17 October 2014 Keywords: Economic benefits Renovation of apartment buildings Cost optimality Energy and cost savings Tax revenue Job generation

a b s t r a c t As a part of the 2030 energy and climate policy discussion, the Estonian energy roadmap ENMAK 2030+ is being developed to set optimal national targets for 2030. Developing such a national roadmap requires solid evidence of which scenarios with varying ambition can be developed. This study looked at economic benefits, including tax revenue, job generation, and disposable net income per 1 MD of investment, and energy savings on both an individual and national level. In addition, economic quantification for the three scenarios was carried out. The study relied on secondary data collection with validation of the data through a sample analysis and interviews with project stakeholders. The main findings show that in all 17 jobs per 1 MD of investment in renovation were generated per year and direct tax revenue was between 32–33%, depending on the renovation project. Results revealed that over a 20 year period, there are essentially two national energy policy options: both the living quality and asset value brought about by integrated renovation at 160D /m2 or alternatively, that brought about by non-energy efficiency repairs at 31D /m2 . The study confirms that investment in energy efficiency is not only environmentally important but provides economic benefits on an individual and government budget level. © 2014 Elsevier B.V. All rights reserved.

1. Introduction “I believe that renovation of buildings to high energy performance standards could be one of the most cost effective investments a nation can make, given the benefits in terms of job creation, quality of life, economic stimulus, climate change mitigation and energy security that such investments deliver”. Oliver Rapf, Executive Director, BPIE [1]. The Estonian energy roadmap ENMAK 2030+ is being developed in line with the objectives described in the Green Paper “A 2030 framework for climate and energy policies” [2]. Developing a national roadmap requires scientific evidence, and on the basis of this evidence, different scenarios may be envisaged. With this in mind, a statistical study involving integrated and energy and

∗ Corresponding author at: Tallinn University of Technology, Faculty of Civil Engineering, Ehitajate tee 5, 19086 Tallinn, Estonia. Tel.: +372 56 455 953. E-mail addresses: ergo.pikas@aalto.fi, [email protected], [email protected] (E. Pikas), [email protected] (J. Kurnitski), [email protected] (R. Liias), [email protected] (M. Thalfeldt). 1 Tel.: +372 5866 4370. 2 Tel.: +372 501 6201. 3 Tel.: +372 520 9657. http://dx.doi.org/10.1016/j.enbuild.2014.10.004 0378-7788/© 2014 Elsevier B.V. All rights reserved.

investment analyses of Estonian building stock, including apartment buildings, was carried out [3]. For each building type, three to four different renovation packages were studied to identify cost optimal solutions [3]. However, the study focused only on energy efficiency/energy savings and investment intensity and did not consider the economic impacts of these renovation measures/packages. Buildings account for a large share of the energy consumed nationally and produce 36% of the EU’s CO2 emissions [4]. In 2010, 20% reduction in both CO2 emissions and energy consumption by 2020 was set as a target for all EU member states [5], the aim being to maintain energy consumption at a 2010 level. According to the above mentioned study [3], in 2010, Estonian building stock account for up to 50% of total national final energy consumption, significantly above an average 37.5% across all EU countries [3]. Estonian final energy use amounted to 33.0 TW h/a, total primary energy use, 45.5 TW h/a (buildings for 55%), and non-renewable primary energy use, 35.3 TW h/a (buildings accounting for 47%) [3]. The Estonian building stock has clearly played a major role in energy use, exceeding consumption by industries such as transportation and manufacturing. If national measures are not adopted, overall energy consumption of buildings may even increase, due to the relatively low replacement rate of existing buildings (0.3% per year)

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and the higher rate of the building of new ones (1–1.5% in a year). In this case, Estonia will not be able to achieve the reduction goals set by the EU by 2020. Up to 71% of Estonians are living in apartment buildings built primarily between 1961 and 1990 [3]. A large number of apartment buildings are concentrated in historically industrialized regions (e.g., East-Virumaa county), or around metropolises (e.g., Tallinn, Tartu and Pärnu) [6,7]. Generally, there are two types of apartment buildings: prefabricated concrete large-panel and brick buildings [7,8]. It has been concluded that structurally the lifecycle of these buildings can be extended if specific precautions are taken, meaning that structural integrity must be checked before developing renovation solutions. Energy efficiency and indoor climate are especially in need of improvement. Due to the vast number of existing dwellings, a remarkable savings in heating energy consumption can be achieved, but at the same time, electric energy consumption is on the rise for most types of building [9]. A similar significant energy savings potential has been recognized in other countries [10]. Theoretically, the technical energy savings potential for apartment buildings may amount to as much as 2.06 TW h/a in terms of non-renewable primary energy, is calculated and 3.74 TW h/a in terms of final energy use. In practice, it depends on the strategies adopted nationally [3]. The realization of this energy savings potential must take into account various kinds of barriers [1,11], including but not limited to: financial; institutional and administrative; awareness, skills and advice; and separation of expenditure and benefit (investor society and landlord–tenant) [12]. For example, owners are not generally keen to improve the energy efficiency of their homes, as it does not lead to a proportionate increase in the value of their property [12]. Member states must consider barriers and develop proper policies and strategies for achieving energy efficiency objectives [1]. When polices are developed, a good understanding of the benefits of different policy measures is required. Benefits can be divided into four categories: economic benefits (energy cost savings, economic stimulus, asset value/property values, employment, impact on public finances, impact on gross domestic product (GDP) and energy import bill), societal benefits (reduced fuel poverty, health and increased comfort and productivity), environmental benefits (carbon savings and reduced air pollution) and energy system benefits (energy security, avoided new generation capacity and reduced peak loads) [1,13]. In Finland, when the economic benefits of a renovation measure were calculated, it was concluded that a one million EUR investment would generate a total of 16 jobs: 8 directly on the construction site; 5 indirectly in the construction materials and products manufacturing industry (hereafter manufacturing); and 3 in the consulting sector (including energy auditors, designers and owners’ supervisors) [14]. Similarly, in another study which looked at economic impacts on a macroeconomic level using macromodels, the authors concluded that renovation strategies would have a negative impact on GDP and the employment rate in the short term but positive effects over the long term, given the large share of the energy industry supplying heating [15]. Another study analyzed the benefits of a variety of energy saving measures on an individual level but not on a national level [16]. Finally, a Lithuanian study analyzed the investment efficiency of renovating apartment buildings built mostly between 1960 and 1990, concluding that separating measures into two categories is important: measures for improving energy efficiency and measures for extending the building life cycle [17]. It is being argued by the present authors that renovation projects can bring needed stimulus to the European economy at a time of economic underperformance, spare capacity and record low real interest rates. By reducing energy consumption and focusing on indoor climate issues when renovating, co-benefits can be achieved

