A budget for the ecological footprint of buildings is possible: A case study using the dwelling construction cost database of Andalusia

Sustainable Cities and Society 51 (2019) 101737

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A budget for the ecological footprint of buildings is possible: A case study using the dwelling construction cost database of Andalusia

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Antonio Freire-Guerrero, M. Desirée Alba-Rodríguez , Madelyn Marrero Escuela Técnica Superior de Ingeniería de Edificación, Departamento de Construcciones Arquitectónicas 2, Universidad de Sevilla, 41012 Sevilla, Spain

A R T I C LE I N FO

A B S T R A C T

Keywords: Building construction Ecological footprint Cost control Environmental assessment

Over the last decade, the ARDITEC research group has developed a methodology for the calculation of the ecological footprint of buildings throughout their life cycle. The model starts with the evaluation of the information in the budget on whether they are urbanization, construction, renovation, or demolition projects, and evaluates its impact employing databases of Life Cycle Analysis. In the present work, the methodology is adapted in order to be valid in the determination of project budgets that simultaneously calculate the economic cost and its ecological footprint. The boundaries of the problem are the ones already defined in the Andalusian construction cost databases. The database has a pyramidal structure (basic elements or units) enables either the impact of work units to be combined or the cost or impact to be determined of different stages (earthworks, foundations, structures, etc.). The present work evaluates, for the first time, all the basic elements in dwelling construction, approximately 7000 items. Finally, a case study of the urbanization and construction of dwellings in Andalusia is presented. The economic control of the budgets provides the opportunity to introduce the control of the environmental impact by using a common language already in place in the sector.

1. Introduction Recent studies evaluate the life cycle of a building and show that the emissions associated with its construction can range between 2% and 80% of the emissions of its entire useful life (Ibn-Mohammed, Greenough, Taylor, Ozawa-Meida, & Acquaye, 2013). This high variability can be due to, among other aspects, the use of the building, its location, the materials used, its life span, and the future energy supply (Sturgis & Roberts, 2010). The timing of emissions is also important; the construction of buildings generates the highest emissions of their life cycle, this moment being the milestone established as the main objective for the mitigation of climate change (Heinonen et al., 2011), whereby the construction materials are the main causes of these emissions. In this respect, Watson, Walker, Wylie, and Way (2012) show that the main barrier to adopting sustainable construction materials is their high cost and the lack of knowledge in the part of technicians and customers

regarding the existence of such materials. In order to overcome the lack of knowledge and put sustainability into practice, several systems have been developed for the evaluation of the environmental performance of buildings, such as the Leadership in Energy and Environmental Design (LEED) and the Building Research Establishment Environmental Assessment Method (BREEAM). These two systems are the most important in current use, having been evolved over many years and updated to meet market demands and needs (Almeida, Ramos, & Silva, 2018). LCA-based software tools also help in the evaluation of the built-up environment, such as Athena, Building environment assessment tool (BEAT), EcoEffect Envest 2, Environmental Load Profile (ELP), EcoQuantum, and Sustainable Building. Several other software packages (e.g. SimaPro, GaBi) are available for the calculation of environmental footprints/impacts from a life-cycle perspective (Sinha, Lennartsson, & Frostell, 2016). One problem with these packages is that they require the purchase of costly licences and involve a great deal of work to

Abbreviations: ACCD, Andalusia construction cost database; ACICS, Andalusia construction information classification system; ARDITEC, Arquitectura: Diseño y Técnica (Architecture: Design and Technique); BEAT, building environment assessment tool; BIM, building information modelling; BREEAM, building research establishment environmental assessment method; CDW, construction and demolition waste; CF, carbon footprint; CTE, Código Técnico de la Edificación (Building Technical Code); EF, ecological footprint; ELP, Environmental load profile; FAO, Food and Agriculture Organization of the United Nations; GFN, global footprint network; INE, Instituto Nacional de Estadística (National Institute of Statistics of Spain); ICYC, information classification system for construction; LEED, leadership in energy and environmental design; LCA, life cycle analysis; MSW, municipal solid waste; WBCSD, world business council for sustainable development ⁎ Corresponding author. E-mail address: [email protected] (M.D. Alba-Rodríguez). https://doi.org/10.1016/j.scs.2019.101737 Received 25 March 2019; Received in revised form 22 July 2019; Accepted 24 July 2019 Available online 08 August 2019 2210-6707/ © 2019 Elsevier Ltd. All rights reserved.

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resources, and solid waste CO2), by applying it to an exhibition centre in Wuhan (China). Solís-Guzmán (2011), in an innovative way, includes labour in the assessment by means of its energy source or food consumption. The food consumption adds cropland, pastures and productive sea footprints, in addition to that of forest. The EF methodology of SolísGuzmán has been adapted in order to measure the life cycle of buildings in Spain. This has been employed to assess the impact of the land transformation and urbanization of six industrial and residential plots (Marrero, Puerto, Rivero-Camacho, Freire-Guerrero, & Solís-Guzmán, 2017), the usage and maintenance of a college dorm (MartnezRocamora, Sols-Guzmn, & Marrero, 2016; Martínez-Rocamora, SolísGuzmán, & Marrero, 2017), and the rehabilitation and demolition of 40 homes following an excavation accident (Alba-Rodríguez, MartínezRocamora, González-Vallejo, Ferreira-Sánchez, & Marrero, 2017). The methodology has also been adapted to two different countries, Mexico (Larralde & González-Vallejo, 2015) and Chile (González-Vallejo et al., 2019). In the present research work, we start from the previous model and develop a methodology capable of determining the EF of all the elements that form part of the traditional construction cost database. A new perspective is proposed, an "environmental budget", using the tools normally employed by architects and engineers in the budgets of building projects, whereby the definition of the direct and indirect environmental costs facilitates the incorporation of ecological indicators in the construction sector. First, the construction breakdown systems are analysed, international and nationally. In second place, the construction elements, which are part of a cost database, are assessed independently and a methodology for the calculation of its specific EF is proposed. All elements in the construction budget (materials, labour and machinery) have a corresponding impact, which together give rise to the total impact of the project. For the first time, all the elements of a construction cost data base are assessed in terms of EF. The Andalusia Construction Cost Database (ACCD) and its 7000 items are analysed, that include all direct and indirect costs of construction projects. For this, a classification of construction materials in families by nature is proposed. As an illustration, a case study of dwelling construction in Spain is analysed and compared with other research results.

