1. Introduction
Approximately 60% of the existing building stock in the European Union was built during the period from the 1960s to the 1980s. This percentage rises to 70–75% in Mediterranean countries, such as Greece, Spain, and Portugal [
1]. Furthermore, the current stock of buildings is expected to increase at a rate of 1% per year due to new construction [
2], but building renovations will increase at a rate of 2–3% by 2020 [
3]. Therefore, building renovations will become a key factor in the future of the European building sector and must be included in strategies to reduce their environmental impact and to reach the global objectives of climate change mitigation.
In the particular case of dwellings in Spain, interventions in existing buildings are not only due to their precarious state but as a reactivating agent of the construction sector, thereby promoting integrated regeneration and energy efficiency in Law 8/2013, of June 26, for rehabilitation, regeneration, and urban renewal [
4]. This normative framework includes urbanistic criteria and sustainability of built heritage, and, as is the case in most European countries, renovations are no longer considered a minor activity with respect to the construction of new buildings [
5].
For the correct analysis of this type of intervention, it is necessary to first clarify the term renovation. According to Vilches et al. [
6], the terms refurbishment, renovation, retrofitting, repair, and restoration can all be used interchangeably. The European Commission uses “Holistic and Deep Renovation” in the 2014–2015 Work Program for Horizon 20/20 [
3] regarding building operations, which considers both a significant energy reduction and district energy systems. The Building Research Establishment [
7] defines a major refurbishment project as an activity that results in the provision, extension, or alteration of thermal components or building services and fittings.
In rehabilitation projects, seriously damaged buildings are assessed. Almeida et al. [
8] studied various sustainability evaluation systems and a model was cross-checked with current European and national urban rehabilitation in order to define a simplified method for the sustainability assessment for rehabilitation in old urban centers. Erlandsson et al. [
9] compared the environmental impact of rebuilding and new construction by conducting an LCA of a multi-dwelling building built in 1966 in Sweden. In the case of single-family dwellings, Gaspar et al. [
10] compared the impact associated with total demolition to a refurbishment scenario of an old detached house in Portugal.
In addition to the environmental evaluation, economic aspects are also key factors of the assessment, and tend to tip the balance towards actions of building renovation rather than demolition and new construction. This is due to the increasing value of the building and the quality of its constructive elements [
11,
12,
13]. Other evaluation methods of renovation projects analyzed an economically optimal combination of energy-saving measures, and concluded that the decision for renovation rather than demolition is influenced by the investment cost and the market value of the buildings [
14].
Recent studies have shown a methodological framework for conducting an economic cost–benefit analysis in the Energy Efficiency Retrofit (EER) of existing buildings, based on the calculation of costs and benefits over their life cycle [
15]. Through cost curves of investments, Toleikyte et al. [
16] analyzed potential energy savings for the building sector by implementing energy efficiency solutions. Final energy demand can be reduced by 56% by the year 2030 if the lowest-cost energy efficiency solutions are implemented. At the neighborhood level, the economic benefit is also higher than that of individual buildings; however, there are positive indications that individual property values may be enhanced in the future [
17].
The geographical consideration also constitutes an important aspect that can be addressed simultaneously. The use of geographical information systems (GIS) makes it possible to relate the use of geo-information and governance, and several studies affirm that these initiatives promote accountability, transparency, legitimacy, and other dimensions of governance [
18]. Several groups of researchers have developed hybrid models that combine the application of GIS and multi-criteria decision analysis, and they conclude that their models can be used in their decision-making processes for sustainable and resilient policy planning at all government levels [
19,
20]. Other authors suggest that GIS can be employed to improve land use, urban planning and renewal, and housing policy [
21].
In the HEREVEA project (Huella Ecológica de la Rehabilitacion de Viviendas en Andalucia or Ecological Footprint of the Renovation of Dwellings in Andalusia), georeferencing has been used together with ecological footprint (EF) analysis instead of LCA methodology. The EF indicator [
22] assesses the amount of land that would be required to provide the resources (grain, feed, firewood, fish, and urban land) and absorb the emissions (CO
2) of humanity. The EF, along with the CF, have become two of the most widespread indicators thanks to the simplicity of their concept. The EF has been employed for construction projects [
23,
24,
25,
26,
27].
The EF methodology by Solís-Guzmán et al. [
28] has been adapted in order to measure the whole life cycle of the building: urbanization [
29], use [
30], maintenance [
31], and the rehabilitation or demolition [
32].
In the particular case of housing renovation, the HEREVEA project [
33] takes advantage of the model by Alba-Rodríguez et al. [
32] to adapt it to fit other buildings. Their model, also called HEREVEA, starts from the constructive description of the renovation project, its budget, and its bill of quantities. Emission or embodied energy factors are then applied to those quantities, which are subsequently converted into environmental impacts. The HEREVEA model is applied for the first time to evaluate the impact of the renovation of actual buildings in Seville, Spain. The EF assessment of construction projects developed by the authors in previous works is adapted to fit renovation projects for the first time, and is based on other research carried out for the assessment of rehabilitation or reconstruction of a building following a major accident. In the latter case, the building was seriously damaged and needed such major reconstruction and repair that it could not be considered a mere renovation; demolition was also considered. In the present work, the methodology is employed for small projects, many of which have insufficient entity to be considered a construction project by itself, but, instead, maintenance and repair work. The Andalusian Construction Cost Database [
34] (ACCD) is used for the cost assessment, and new renovation costs, which are not included in the database, are created based on the work breakdown system of ACCD. First, 50 buildings are studied in order to statistically normalize the EF and cost. Secondly, five specific cases are studied in depth. This model not only enables the most important pathologies to be analyzed in terms of costs and EF, but it also determines the elements that control the impacts in each project. A comparison with the results of previous studies means that the influence of the building materials that control these impacts can be analyzed [
35,
36,
37]. The impacts are visualized simultaneously by combining the economic and environmental impact graphically. The HEREVEA tool has been integrated into a GIS in order to generate georeferenced results. Even in these small projects, the methodology has proved itself to be effective in detecting the level of environmental impact and allows comparisons to be made between various renovation projects.