such as reduced outlays for government subsidies and improved health due to lower air pollution levels and a better indoor climate, both of which also lead to lower hospitalization rates and improved worker productivity [18]. The present study focuses on the economic stimulus/benefits provided by renovation projects. Aspects, such as the effects of indoor climate on a person’s health and productivity are not studied, as these are already well-documented elsewhere [19,20]. The directive on the energy performance of buildings (2007–2010) [21] led in Estonia to a deep renovation of 520 apartment buildings under the KredEx support scheme [22]. The experience garnered and technical solutions applied have been utilized in this study. KredEx is a financing institution and in connection with renovation measures, have been offering grants for solutions aimed at energy efficiency. Our hypothesis is that policy measures would not only lead to a decrease in energy consumption but would have a significant economic impact, which this study seeks to quantify. The results of this study are intended to be used as input for the establishing of national measures within the framework of the development of a national energy roadmap ENMAK 2030+. 2. Methods The study relied primarily on secondary data collection, which was validated by the conducting of interviews with project stakeholders, including owners, designers, contractors, and owners’ supervisors. The initial selection of projects was made according to the following criteria: • the project must have received a 35% subsidy grant from Kredex (according to MKM [23] projects, a project must achieve a 50% savings in heating energy consumption, renovate the building systems, including ventilation, with heat recovery, and improve the thermal performance of the building envelope—Kredex providing the funds for reconstruction); • the project should be well documented; • the authors have access to project information. Overall framework of the analysis: • Step 1: a macroeconomic analysis of construction goods and materials, consulting and manufacturing to estimate jobs and taxes per 1 MD of revenue; • Step 2: data collection from Kredex and stakeholders of selected projects; • Step 3: analysis of the distribution of costs on the construction site (materials, labor, and project management costs); • Step 4: validation of step 1 by analyzing the annual reports (2011 and 2012) of consultants and manufacturers selected on the basis of steps 2 and 3. This means that only consultants and manufacturers whose services and products were connected with the renovation of the given apartment buildings were selected; • Step 5: analysis of direct and indirect energy savings, job creation, tax revenues and net salaries; • Step 6: analysis of the (direct) economic impact of three different scenarios developed elsewhere [3]. 2.1. Description of selected projects A total of 7 projects were initially selected for this study, but one of these projects was later excluded due to the fact that it had been designed and constructed in different stages. This made data collection complicated and rendered a comparison with the other projects impracticable. A summary of the selected projects is

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Table 1 Overview of the six renovation projects of apartment buildings selected for in-depth economic analysis and calculation of direct benefits.

Description Project nr 2

Project nr 3

Project nr 1 Construction year Renovation year No. of stories Net area (m2 ) Heated floor area (m2 ) Apartment area (m2 ) Volume (m3 ) No. of apartments * Compactness A/V, (m−1 ) Heating (kW h/m2 a) Electricity (kW h/m2 a) Primary energy (kW h/m2 ) *

Project nr 5

Project nr 6

1976 2013 5 3280 2677 2677 12 484 55 0.26 263 43 322

1982 2013 5 2804 2367 2046 10 239 30 0.37 156 30 201

Project nr 4

1970 2013 9 11 374 10 620 9630 43 658 162 0.23 179 36 233

1972 2013 10 4809 3986 3607 19 084 54 0.17 197 41 260

1983 2013 2–5 10 899 9081 7876 39 230 102 0.41 227 35 275

1966 2013 5 7461 6270 3977 15 676 119 0.40 169 27 206

Compactness is defined as the ratio of building envelope surface area to volume.

provided in Table 1. The projects included in this study involved buildings with have two different types of structures: prefabricated concrete large-panel and brick buildings. Overall these buildings were relatively compact but had high primary energy levels, 250 kW h/m2 on average. Most of the selected buildings had undergone some degree of minor renovation or repair work within the last 5–10 years. Generally, projects made most active use of building envelope renovation methods, depending on the existing situation and solutions provided by the designers. However, as 35% of the costs of these projects were being subsidized by Kredex, all projects included ventilation heat recovery. In most cases, this meant using an exhaust air heat pump to fulfill the Kredex requirement to achieve a 50% energy savings [22,23]. Even though the energy efficiency required is not related to the energy performance class (EPC), all projects, except for project nr. 2, also achieved EPC class C (121–150 kWh/(m2 a)). Table 2 summaries all the renovation methods used in different

projects and the estimated energy use after renovation, based on the energy audits. 2.2. Macroeconomic analysis, data collection, and validation Macroeconomic aspects of consulting (including energy audit, design and owners’ supervision services) and manufacturing sectors were studied on the basis of data found in the statistics Estonia database [24]. We analyzed how many jobs had been created and taxes paid per 1 MD of revenue. To validate figures for consultancy industry job creation and taxes paid per 1 MD of revenue, we made use of information collected by the Estonian Association of Architectural and Consulting Engineering Companies (EAACEC) [25]. To validate manufacturing sector data, we selected 10 companies from the construction goods and materials sector from among members of the Estonian Association of Construction Materials and Products Manufacturers (EACMPM). In addition, only