perform a life-cycle assessment. An international study, held in 2012 by Arup for the World Business Council for Sustainable Development (WBCSD), showed that, despite a large number of factors influencing the selection of material, the economic cost remains the priority criterion. The sustainability of the material carries less influence even if there is previous knowledge and experience on the part of the technical staff who select the project materials (ARUP, & WBCSD (World Business Council for Sustainable Development), 2012). This gives rise to new approaches, which correlate economic cost and environmental impact to project management and construction practices, through the adoption of technologies such as BIM. The bibliographic review performed by Chong, Lee, and Wang (2017) reveals that although there has been a significant amount of research and development about the use of BIM during various project phases, new BIM tools are required for the assessment of sustainability criteria. Economic tools can work in conjunction with environmental analysis methodologies but they do present challenges, which require time and research to address the different environmental, economic and social requirements (Chong et al., 2017; Tadeu, Rodrigues, Tadeu, Freire, & Simões, 2015). Construction cost databases, widely used in the construction sector, can contribute to communicate and disseminate environmental assessment. Borja et al. (2019) mapped 24 environmental indicators included in construction cost databases. In Spain, the present strategy is the inclusion of environmental impact assessment in the budget of construction projects. The Law of Contracts of the Spanish State, Law 9/2017 of November 8, states that environmental considerations should be incorporated as a positive aspect in awarding public contracts (Ley9/2017. Ministerio de la Presidencia del gobierno de España, 2017). In this regard, it is important to incorporate a simpler methodology, such as the ecological footprint (EF), that can be easily understood by society whose application is faster and more direct, since not only are the results it produces understandable by the non-academic field, but it also presents an easy application in environmental policies and decision making (SolísGuzmán & Marrero, 2015). The EF indicator (Wackernagel & Rees, 1997) assesses the amount of land that would be required to provide the resources (grain, feed, firewood, fish, and urban land) and absorb the emissions (CO2) of humanity. The EF, along with the carbon footprint (CF), have become two of the most widespread indicators thanks to the simplicity of their concept and their ability to place sustainability on the world agenda. The CF is one of the elements included in the calculation of the EF, since the last includes, among others, the land necessary to absorb the emissions (CO2). However, due to the major simplification of such an extremely complex process as that of the environmental impact on Earth caused by humans, certain flaws regarding their scientific value have been highlighted by several authors (Fiala, 2008; Grazi, van den Bergh, & Rietveld, 2007; van den Bergh & Verbruggen, 1999). Despite these imperfections, the EF is employed in various assessment systems of projects in the construction sector. Bastianoni, Galli, Pulselli, and Niccolucci (2007) calculated the EF of two Italian buildings, by primarily considering the embodied energy of materials and the construction process (the latter is estimated as 5% of the total energy of the materials). It was demonstrated that EF analysis can also be applied as an environmental-impact assessment tool of small-scale urban developments (Olgyay, 2008), high-rise districts in Tehran (Samad Pour & Faryadi, 2008); farm labourers’ homes (Zhao & Mao, 2013); eco-industrial development in industrial parks (Fan, Qiao, Xian, Xiao, & Fang, 2017); urbanization (Luo, Bai, Jing, Liu, & Xu, 2018); rural residential houses (Liu, Zhang, Ren, Gu, & Yuan, 2018); and, in Rawalpindi (Pakistan), from an urbanization perspective (Rashid et al., 2018). A group of researchers from China (Teng, Wang, Wu, & Xu, 2016) use the EF indicator for the evaluation of the current state and future trend of variation of the eco-environmental impact of green building development. Teng and Wu (2014) analysed the life-cycle of buildings (project execution, use, and demolition) and their EF (energy,

2. Construction breakdown systems 2.1. Classification of construction works One major aspect in the incorporation of environmental impacts into project budgets is that of being part of the construction work breakdown system (WBS) or classification system. All WBSs have the same goals and similar methodologies. The basic concept in all of these systems is to divide a complex problem into simpler parts that can be aggregated to define a complete construction development. The most representative include: MasterFormat (CSI/CSC, 1983), UniFormatTM. The Construction Specifications Institute (1998)), Standard Method of Measurement of Civil Engineering (Telford, 1991), CI / SfB (Jones, 1987), and Uniclass (Omniclass, 2012). The ICYC MasterFormat is a standard for the construction of design and construction projects in North America in which the titles and section numbers organize the data of the construction requirements, products, and activities. Each number and title defines a section, arranged in levels according to their coverage amplitude. Each title is composed of four levels, each delimiting a gradually more detailed area of work. Another American classification system is that of Uniformat, which organizes the preliminary construction information into a standard order or sequence based on functional elements. Functional elements, often referred to as systems or assemblies, are the main common components in most buildings that generally perform a given function, 2

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• It allows precise identification of the encoded concepts. This func-

regardless of the design specifications, construction method, or materials used. The CESMM, Standard Method of Measurement in Civil Engineering, is the British ICYC for civil engineering work. It has a work breakdown structure and measurement criteria. Letters represent the main divisions, which are the main processes that take place during a construction, such as demolition, earth movement, and concrete in situ. The European CI/SfB, which stands for Construction Index/ Samarbetskommitten for Byggnadsfragor, is for technical literature and the construction trade. This is a standard, common framework or list of items that collects information about the design, the preparation of reports, cost plans, plans, specifications, invoices of quantities and other types of information for construction. The CI/SfB is an enumerative decimal, which has been replaced by an international framework developed by the ISO technical committee for a system for the classification of information in the construction sector (ISO12006-2, 2015). This framework is applied in the Uniclass system. The ISO framework organizes construction information into eight facets, including facilities, space, elements, work sections, construction products, construction aids, management, and attributes. The scope of the ISO classification includes life cycle information, construction, and product management. In Spain, construction cost databases have their own WBS, the most representative of which are regional oriented. These include: the Institute of Construction Technology of Catalonia (ITeC, 2012), the BPCM Madrid (Ministry of Infrastructure, Territory & Environment, G. V., 2007), the BDC-IVE in Valencia (Ministry of Infrastructure, Territory & Environment, G. V., 2007), the BDEU in the Basque Country (Department of Housing, P. W. & T. of the B. G., 2012), PRECIOCENTRO of Guadalajara (Official College of Quantity Surveyors, T. A. & B. E. of G., 2012), and the ACCD in Andalusia (Marrero & Ramirez‐De‐Arellano, 2010). Efforts have been made towards unifying all the Spanish systems by the Association of Construction Data Base Redactors by means of developing a standard exchange format (FIEBDC, 2007).

