Balancing construction and operational carbon emissions: Evaluating neighbourhood renovation strategies

Journal of Building Engineering 94 (2024) 109993 Available online 27 June 2024 2352-7102/© 2024 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). Contents lists available at ScienceDirect Journal of Building Engineering journal homepage: www.elsevier.com/locate/jobe Balancing construction and operational carbon emissions: Evaluating neighbourhood renovation strategies Javier García-Lópeza, Miguel Hernández-Valenciab,*, Jorge Roa-Fernándeza, Emilio J. Mascort-Albeab, Rafael Herrera-Limonesa aUniversidad de Sevilla, Escuela Técnica Superior de Arquitectura, Departamento de Construcciones Arquitectónicas 1, Instituto Universitario de Arquitectura y Ciencias de la Construcción, Avenida de Reina Mercedes 2, 41012, Sevilla, Spain bUniversidad de Sevilla, Escuela Técnica Superior de Arquitectura, Departamento de Estructuras de Edificación e Ingeniería del Terreno, Instituto Universitario de Arquitectura y Ciencias de la Construcción, Avenida de Reina Mercedes 2, 41012, Sevilla, Spain ARTICLE INFO Keywords: Sustainable urban regeneration Geographic information system Urban modelling interface Decarbonisation Residential buildings Residential energy consumption Open data ABSTRACT Compliance with the global decarbonisation commitments set out in Horizon 2050 undoubtedly involves optimising the conditions of the housing stock. In this respect, the massive energy renovation of obsolete housing blocks in southern EU countries holds the key for the achievement of such compliance. This research strives to demonstrate the suitability of intervention strategies at district scale. For this purpose, an innovative methodology that combines open data, Geographic Information Systems (GIS), Urban Energy Modelling (UBEM), and Life Cycle Assessment (LCA) is proposed and tested in a case study, whilst considering several renovation and new-building hypotheses. As an innovative approach, this study concurrently analyses greenhouse gas emissions arising from both use-related energy consumption (operational carbon footprint) and the construction process (embodied carbon footprint). This dual perspective provides added value to the results obtained, since it offers a more comprehensive representation of reality. Based on the results from the LCA and UBEM models, this study unveils the entire impact of residential energy use combined with either the carbon footprint of energy renovation or that of new buildings. The case study analysis reveals that total emissions, encompassing both embodied and operational aspects, are lower for retrofitting existing buildings when compared to new construction, up to Horizon 2050. Remarkably, this preference for renovation persists even as far as 2100. The study underscores the critical importance of upgrading the existing residential stock in order to achieve the ambitious goal of net-zero greenhouse gas emissions by 2050. Abbreviations CAT Category CPR Construction Products Regulation EPC Energy Performance Certificate * Corresponding author. E-mail addresses: [email protected] (J. García-López), [email protected] (M. Hernández-Valencia), jr[email protected] (J. Roa-Fernández), emas[email protected] (E.J. Mascort- Albea), [email protected] (R. Herrera-Limones). https://doi.org/10.1016/j.jobe.2024.109993 Received 14 March 2024; Received in revised form 9 June 2024; Accepted 19 June 2024 Journal of Building Engineering 94 (2024) 109993 2 J. García-López et al. EPD Environmental Product Declaration EPW EnergyPlus Weather file EUI Energy Use Intensity DHW Domestic Hot Water HVAC Heating, Ventilation, and Air-Conditioning LCA Life Cycle Analysis GIS Geographic Information System GWP Global Warming Potential GWP-total Total Global Warming Potential (kg CO2eq) NZEB Nearly Zero-Energy Building OSEMN Acronym for a data science life cycle: Observe, Scrum, Explore, Model, and iNterpret. PENRT Total use of Non-Renewable Primary Energy resources (MJ) PV Photovoltaic UBEM Urban Building Energy Model UMI Urban Modelling Interface (MIT Sustainable Design Lab) WWR Window-to-Wall Ratio ZEB Zero-Energy Building. Carbon neutral 1. Introduction 1.1. Background and established knowledge Article 2 of the 2015 Paris Agreement (United Nations Climate Change Conference 2015 - COP21) aims to maintain the global average temperature at 1.5 °C below the pre-industrial levels at the end of the 19th century. This objective recognises that achieving this temperature would significantly reduce the effects of climate change. In order to reach this goal, it is necessary to reduce greenhouse gas emissions by approximately 55 % by 2030 compared to 1990 levels, and to achieve net-zero greenhouse emissions by 2050 [1]. Faced with this global challenge, as well as with Global Goal 11, ‘sustainable cities and communities’of the UN 2030 Agenda, sustainable urban regeneration of obsolete residential neighbourhoods is a key aspect. This issue encompasses the social, economic, and environmental principles of sustainability, with particular impact on the southern regions of the European Union, including Portugal, Italy, and Greece. In Spain, where the case study of this research originates, 49.14 % of the main dwellings (which function as habitual residences) are pre-1981, and 38.27 % of the total number of dwellings were built between 1951 and 1980. Of the total number of principal dwellings, only 2.53 % were built between 2011 and 2020 [2]. In order to meet the net-zero greenhouse emission targets for Horizon 2050, it is a priority to improve the existing residential stock, especially those buildings constructed between 1951 and 1980. 