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

Depósito de investigación de la Universidad de Sevilla https://idus.us.es/ Esta es la versión aceptada del artículo publicado en: This is an accepted manuscript of a paper published in: Sustanaible Cities and Society (2019): 20/1/2025 DOI: https://doi.org/10.1016/j.scs.2019.101737 Copyright: El acceso a la versión publicada del artículo puede requerir la suscripción de la revista. Access to the published version may require subscription. “This is an Accepted Manuscript of an article published by Elsevier in Sustanaible Cities and Society on 2019, available at: https://doi.org/10.1016/j.scs.2019.101737.” A budget for the ecological footprint of buildings is possible: a case study using the dwelling construction cost database of Andalusia. Antonio Freire-Guerrero, M. Desirée Alba-Rodríguez (1), Madelyn Marrero (1) (1) Escuela Técnica Superior de Ingeniería de Edificación. Departamento de Construcciones Arquitectónicas 2. Universidad de Sevilla. 41012 Sevilla. España. e-mail: malba[email protected]s Abstract 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. Keywords: Building construction; ecological footprint; cost control; environmental assessment. 2 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 et al., (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), Eco-Quantum, 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 perform a life-cycle assessment. 3 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 and WBCSD, 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 et al. (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, Lee, & Wang, 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 (Ley 9/2017). 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 nonacademic field, but it also presents an easy application in environmental policies and decision making (J. Solís-Guzmán & Marrero, 2015). 4 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 et al.(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, resources, and solid waste CO2), by applying it to an exhibition centre in Wuhan (China). 5 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 Solís-Guzmán 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 (Alejandro Martínez-Rocamora, Solís-Guzmán, & Marrero, 2016b, 2017), and the rehabilitation and demolition of 40 homes following an excavation accident (Alba- Rodríguez et al., 2017). The methodology has also been adapted to two different countries, Mexico (Larralde & González-Vallejo, 2015) and Chile (González-Vallejo, Muñoz-Sanguinetti and Marrero, 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 7,000 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 6 proposed. As an illustration, a case study of dwelling construction in Spain is analysed and compared with other research results. 2. CONSTRUCTION BREAKDOWN SYSTEMS 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), Uniformat (UniFormatTM, 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, 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. 7 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 (ISO 12006-2, 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 the Environment and Planning of the Territory, 2007), the BDC-IVE in Valencia (Ministry of Infrastructure, Territory and Environment, 2012), the BDEU in the Basque Country (Department of Housing, 2012), PRECIOCENTRO of Guadalajara (Official College of Quantity Surveyors, 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 (FIE-BDC, 2007). 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, 8 Spain. In ACICS, work units are divided into a hierarchic organization. Figure 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 Figure 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: • It allows precise identification of the encoded concepts. This function 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. 