• • •

tion is possible because the correspondence between each code and the element it represents is unique, which means that each code corresponds to a single concept and vice versa. It facilitates the rapid management of concepts in computer systems. It solves the location of the concepts in the budget structure. It facilitates the exchange of information.

Within this structure, the representation process needs a detailed description of each work unit that refers to a set of resources (material, machinery, or manual labour) necessary to construct an indivisible unit which is then incorporated into the construction site. This constitutes the smallest part in the classification and includes the following elements: a measurement unit, frequently used name, the elements that integrate this work unit, the corresponding construction methods, their reference norms and/or regulations, and measurement criteria (see Fig. 1, part C). The set cost-unit of work is reinforced by establishing a single meaning for each pair in a rigid manner between the measurement criteria established for a given work unit and its corresponding cost; there is therefore an understanding that, if the criteria are modified, then the cost must also be changed in turn, using common measurement criteria for similar prices. The concepts described above constitute the epigraph of a cost, resulting in that all costs have an epigraph and that this is different for each element of the system. All the above characteristics facilitate the incorporation of the environmental cost starting from the same assumptions and contours defined in the calculation of the economic cost. The indirect costs correspond to those in a housing project used as reference in the ACCD for the definition of each of its costs. 3. EF Methodology In Spain, specialized platforms such as the BEDEC cost database, SOFIAS tool, or E2CO2Cero enable the detailed calculation of CO2 emissions based on the project’s bill of quantities. The BEDEC was developed by the Institute of Construction Technology of Catalonia (ITeC), and uses environmental data of construction materials from the Ecoinvent LCA database; SOFIAS tool uses data from the OpenDAP database (SOFIAS project, 2017) and E2CO2Cero, by the Basque Government, a software that enables the embodied energy and carbon footprint of a building to be estimated in terms of the materials consumed (E2CO2cero, 2014). In the present study, the ACCD is employed to introduce the calculation of the EF by including all elements and activities present in a construction budget, and not solely its construction materials. Ecological Footprint analysis always relates the impact, generated by a certain activity in terms of consumption, to the productivity of the territory where the activity takes place (Wackernagel & Rees, 1997). The construction impact occurs at a specific moment in time, while the productivity is, in contrast, continuous. In the present analysis, the pressure is evenly distributed over the period of a year. If the construction project lasts more than a year, then the distribution is proportional to the time, for example, for work that lasts 15 months, four fifths of its impact is evenly distributed across the first year and the remaining fifth belongs to the second year. The contours of the problem are those defined by the ACCD, that is, all costs included in a budget have an associated environmental impact. The transport cost of the materials from the warehouse or factory to the worksite are included in the database, and its corresponding EF becomes from the cradle to the site. The elements that form part of the work units and the corresponding yields and quantities of resources used are thus determined in the budget (Fig. 2). The EF calculation therefore includes labour, materials and machinery: the basic elements of construction budgets. The labour energy source is food expenditure by operators, and their subsequent generation of municipal solid waste (MSW). Building materals consume

2.2. Andalusia construction cost database In particular, the present work uses the Andalusia Construction Information Classification System (ACICS) (ACCD, 2016), which is open and enjoys free access Its most extended usage is for estimating cost in dwelling construction and is mandatory in public developments in Andalusia, Spain. In ACICS, work units are divided into a hierarchic organization. Fig. 1, part A, illustrates in the top of the pyramid, the highest level is the construction site, the following divisions are chapters, each of which represents a construction process: Demolition, Earthworks, Foundation, Water disposal, Structure, Partition, Roof, Installation, Insulation, Finish, Carpentry, Glass and Polyester, Finishes, Decoration, Urbanization, Safety, and Waste Management. The subsequent divisions are the unit, auxiliary and basic costs. The ACCD is hierarchical and has an arborescent cost structure with clearly defined levels; from the top of the hierarchy down to lower levels, each group is divided into subgroups of homogeneous characteristics. Conversely, the ascent from the lower levels to the higher groups aggregates the amounts of all lower-level work units belonging to each group. This organization of work units and their components defines the resources of materials, labour and machinery necessary to complete the project. Together, these provide a stable and highly robust system (the ACCD has been widely used in Andalusia for over 30 years) that guarantees the viability of the developed model. The coding is a combination of letters and numbers, where "A" refers to alphabetic and "N" to numeric characters (ACCD, 2016), see Fig. 1 part B. The classification system specified in the code constitutes the set of all the work units of a specific project and has the following main functions: 3

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Fig. 1. A) Pyramidal cost structure with internal cost classification. B) Coding structure of the ACCD. C) Example: Unit cost 04E90002, measurement unit, short description and epigraph, and the all basic and auxiliary costs and quantities that form the unit cost.

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Fig. 2. EF methodology: A) applied to a construction cost database B) applied to the use of ACCD (adapted from Gonzlez-Vallejo et al. (2019)).

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fuel or electricity through production processes. Likewise, the machinery used in the work consumes fuel or electricity, and also has its corresponding footprint. The proposed methodology evaluates the consumptions produced on site (electricity and water consumptions). In summary, the EF calculation model (Fig. 2) determines the total footprint, which in turn consists of different partial impacts by applying the corresponding natural productivity and the factor of equivalence of each productive territory, cropland 2.51, pastures 0.46, forest 1.26, productive sea 0.37, and built-up land 2.51 gha/ha (WWF International, 2014).