1.2. Related research 1.2.1. Previous research into UBEM The development of energy plans and policies requires research into decarbonising the residential stock and analysing potential climate change scenarios. Predictive models, such as bottom-up engineering models, can be utilised to estimate the residential energy consumption of a building or group of buildings [3]. Using this estimate, it is possible to predict the progress towards the targets regarding the reduction of greenhouse gas emissions, and to conduct exploratory analyses to evaluate the impact of various mitigation strategies. Urban Building Energy Modelling (UBEM) is an emerging discipline, which, over the last decade, has developed tools and strategies for energy simulation at district scale in highly populated environments [4,5] Through the comprehensive and massive analysis of the energy consumption of buildings during their use phase, numerous factors can be considered, such as urban fabric, building morphology, boundary conditions, typological diversity, building design, and climate. Reinhart and Cerezo-Dávila (2016) [5] provide an overview of the contributions made to this discipline and establish the main actions required for the creation of energy models in urban sectors [5]. Moreover, in recent years, UBEM-based research has increased in both quantity and quality [6–8], and has established a challenging and innovative framework [9]. Likewise, the most relevant case studies include those using a combination of Urban Modelling Interface (UMI) and Geographic Information System (GIS) tools for the energy modelling of neighbourhoods in Boston [10], Lisbon [11], Jaen [12], and Dublin [13]. Validation methods and the simplifications assumed by the models also constitute a key factor in understanding the fundamentals of the various UBEM strategies. One major development in this field involves the initiative of the International Building Performance Simulation Association (IBSPA) for the development of a district-scale energy model (DESTEST) [14,15]. It aims to adapt validation methods for Building Energy Modelling (BEM) tools based on the Building Energy Simulation Tests (BESTEST) of the International Energy Agency (IEA) [16]. Through this process, a series of standard buildings simulated with different calculation engines define a range of values within which the tools to be validated should lie. However, it is also important to point out that there is currently no commonly accepted international standard for UBEM metrics [7]. For the present case study, the validation and calibration process of UBEM models adopts that described by García-López et al. (2024) for the Andalusia region in Spain [12] by adapting the methodology based on confidence bands similar to BESTEST [17] through the proposed standard for the official authorisation of tools for the energy performance certificates (EPC) of buildings [18]. Journal of Building Engineering 94 (2024) 109993 3 J. García-López et al. 1.2.2. Previous research into LCA Moreover, in the exploratory analysis of time projections of energy renovation scenarios, the calculation of the energy included in the retrofit processes must also be incorporated into the estimation of the previous consumption by means of the Life Cycle Analysis (LCA) of the actions. For the calculation of Nearly Zero-Energy Buildings (NZEB), operational energy is incorporated, although embodied energy is usually excluded [19]. In residential buildings in Southern Europe, embodied energy represents approximately 25 % of operational energy over a service life of 50 years [20]. Moreover, the reduction of operational energy due to technological advances in installations is leading to an increase in the ratio of embodied energy to operational energy in new residential buildings [21]. As Seyedabadi (2023) has pointed out, there is a need for LCA studies applied at neighbourhood scale [22]. If embodied carbon emissions are not considered for the renovation of old residential areas, then the reduction thereof can beoverestimated [23]. Consequently, it is important to consider embodied energy and carbon emissions when assessing the cost effectiveness of emissions in building renovation. Along these lines, research combining LCA and GIS methodology shows the possible strategic impacts of including LCA methods for policy development at urban scale in cities such as Barcelona (Spain) [24]. Another study links BIM-LCA-GIS tools by establishing an Eco-Efficiency Matrix, oriented towards the evaluation of the sustainable development of an area of tall buildings in the city of Quito (Ecuador) [25]. The validation of this type of method is based on the LCA of a cradle-to-site approach. This environmental impact analysis includes production, transport to the construction site, and installation in the construction processes. To this end, the data of the construction systems applied in the retrofitting are obtained from the Environmental Product Declarations (EPD) of each of the retrofitting scenarios considered. The EPDs have been developed according to the European standard EN 15804. 1.2.3. Shortcomings in previous research Following the approach made to the research topic, it can be stated that hardly any research references comprehensively address UBEM and LCA strategies for the assessment of the impact of the carbon footprint in residential developments. Likewise, this type of work seldom considers district-scale retrofitting as a priority strategy over new construction. Furthermore, the validation of the results of UBEM models is generally carried out using reference models, without incorporating real consumption values at neighbourhood scale that would allow the model to be calibrated. 1.3. Research proposal Given the aforementioned context, this study develops and applies a methodology for the assessment of energy consumption and greenhouse gas emissions of various residential renovation scenarios at district scale, and calculates the effects of the energy incorporated in the interventions and the operational energy use up to the 2050 horizon. This research aims to facilitate decision-making regarding possible residential retrofitting strategies by considering the impact of the carbon footprint in each case, both during the intervention and during the use phase of retrofitted buildings. To this end, the proposed methodology combines GIS, UBEM, and LCA tools to assess the effects of the different intervention hypotheses. This is carried out through the calculations performed by the Urban Modelling Interface (UMI) open tool, developed by the Massachusetts Institute of Technology (MIT) Sustainable Design Lab [26], which enables the energy consumption and CO2emissions derived from the construction processes to be obtained, as well as the consumption and emissions from the activities of the various residential user profiles. 