Table 2 Summary of renovation measures used and estimated energy use after renovation. Energy use values after renovation were obtained from energy audit appendices compiled after the completion of the reconstruction work.

External wall

Roof

Floor

Project nr 1

Project nr 2

Project nr 3

Project nr 4

Project nr 5

Project nr 6

Insulation: end wall 100 mm and long wall 150 mm, U = 0.18 and 0.19 W/(m2 K) Insulation 250 mm + 50 mm, U = 0.14 W/(m2 K) Lobby ceiling insulation: 100 mm

Insulation 150 mm all walls, U = 0.20 W/(m2 K)

Insulation 150 mm all walls, U = 0.22 W/(m2 K)

Insulation 150 mm all walls, U = 0.22 W/(m2 K)

Insulation 150 mm all walls, U = 0.22 W/(m2 K)

Insulation 150 mm all walls, U = 0.21 W/(m2 K)

Insulation 250 mm, U = 0.13 W/(m2 K)

Insulation 200 mm, U = 0.17 W/(m2 K)

Insulation 250 mm, U = 0.11 W/(m2 K)

Insulation 250 mm, U = 0.11 W/(m2 K)

Insulation 250 mm, U = 0.14 W/(m2 K)

–

Foundation insulation 100 mm, U = 3.0 W/(m2 K) U = 1.1 W/(m2 K); moved to insulation layer Insulating thermal bridges District heating; two pipe heating system

Foundation insulation 100 mm, U = 0.25 W/(m2 K) U = 1.1 W/(m2 K); moved to insulation layer Closing loggias

Foundation insulation 120 mm, U = 0.25 W/(m2 K) U = 1.1 W/(m2 K)

First floor ceiling insulation 150 mm, U = 0.39 W/(m2 K) U = 1.1 W/(m2 K)

–

–

District heating; two pipe heating system

District heating; two pipe heating system

Exhaust air heat pump and mechanical exhaust

Mechanical supply and exhaust ventilation with room units 106 27 149

District heating; two pipe heating system; solar collectors for hot water Exhaust air heat pump and mechanical exhaust

U = 1.1 W/(m2 K); moved to insulation layer Closing loggias

U = 1.1 W/(m2 K); moved to insulation layer Closing loggias

Heating system

District heating; two pipe heating system

District heating; two pipe heating system

Ventilation type

Exhaust air heat pump and mechanical exhaust 77 35 139

Exhaust air heat pump and mechanical exhaust

Windows and doors

Loggia

Heating (kW h/m2 a) Electricity (kW h/m2 a) Primary energy (kW h/m2 a)

92 35 152

Mechanical supply and exhaust ventilation with room units 102 27 146

85 35 146

78 35 140

13.8

20.7

7.7

12.3

9.3

31.7 17.8

6.3

47.0 36.5

14.6

53.0 63.5

30.1

19.2 11.6

69.9

14.1 8.0

8.8

32.6 18.5

6.6

45.5 36.8

15.2

54.5 63.2

29.4

C6 Windows and doors C6 Windows and doors

17.1 10.7 5.0 2.5 5.1 3.6

6.8

8.4 9.8 2.5 3.6 3.8 3.2

4.0

19.3 22.6 5.8 8.4 8.8 7.3

9.3

31.7 30.4 21.9 27.8 29.0 21.7

24.7

68.3 69.6 78.1 72.2 71.0 78.3

Direct costs per 1 M EUR of revenue (%) Margin per 1 M EUR of revenue (%) Labor cost for employer per 1 M EUR of revenue (%) Labor related taxes per 1 M EUR of revenue (%) Number of jobs per 1 M EUR o revenue, jobs/MD a 2011

75.3

16.6 10.7 5.2 2.1 3.9 3.7

5.6

9.7 9.5 3.2 3.4 3.2 3.7

4.4

22.3 21.9 7.3 7.9 7.5 8.6

10.1

33.0 28.3 20.0 25.2 29.0 21.2

25.8

67.0 71.7 80.0 74.8 71.0 78.8

Direct costs per 1 M EUR of revenue (%) Margin per 1 M EUR of revenue (%) Labor cost for employer per 1 M EUR of revenue (%) Labor related taxes per 1 M EUR of revenue (%) Number of jobs per 1 M EUR o revenue, jobs (MD a) 2012

74.2

C6 Windows C5 Windows C4 Dry mixtures C4 Dry mixtures C2 Rigid insulation boards C1 Rigid insulation boards Description

C3 Rigid insulation boards

Fig. 1. Cost structure for average consulting company per 1 MD of revenue.

Year

Table 3 Analysis of 9 manufacturers and resellers selected for validating macroeconomic analysis.