Table 1 EF calculation equations (Alba-Rodríguez et al., 2017). equation Electricity. EFel: Partial Ecological Footprint of electricity consumption (gha/yr) 1 EFel = Cel·Eel ·(1 − A oc)/Af ·EQFca Cel: Electricity consumption per year (kWh/yr) Eel: Emission factor of electricity (0.000248 tCO2/kWh) (REE, 2014) Aoc: Reduction in emissions due to the CO2 absorption in oceans (0.28) (Borucke et al., 2013; GFN, 2014) Af: Absorption factor of forests (3.59 tCO2/wha) (GFN, 2014) EQFca: Equivalence factor of carbon absorption land (1.26 gha/wha) (GFN, 2014) Water consumption. EFwa: Partial Ecological Footprint of water consumption (gha/yr) 2 EFwa = Cwa·EIwa ·Eel ·(1 − A oc)/Af ·EQFca

3.1. Manpower The analysis of the impacts generated by construction workers includes the generation of MSW and food consumption. In the present methodology, unlike the previous methodology by Sols-Guzmn, Marrero, & Ramrez-de-Arellano (2013), the food and waste footprints are updated based on studies and publications of the Ministry of the Environment (Almasi & Milios, 2013; EUROSTAT, 2015; IDAE, 2011). The workers´ food intake is attributed to the EF of the building construction, since this activity takes place on the worksite and is considered as the workers´ ‘fuel’ (Domenech Quesada, 2009; GonzálezVallejo, Marrero, & Solís-Guzmán, 2015; Martínez-Rocamora et al., 2016b; Solís-Guzmán & Marrero, 2015; Solís-Guzmán, GonzálezVallejo, Martínez-Rocamora, & Marrero, 2015; Sols-Guzmn et al., 2013). The quantities consumed of each food family are obtained from the Spanish average food consumption as defined by the Food and Agriculture Organization of the United Nations (FAO) (Statistic division of the FAO, 2014), and the world-average productivities of food families are obtained from the Global Footprint Network (2014). This data is then analysed and combined (using weighted averages) in order to determine the footprint of food consumption per capita following land categories: cropland, grazing land, fishing grounds, and CO2-absorption land. According to Moreno Rojas et al. (2015), breakfast and lunch, which are assumed to occur at the construction site, represent 61% of the daily diet of an adult. The total number of labour hours worked is in the project’s bill of quantities. The EF of food consumption by labour is thereby calculated using Eq. (4) (Table 1). In 2013, the average annual MSW generated by each Spaniard was 449 kg (EUROSTAT, 2015). If a person produces MSW only while awake (16 h each day), then the quantity per hour is 0.077 kg/h. The emission factor is 0.244 t CO2 per ton of MSW, as calculated by Almasi and Milios (2013). The EF is calculated using equation 5 (Table 1).

Cwa: Water consumption per year (m3/yr) EIwa: Energy intensity of drinking water (0.44 kW h/m3) (EMASESA, 2005) Built-up land. EFbl: Partial Ecological Footprint of built-up land (gha/yr) 3 EFbl = S·EQFbl S: Total surface occupied by the building or parcel (wha) EQFbl: Equivalence factor of infrastructure land (2.51 gha/wha) (GFN, 2014) Manpower. EFfoi: Partial Ecological Footprint of food consumption in EF category i (gha/yr) EF H 4 EF = w ·0.61· i foi

Hd

365

Hw: Total number of hours worked per year (h/year) Hd: Number of hours worked per day (8 h/day) 0.61: Breakfast and lunch as a percentage of the total daily food intake of a Spanish adult (61%) EFi: Footprint of food consumption in EF category i (gha/person) 365: Days in a year EFMSW: Partial Ecological Footprint of MSW management (gha/yr) 5 EFMSW = Hw ·Gw·EMSW ·(1 − A oc)/ Af ·EQFca Hw: Total number of hours worked per year (h/yr) Gw: Hourly waste generation (0.000077 t/h) (EUROSTAT, 2015) EMSW: Emission factor of MSW (0.244 tCO2/t) (Almasi & Milios, 2013) Construction materials EFma: Partial Ecological Footprint of consumption of materials (gha/yr) EFma = ∑ (Cmai·Emai )·(1 − A oc)/Af ·EQFca

6

Cmai: Consumption of material i per year (kg/yr) Emai: Emission factor of material i (tCO2/kg) EFwo: Partial Ecological Footprint of wooden materials (gha/yr) EFwo = ∑ (Cwoi /Ywoi )·EQFfo

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Cwoi: Consumption of wooden material i per year (t or m3/yr) Ywoi: Yield of wooden material i (t or m3/wha) EQFfo: Equivalence factor of forest land (1.26 gha/wha) (GFN, 2014) EFtr: Partial Ecological Footprint of the transport of materials (gha/yr)

EFtr = ∑ (

Wmai ·Dma )·Tcon·Ef ·(1 Tcap

− A oc)/ Af ·EQFca

8

Wmai: Weight consumption of material i (t/yr) Tcap: Truck capacity (t) Dma: Average distance (km) Tcon: Truck consumption (l/100 km) Ef: Emission factor of fuel (tCO2/l) Machinery. EFmc: Partial Ecological Footprint of machinery (gha/yr) 9 EFmc = ∑ (Hmc i ·Cf i·Ef i )·(1 − A oc)/Af ·EQFca

3.2. Construction materials Each basic material of the ACCD (formed of 4900 different elements) transforms into kilograms of material in order to obtain its embodied emissions. To this end, the aforementioned identification system classifies them in its application: the first letter of the code identifies the family to which the item under analysis belongs, and the second letter is for the subfamily. By using these codes, new environmental combinations are generated for the nature of the materials, Annex A. The environmental groups more or less match the cost families except for families that do not have material basic elements, such as labour, machinery and construction equipment, waste management, and analysis, test, and trial. It is necessary to change the units from the original units of each basic cost (m3, m2, metres, tons, thousands of units, etc. which are typical units employed in the construction sector) into volume, measured in m3. The density is then used, as established in the Catalogue of Building Solutions of the Technical Building Code (CTE) and the Basic Document of Structural Safety of the Technical Building Code, both of which are official documents in Spain, DB-SE AE (RD314/2006. Ministerio de Vivienda del gobierno de España, 2006). Finally, life cycle

Hmci: Hours of use of machinery i (h/yr) Cfi: Consumption factor of machinery i (l/h or kW) Efi: Emission factor of fuel used by machinery i (tCO2/l or tCO2/kWh)

analysis databases (LCA) define the emissions contained in each kg of material. Each basic cost, on similarity, is assigned to an LCA database family, (see families and its transformations in Annex A.1 and A.2). The database chosen for use in the present work is that of Ecoinvent, implemented in SimaPro and developed by the Swiss Centre for Life-cycle Inventories (Ecoinvent Association, 2018; SimaPro, 2016) due to its transparency in the development of processes, its consistency, and references, and the fact that it merges data from several databases of the construction industry (Alejandro Martínez-Rocamora, Solís-Guzmán, & Marrero, 2016). In order to obtain the embodied CO2 emissions, the Life-cycle Inventory of the materials is analysed using the IPCC 100a 6