1.3.1. Relevance and innovation The development of this applied research has made it possible to estimate the energy consumption and greenhouse gas emissions of a neighbourhood over time, and to integrate data and results relating to the use of housing facilities, as well as integrating those of the construction processes and systems applied in retrofitting. The results obtained enable an integrated analysis of use and renovation, thereby making it possible to assess the effectiveness of solutions aimed at improving the health and comfort conditions of the inhabitants, with the goal of achieving net-zero greenhouse emissions in 2050. Moreover, the study uses only open data and tools for its development, which enables replication in other alternative locations and for various exploratory scenarios. The method also integrates the validation of the model of useful and embodied energy consumption with benchmarks and real data. Lastly, the compatibility of the study with the UBEM.IO platform [27] fosters the sharing of results with other studies being carried out in widely differing contexts, thereby contributing towards the creation of knowledge and transfer on the decarbonisation of buildings. 1.3.2. Case study approach: district of San Pablo (Seville, Spain) To illustrate the research approaches, a case study of an obsolete residential housing estate in Southern Europe from the period 1951–1980 has been selected. Obsolete residential neighbourhoods present common characteristics that justify the development of a specific methodology, based on prominent levels of urban vulnerability and the repetition of construction solutions and residential typologies belonging to the large peripheral urban developments of European cities, which are characteristic of the second half of the 20th century [28,29]. In particular, this stock of residential buildings, built in Spain before the first energy-saving standards published in the 1970s, presents similar issues like: ageing population, lack of accessibility and energy inefficient building envelopes and comfort systems. In order to comply with the vulnerability indicators proposed by the methodology, the A and B neighbourhoods of the San Pablo housing estate (Polígono de San Pablo) in Seville (built 1964–1966) were selected (Fig. 1). These neighbourhoods contain approximately 4000 dwellings of low-income households, mostly located in linear blocks of 5 floors with two dwellings per floor. The con- Journal of Building Engineering 94 (2024) 109993 4 J. García-López et al. Fig. 1. Comparison of the study area: year 1977 (left) and year 2023 (right). Source: REDIAM, 2024 [28]. struction of the dwellings was massive and serial, using repetitive construction systems: reinforced concrete structure, double brick façades with air cavity without thermal insulation, metal carpentry with single glazing, and flat roofs without thermal insulation. Regarding the economy viability, it is assumed that without external support and funding, energy renovation will be very limited. However, in the long term, the intervention cost can be paid back through energy savings. Nevertheless, the feasibility of the massive retrofitting of low-income neighbourhoods can be supported with public funding, such as the Next-Generation EU funds, or by issuing Energy Savings Certificates (ESCs) that the utilities companies can purchase. 1.3.3. Aims and manuscript organisation Consequently, the main objective of the research involves the design of a methodology to assess retrofitting and decarbonisation scenarios at district scale in obsolete residential neighbourhoods. This is in line with the Net-Zero 2050 emission targets. According to that, the study focuses in assessing the energy efficiency of the retrofitted buildings during the operational phase, while also considering the embodied energy used during the renovation processes. After an introductory presentation (Section 1), the article describes the development of the methodology applied to the case study of neighbourhoods A and B of the San Pablo housing estate, located in Seville (Section 2). The results obtained have made it possible to specifically evaluate the energy consumption and carbon footprint up to the year 2050 (Section 3) for these two neighbourhoods. The discussion of the results (Section 4) is organised based on the main topics of the research and evaluates the suitability and replicability of the methodology designed for these obsolete neighbourhoods. Lastly, the conclusions (Section 5) reflect on the relevance of the results in defining appropriate energy rehabilitation criteria, which contribute towards a better allocation of energy and economic resources in vulnerable neighbourhoods. 2. Material and methods The objective of this study is to define and test a methodology to assess energy consumption and carbon footprint at district scale, in extensive retrofitting scenarios of obsolete residential neighbourhoods, using open data and GIS, UBEM, and LCA tools. This method integrates the analysis of energy consumption and greenhouse gas emissions due both to the use and to the construction processes of renovation. The three main phases of the proposed methodology are presented below (Fig. 2). 