70.6

E. Pikas et al. / Energy and Buildings 86 (2015) 151–160

Average

154

manufacturers whose product types had been used in the renovation projects, were selected for validation purposes. These types include, for the most part, rigid thermal isolation boards, windows/doors and dry mixtures (such as self-layering concrete, tiling glue, etc.,). According to the EAACEC, the average charge for consultancy services is 38D /h, and 58% of this goes towards labor costs (salaries and taxes). On a macroeconomic level, 1 MD of revenue creates 27.8 jobs per year. Average direct costs for providing services was 86.3%, with a margin of 13.7%, of which approximately 7.8% was profit. Fig. 1 summarizes the cost structure of consulting services. For the analysis of the manufacturing industry, information for the years 2006–2012 was summarized. On average, 16.4% of 1 MD of revenue was spent on labor costs, and 7.12% was spent on taxes. Per 1 MD of revenue, 11.1 jobs were created per year. Fig. 2 summarizes the cost structure of revenue. To validate these results, 9 Estonian manufacturers and resellers based on the analysis of material types used on the construction sites were selected. On average 21% of all materials used in selected projects were from Estonia, and many of the materials used in the renovation projects were from countries such as Poland, Germany, Finland and Denmark. Following Table 3 summarizes the economic analysis of 9 selected companies. C4 in table is a only reseller, all the other are local manufacturers. In 2012, on average 15.2% of 1 MD of revenue was spent on labor costs and 6.6%, on taxes. 8.8 jobs per year had been created in the selected companies per 1 MD of revenue. Numbers vary for the year 2011 but in general, the macroeconomic analysis seems to agree with the analysis of sample companies with small discrepancies.

Fig. 2. Cost structure for manufacturers per 1 MD of revenue.

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Fig. 3. Distribution of construction costs.

2.3. Distribution of projects costs The size of the selected projects varied from small to large in terms of square meter and cost as summarized in Table 4. 35% of the cost of all reconstruction projects had been subsidized by Kredex. Additionally, three projects out of six were selected as a Kredex pilot project, which means that 90% of the consulting costs of three projects had also been subsidized by Kredex. Therefore, the percentage of Kredex support for non-pilot projects amounted to 35% and for Kredex pilot projects 38% on average. The cost for consultancy services per heated area of buildings differed by up to a factor of 2.3: without Kredex support, consultancy costs were 3.77D /m2 , and with Kredex support, 8.78D /m2 . Construction costs ranged from 136D /m2 to 216D /m2 . On average, 3.1% of the total project cost was spent on consultancy, and 96.1% was spent on construction, indicating a remarkable gap between resources spent on consultancy and that spent on construction sectors. Fig. 3 summarizes the distribution of construction costs. The projects were analyzed on the basis of the project budget, while costs were classified into three different categories. For validation purposes, we analyzed the results together with the contractors. On average, 12% had been spent on project management costs. These include general contractor management costs: site and company overheads and risk/profit margins. A part of this 12% went towards salaries, but our analysis did not include these salaries in the calculation of jobs created per year and tax revenues, as it was difficult to measure it, and we did not have direct access to this information. Labor costs account for 34% of construction costs; material costs, 54%. Per 1 MD of investment, the average cost of materials, labor and project management was 440 128D , 275 035D , and 98 365D , respectively. The distribution of project costs was used to calculate job creation and tax revenues per 1 MD of investment (directly) in the construction site and (indirectly) in the consultancy and manufacturing sectors. In addition, net salaries per 1 MD of investment were calculated, to indicate the disposable income of the labor force. 2.4. Calculation of energy savings Calculation of energy savings and net present value (NPV), according to the commission’s cost optimality methodology [26], relied on the following parameters: • • • • • • • •

NPV calculation and loan period: 20 years; real interest rate: 4%; escalation of energy prices: 3% (adjusted for inflation); heating energy (district heating) price: 0.075D /kW h (VAT included); price of electricity for residential buildings: 0.14D /kW h (VAT included); maintenance and contingency fund required by bank: 0.10D /m2 ; the present value factor (Eq. (3)): fpv(n) = 18.05; all costs include VAT: 20%.

Fig. 4. Jobs created in different construction sectors per 1 MD of investment (* Project number six does not include MEP/HVAC work).

Construction costs for renovation were calculated as full cost (i.e., not only energy performance related costs), where all costs of construction work and installations were taken into account. This means that not all costs were directly related to the improvement of energy performance. Energy costs were calculated per apartment area per month. The net present value was calculated as global cost, consisting of construction costs and discounted energy costs: Cg =

CI + Ca × fpv (n) Afloor

(1)

where Cg global incremental energy performance related costs included in the calculations, NPV (D /m2 ); CI energy performance related construction costs included in the calculations (D ); Ca annual energy costs during the starting year (D ); fpv (n) present value factor for a calculation period of n years (–); Afloor net heated floor area (m2 ). To calculate the present value factor fpv (n), the real interest rate RR must be calculated. RR depends on the market interest rate R and inflation rate Ri : RR =

R − Ri 1 + Ri /100

(2)

An inflation rate of 3% (Ri ) was used for the calculation of the real interest rate. To calculate the percent value factor, the escalation rate e must be subtracted from the real interest rate RR [26]. The present value factor fpv (n) for a calculation period of n years is calculated as follows [27]:



fpv (n) =

−n

1 − 1 + (RR − e) /100 (RR − e) /100

(3)

where: RR the real interest rate, % e escalation of energy prices, % n the number of years considered, i.e., the length of the calculation period 3. Results 3.1. Generation of jobs and disposable income per 1 MD investment In this section, job creation in the construction field as a direct benefit was calculated on the basis of a macroeconomic analysis and detailed study of selected projects. In addition, as the cost distribution on the construction site had been calculated and the cost of consultancy and materials was known, this information could be used to calculate indirect benefits in the manufacturing and consulting sectors.