15 3.2. Construction Materials Each basic material of the ACCD (formed of 4,900 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 (RD 314/2006). Finally, life cycle 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, 2016a). In order to obtain the embodied CO2 emissions, the Life-cycle Inventory of the materials is analysed using the IPCC 100a 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 16 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 Equation 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) (Equation 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, equation 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/100km, 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 17 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. 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; J. Solís-Guzmán & Marrero, 2015). Consumption and emission factors of diesel and petrol engines are combined to calculate the impact of machinery, as presented in equation 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 equation 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 (equation 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). 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. 18 Table 1. EF calculation equations (Alba-Rodríguez et al., 2017) equation Electricity. EFel: Partial Ecological Footprint of electricity consumption (gha/yr) 𝑬𝑭𝒆𝒍 =𝑪𝒆𝒍 ·𝑬𝒆𝒍 ·(𝟏−𝐀𝒐𝒄) 𝑨𝒇 ⁄·𝑬𝑸𝑭𝒄𝒂 1 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) 𝑬𝑭𝒘𝒂 = 𝑪𝒘𝒂 ·𝑬𝑰𝒘𝒂 ·𝑬𝒆𝒍 ·(𝟏−𝐀𝒐𝒄) 𝑨𝒇 ⁄·𝑬𝑸𝑭𝒄𝒂 2 Cwa: Water consumption per year (m3/yr) EIwa: Energy intensity of drinking water (0.44 kWh/m3) (EMASESA, 2005) Built-up land. EFbl: Partial Ecological Footprint of built-up land (gha/yr) 𝑬𝑭𝒃𝒍 =𝑺·𝑬𝑸𝑭𝒃𝒍 3 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) 𝑬𝑭𝒇𝒐𝒊=𝑯𝒘 𝑯𝒅·𝟎.𝟔𝟏·𝑬𝑭𝒊 𝟑𝟔𝟓 4 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) 𝑬𝑭𝑴𝑺𝑾 = 𝑯𝒘·𝑮𝒘·𝑬𝑴𝑺𝑾 ·(𝟏−𝐀𝒐𝒄) 𝑨𝒇 ⁄·𝑬𝑸𝑭𝒄𝒂 5 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−𝐀𝒐𝒄)/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 7 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 𝑻𝒄𝒂𝒑 ·𝑫𝒎𝒂)·𝑻𝒄𝒐𝒏 ·𝑬𝒇·(𝟏−𝐀𝒐𝒄)/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) 𝑬𝑭𝒎𝒄 = ∑(𝑯𝒎𝒄𝒊·𝑪𝒇𝒊·𝑬𝒇𝒊)·(𝟏−𝐀𝒐𝒄) 𝑨𝒇 ⁄·𝑬𝑸𝑭𝒄𝒂 9 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) 19 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 gha/u C12 EXECUTION OF WORK Labour C121 Special workers h/month C1211 Construction site manager 127.08 0.031 C1212 Group leaders 127.08 0.031 C1213 Store-room keeper 127.08 0.031 C1214 Security 127.08 0.031 C122 AUXILARY WORK Labour C1221 Auxiliary personnel h/m2 C12211 Interior transport 0.02 6.00E-06 C12212 Cleaning 0.05 1.10E-05 C12213 Machine and utensil internal transport 0.04 1.00E-05 C1223 Machines. utensils and tools Labour Power Fuel C12231 Elevation equipment h/month kWh/month l/month C122311 Tower crane 127.08 1.525.00 0.126 C122313 Telescopic platform 101.67 1830.00 0.025 C122314 Lifting platform 101.67 305.00 0.044 C122315 Lift 101.67 305.00 0.044 C12232 Concrete mixer 101.67 149.45 0.034 C12233 Machine shop of steel reinforcement 101.67 162.67 0.035 C123 COMPLEMENTARY INTALLATIONS Labour Power Water C1231 Worksite h/u kWh/m2 m3 water/ m2 room C12311 Offices 208.00 0.16 0.013 C12312 Meeting rooms 208.00 0.16 0.013 C12313 Storage rooms 208.00 0.16 0.013 C12321 Provisional power connection to the grid 32.82 0.008 C12322 Provisional water and sewers 6.56 0.002 C12323 Power grid 21.88 0.005 C12324 Water installations 4.38 0.001 C1233 Road signalling and stacking 18.98 0.005 C124 PERSONAL Labour C1241 Technicians h/month C12411 Work site manager 127.08 0.031 C12412 Production manager 127.08 0.031 C12413 Auxiliary technicians 127.08 0.031 C1242 Secretary. administration personnel 127.08 0.031 C125 OTHERS Power C1251 Offices kWh/m2 C12511 Paper work in offices None C1253 Others C12531 Lighting 1.49 Occupation 1.00E-04 C12532 Testing facilities (a7C. heating. cooling) 1.11 ha 1.00E-04 C12533 Plot size 1.00E-04 3.00E-04 20 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 (RD 842/2002). The total annual consumption (eight hours a day, 5 days a week and 52 weeks a year) is 208.00 kWh/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 lumen/m2 (RD 486/1997). Low-consumption lamps have an average consumption of 70 lumen/W. Artificial light, based on the average daylight in southern Spain (CTE, 2006) is switched on for 4 h/day on average (2h in the early morning and 2h in the evenings). Finally, lighting power consumption is 1.49 kWh/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 kWh 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 (equation 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 built-up surface into EF terms (equation 3. Table 1). 