2.1. Phase 1: characterisation of the case study This phase involves a process of selection and technical characterisation of a case study that complies with the necessary conditions for the application of the method. The work area must verify the conditions of an obsolete residential neighbourhood, based on a set of indicators related to the current state of the building. Subsequently, the architectural characterisation of those representative building-types is to be conducted using GIS and open data. To select the case study of the obsolete neighbourhood, open data was collected from the catalogue of the National Statistics Institute (Instituto Nacional de Estadística, INE) [30], which provides information on the state of the buildings. Geospatial analyses carried out using GIS have made it possible to obtain indicators relating to the vulnerability, age, and typological definition of the dwellings. •Urban vulnerability: The Catalogue of Vulnerable Neighbourhoods in Spain (CBVE) [31] helps to define one of the fundamental criteria for the selection of case studies. A vulnerable neighbourhood consists of an urban area of a certain homogeneity and urban continuity with an approximate population of between 3500 and 15,000 inhabitants. In this residential area, at least one of the three Basic Indicators of Urban Vulnerability (IBVU) related to educational attainment, housing, or unemployment exceeds a vulnerability benchmark [32]. •Housing more than 50 years old: An age of more than 50 years is established as an indicator of obsolescence for the selection of the neighbourhood. In Spain, this reference date is taken as the date of entry into force of the Regulations on Thermal Journal of Building Engineering 94 (2024) 109993 5 J. García-López et al. Fig. 2. General methodology schema. Conditions in Buildings (Norma Básica de Edificación NBE-CT-79) [33], which specify minimum technical requirements aimed at saving energy and achieving minimum conditions of habitability and thermal comfort. •Typological homogeneity: This is a characteristic of obsolete residential neighbourhoods. These urban developments correspond to actions carried out over a brief period, less than 10 years, with projects based on mass production. Thus, architectural types (double bay, linear block, two dwellings per communication nucleus, cross ventilation, double orientation, number of floors) and construction types (double brick façades with air chamber without insulation, flat roofs without insulation, metal frames with single glazing) are repeated in each neighbourhood. Typological homogeneity is identified with the concept of urban cluster and allows the definition of extensive rehabilitation solutions, which facilitates the application of the same solution to all the buildings in a neighbourhood. In accordance with the aforementioned criteria, if the neighbourhood meets the above conditions, then it is labelled as an obsolete residential neighbourhood and the application of the designed methodology is feasible. The typological identification is carried out using GIS tools and open databases, with which representative parameters of the buildings in the neighbourhood are determined: number of floors, number of dwellings, height, roof surface, façade surface, and age of the building. These parameters are employed to define the typical buildings that represent all the dwellings in the neighbourhood. A bottom-up methodology is applied for constructive characterisation, based on data obtained in situ from a representative building in the neighbourhood. The collection of data on this sample of buildings enables the calculation models to be calibrated and, therefore, the obtained results to be validated. Journal of Building Engineering 94 (2024) 109993 6 J. García-López et al. 2.2. Phase 2. definition of intervention hypothesis The concept of extensive renovation refers to interventions that can be applied to the broad range of dwellings in a neighbourhood and not only to isolated buildings, in order to ensure a better allocation of resources in vulnerable neighbourhoods. Renovation scenarios aim to reduce energy demand, consumption, and carbon footprint and to improve energy efficiency, and to provide ‘on site’renewable energy, while, at the same time improving the comfort conditions of the users. Building envelope renovation scenarios are defined for which the implementation is feasible for the totality of dwellings in the neighbourhood. Interventions on the interior of dwellings and individual renovations of individual active facility systems like individual DHW or HVAC equipment, are generally excluded since they fall outside the scope of the extensive retrofit concept. Each scenario must incorporate the characteristics of the existing building systems and of each of the renovation proposals. Therefore, variations of the models are necessary for the energy and carbon footprint assessment of each proposal. 2.3. Phase 3. UBEM-LCA district-level implementation In the following, the UBEM-LCA application process on the existing building stock and on the different renovation scenarios is presented. With a bottom-up engineering model, and at district scale, the aim is to evaluate the emissions and operational energy consumption and the embodied energy of the renovation scenarios [3]. The results obtained enable the evaluation of the temporal evolution of decarbonisation scenarios. The LCA and operational energy modules of the UMI tool of the MIT Sustainable Design Lab [26] are employed for the calculation. The UMI tool enables the final energy consumption of buildings during their use (operational energy) to be attained, as well as the embodied energy and CO2embedded in the construction processes (life cycle assessment). The results obtained by both applications in combination lead to an evaluation with a time projection of energy consumption and carbon footprint up to 2050, in coherence with the Net-Zero 2050 emission targets. A typical data science process model, known as OSEMN [34], has been implemented to estimate emissions during the use phase of the dwellings. The graphical representation of the process is included in Fig. 3, where phases, tasks, and intermediate results are laid out in columns. 