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In Table 2, all indirect costs, as defined in the ACCD, are transformed into EF. To this end, the electric mix in Andalusia, Spain is analysed and the corresponding energy productivity (EP) of each source is applied. Renewable sources are irrelevant in the present analysis because they have high efficiency (Martinaitis, Rogoža, & Bikmanien, 2004) as compared to fossil fuels and nuclear energy. See Table 1, equation 1. For the energy consumption of the offices and meeting rooms, an average consumption of 0.10 kW/m2 for commercial and office buildings is considered (RD842/2002. Spain MS (Ministry of Science), 2002). The total annual consumption (eight hours a day, 5 days a week and 52 weeks a year) is 208.00 kW h/m2/year. In order to determine the lighting power consumption, the area of construction site in square metres and the minimum light necessary for a safe workplace is 100 lm/m2 (RD486/1997. Spain ML (Ministry of Labor), 1997). Low-consumption lamps have an average consumption of 70 lm/W. Artificial light, based on the average daylight in southern Spain (CTE, 2006) is switched on for 4 h/day on average (2 h in the early morning and 2 h in the evenings). Finally, lighting power consumption is 1.49 kW h/m2. The building start-up tests (A/C, heating, power supply, lighting, elevators, etc.) have a power consumption that is estimated using the electricity bills of 30 different construction sites. The power consumption, during the testing of the facilities at the end of the project, is 1.11 kW h per m2 of the construction area (Marrero, Freire Guerrero, Solís-Guzmán, & Rivero-Camacho, 2014). The EF of water consumption is due to the energy necessary to bring it to the point of consumption, including previous and subsequent treatment. This energy intensity (EI) is obtained from the supply company (EMASESA, 2005), and is assumed to be electric energy (Eq. (2). Table 1). The area used by the urbanization and the building under study produces a direct footprint on the environment, which corresponds to the area of the plot. This land is assumed to be appropriate for agricultural purposes (Borucke et al., 2013; Wackernagel & Rees, 1997). Therefore, the same equivalence factor of cropland transforms the builtup surface into EF terms (Eq. (3). Table 1).

methodology (IPCC, 2006). Annex B.1 shows one example of each of the families of the ACCD that include construction materials, and consider their processes or transformations (formation of tubes, formation of metal sheets, etc.). The families are: aggregate and stone (A); concrete and steel for structures (C); decoration and equipment (D); masonry (F); binders and mortars (G); safety and health (H); installations (I); carpentry (K); paints (P); roofs (Q); coatings and finishes (R); sanitation (S); urbanization (U); glass and synthetics (V); others (W); and insulation (X). In the case of installations, eight examples are included due to its high variability. The CO2 emissions of each material generate an EF, calculated using Eq. (6) of Table 1. In the particular case of wooden materials, the EF calculation not only includes CO2-absorption land but also wood productivity, according to its typology and the forest equivalence factor (Alejandro Martínez-Rocamora et al., 2016b) (Eq. (7) of Table 1). World-average productivities of the various wooden materials (GFN, 2014) are: general wood and plywood 1.82 m3/wha, particle board 1.28 m3/wha; medium/high-density fibre or particle boards and cork insulating boards are 0.98 m3/wha; and wood pulp and printing paper are 0.38–0.75 t/wha. The EF of transport of manufactured materials is determined for average distances travelled in Andalusia, along with the consumption and emission factors (Alba-Rodríguez et al., 2017). For the EF calculation, Eq. (8) (Table 1) is used. The maximum load per vehicle considered is 24 tons, with an average distance from the factory to the construction site (back and forth) of 100 km. The consumption of diesel during the transport of material is 26.0 l/100 km, while for machine operation this figure is 0.15-0.20 l/h (Moya de los Reyes, 2013). The petrol machinery consumes 0.30-0.40 l/h. The emission factors are for diesel and petrol at 0.0026 and 0.0022 t CO2/l, respectively. The transport impact takes into consideration the average distances travelled for each family of materials (Freire & Marrero, 2014). The families of materials with the highest basic impacts correspond to complex construction products, such as elevators, air-conditioning units, water-heating units, storage rooms, and fences. These products have the highest EF, as expected, due mainly to their volume and material composition: mainly metallic materials, see Annex B.2. Only bricks fail to match this description; this is since the basic unit is formed by one thousand bricks in a pallet.

4. Case study A total of 107 multi-family dwellings, parking lots, storerooms and commercial premises in La Palma del Condado (Huelva), which correspond to a previously analysed project by Solís-Guzmán (2011), is assessed with this new methodology proposed. The project is representative of the most common dwelling type in Spain (GonzálezVallejo, Solís-Guzmán, Llácer, & Marrero, 2015; Mercader-Moyano, 2010; del Mercader, Marrero, Solís, Montes, & Ramírez, 2010), which corresponds to 4-storey blocks of flats with commercial premises at ground level. The housing development takes place in two independent plots, whose lot sizes are 1,484.80 m2 and 1,320.08 m2. The floor areas are 8,510.70 and 7,504.22 m2, respectively. The distribution of each of the dwellings is that of a living room, kitchen, two bedrooms, and a reception hall. The floor area is 88.81 m2 per dwelling in block 1 (57 dwellings) and 89.24 m2 in block 2 (50 dwellings). The only activity taken place on the land is that of the project construction. This impact lasts one year; the time needed for the construction to be completed. The total basic costs employed in the budget are 342, of which 22 are labour, 11 machinery, and 309 of material type.

3.3. Machinery The EF of machinery corresponds to its consumption of electricity or fuel. Technical data on the engine power of different models and types of machines on the market have been collected (Freire & Marrero, 2014; Solís-Guzmán & Marrero, 2015). Consumption and emission factors of diesel and petrol engines are combined to calculate the impact of machinery, as presented in Eq. (9) (Table 1) (IDAE, 2011). On the other hand, for electric machinery, its power consumption is as per technical data. This consumption, combined with the hours of utilization, determines its EF through Eq. (1) (Table 1). The emission factor corresponding to the electric mix in Spain (REE, 2014), as well as a reduction of 28% in the emissions due to the carbon uptake in oceans (Borucke et al., 2013; GFN, 2014) are included in the calculations of the EF of electricity consumption (Eq. (1), Table 1). 3.4. Indirect cost Indirect costs associated with any business are normally neglected in the EF assessment. This oversight can be overcome by grouping together all indirect activities that take place on the construction site into the previously defined categories, manpower (food and mobility), machinery (fuel and electricity), and/or construction materials (embodied energy). Subsequently, by following the same methodology as that applied to the direct costs, the corresponding calculation procedure can be applied (Freire Guerrero & Marrero, 2015).