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 21 most common dwelling type in Spain (González-Vallejo, Solís-Guzmán, Llácer, & Marrero, 2015; Mercader-Moyano, 2010; 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. 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 211.86 gha (Jaime Solís-Guzmán, 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 (RD 105 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. 4.2. 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 22 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. 4.3. 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 a machine has an equivalent hour of labour. 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. 4.5. Total footprint In Figure 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. 23 Figure 3. EF per chapter in the ACCD 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 (Jaime Solís-Guzmán et al., 2015), even though in other types of construction projects, such as maintenance, workers exert a major impact of over 60% (Alejandro Martínez-Rocamora et al., 2017). 0,28 0,89 0,14 3,69 0,16 4,63 12,40 0,23 9,19 3,65 8,17 34,50 0,25 19,20 2,52 0,12 0,28 0,90 1,72 1,17 0,24 5,83 9,67 17,30 13,90 2,39 8,98 23,80 0,15 9,44 4,16 0,04 Waste management Safety Decoration Paint Glass Carpentry Finishes Insulation Installation Rooftops Masonry Structures Sewers Foundation Excavation Demolition % Cost % EF 24 Table 3. Total EF Impact Fossil Grazing land Forests Productive sea Crops Occupied directly Materials 179.621 Machinery 310.258 0.136 0.013 0.358 0.612 Manpower 1.683 1.439 0.136 3.783 6.467 Indirect costs 0.850 0.086 0.008 0.227 0.389 2.416 Total 492.412 1.661 0.157 4.369 7.468 2.416 URBANIZATION TOTAL EF 508.483 gha Materials 2,090.708 Machinery 45.216 0.091 0.009 0.240 0.411 Manpower 2.913 2.490 0.235 6.549 11.196 Indirect costs 4.947 0.323 0.031 0.849 1.452 0.704 Total 2,143.784 2.904 0.275 7.638 13.059 0.704 CONSTRUCTION TOTAL EF 2,168.366 gha 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 (A Martínez- Rocamora, 2016). In this way, the EF of the life cycle of the building can be attained. In previous studies by the research group (Jaime Solís-Guzmán, 2011), the total EF is 12,283 gha and is distributed in 3,977 gha in urbanization and 8,306 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 (Jaime Solís-Guzmán, 2011) were not 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 (RD 1359/2011) in the original methodology overestimating the on-site power consumption by a factor of 10 when compared to the empirical data collected (Freire-Guerrero & Marrero-Meléndez, 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 et al., 2019). This generates a significantly 31 for green buildings. Retrieved from https://www.wbcsdcement.org/pdf/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. SpringerReal Academia Sueca de Ciencias. https://doi.org/10.2307/25547812 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 Chong, H.-Y., Lee, C.-Y., & Wang, X. (2017). A mixed review of the adoption of Building Information Modelling (BIM) for sustainability. Journal of Cleaner Production, 142, 4114–4126. https://doi.org/10.1016/J.JCLEPRO.2016.09.222 CSI/CSC. (1983). Construction Specifications Institute/Construction Specifications Canada. Masterformat manual of practice (MP2-1). Alexandria, Va. CTE. (2006). Spain MH (Ministry of Housing). Código Técnico de la Edificación (Building Technical Code). Madrid. Spain. Retrieved December 1, 2013, from http://www.codigotecnico.org/web/ Department of Housing, P. W. and T. of the B. G. (2012). BDEU in the Basque Country. Domenech Quesada, J. L. (2009). Huella ecológica y desarrollo sostenible (Ecological Footprint and Sustainable Development). Madrid: AENOR-Asociación Española de Normalización y 32 Certificación. E2CO2cero. (2014). Calcula de forma sencilla la energía embebida y la huella de carbono de un edificio. Retrieved February 13, 2019, from http://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 from http://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, from