2.3.1. Operational energy and emissions (UBEM) It is proposed to start by obtaining open data from the cadastre in GIS format. Subsequent to cleaning and preparation, the data must be categorised in terms of typology and age and assigned to a specific “building type”. The next step is to transform the GIS information into a three-dimensional UBEM model using the online tool UBEM.IO developed at the MIT [35]. The three-dimensional model of the buildings, where each building is identified by its cadastral reference and a specific building type, is processed with the Rhinoceros tool, using the UMI v.3.0 plugin interface [36]. Each building type is assigned a building template that includes the dimensional characterisation, construction, facilities, and use profile, as well as the embodied energy and CO2of the components of the retrofitting scenarios. The weather conditions are characterised with a climate file in EPW format, obtained from the PVGIS database [37] for that location. Each intervention scenario requires its own UMI model, which incorporates the variations in the building elements (thermal envelope) and architectural elements (PV roofs) specific to each scenario. After this set of steps, the results of the first model can be obtained, and the data of the standard building in UBEM can be compared with that of the BEM EnergyPlus database that represents the same building casuistry. Through the adoption of the criterion of confidence bands [38], the UBEM model can be adjusted by modifying the operational and system conditions of the UMI templates to fit the confidence bands defined in the BESTEST-derived reference method [12]. This is the hypothesis H0. 2.3.2. Embodied energy and emissions of LCA intervention scenarios Following the validation of the UBEM model, simulations can be carried out and the energy consumption results of the operational and energy phases can be extracted as can the CO2incorporated with UMI's energy and LCA modules. 2.3.3. Evolution of decarbonisation scenarios Lastly, in order to obtain the results relating to the temporal evolution of the various decarbonisation scenarios, the results must be processed by transforming the final energy consumption into CO2emissions in accordance with the official pass-through coefficients. Similarly, the emissions incorporated in the construction phase must be computed to reveal the evolution of the emission scenarios. This is carried out by considering the initial emissions and those that differ over time according to the simulations of each scenario. 3. Results, analysis, and discussion 3.1. PH01: description of the case study proposal The San Pablo housing estate is a district of Seville consisting of more than 8800 dwellings that belong to the III National Housing Plan (1961–1976). Neighbourhoods A and B form part of the first phase, executed between 1964 and 1966, and include some 4000 dwellings [39,40]. The Spanish Housing Union (Obra Sindical del Hogar) built the neighbourhood, together with the National Housing Institute (Instituto Nacional de Vivienda) and the Seville Town Planning Department (Gerencia de Urbanismo de Sevilla). The methodology developed in the previous section is applied below. Journal of Building Engineering 94 (2024) 109993 7 J. García-López et al. Fig. 3. Phase 3 workflow: Carbon footprint of district-level embodied and operational energy modelling. Journal of Building Engineering 94 (2024) 109993 8 J. García-López et al. 3.1.1. Neighbourhoods A and B of the San Pablo housing estate (Seville, Spain) These constitute a representative case of obsolete residential neighbourhoods, included in CBVE [31] that are over 50 years old (1964–1966). There is a repetition of the construction systems utilised in all the dwellings: reinforced concrete structure, double brick façades with an air chamber without thermal insulation, flat roofs without thermal insulation, and metal window frames with single glazing. Furthermore, the main architectural type is a 5-storey linear block with 10 dwellings per block [41]. 3.1.2. Building typological identification The representative data of the buildings has been obtained from open databases of the Cadastre of the Spanish Government (Sede de Catastro del Gobierno de España) [42], and includes the number of floors, number of dwellings, height, roof surface, and façade surface. The typical buildings of the neighbourhood are identified, for which differentiated templates of construction characteristics are developed (Table 1). The neighbourhood is made up of 442 building blocks (Fig. 4), with a housing density of 154 dwellings per hectare. Of these, 80.77 % are residential buildings. The height distribution of these residential buildings corresponds to the categories and building typologies. Of the 3889 dwellings counted, 81.28 % correspond to the ‘C’or ‘Social’categories. Dwellings within these two categories have less built area and are of lower quality according to the design regulations. The sample residential building used as a baseline for the constructive characterisation corresponds to this category. 3.1.3. H0: constructive characterisation of building types To extrapolate the constructive characterisation to the rest of the neighbourhood, data was gathered from a representative sample building. In this case, a 5-storey linear block with 10 dwellings located at 1, Saeta street (37°23′35.3″N 5°58′05.5″W) was considered (Fig. 5). The collection of data on this building model enables the calibration of the calculation models used, and therefore the validation of the results obtained. Table 1 Statistics of buildings and dwellings in the neighbourhood. Category Blocks Floors Dwellings WWR Built Area Rooms Type Dwellings % per floor % m2% 1st Category A1 4 0.90 % 13 3 24.67 % 80/200 4 & 5 Tower 146 1st Category A2 4 0.90 % 13 2 24.67 % 80/200 4 & 5 Block 96 TOTAL A 242 6.22 % 2nd Category B1 12 2.71 % 10 2 17.71 % 60/125 3 & 4 Block 195 2nd Category B2 18 4.07 % 9 2 17.71 % 60/125 3 & 4 Block 291 TOTAL B 486 12.50 % 3rd Category