4.1. Machinery The EF due to all the machinery in the urbanization work and in the construction is summarized in Annex C.1, where the EF is due to fuel consumption. The urbanization and construction machinery generates 356.43 gha of fossil footprint, compared to that of previous work, of 7

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Table 2 Indirect costs in the ACCD (m2 corresponds to the plot size except where rooms in m2 are defined). ACCD CODE

CONCEPT

SPECIFIC CALCULATION

C12 C121 C1211 C1212 C1213 C1214 C122 C1221 C12211 C12212 C12213 C1223 C12231 C122311 C122313 C122314 C122315 C12232 C12233 C123 C1231 C12311 C12312 C12313 C12321 C12322 C12323 C12324 C1233 C124 C1241 C12411 C12412 C12413 C1242 C125 C1251 C12511 C1253 C12531 C12532 C12533

EXECUTION OF WORK Special workers Construction site manager Group leaders Store-room keeper Security AUXILARY WORK Auxiliary personnel Interior transport Cleaning Machine and utensil internal transport Machines. utensils and tools Elevation equipment Tower crane Telescopic platform Lifting platform Lift Concrete mixer Machine shop of steel reinforcement COMPLEMENTARY INTALLATIONS Worksite Offices Meeting rooms Storage rooms Provisional power connection to the grid Provisional water and sewers Power grid Water installations Road signalling and stacking PERSONAL Technicians Work site manager Production manager Auxiliary technicians Secretary. administration personnel OTHERS Offices Paper work in offices Others Lighting Testing facilities (a7C. heating. cooling) Plot size

Labour h/month 127.08 127.08 127.08 127.08 Labour h/m2 0.02 0.05 0.04 Labour h/month 127.08 101.67 101.67 101.67 101.67 101.67 Labour h/u

gha/u

0.031 0.031 0.031 0.031

6.00E-06 1.10E-05 1.00E-05 Power kWh/month 1.525.00

Fuel l/month 1830.00

305.00 305.00 149.45 162.67 Power kWh/m2 208.00 208.00 208.00

Water m3 water/ m2 room 0.16 0.16 0.16

32.82 6.56 21.88 4.38 18.98 Labour h/month 127.08 127.08 127.08 127.08

0.126 0.025 0.044 0.044 0.034 0.035

0.013 0.013 0.013 0.008 0.002 0.005 0.001 0.005

0.031 0.031 0.031 0.031 Power kWh/m2 None 1.49 1.11

Occupation ha 1.00E-04

1.00E-04 1.00E-04 3.00E-04

a machine has an equivalent hour of labour.

211.86 gha (Sols-Guzmn, 2011). This is 68% higher mainly due to CDW management, which is now included in the analysis since it forms part of the budget as established in the Spanish norm (RD105/2008, 2008). This helps to include waste management machinery into the strategies for the reduction of the project footprint (Marrero et al., 2017). During the urbanization, the trucks that transport the excavated soil constitute the elements of the highest impact.

4.4. Indirect costs All indirect costs per ACCD, have an EF as previously described in Table 2. The urbanization and construction budget EFs are 3.977 and 8.306 hag, respectively. The indirect costs only represent 1% of the total impact in the urbanization and construction even though economically they represent 13% according to the ACCD.

4.2. Materials The project budget has 309 basic costs of construction materials, which are divided into 100 urbanization and 242 construction materials. Ten urbanization materials (10 basic costs) control 91% of the total material EF. Among these, the most influential are asphalt and concrete (see Annex C.2). In construction, ten materials control 71% of the total EF of materials; the most impacting materials are concrete, steel, mortar, and bricks.

4.5. Total footprint In Fig. 3, the budget chapters Structure, Foundation and Finishes, have the highest environmental impacts; the latter two, however, economically, are replaced by Insulation and Installations. Structures have the highest EF due to the high volume of concrete and steel consumed. The same happens with Foundations. Insulation has a high cost due to its expensive material and labour but little total weight in the project and corresponding EF. Table 3 shows the total footprints of the urbanization and construction phase. In this type of project, the impact from the machinery is greater in urbanization work than in construction where materials control the EF. The labour contribution is less than 3% in both cases. This matches the results in new construction evaluated by (Sols-Guzmn et al., 2015), even though in other types of construction projects, such

4.3. Labour The labour EF is 39.00 gha, 38% in urbanization and 62% in construction work, see Annex C.3. In previous studies, machinery operators were not included in the analysis. However, in the present methodology, which is based on the project budget, machine rental costs include their operators, who also leave a footprint; each working hour of 8

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Fig. 3. EF per chapter in the ACCD.

determined separately. The new calculations and methodology reduce the EF related to indirect costs by 97%. The huge difference is due to the polynomial formulas (RD1359/2011. Ministerio de Economía y Hacienda del Gobierno de España, 2011) in the original methodology overestimating the on-site power consumption by a factor of 10 when compared to the empirical data collected (Freire-Guerrero & MarreroMeléndez, 2015). The indirect cost calculation proposed in the present work is therefore a better approximation. A new calculation of the food consumed by workers is now employed which uses macroeconomic data instead of a generic food menu (González-Vallejo, Muñoz-Sanguinetti, & Marrero, 2019). This generates a significantly smaller food consumption and impact. Another difference in the new methodology is the direct imputation of machinery CO2, which depends on the engine power and not on its rental cost. The machinery necessary for the waste management is also directly calculated, which was not included in the original model. It is also possible to perform the analysis by substituting the

as maintenance, workers exert a major impact of over 60% (MartnezRocamora et al., 2017). Of the EF of the urbanization and construction projects, the most important sources of impact are those of machinery (61%) and materials (96%), in urbanization and construction, respectively. The EF produced by construction work is 0.228 gha/m2 floor area and the EF produced by urbanization is 0.053 gha/m2. The results can be compared to previous investigations where the EF produced by the rehabilitation phase of a building is 0.060 gha/m2 (Alba-Rodríguez, 2016). The use and maintenance phase is 0.007 gha/m2per year of the life of the building (Martnez-Rocamora, 2016). In this way, the EF of the life cycle of the building can be attained. In previous studies by the research group (Sols-Guzmn, 2011), the total EF is 12,283 gha and is distributed in 3977 gha in urbanization and 8306 gha in construction. That EF is 62% higher than in the new methodology. This is mainly due to the inclusion of the food and power consumption calculations. Indirect costs in previous studies (Sols-Guzmn, 2011) were not Table 3 Total EF. Impact Materials Machinery Manpower Indirect costs Total URBANIZATION TOTAL EF Materials Machinery Manpower Indirect costs Total CONSTRUCTION TOTAL EF