http://ec.europa.eu/eurostat/statisticsexplained/index.php/File:Municipal_waste_generated_by_country_in_selected_years_%2 8kg_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. Resources, Conservation and Recycling, 125, 293–299. https://doi.org/10.1016/J.RESCONREC.2017.07.003 Fiala, N. (2008). Measuring sustainability: Why the ecological footprint is bad economics and bad environmental science. Ecological Economics, 67(4), 519–525. https://doi.org/10.1016/J.ECOLECON.2008.07.023 FIE-BDC. (2007). Association of Construction Data Base Redactors by means of developing a standard exchange format. Retrieved from http://www.fiebdc.es Freire-Guerrero, A., & Marrero-Meléndez, M. (2015). Ecological footprint in indirect cost of construction. In II Congreso Internacional de Costrucción Sostenible y Soluciones Ecoeficientes (pp. 958–979). Universidad de Sevilla. Escuela Técnica Superior de 33 Arquitectura. Retrieved from https://idus.us.es/xmlui/handle/11441/59685 Freire, A., & Marrero, M. (2014). Analysis of the ecological footprint produced by machinery in construction. In World Sustainable Building 14. Barcelona. Freire Guerrero, A., & Marrero, M. (2015). Evaluation of the embodied energy of a construction project using the budget. 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 34 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). Guidelines for National Greenhouse Gas Inventories, vol. 4: Agriculture Forestry and Other Land Use. Technical report, IPCC, 2006. Retrieved August 22, 2018, from https://www.ipcc-nggip.iges.or.jp/public/2006gl/vol4.html ISO12006-2. Building construction -- Organization of information about construction works -- Part 2: Framework for classification (2015). ITeC. (2012). Institute of Construction Technology of Catalonia. Retrieved from https://en.itec.cat/database/ ITeC BEDEC. (2019). Retrieved January 26, 2019, from https://metabase.itec.cat/vide/es/bedec Jones, A. R. (1987). CI/SfB construction indexing manual. Royal Institute of British Architects RIBA. London, U.K. Larralde, L., & González-Vallejo, P. (2015). Ecological footprint in of dwelling construction in Mexico. Congreso Internacional de Costrucción Sostenible y Soluciones Ecoeficientes, (978- 84-617-3964–6), 795–817. Retrieved from https://idus.us.es/xmlui/handle/11441/59663 Ley9/2017. Ministerio de la Presidencia del gobierno de España. Ley 9/2017, de 8 de noviembre, de Contratos del Sector Público, por la que se transponen al ordenamiento jurídico español las Directivas del Parlamento Europeo y del Consejo 2014/23/UE y 2014/24/UE, de (2017). Liu, M., Zhang, B., Ren, J., Gu, H., & Yuan, J. (2018). Sustainability Evaluation of the Ecological Footprint of Rural Residential Houses with Difference Martials. IOP Conference Series: Materials Science and Engineering, 394, 032040. https://doi.org/10.1088/1757- 899X/394/3/032040 Luo, W., Bai, H., Jing, Q., Liu, T., & Xu, H. (2018). Urbanization-induced ecological degradation in 35 Midwestern China: An analysis based on an improved ecological footprint model. Resources, Conservation and Recycling, 137, 113–125. https://doi.org/10.1016/J.RESCONREC.2018.05.015 Marrero, M., Freire Guerrero, A., Solís-Guzmán, J., & Rivero-Camacho, C. (2014). Estudio de la huella ecológica de la transformación del uso del suelo. Fundación MAPFRE. Instituto de Prevención, Salud y Medio Ambiente. Seguridad y Medio Ambiente, 136(136), 6–14. Retrieved from https://dialnet.unirioja.es/servlet/articulo?codigo=4960039 Marrero, M., Puerto, M., Rivero-Camacho, C., Freire-Guerrero, A., & Solís-Guzmán, J. (2017). Assessing the economic impact and ecological footprint of construction and demolition waste during the urbanization of rural land. Resources, Conservation and Recycling, 117, 160–174. https://doi.org/10.1016/J.RESCONREC.2016.10.020 Marrero, M., & Ramirez-De-Arellano, A. (2010). The building cost system in Andalusia: application to construction and demolition waste management. Construction Management and Economics, 28(5), 495–507. https://doi.org/10.1080/01446191003735500 Martinaitis, V., Rogoža, A., & Bikmanien, I. (2004). Criterion to evaluate the “twofold benefit” of the renovation of buildings and their elements. Energy and