C1 8 1.81 % 6 2 13.44 % 50/80 3 & 4 Block 72 3rd Category C2 55 12.44 % 5 2 13.44 % 50/80 3 & 4 Block 534 TOTAL C 606 15.58 % Social Category 256 57.92 % 5 2 15.41 % 50/60 3 Block 2555 TOTAL Social 2555 65.70 % TOTAL RESIDENTIAL 357 80.77 % 3889 100.00 % Non-residential 85 19.23 % 1–3– – – TOTAL BUILDINGS 442 Fig. 4. Building categories and number of floors. The location of the sample building is indicated. Journal of Building Engineering 94 (2024) 109993 9 J. García-López et al. Fig. 5. Plans of representative sample building located at 1, Saeta street (Seville, Spain). Prior to its construction, in 1954, the Technical Standards for Limited-Income Housing (Ordenanzas y Normas Constructivas de las Viviendas de Renta Limitada) [43] were drawn up in Spain. The principles set out in these norms have a strong typological, functional, and hygienic basis, and clearly delimit the minimum built and useable areas per category. These internal standards were designed to be a guide for the drafting of projects, and they contain a series of non-innovative construction recommendations that sought to standardise systems, to provide an immediate economy of resources, and to guarantee at least a minimum level of health and safety of the dwelling. In the San Pablo project, these standards are translated into the construction systems (Table A1). Since all the residential buildings correspond to the same construction period, the building characterisation used for the GISUBEM-LCA predictive models has been carried out with 4 templates corresponding to the 4 categories of building types. The templates differ in the percentage of openings in the façade. Each building, in the model, will be assigned a certain template that includes the constructive characterisation, the thermal systems, and the use profile with which it will be modelled. Annex A includes the construction, structure, and installation features of the current state (H0). 3.2. PH02: characterisation of proposed interventions In accordance with prior case study analysis, a set of intervention strategies was designed, that combines envelope renovation actions and contributions from renewable energy systems. Due to the lack of collective MEP, HVAC, and DHW installations, no renovation systems are considered, nor are any interventions inside the dwellings, since these are generally excluded from the ‘extensive retrofit’concept. Consequently, five intervention hypotheses (H1, H2, H3, H4, and H5) have been designed: four with common lowimpact, extensive energy-rehabilitation solutions with minimal influence on domestic use, and a fifth scenario based on new construction. Journal of Building Engineering 94 (2024) 109993 16 J. García-López et al. Fig. 13. Evolution of the EPC standard lifetime operational and embodied CO2emission scenarios until 2100. sions by 46.97 % compared to the baseline scenario. In this respect, in 2050, the lowest expected carbon footprint per housing area (H1234) is 220.28 kg CO2/m2, with a base scenario H0 of 415.41 kg CO2/m2and a maximum of 540.42 kg CO2/m2for the new building (H5). This scenario presents the least inclined slope of the whole complex, in accordance with the greater efficiency of its buildings, not only for their thermal envelope, but also for their installations (air-conditioning, solar DHW, etc.). For future studies, it would be advisable not to disregard the potential of installation renovations in the intervention strategies. Even if the life cycle is exceeded, if the results are extrapolated to the 22nd century, then the H5 new-building scenario still fails to offset the H1234 comprehensive retrofit +PV scenario emissions 140 years from now. It can be noticed that the incorporation of PV almost immediately offsets the emissions (0.98 years), as described in similar studies [53], and by 2050 (the end of the foreseeable lifetime of the installation) would reduce the carbon footprint of the baseline scenario by 30 %, and hence there is a clear benefit of extensive PV installation for self-consumption in existing buildings. The new building outperforms any real intervention in terms of emissions, while its standard emissions are equivalent to the comprehensive retrofit H123=H5, thereby improving on the current state and partial interventions. The emissions of the new plant would be equal to those of the full retrofit with PV, H5=H1234, in 2100. 3.6. Final discussion This research has applied an innovative methodology that integrates UBEM and LCA models in the same case study. This approach has enabled an assessment of the environmental impact at the 2050 horizon regarding greenhouse gas emissions, both due to the functioning of buildings (operational emissions) and construction processes (embedded emissions). Its application to the case study of an obsolete neighbourhood was intended to evaluate the results of several environmentally low-impact retrofitting scenarios, which has been achieved, as the results show. Furthermore, it has been possible to compare the results of the extensive retrofit strategies with an alternative scenario of constructing equivalent new buildings in accordance with current quality standards. For this comparison, a time projection with various intervention scenarios has been considered. It has been demonstrated that this GIS-UBEM-LCA methodology has been particularly suitable for the assessment of obsolete residential areas of low-income, using open data. The typological repetition that characterises this type of dwelling has facilitated the collection of data using a reduced number of archetype templates for their characterisation. The use of the UBEM-LCA tool (UMI v3.0) has enabled an assessment to be carried out at district scale, by developing simulation models that incorporate the environmental complexity of the urban layout (shade from buildings and various solar orientations), and also the material and constructive characterisation of a set of 357 buildings in a single scenario. The energy simulation of the model, once having been calibrated with reference methods, provides not only results on aggregate energy consumption and on embodied energy, but also specific results for every building for each intervention scenario analysed. The findings show that total emissions (embedded and operational) are lower for retrofitting existing buildings compared to new construction at horizon 2050. The results are still in favour of retrofitting even at horizon 2100. The study indicates that, in order to reach the targets of net-zero greenhouse gas emissions by 2050, it is a priority to upgrade the existing residential stock, especially obsolete residential neighbourhoods built between 1951 and 1980. 