Fossil 179.621 310.258 1.683 0.850 492.412

Grazing land

Forests

Productive sea

0.136 1.439 0.086 1.661

0.013 0.136 0.008 0.157

0.358 3.783 0.227 4.369

Crops

Occupied directly

0.612 6.467 0.389 7.468

2.416 2.416

0.411 11.196 1.452 13.059

0.704 0.704

508.483 gha 2,090.708 45.216 2.913 4.947 2,143.784

0.091 2.490 0.323 2.904

0.009 0.235 0.031 0.275

9

0.240 6.549 0.849 7.638 2,168.366 gha

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Table 4 Work units of the original project and less impacting substitution. Code (Units measured in m2) 03ERT80060 05HRL80010 QW00700 10SCS00001

EF (gha/ m2) Metallic formwork Concrete slab Polystyrene panels Ceramic tile

Code (Units measured in m2)

0.0032 0.0497 0.048 0.0111

03ERM80070 05FUA00005 XT80010 10SMS00001

EF (gha/ m2) Wood formwork Waffle slab Mineral wool panels Wood floor

−0.0193 0.0292 0.025 −0.0065

Fig. 4. The EF reduction in in each budget chapter.

gha, respectively. The structural concrete with recycled aggregates substitutes 20% of the original concrete; this represents a high increase in the total cost of the project of 10%, as can be consulted in Catalonia’s cost data base (“TeC BEDEC”, 2019). These two proposals, alternative constructive solutions and recycled/reused material, can be combined. The total EF is reduced by 22% and the budget increases by 15% (see the third column in Fig. 4. A higher reduction is possible by improving the construction and demolition waste management, whereby reusing the excavated soil can reduce the footprint of this chapter by up to 50% (Marrero et al., 2017).

constructive solutions, or unit costs, with other traditional construction units already available in the ACCD. To this end, the budget chapters with high impact (Foundation, Structures, Rooftops and Finishes) are modified by employing alternative traditional solutions with a lower EF (see Table 4, where the original work units are found on the right-hand side, and their main impacting material of a less aggressive solution is found on the left-hand side. The new figures correspond to the formwork made of wood instead of steel for the foundation, a waffle slab of ceramic material substitutes the concrete slab, mineral wool replaces polystyrene insulation, and the ceramic flooring is now of wooden material. In Fig. 4, the EF is consequently lowered in each chapter. The total reduction of the EF is 18% and the total cost increases by 7%. Other more innovative solutions are proposed in the project and their impacts are analysed. The defined methodology can easily detect the effect of the replacement of the three main impacting materials in the project, such as steel, concrete and bricks, with 100% recycled/ reused materials. In Spain, regulation has been in place since 2008 in order to substitute reinforced concrete aggregate with recycled materials. Their market availability remains low, however, since only 8% is being recycled in building construction, even though 70% of aggregates are recycled in other applications, such as quarry refill as reported by the National Institute of Statistics (Instituto Nacional de Estadística (INE, 2012)). This low usage is mainly due to the lengthy authorisation procedures in the town halls for the acceptance of recycled aggregates in construction projects, and the difficulties in obtaining material with good quality control that meet the required norms (EHE-08, 2008). Since steel has high recycling rates in Spain, it will be possible to use 100% recycled material in the near future (UNESID. Unión de Empresas Siderúrgicas, 2013). Finally, the reutilization of recycled bricks is not common in this country other than for decorative purposes. The use of masonry bricks is regulated in Spain but the European Union is working on a common regulatory framework to improve its re-use (UNE-EN771-1, 2003). The EF with these innovative materials, not commonly used in Spain, is reduced by 3% during the urbanization and 10% in the construction, and the new total EFs become 495.643 gha and 1,959.835

5. Conclusions The incorporation of an environmental indicator, such as the ecological footprint, within the cost structure and the budgeting of construction projects (both construction and urbanization) is certainly possible. The environmental and economic aspects can be simultaneously assessed. The EF indicator has been adapted to the systematic classification system of the construction cost databases. This has been made possible through the evaluation in Spain of the Andalusian Construction Cost Database (ACCD), whereby its cost boundaries are employed for ecological assessment. 5.1. EF inclusion in the construction cost database Within the analysis of the elements that form the ACCD, the methodology allows the conversion of each of the construction elements, which are part of the budget, into quantities that translate into the EF. To this end, 4900 basic construction elements have been analysed in detail. The elements are assessed differently according to their nature (labour, materials, or machinery) and their type of imputation (direct or indirect cost). In general, the current classification system enables any professional in the sector to rapidly comprehend its organisation, and develop a detailed economic and environmental budget. The EF allows the analysis from cradle to site of all economic costs, such 10

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as that of the workforce by means of its energy source (food intake), machinery by its energy sources, and materials by their CO2 emissions. The analysis of a project identifies the elements with the highest impact. In the case of construction, these materials are asphalt or a bituminous mixture, and concrete and steel elements; regarding waste treatment, these elements are the machinery that manages the treatment process. I In this way, it is possible to ascertain the elements upon which it is necessary to act and control, in order to achieve an improvement in the environmental aspect of the projects. Therefore, the EF indicator is sensitive to the decisions made during all phases of project preparation (construction materials, size of plot, characteristics of areas for buildings when urbanizing, transportation distance to the site, management of waste on site, etc.). The present methodology can easily be applied by public administration, since the model developed is easy to adapt to the established construction cost classification systems. In particular, the ACCD could provide a differentiating element in the decision-making of the administration, as for example in public project adjudication or in fiscal aspects of urban planning and property tax rebates.