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Table 4 Distribution of project investment. Description Total project cost (D ) (VAT included) Kredex subsidy of total project cost (D ) (VAT included) Kredex subsidy of total project cost (%) Consultancy cost (D ) Construction cost (D ) Total VAT (D ) Investment per heated area (D /m2 )

Project nr 1

Project nr 2

2083 901 731 688 35 19 084 1717 500 347 317 196

Fig. 4 summarizes the number of jobs created per 1 MD of investment in six selected projects, which ranged from 15 to 19 jobs per year, with an average of 17. Due to the cultural similarities and economic relationship with Finland, we are contrasting Estonian numbers with Finnish ones. On average, one more job is created in Estonia than the average reported in the Finnish study [14]. The largest difference appeared in the consulting sector, where three jobs had been created in Finland and only one in Estonia. A similar difference appeared on the construction site but with positions reversed, while 10 jobs per year had been created in Estonia and only 8 in Finland. Net salaries per person per month were calculated to show the creation of disposable incomes per project cost. Calculation of the monthly net salary in the consulting sector was not included, as the design duration was not known. However, considering that on a macroeconomic scale the average net salary was 1324D /month in 2012 (analyzed in Section 2.2), we can calculate the design duration per person. The consultancy duration per person for the six selected projects was, respectively, 5, 3, 11, 1, 7 and 4 months, on average, 5 months per person. Consultancy also included energy audits, design, and owners’ supervision services, meaning that in practice, consultants had to work on many projects in parallel to earn a reasonable net salary per month. Net salaries in construction were calculated by dividing the net salary fund per project duration by the average number of workers in a month. Fig. 5 shows that projects in the capital of Estonia (all except project nr 5) and around it provided a greater net salary per person per month than those located outside the capital. The average net salary was 1088D /month. 3.2. Tax revenues Fig. 6 indicates that average total tax revenue from the six projects was 32–33%, including VAT and direct and indirect labor taxes. As on average, labor tax revenue included social security tax (33%, paid by the employer), unemployment insurance (1%, paid by the employer), funded pension contribution (paid by the employee, 2%), unemployment insurance (paid by the

861 734 302 208 35 11 540 706 572 143 622 216

Project nr 4

Project nr 5

Project nr 6

855 694 300 718 35 5417 707 661 142 616 136

504 154 194 158 39 27 331 392 798 84 026 188

361 274 137 032 38 16 592 284 470 60 212 153

employee, 2%) and income tax (paid by the employee, 21%). Average total tax revenue per 1 MD of investment was 324 170D . Average Kredex subsidy per 1 MD of investment was 364 372D (Table 5). In Fig. 6, tax return from selected projects compared to Kredex subsidy is visualized. Average direct tax revenue from construction was 28%, while average indirect tax revenue was 1% from consultancy and 3% from manufacturing. Tax revenue from manufacturing only included labor-related taxes, as VAT is paid during the construction phase, making tax revenue from construction the highest. Results indicate that the 35% subsidy for construction and additional subsidy, in some cases, for consultancy do not at first seem economically sensible, since investment expenditures exceed additional tax revenue gained. However, if indirect economic benefits that renovation projects bring are considered, then benefits outweigh the costs—jobs are created, asset value is increased (a residential building can apply for higher loan amounts), reduced social security costs for the government, etc., but this kind of quantification would require a modelling of the national economy, which is outside the scope of this study. If the objective is to balance tax revenue with governmental investment, then a more suitable subsidy per project cost would be 32–33%, as 28% from construction and 4% from manufacturing and consultancy are remitted on average. This revenue can be counted on, as design services and materials will always be used. 3.3. Energy savings and disposable income On the national level, citizens receive many direct and indirect benefits, ranging from increased tax revenue to improvements in general health, which can be equated to lower social service expenditures, such as spending on unemployment benefits. As stated before, national investment in buildings to improve energy efficiency is probably one of the most cost effective investments a nation can make [1]. However, the “flipside of that coin” is that a person is living in these renovated buildings. When policy measures are developed, benefits brought to individuals must also be

0

Fig. 5. Net salary in different sectors per one million D of investment.

Project nr 3 1542 405 568 478 37 43 012 1242 326 257 068 170

1

1

0

2

2

Fig. 6. Comparison of Kredex subsidy and tax revenue.

1

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157

Table 5 Tax revenue per 1 MD of investment. Description

Project nr 1

Project nr 2

Project nr 3

Project nr 4

Project nr 5

Project nr 6

Total VAT revenue (D ) Total labor tax revenue (D ) Total tax revenue per 1 MD of investment (D ) Kredex subsidy per 1 MD of investment, D (VAT included) Total tax revenue per project cost (%) Tax revenue from consultancy (%) Tax revenue from construction (%) Tax revenue from manufacturing (%)

347 317 313 477 317 095 351 115 32 0 28 3

143 622 140 774 330 028 350 698 33 1 29 3

257 068 238 424 321 246 368 566 32 1 28 3

142 616 141 072 331 529 351 432 33 0 30 3

84 026 81 785 328 890 385 117 33 2 27 3

60 212 56 495 323 043 379 303 32 2 27 3

Average 172 477 162 005 324 170 364 372 33 1 28 3

Table 6 Static analysis of monthly household expenditures on heating energy before and after renovation; electric energy not included. Description