Buildings, 36(1), 3–8. https://doi.org/10.1016/S0378-7788(03)00054-9 Martínez-Rocamora, A. (2016). Evaluación económica y ambiental del uso y mantenimiento de edificios. Universidad de Sevilla. Retrieved from https://idus.us.es/xmlui/handle/11441/44478 Martínez-Rocamora, A., Solís-Guzmán, J., & Marrero, M. (2016a). LCA databases focused on construction materials: A review. Renewable and Sustainable Energy Reviews, 58, 565–573. https://doi.org/10.1016/J.RSER.2015.12.243 Martínez-Rocamora, A., Solís-Guzmán, J., & Marrero, M. (2016b). Toward the Ecological Footprint of the use and maintenance phase of buildings: Utility consumption and cleaning tasks. 36 Ecological Indicators, 69, 66–77. https://doi.org/10.1016/j.ecolind.2016.04.007 Martínez-Rocamora, A., Solís-Guzmán, J., & Marrero, M. (2017). Ecological footprint of the use and maintenance phase of buildings: Maintenance tasks and final results. Energy and Buildings, 155, 339–351. https://doi.org/10.1016/J.ENBUILD.2017.09.038 Mercader-Moyano, P. (2010). Cuantificación de los recursos consumidos y emisiones de CO2 producidas en las construcciones de Andalucía y sus implicaciones en el protocolo de Kioto. Retrieved from https://idus.us.es/xmlui/handle/11441/15660 Mercader, M. del P., Marrero, M., Solís, J., Montes, M. V., & Ramírez, A. (2010). Cuantificación de los recursos materiales consumidos en la ejecución de la cimentación. Informes de La Construcción, 62(517), 125–132. https://doi.org/10.3989/ic.09.000 Ministry of Infrastructure, Territory and Environment, G. V. (2012). BDC-IVE in Valencia. Ministry of the Environment and Planning of the Territory, C. of M. (2007). BPCM Madrid. Moreno Rojas, R., Fernández Torres, A., García Pereda, J., Cámara Martos, F., Amaro López, M. A., Ros Berruezo, G., … Martínez de Victoria Carazo, I. (2015). Estimación de la distribución diaria de nutrientes en la dieta estándar en España. Nutrición Hospitalaria, 31(6), 2660– 2667. https://doi.org/10.3305/nh.2015.31.6.8896 Moya de los Reyes, J. (2013). La influencia de la maquinaria en los costes globales, Trabajo fin de grado ETS Ingeniería de Edificación. Seville: University of Seville. Official College of Quantity Surveyors, T. A. and B. E. of G. (2012). PRECIOCENTRO of Guadalajara. Olgyay, V. (2008). Greenfoot: A tool for estimating the carbon and ecological footprint of buildings. American Solar Energy Society - SOLAR 2008, Including Proc. of 37th ASES Annual Conf., 33rd National Passive Solar Conf., 3rd Renewable Energy Policy and Marketing Conf.: Catch the Clean Energy Wave, 8, 5058–5062. Omniclass. (2012). A strategy for classifying the built environment - Table 13: Spaces by function. Rashid, A., Irum, A., Malik, I. A., Ashraf, A., Rongqiong, L., Liu, G., … Yousaf, B. (2018). Ecological 37 footprint of Rawalpindi; Pakistan’s first footprint analysis from urbanization perspective. Journal of Cleaner Production, 170, 362–368. https://doi.org/10.1016/J.JCLEPRO.2017.09.186 RD105/2008. Producción y gestión de los residuos de construcción y demolición (Production and management of Construction and DemolitionWaste) (2008). RD1359/2011. Ministerio de Economía y Hacienda del Gobierno de España.: Real Decreto 1359/2011, de 7 de octubre, por el que se aprueba la relación de materiales básicos y las fórmulas-tipo generales de revisión de precios de los contratos de obras y de contratos de su (2011). RD314/2006. Ministerio de Vivienda del gobierno de España: Real Decreto 314/2006, de 17 de marzo, por el que se aprueba el Código Técnico de la Edificación. BOE no 74, 28-03-2006. (2006). RD486/1997. Spain ML (Ministry of Labor). Real Decreto 486/1997. de 14 de abril. por el que se establecen las disposiciones mínimas de seguridad y salud en los lugares de trabajo. (Royal Decree 486/1997. of minimum safety and health in the workplace) (1997). RD842/2002. Spain MS (Ministry of Science). Real Decreto 842/ 2002. por el que se aprueba el Reglamento electrotécnico para baja tensión (Royal Decree 842/2002. low voltage electrical regulation) (2002). REE. (2014). El sistema eléctrico español / The Spanish electric system. Samad Pour, P., & Faryadi, S. . (2008, January 1). Determination of ecological footprints of dense and high-rise districts, case