WBCSD_Material choice for green buildings_201201 (Jan).pdf. Bastianoni, S., Galli, A., Pulselli, R. M., & Niccolucci, V. (2007). Evaluación ambiental y económica de la apropiación del capital natural a través de la construcción: Estudio de caso práctico en el contexto italiano. Ambio. https://doi.org/10.2307/25547812 SpringerReal Academia Sueca de Ciencias. Borja, L., César, S., Cunha, R., Kiperstok, A., Borja, L. C. A., César, S. F., ... Kiperstok, A. (2019). Getting environmental information from construction cost databases: Applications in Brazilian courses and environmental assessment. Sustainability, 11(1), 187. https://doi.org/10.3390/su11010187. Borucke, M., Moore, D., Cranston, G., Gracey, K., Iha, K., Larson, J., ... Galli, A. (2013). Accounting for demand and supply of the biosphere’s regenerative capacity: The National Footprint Accounts’ underlying methodology and framework. Ecological Indicators, 24, 518–533. https://doi.org/10.1016/j.ecolind.2012.08.005. 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Retrieved February 13, 2019, fromhttp://online.e2co2cero.com/. Ecoinvent Association (2018). Ecoinvent database v3. Retrieved February 22, 2018, from http://www.ecoinvent.org/database/ database.html. EHE-08 (2008). Instrucción de Hormigón Estructural EHE-08 serie normativas 2011 GOBIERNO DE ESPAÑA MINISTERIO DE FOMENTO SECRETARÍA GENERAL TÉCNICA. Retrieved fromhttp://www.ponderosa.es/docs/Norma-EHE-08.pdf. EMASESA (2005). Sostenibilidad y gestión. Así éramos, así somos. 1975-2005 / Sustainability and management. How we were, how we are.1975–2005. EUROSTAT (2015). Municipal waste generated by country in selected years (kg per capita). Retrieved June 8, 2015, fromhttp://ec.europa.eu/eurostat/statistics-explained/ index.php/File:Municipal_waste_generated_by_country_in_selected_years_%28kg_per_ capita%29_new.png. Fan, Y., Qiao, Q., Xian, C., Xiao, Y., & Fang, L. (2017). A modified ecological footprint method to evaluate environmental impacts of industrial parks. 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Habitat Sustentable, 5(1), 54–63. GFN (2014). Learning package of national footprint accounts 2014 edition. Global footprint network. Global Footprint Network (2014). National footprint accounts workbook learning license. González-Vallejo, P., Marrero, M., & Solís-Guzmán, J. (2015). The ecological footprint of dwelling construction in Spain. Ecological Indicators, 52, 75–84. https://doi.org/10. 1016/j.ecolind.2014.11.016. González-Vallejo, P., Muñoz-Sanguinetti, C., & Marrero, M. (2019). Environmental and economic assessment of dwelling construction in Spain and Chile. A comparative analysis of two representative case studies. Journal of Cleaner Production, 208, 621–635. https://doi.org/10.1016/j.jclepro.2018.10.063. González-Vallejo, P., Solís-Guzmán, J., Llácer, R., & Marrero, M. (2015). La construcción de edificios residenciales en España en el período 2007-2010 y su impacto según el indicador Huella Ecológica. Informes de La Construcción, 67(539), e111. https://doi. org/10.3989/ic.14.017. Grazi, F., van den Bergh, J. C. J. M., & Rietveld, P. (2007). Spatial welfare economics versus ecological footprint: Modeling agglomeration, externalities and trade. Environmental and Resource Economics, 38(1), 135–153. https://doi.org/10.1007/ s10640-006-9067-2. Heinonen, J., Säynäjoki, A., Junnila, S., Heinonen, J., Säynäjoki, A., & Junnila, S. (2011). A longitudinal study on the carbon emissions of a new residential development. Sustainability, 3(8), 1170–1189. https://doi.org/10.3390/su3081170. Ibn-Mohammed, T., Greenough, R., Taylor, S., Ozawa-Meida, L., & Acquaye, A. (2013). Operational vs. embodied emissions in buildings—A review of current trends. Energy and Buildings, 66, 232–245. https://doi.org/10.1016/J.ENBUILD.2013.07.026. IDAE (2011). Factores de emisión de CO2 / CO2 emission factors. IPCC (2006). 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5.2. Future research Future lines of research identified include: 1 An application of the model to a representative set of projects that allows the extrapolation of these results at national level. 2 The development of an EF calculation model for the complete life cycle of buildings starting from project budgets. 3 The integration of the EF calculation in Building Information Modelling (BIM) tools. 4 The complementation of the model with other environmental indicators, such as the water footprint and the carbon footprint. 5 The incorporation of the EF into the environmental certification systems of projects such as BREAM and LEED. 6 The direct integration of the calculation of the EF into budgets, through its incorporation into the exchange format of construction cost databases. Acknowledgements The research is developed as part of the project “Study of the ecological footprint of the transformation of land use”, financed by the MAPFRE Foundation with the Research Grants "Ignacio H. de Larramendi" (Project Type: MAPFRE Ref: BIL/13/MA/048). Appendix A. Supplementary data Supplementary material related to this article can be found, in the online version, at doi:https://doi.org/10.1016/j.scs.2019.101737. References ACCD (2016). Andalusia construction cost database. Retrieved from https://www. juntadeandalucia.es/organismos/fomentoyvivienda/areas/vivienda-rehabilitacion/ planes-instrumentos/paginas/bcca-sept-2017.html. Alba-Rodríguez, M. D. (2016). Model for evaluating the economic and environmental viability of building recovery. Spain: University of Seville PhD Thesis, Retrieved from https:// idus.us.es/xmlui/bitstream/handle/11441/44469/VEARE Acceso cerrado.pdf?sequence=1. Alba-Rodríguez, M. D., Martínez-Rocamora, A., González-Vallejo, P., Ferreira-Sánchez, A., & Marrero, M. (2017). Building rehabilitation versus demolition and new construction: Economic and environmental assessment. Environmental Impact Assessment Review, 66, 115–126. https://doi.org/10.1016/j.eiar.2017.06.002. Almasi, A. M., & Milios, L. (2013). Municipal waste management in Spain. Technical report. European Environment Agency. Almeida, C. P., Ramos, A. F., & Silva, J. M. (2018). Sustainability assessment of building rehabilitation actions in old urban centres. Sustainable Cities and Society, 36, 378–385. https://doi.org/10.1016/J.SCS.2017.10.014. ARUP, & WBCSD (World Business Council for Sustainable Development) (2012). Material choice for green buildings. Retrieved from https://www.wbcsdcement.org/pdf/

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