Project nr 1

Project nr 2

Project nr 3

Project nr 4

Project nr 5

Project nr 6

Average

Monthly costs before renovation (D /m2 month) Monthly costs after renovation per heated area (D /m2 month) Heating energy cost after renovation (D /m2 ) Electric energy cost after renovation (D /m2 ) Loan payments, including interest, per heated area (D /m2 ) Bank’s required maintenance and contingency fund (D /m2 ) Ratio of monthly costs after renovation to energy costs before renovation (%)

1.54 1.83

1.72 2.02

1.83 1.88

1.37 1.87

2.14 1.81

1.33 1.68

1.65 1.85

0.48 0.41 0.86

0.57 0.41 0.95

0.70 0.32 0.77

0.53 0.41 0.84

0.66 0.32 0.74

0.48 0.41 0.70

0.57 0.38 0.81

0.10

0.10

0.10

0.10

0.10

0.10

0.10

1.19

1.18

1.03

1.36

0.84

1.26

1.12

considered. This section analyzes the energy costs of a household per month and year. More specifically, the objective is to understand if renovation of an apartment building increases or decreases monthly expenses per household. All projects that achieve at least a 50% energy savings in heating consumption can apply for a 35% subsidy. Monthly costs were calculated per heated area. The average consumption of electric energy based on an analysis of Estonian building stock in a previous study was 35 kW h/(m2 a) in the current situation, 24 kW h/(m2 a) in the standard use case, and 27 kW h/(m2 a) for buildings achieving C energy performance class [3]. In this study, the average consumption of electric energy before renovation equaled the current consumption rate of apartment buildings, 35 kW h/(m2 a), on average. As the energy audits only considered the electricity cost before renovation, values for the consumption of electric energy after renovation were chosen based on the analysis in the previous study, 35 kW h/(m2 a) for exhaust air heat pump ventilation and 27 kW h/(m2 a) for mechanical supply and exhaust ventilation with room units [3]. On average, energy costs before renovation were 1.65D /(m2 month). After renovation, average energy costs had decreased by 0.70D /m2 to 0.95D /(m2 month). If monthly loan payments, including interest, and the maintenance and contingency funds required by banks are included, then average monthly costs after renovation had increased to 1.85D /(m2 month), making the ratio of monthly costs after renovation to energy costs before renovation 1.12. Annual energy cost per average size apartment (59 m2 ) before renovation was 1176D /a, after renovation 673D /a or 1307D /a, if bank loan payments and maintenance and contingency funds are included. This is summarized in Table 6. However, since this is only a static view, the NPV for 20 years was calculated to see the impact of inflation and escalation of energy costs. According to the previous study [3], the cost optimal investment per m2 is about 160D /m2 per net area. In this study, we have used heated area for calculations, and the average investment cost per net area was 150.2D /m2 . In Fig. 7, cost optimality was found to be at around 184D /m2 (per heated area) according to the second order polynomial approximation. Project nr 3 and project nr 5 appear to be in the cost optimality range. However, only Project nr 5 had reduced monthly household costs. This might be due to

the fact that the budgets of the selected projects also included work not connected with improving energy efficiency (e.g., renovation of tap water plumbing, electric cables, and staircases). Kredex has estimated that around 20–25% of project costs are not directly related to energy efficiency measures. This information is used for further analysis. The average energy savings unit cost was 1674D /MW h/a, which was higher than the average provided in the previous study [3]. However, if 20% is subtracted as investment costs, than the average was 1339D /MW h/a, which is very close to the 1360D /MW h/a reported in the previous study [3]. Total annual energy savings per project were calculated together with the unit cost for energy savings as shown in Fig. 8. For a better understanding of the efficiency of the renovation solutions, a 20 year NPV was calculated. Average total annual energy savings amounted to 645 MW h/a. The cost information used in the calculations is summarized in Table 7. Fig. 9 summarizes 3 different NPV calculations. The blue line indicates NPV values for the projects before renovation, the red line, NPV values after renovation, and the green line, NPV values after renovation but excluding excess costs. The lowest NPV values were, in most cases, before renovation. However, as most of these apartment buildings had been built between 1960 and 1990,

Fig. 7. Investment efficiency.

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Table 7 Summary of cost information used in the 20 year NPV calculations, total energy savings and unit cost of energy savings. Before renovation

After renovation

Description

Heating (D /m2 a)

Electricity (D /m2 a)

Heating (D /m2 a)

Electricity (D /m2 a)

Total energy savings (MW h/a)

Project nr 1 Project nr 2 Project nr 3 Project nr 4 Project nr 5 Project nr 6 Average

13.40 14.81 17.02 12.69 19.70 11.73 14.89

5.08 5.80 4.92 3.78 6.01 4.20 4.96

5.76 6.87 7.66 6.35 7.92 5.82 6.73

4.90 4.90 3.78 4.90 3.78 4.90 4.53

1095 447 1207 480 463 175 645

3.4. Simplified economic analysis of three scenarios developed in previous study [3]

Fig. 8. Energy savings unit cost.

many of them would have to be repaired or renovated to some extent within a much shorter time period than the 20 years used in the calculation. Typically, windows have to be replaced, roofs have to be repaired, and many other kinds of work have to be carried out—i.e., not doing anything is basically not an option. Project nr 3 and Project nr 5 can be considered cost optimal solutions in either case, whether including or not including costs not directly related to energy efficiency improvement (an estimated 20% of the project cost). The other projects did not achieve cost optimality but came close. The reason might be under—or overinvestment (nonoptimal technical solutions). In other words, when design solutions are being developed, they must be carefully analyzed to ensure that benefits are gained on an individual level. In this way, renovation costs will balance out with costs before renovation through energy savings.