study of elahie neighborhood, Tehran. JOURNAL OF ENVIRONMENTAL STUDIES. Retrieved from http://www.sid.ir/En/Journal/ViewPaper.aspx?ID=109412 SimaPro. (2016). PRé Sustainability SimaPro 8. Retrieved February 22, 2018, from ttps://www.pre-sustainability.com/ 38 Sinha, R., Lennartsson, M., & Frostell, B. (2016). Environmental footprint assessment of building structures: A comparative study. Building and Environment, 104, 162–171. https://doi.org/10.1016/J.BUILDENV.2016.05.012 SOFIAS project. (2017). SOFIAS project website. Solís-Guzmán, J. (2011). Evaluación de la huella ecológica del sector edificación (uso residencial) en la Comunidad Andaluza. Universidad de Sevilla. Retrieved from https://dialnet.unirioja.es/servlet/tesis?codigo=39755 Solís-Guzmán, J., González-Vallejo, P., Martínez-Rocamora, A., & Marrero, M. (2015). The Carbon Footprint of Dwelling Construction in Spain. In The Carbon Footprint Handbook (pp. 261– 283). CRC Press - Taylor & Francis Group. Solís-Guzmán, J., & Marrero, M. (2015). The ecological footprint of building construction: a Spanish case study (Bentham eB). Bentham eBooks. Solís-Guzmán, J., Marrero, M., & Ramírez-de-Arellano, A. (2013). Methodology for determining the ecological footprint of the construction of residential buildings in Andalusia (Spain). Ecological Indicators, 25, 239–249. https://doi.org/10.1016/j.ecolind.2012.10.008 Statistic division of the FAO. (2014). FAOSTAT. Statistics National Institute. (2012). Estadísticas sobre la recogida y tratamiento de residuos Encuesta sobre generación de residuos en la Recogida Mezclada Recogida Separada. https://doi.org/10.0 Sturgis, S., & Roberts, G. (2010). Redefining Zero: Carbon profiling as a solution to whole life carbon emission measurement in buildings. RRCIS Research Report. Tadeu, S., Rodrigues, C., Tadeu, A., Freire, F., & Simões, N. (2015). Energy retrofit of historic buildings: Environmental assessment of cost-optimal solutions. Journal of Building Engineering, 4, 167–176. https://doi.org/10.1016/J.JOBE.2015.09.009 Telford, T. (1991). Civil engineering standard method of measurement. 3rd Ed., LTD., U. K., 4–39. 39 Teng, J., Wang, P., Wu, X., & Xu, C. (2016). Decision-making tools for evaluation the impact on the eco-footprint and eco-environmental quality of green building development policy. Sustainable Cities and Society, 23, 50–58. https://doi.org/10.1016/j.scs.2016.02.018 Teng, J., & Wu, X. (2014). Eco-footprint-based life-cycle eco-efficiency assessment of building projects. Ecological Indicators, 39, 160–168. https://doi.org/10.1016/J.ECOLIND.2013.12.018 UNE-EN-771-1. (2003). Specification for masonry units - Part 1: Clay masonry units. European Standard. Retrieved from https://static1.squarespace.com/static/541a52e0e4b02b592c36f723/t/582bd1a4f7e0ab3f 4aef6610/1479266731780/WB+Exp+EN771-1_A1+eing_E+Brick+standard.pdf UNESID. Unión de Empresas Siderúrgicas. (2013). Informe 2013 sobre el RECICLAJE DEL ACERO en la Industria Siderúrgica Española. Retrieved January 9, 2019, from https://unesid.org/iris2013/industria.html UniFormatTM. The Construction Specifications Institute. (1998). A Uniform Classification of Construction Systems and Assemblies. Alexandria, VA. van den Bergh, J. C. J. ., & Verbruggen, H. (1999). Spatial sustainability, trade and indicators: an evaluation of the ‘ecological footprint.’ Ecological Economics, 29(1), 61–72. https://doi.org/10.1016/S0921-8009(99)00032-4 Wackernagel, M., & Rees, W. (1997). Our Ecological Footprint: Reducing Human Impact on the Earth. New Catalyst Bioregional Series. Watson, N., Walker, P., Wylie, A., & Way, C. (2012). Evaluating the barriers to entry for nonconventional building materials. International Association for Bridge and Structural Engineering., 98, 9–16. Retrieved from https://www.ingentaconnect.com/content/iabse/report/2012/00000098/00000003/art00 002 40 WWF International. (2014). Living Planet Report 2014. Global Footprint Network, ZSL (Zoological Society of London). Gland, Switzerland. Zhao, X. Y., & Mao, X. W. (2013). Comparison environmental impact of the peasant household in han, zang and hui nationality region: case of Zhangye, Gannan and Linxia in Gansu Province. Acta Ecologica Sinica, 33(17), 5397–5406.