3. Results and Discussion
The HEREVEA tool analyzed 50 dwellings located within the same urban area whose state of conservation is susceptible to submission for renovation.
Figure 8 shows a sample of 27 plots out of 50 cases analyzed (number of the colored plot). Each dwelling analyzed is identified in red, yellow, or green. The color represents how the value of the sum of the two normalized indicators (
N_costi + N_EFi) is positioned with respect to the complete sample of 50 cases (for which the distribution of the two populations is similar). The percentile has been used because it relates each value to the sample by providing a measure of the group and the values within the group, whereby percentile 0 represents the lowest value of the sample, and 100 the highest.
Pi is the
i–th percentile, where
i takes values from 1 to 100. Of the sample values,
i% are lower than
Pi and the remaining (100 −
i)% are greater. In this way, a scale is set: those above or equal to
P67 (red plots), above or equal to
P33 (yellow plots), and below
P33 (green plots) are shown in
Figure 8. Therefore, in the aerial view of the sample, plots are colored with respect to the corresponding sum of normalized economic and environmental indicators. For each plot, the graphical representation of the data also includes the information referring to the comparison of
N_costi and
N_EFi in a bar chart, blue for cost, and green for the
EF, whereby the green column of plot 50 is equal to one standard deviation.
In order to represent the significance of the normalized economic and environmental variables, the five projects from
Figure 6 and
Figure 7 are summarized in
Table 5. It is noteworthy that the environmental aspect is as significant as the economic impact. Only the environmental impact of project 2 is above the average. This indicates that all projects evaluated are not seriously damaged with respect to the population; all are close to the average values.
A more in-depth analysis can be performed on the five projects.
Table 6 shows the quantification of the basic resources (kgs of materials and working hours) contained in the complex units. The materials selected are the most representative in the renovation activities carried out.
Figure 9 shows the relative contribution of the main building materials to the CO
2 emissions per square meter of built area. Constructively, similar buildings, such as those in Spain [
35] and Portugal [
36], are compared with other constructions in Korea [
37]. The high impact of commonly used materials, such as steel, cement, and ceramics, is worth noting. This verifies the coherence of the order of magnitude of the results obtained with the model.
In
Figure 10, the results of the five projects are compared economically and environmentally per chapter. In Project 5, the EF of the foundations chapter is highlighted; this is due to the high material consumption (cement slurry injected to improve the poor carrying capacity of the soil) during the underpinning process. However, comparatively, the economic impact is not of major importance in the same chapter.
Project 2 stands out since it presents the greatest economic impact in the installations chapter, also with a high environmental impact in this chapter. This is due to the replacement of obsolete elements. Nevertheless, the roof repair work in this project generates the highest environmental impact (
Figure 10).
One last comparison, as shown in
Figure 11, is given between the EF generated by energy consumption during the use phase of the building (for a period of 25 years) and the EF generated by the renovation work. For the energy simulation, the CE3 software has been employed [
61]. CE3 is the free and official calculation software used in Spain for the energy certification of existing buildings. Its levels of accuracy and detail have been contrasted in tests which are publicly accessed. Similar to rest of the software available in Spain, CE3 evaluates the following aspects for dwellings: heating, air-conditioning, and domestic hot water. Other aspects of energy consumption are not assessed.
Upon analyzing the results in
Figure 11, it can be observed that projects 1 and 2, where insulation has been incorporated into the roof, the total
EF (use + renovation) is much smaller than the
EF of energy consumption of the use phase in its initial state; the energy retrofitting appreciably reduces the
EF of the use phase. However, in the other three projects, this measure has not been incorporated. In project 3 the balance between initial and renovated state is practically null from the point of view of
EF energy. In projects 4 and 5, where the renovation does not suppose an appreciable decrease of the energy consumption, it is more profitable from the environmental point of view to maintain the initial state of the building.
Therefore, it can be concluded that the renovation will be environmentally profitable when a major energy retrofitting is carried out.
4. Conclusions
The HEREVEA model, through geographical information that correlates the economic and environmental variables, analyses the renovation intervention from a holistic perspective (technical, economic, and environmental analysis). The model takes into account the importance that these variables bear in the decision process by normalizing their values for the corresponding population, cost, and EF. The new model, a free and open-access computer tool in GIS, facilitates the assessment of buildings of priority action in the city and integrates, in an intuitive way, the environmental variable, which becomes a key in this decision-making process in terms of reducing environmental impact.
From the disaggregated economic and environmental comparison, it is clear which chapters are the most relevant—in the case of large-scale interventions where the building has load-bearing deficiencies and structural affection, the foundations and masonry chapter stand out due to the need to repair cracks and fissures. The environmental impact is mainly due to the embodied energy of the materials incorporated in the renovation process. In smaller interventions, the masonry and roof sections stand out in a more homogeneous manner, whereby their environmental impact is higher than their economic impact, while in the installations chapter the economic impact is greater than the environmental impact, due to the high cost of the systems and components. From these results it can be concluded that the model is sensitive to changes in construction solutions and the severity of pathologies or level of damage.
In future work, the EF can be combined with other indicators, such as the water footprint in the life cycle of buildings, by taking into account all the aspects that can be assessed in a simplified way from the perspective of the budget and systematic work breakdown classification. The long-term objective involves the creation of a differentiating and open economic and environmental indicator that enables all impacts throughout the life cycle of the building to be predicted during the design stage of buildings.