Fig. 9. Net present value of selected projects.

In this section, a simplified analysis of the economic aspects of the three scenarios developed in the previous study [3] is presented. It is also important for policy makers to understand the economic stimulus provided by investment in energy efficiency. For further details of the scenarios developed, please refer to the previous study [3]. For the three scenarios, the potential technical energy savings was calculated for the period 2011–2030. 2010 was used as a base reference year. Renovation rates, which were fixed for scenario calculations, were selected based on KredEx experience funding renovation projects for 520 apartment buildings. The assumptions made when developing the scenarios have been summarized in Table 8. In the economic calculations, governmental subsidies of 15% (S1), 25% (S2) and 35% (S3) were used with 15%, 30% and 50% renovation rates over 20 years, respectively. As shown in Table 9, in the case of S1 and S2, the government will gain more than they invest through direct tax revenue. When indirect tax revenue and job generation are included, the benefits are even more substantial. In the case of S3, the government does not directly benefit from the investment; however, the difference between the investment and tax revenue was relatively small (47.9 versus 44.4 M D /a). This difference may be affected by indirect benefits, which were not quantified in this study (since many jobs are generated and social security costs on a national level are, as a consequence, reduced, energy consumption on a national level means less energy imported and improved national security). In addition to these benefits, the renovation of apartment buildings also increases their asset value. According to the previous study [3], the renovation of apartment buildings increases their asset value by 60–90 D per m2 , bringing a clear benefit to building owners. In total, over a period of 20 years, 462.2, 1643.3 and 2738.9 MD /20 a is invested (government + private) in three different renovation scenarios, (see Table 10). The investment in the second and third scenarios, 3.55 and 5.92 times larger, respectively, than the investment in the first scenario, is a significant boost to the renovation construction industry. When total tax revenue and energy savings over 20 years are deducted from the total investment, the total cost for the government and private sector can be calculated. This is the expenditure that the private sector and government need to make to achieve the required results, making up 25D per renovated square meter in S1 and 31.2D /m2 in S2 and S3. These expenditures can be compared to renovation costs, which were considered in the previous study (Kurnitski et al., 2014): 90D /m2 for the minimal integrated renovation package in S1 and 160D /m2 for the more comprehensive integrated renovation in S2 and S3. If compared to equal non-energy investment merely to maintain the building (not to save energy), as in the case of roof and fac¸ade repairs which do not include additional insulation, it can be seen that the non-energy investment of 25D /m2

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159

Table 8 Assumptions made in the apartment building scenarios for the period 2011–2030.

Integrated renovation variants Renovation rate of apartment buildings (%/a) Building stock loss (demolition) (%/a)

Scenario 1 (S1)

Scenario 2 (S2)

Scenario 3 (S3)

Min 0.75 0.3

Cost optimal 1.5 0.3

Cost optimal 2.5 0.3

Table 9 Summary of economics of three scenarios. Investment costs

Scenario 1 Scenario 2 Scenario 3

Tax revenue

Jobs

Government (MD /a)

Private (MD /a)

Total (MD /a)

Direct (MD /a)

Indirect (MD /a)

Total (MD /a)

Coefficient

Direct Job (a/a)

Indirect Job (a/a)

Total Job (a/a)

3.5 20.5 47.9

19.6 61.6 89.0

23.1 82.2 136.9

6.5 23.1 38.5

1.0 3.5 5.9

7.5 26.6 44.4

2.2 1.3 0.9

234.5 833.7 1389.4

147.0 522.5 870.9

381.4 1356.2 2260.3

Energy savings (MD /a)

0.88 3.76 6.27

Table 10 Totals for the three scenarios over 20 years. Total costs are compared to corresponding non-energy investment costs having the same expenditures as integrated renovation at 90D /m2 in S1 and 160D /m2 in S2 and S3.

Scenario 1 Scenario 2 Scenario 3

Total investment (MD /20 a)

Tax revenue (MD /20 a)

Energy savings (MD /20 a)

Total cost (MD /20 a)

Non-energy investment (D /m2 )

% Of total investment

462.2 1643.3 2738.9

149.8 532.7 887.9

184 790 1317

128 320 534

25.0 31.2 31.2

28 19 19

assumed in S1 would lead to the same expenditures as integrated renovation with a cost of 90D /m2 . In the case of S2 and S3, comprehensive integrated renovation at a cost of 160D /m2 leads to an expenditure of 31.2D /m2 for non-energy renovation. Though expenditures are higher in S2 and S3, they constitute only 19% of integrated renovation costs instead of 28% in the case of S1. This study does not estimate the minimal investment in non-energy repairs that have to be carried out in any case to maintain living conditions in the building stock, as there is no real choice involved. But results show that for the same expenditure, one can opt for the living quality and asset value brought about by integrated renovation at 160D /m2 or alternatively, that brought about by non-energy repairs at 31.2D /m2 , as in scenarios S2 and S3. Thus the choice on a national level remains. Do we prefer to live in buildings that are neither healthy nor energy efficient or are we ready to invest in energy efficiency and receive significant economic and environmental benefits?

(8). A cultural difference may very well underlie this discrepancy in the figures. In Finland more time is spent on planning, design and controlling project work than in Estonia. Two more jobs on a construction site may be due to two different facts, the first, that Estonian construction sites are less automated than Finish ones, a fact which is not likely to be connected with the nature of the renovation work and two, that Estonians need additional labor to deal with daily problems caused by less planning and proper design. Second, property value effects need to be further studied to understand better how and by how much it will be increased by renovation. Thirdly, in this study, the calculation of economic benefits is considered outside the overall economic context; therefore, a future study should analyze the macroeconomic influences on GDP, as was done, for example, in the study on the Finnish building stock [15].