4. Conclusions The feasibility of the methodology has been demonstrated in the case study of the district of San Pablo in Seville, where it has been possible to develop a physical bottom-up model for the estimation of energy consumption and its carbon footprint from open data at the scale of individual buildings for an entire residential sector. The described method has enabled the life cycle of the neighbourhood Journal of Building Engineering 94 (2024) 109993 17 J. García-López et al. to be analysed with an extended time scenario (2050–2100) based on LCA and UBEM models and validated with reference methods. Moreover, it evaluates various scenarios of extensive intervention, by integrally computing energy consumption and gross or standard CO2emissions, in accordance with the objectives of the study. Modelling using UBEM methodology and open data is cost-effective and comparable to other much more resource-intensive and time-comsuming BEM models. This model can rigorously analyse the impact of massive intervention strategies at neighbourhood scale and can determine the foreseeable effects over their lifecycle with an acceptable range of confidence. Based on the results and their analysis, the research findings have provided evidence that: •In the analysis of operational emissions, it is necessary to use a double metric adapted to two different phenomena: actual gross consumption and emissions, towards an environmental approach and a reduction target scope; and EPC standard emissions, for technical and administrative verification of technical solutions and compliance with standards for renovation incentives. •During the construction phase, energy and associated emissions are in the order of 100 times lower in the retrofit cases compared to the equivalent new construction. Initial energy over a 70-year lifetime horizon constitutes up to 3 % of operational energy in the retrofit cases, and 116 % for new buildings. •In our study, Net-Zero EPC standard emissions in building stock by 2050 are only observed in the scenario of new buildings. None of the renovation hypotheses analysed reaches that neutrality level, and hence additional measures should be considered towards achieving this level in extensive renovations. •The alternative of building new districts at the present time would lead to future higher greenhouse emissions, caused by the impact of the construction process of new energy-efficient buildings. To clarify this consequence, emission targets should consider the cumulative emissions of the period from now up to the year 2050, and not only the emission rate in 2050. •The minimum real carbon footprint expected by 2050, in the best-case scenario (H1234), is of 220.28 kg CO2/m2, which improves on the base scenario (H0) by 46.97 %, whose footprint is 415.41 kg CO2/m2. The new-building hypothesis (even excluding demolition energy) presents the highest impact of all the options, at 540.42 kg CO2/m2. That worsens the base scenario by 30.09 %, and therefore it can be concluded that this is the worst option for the 2050 horizon, and would remain a worse option than the full envelope renovation with PV by 2100. •The incorporation of on-grid PV for self-consumption at neighbourhood scale offers major benefits even from a very early stage, and hence its massive incorporation into urban regeneration actions seems clearly indicated to help meet the 2050 decarbonisation targets. Limits for the present research consist of certain simplifications in the formulation of time scenarios, whereby the energy consumption is considered constant, while in fact it might be affected by changes in climate, user behaviour, and active systems such as HVCA and DHW. No energy spent on building conservation during the lifetime has been taken into account. Changes in future weather conditions influencing the evolution of the operational energy use has not been considered. Conversion factors from final energy to the equivalent primary and carbon emissions could change in the future according to the energy distribution framework. Lastly, the future lines of research that this investigation has entailed are set out below. •The results obtained at neighbourhood level, broken down into result per building, will enable the prioritisation of interventions according to their degree of effectiveness and potential for improvement over the baseline scenario. •Current consumption forecasting models can be improved through the characterisation of the usage profile and the installation systems present in buildings, by employing reference consumption and socio-economic open datasets available at district scale. •Extensive interventions, including hypotheses regarding the renovation of active systems (HVAC & DHW), deserve to be explored in future case studies, as do smart metering and control systems. •The developed methodology can be replicated for the assessment of other cases of obsolete residential neighbourhoods and can serve as a tool for the environmental impact assessment of rehabilitation strategies at district level. Funding This article is included in the project ‘Aplicación directa de la Estrategia Aura del Equipo Solar Decathlon–U.S., en rehabilitación de barriadas obsoletas andaluzas’supported by the Ministry of Development, Infrastructure and Territorial Planning of the Local Andalusian Government (Spain), with ref. US.20–11, although no economic financing has been received for its production. CRediT authorship contribution statement Javier García-López: Writing –review & editing, Writing –original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. Miguel Hernández-Valencia: Writing –review & editing, Writing –original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. Jorge Roa-Fernández: Writing –review & editing, Writing –original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. Emilio J. Mascort-Albea: Writing –review & editing, Writing –original draft, Visualization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. Rafael Herrera-Limones: Writing –review & editing, Writing –original draft, Visu- Journal of Building Engineering 94 (2024) 109993 18 J. García-López et al. alization, Validation, Supervision, Software, Resources, Project administration, Methodology, Investigation, Funding acquisition, Formal analysis, Data curation, Conceptualization. Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Data availability Data will be made available on request. Acknowledgements Our special thanks go to Zachary Berzolla for kindly giving invaluable support with the UBEM.IO workflow, to Lesley Burridge for proofreading and translation, and to Victoria Patricia López Cabeza for her helpful contribution during the creation of the threedimensional model of the district. Appendix A ANNEX A. Case Study Characteristics Table A1 Construction, structure, and installation features of the current state (Hypothesis H0) Hypothesis H0 BUILDING TYPE U value Thick. CONSTRUCTION SYSTEM CAT A CAT B CAT C CAT SOCIAL W/m2·K cm Façade Cladding +12 cm brick +5 cm air chamber +7 cm hollow brick 1.56 27 Ground floor Artificial stone paving +Cavity floor slab 0.75 17 Partition floors Artificial stone paving +Floor slab 2.23 20 Party wall 12 cm brick masonry +MW insulation blanket 1.83 16 Roof Floor slab +membrane +slag insulation +ceramic tile flooring 1.60 28 Windows Steel window frame +one single-pane glazing 5.70 5 Vertical partitions Gypsum-rendered hollow brick partition 2.48 8 Window/Wall Ratio, WWR 24.67 % 17.71 % 13.44 % 15.41 % Structure One-way reinforced concrete slabs & concrete columns Domestic Hot Water, DHW Electric heater Ventilation Natural Heating Heat pump DX A/A Split COP 2.5 Cooling Heat pump DX A/A Split EER 1.8 Table A2 Construction, structure, and installation characteristics of H5, new-building hypothesis H5 BUILDING TYPE U value Thick. CONSTRUCTION SYSTEM CAT A CAT B CAT C CAT SOCIAL W/m2·K cm Façade Cladding +12 cm brick masonry +3 cm PUR +5 cm air chamber +Lightweight gypsum plasterboard cladding with 5 cm MW insulation 0.31 27.0 Ground floor Artificial stone pavement +Cavity floor slab 0.75 28.0 Partition floors Artificial stone pavement +Floor slab 2.23 28.0 Party wall 12 cm brick masonry 12 cm +MW insulation blanket 1.83 16.0 Roof Floor slab +membrane +8 cm XPS insul. +ceramic tile flooring 0.42 28.5 Windows Aluminium window frame with thermal break +Low-emissivity double-pane glazing 2.56 7.0 Vertical partitions Lightweight gypsum plasterboard partition system with MW 0.68 8.0 Window/Wall Ratio, WWR 24.67 % 15.41 % 17.71 % 13.44 % Structure One-way reinforced concrete slabs & concrete columns Domestic Hot Water, DHW Gas boiler +solar thermal 70 % contribution Ventilation Mechanical Heating Heat pump DX A/A Split COP 2.7 Cooling Heat pump DX A/A Split EER 2.5 Journal of Building Engineering 94 (2024) 109993 19 J. García-López et al. Table A3 Physical characteristics of intervention hypotheses H1, H2, H3, and H4 Systems Description U value Density Thick. W/m2·K kg/m³ cm H1: Façade 12 cm brick masonry +5 cm cavity insulation +7 cm brick masonry 0.53 50 27 H2: Openings PVC window frame thermal break +triple glazing and low-e glazing 2.26 873 7 H3: Roof Ash waterproofing and insulating sheet +Floor screed with 5 cm insul. 0.42 1007 38 H4: Roof Photovoltaic panels on auxiliary structure – – – ANNEX B. Case Study Results of Energy and Carbon Emissions Table B1 Intervention scenarios: LCA Embodied energy and GWP CO2eq in sector Case Description Embodied energy GWP emissions kWh kWh/m2kgCO2eq kgCO2eq/m2 H0 Base – – – – H1 Cavity injection 24,158,461 88.01 1,273,864 4.64 H2 Window renovation 935,391 3.41 90,799 0.33 H3 Roof improvement 2,826,814 10.30 228,362 0.83 H123 Envelope retrofit 27,920,666 101.72 1,593,024 5.80 H4 Base +PV 8,886,807 32.38 2,596,506 9.46 H1234 Envelope retrofit +PV 36,807,472 134.10 4,189,531 15.26 H5 New building with PV 314,816,063 1146.95 112,389,334 409.46 Table B2 UBEM-modelled intervention scenarios: annual operational final energy use and carbon emissions Case Description Annual Consumption Annual Emissions Reduction kWh kWh/m2kgCO2kgCO2/m2% H0 Base 23,533,681 85.7 8,401,524 30.61 - H1 Cavity injection 20,600,301 75.1 7,354,307 26.79 12.46 % H2 Window renovation 22,517,655 82.0 8,038,803 29.29 4.32 % H3 Roof improvement 22,770,969 83.0 8,129,236 29.62 3.24 % H123 Envelope retrofit 19,016,999 69.3 6,789,069 24.73 19.19 % H4 Base +PV 16,116,628 58.7 5,753,636 20.96 31.52 % H1234 Envelope retrofit +PV 11,614,392 42.3 4,146,338 15.11 50.65 % H5 New building with PV 7,419,028 27.0 2,648,593 9.65 68.47 % Table B3 UBEM-modelled intervention scenarios: annual EPC standard operational final energy use and carbon emissions (HVAC and DHW services) Case Description Annual Consumption Annual Emissions Reduction kWh kWh/m2kgCO2kgCO2/m2% H0 Base 16,403,981 59.76 5,856,221 21.34 - H1 Cavity injection 13,470,601 49.08 4,809,005 17.52 17.88 % H2 Window renovation 15,387,955 56.06 5,493,500 20.01 6.19 % H3 Roof improvement 15,641,269 56.98 5,583,933 20.34 4.65 % H123 Envelope retrofit 11,887,299 43.31 4,243,766 15.46 27.53 % H4 Base +PV 8,986,928 32.74 3,208,333 11.69 45.21 % H1234 Envelope retrofit +PV 4,484,692 16.34 1,601,035 5.83 72.66 % H5 New building with PV 289,328 1.05 103,290 0.38 98.24 % Journal of Building Engineering 94 (2024) 109993 20 J. 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