4. Discussion

This study considered the economic benefits of renovating apartment buildings, classified as direct when deriving from renovation projects and indirect when deriving from the related consultancy and manufacturing industry, and presented an economic analysis of Estonian renovation scenarios. The study relied on secondary data collection with validation of the data through sampling and interviews with project stakeholders. We found that in all 17 jobs per 1 MD of investment in renovation had been generated, directly and indirectly, per year. Directly, on the construction site, 10 jobs had been created. Additionally, 1 and 6 jobs had been created in the consultancy and manufacturing industries, respectively. Tax revenue from renovation construction projects was 28% but increased to 32–33% of the total renovation project cost when tax revenue from consultancy and manufacturing were included. Therefore, an economically neutral governmental renovation grant, as direct financial support, would be about 32%. However, if many indirect benefits not quantified in this study were taken into account, this figure could be increased. On an individual level, when solutions are carefully designed, there are also economic and health benefits for the owners of the buildings, as investment costs and energy savings

There are some aspects of the study that need be borne in mind when considering its results. First, the study applied a rigid research methodology to ensure the quality of input data; i.e., a triangulation method, which in practice meant that when deriving figures for job creation and tax revenue per 1 MD of investment, different sources of data were used to arrive at the same conclusions. Second, primary data came from the Estonian statistics database and the annual reports of a sampling of selected companies. Thirdly, study relied on the quality of project-related documentation. Finally, to mitigate possible problems with the data used in calculations, we were in continuous communication with project stakeholders to validate the results and clarify shortcomings in the documentation. Several observations were made that require further analysis involving a larger sample. First, the comparison of consulting services in Estonia and Finland needs to be more thorough. While three jobs per 1 MD of investment were created in consultancy in Finland as opposed to less than 1 job in Estonia, two more jobs were created on the construction site in Estonia (10) than in Finland

5. Conclusions

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after renovation balance out over 20 years. In two out of six of the projects studied, costs after renovation, including energy and monthly loan payments, with interest, and maintenance funds, were roughly equal to or lower than energy costs before renovation. The other projects showed slightly higher costs after renovation, indicating that not fully optimal technical solutions had been used and some additional non-energy related work had been included. A cost-effectiveness analysis of national renovation scenarios based on both minimal integrated and more comprehensive cost optimal renovation measures resulted in a calculation of the total cost over 20 years, including investments by the government and the private sector, tax revenue and energy savings. The main finding was that a non-energy efficiency related investment of 31D /m2 would lead to the same cost as an integrated renovation at 160D /m2 . As some investment must to be made in any case, to maintain the habitability of buildings, the results show essentially that there are two choices for a national energy policy: the country can opt for the living quality and asset value brought about by integrated renovation at 160D /m2 or alternatively, that brought about by non-energy efficiency repairs at 31D /m2 . Therefore, the choice on a national level remains, between continuing to live in buildings that are unhealthy and waste energy or investing in integrated energy renovation and enjoying significant economic and environmental benefits. The results confirm that investing in energy efficiency is not only environmentally important but provides economic benefits on an individual and government budget level. Acknowledgements The research was supported by the Estonian Research Council, with Institutional Research Funding grant IUT1–15, and with a grant from the European Union, through the European Social Fund, Mobilitas grant no. MTT74. References [1] D. Staniaszek, in: Oliver Rapf, Marine Faber, R. Ingeborg Nolte, P. Bruel, E. Fong, Lees (Eds.), A Guide to Developing Strategies for Building Energy Renovation Delivering Article—Delivering Article 4 of the Energy Efficiency Directive, Buildings Performance Institute Europe, Brussels, Belgium, 2013, p. 36. [2] E. Comission, A 2030 Framework for Climate and Energy Policies, COM(2013), Brussels, Belgium, 2013, pp. 169. [3] J. Kurnitski, K. Kuusk, T. Tark, A. Uutar, T. Kalamees, E. Pikas, Energy and investment intensity of integrated renovation and 2030 cost optimal savings, Energy and Buildings 75 (0) (2014) 51–59. [4] W. Eichhammer, T. Fleiter, B. Schlomann, S. Faberi, M. Fioretto, N. Piccioni, S. Lechtenböhmer, A. Schüring, G. Resch, Study on the energy savings potentials in EU member states, candidate countries and EEA countries, in: Final Report for the European Commission Directorate-General Energy and Transport, Fraunhofer-Institute for Systems and Innovation Research, 2009. [5] European Parliament Council, The Directive 2010/31/EU of the European Parliament and of the Council of 19 May 2010 on the energy performance of buildings, Off. J. Eur. Union 53 (2010) http://eur-lex.europa.eu/LexUriServ/ LexUriServ.do?uri=OJ:L:2010:153:0013:0035:EN:PDF [6] T. Kalamees, S. Ilomets, R. Liias, L.-M. Raado, K. Kuusk, M. Maivel, M. Ründva, P. Klõˇseiko, E. Liho, L. Paap, A. Mikola, E. Seinre, I. Lill, E. Soekov, K. Paadam, L. Ojamäe, U. Kallavus, L. Mikli, T.-A. Kõiv, Eesti eluasemefondi ehitustehniline seisukord—ajavahemikul 1990–2010 kasutusele võetud korterelamud, Tallinn Univeisty of Technology, Tallinn, 2012, pp. 252.

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