Energy saving, global warming and waste recovery potential of retrofitting process for a district

Journal of Cleaner Production 238 (2019) 117915

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Journal of Cleaner Production journal homepage: www.elsevier.com/locate/jclepro

Energy saving, global warming and waste recovery potential of retrofitting process for a district € zer*, Hüseyin So € zen Hatice So Istanbul Technical University, Energy Institute, 34469, Maslak, Istanbul, Turkey

a r t i c l e i n f o

a b s t r a c t

Article history: Received 15 March 2019 Received in revised form 31 July 2019 Accepted 3 August 2019 Available online 7 August 2019

In the paper, the retrofitting process in a district was examined to understand its effects on energy consumption and environment via Life Cycle Assessment (LCA) methodology. Correspondingly, waste recovery potential was evaluated to obtain energy recovery rate from retrofitting processes. The methodology was set based on LCA, which covers cradle-to-grave approach to evaluate the steps of retrofitting activities on a district that have 82 building blocks with a total 41168 m2conditioned area. The aim of the retrofitting is to improve energy performance of the buildings and increase percentage of renewable energy sources on total consumption. While the applied interventions decrease the energy consumption, they further have negative effects on environment because of their production, transportation and end of life stages. Therefore, boundaries of the study were defined to analyze the applied interventions effects from raw material extraction till disposal. Hence, waste management processes of the retrofitting materials were proposed and evaluated. As a results, reduction rate of retrofitting for global warming potential and cumulative energy demand are considerable high. Also, the most negatively effective process was operational energy consumption during building lifetime based on cumulative energy consumption. The second negatively effective process was material production. Contrarily, end of life has positive effect because of materials recycle potential. © 2019 Elsevier Ltd. All rights reserved.

Handling Editor: Sandro Nizetic Keywords: Life cycle assessment Retrofitting Waste management Operational energy use Cradle-to-grave approach

1. Introduction Energy is mostly consumed in industry, residential, agricultural and transportation sectors. According to Eurostat Static Explained database, percentage of final energy consumption by end-users in residential sector was 25.4% in overall final energy consumption in Europe in 2016 (Eurostat Static Explained, 2018). On the other hand, the production, transportation stages of energy as well as building materials also create environmental problems due to the energy consumption and CO2 emission of the process. Therefore, entire process has to be taken in careful consideration to decrease its negative effects. Likewise, not only designing and constructing energy efficient buildings should be targeted, but also retrofitting the building with energy efficient strategies to improve buildings performance through its lifespan should be considered. Retrofitting could include both passive and active strategies to reduce

* Corresponding author. €zer), [email protected] E-mail addresses: [email protected] (H. So € zen). (H. So https://doi.org/10.1016/j.jclepro.2019.117915 0959-6526/© 2019 Elsevier Ltd. All rights reserved.

consumption. While insulation can be given as an example for passive strategies, application of photovoltaic, solar thermal and radiant heating systems can be an example for active strategies. LCA methodology is a common way to analyze impact of products during their life cycle as there are many published papers in the literature. LCA methodology examines products, processes or activities from their background through end of life; hence, it takes into account their manufacturing, transportation, usage, end of life stage as a whole, and analyze their energy consumption and environmental effects. Sharma et al. give similar definition for LCA. According to them, LCA is a tool to make quantitative calculation on material, energy flows and their environmental impacts; besides, it includes raw material, manufacturing, use and final disposal steps (Sharma et al., 2011). There would be wide spectrums of descriptions of LCA based on the area or the aim of applications. As Wiedmann and Minx indicate that LCA provides calculation method for carbon footprint, especially at the product level which is defined as the amount of CO2-equivalent emissions caused directly and indirectly by an activity (Wiedmann and Minx, 2008). There are different approaches such as gate-to-grave, cradle-to-

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€zer, H. So €zen / Journal of Cleaner Production 238 (2019) 117915 H. So

gate, and cradle-to-grave for performing LCA. Cradle-to-grave that is the most extensive approach is used for analyses. Thomas et al. analyzed milk production via cradle-to-grave approach because they also added production, transportation and end of life stages in addition to usage stage (Thoma et al., 2013). Life cycle impact of building sector also have been investigated in various published papers. According to Adalberth, evaluating the building energy consumption within environmental concerns by relating it with LCA is becoming important. In fact, environmental impacts of building products are critical due to their long life span compare to many industrial products, as well as building operation stage which associated with energy consumption for heating, cooling, lighting (Adalberth, 1997). Russell-Smith et al. suggested LCA to adopt the process of sustainable decision making that the environmental impacts of buildings during the lifecycle can be predicted (Russell-Smith et al., 2015). Bastos et al. made an analysis in Lisbon to analyze envelope impact on environment. Their results showed that the most effective envelope is wall (Bastos et al., 2014). Asif et al. also worked on building sector based on material type, and resulted as the concrete had the highest influences on energy consumption (Asif et al., € rjesson and Gustavsson made a comparison between 2007). Bo concrete frame and wooden frame based on global warming potential; also, emission from concrete is 1.5e2 times higher than € rjesson and Gustavsson, 2000). Chen et al. showed that wooden (Bo shared of steel is 68% on total energy consumption in Hong Kong (Chen et al., 2001). Beccali et al. investigated energy retrofitting processes in a single-family house; besides, their results showed that more embodied energy consumption due to material production cause lower operational energy demand (Beccali et al., 2013) Sierra-Perez et al. analyzed conventional and Passivhaus renovation techniques in Sweden; moreover, they represented that while embodied energy consumption in conventional techniques are lower, they cause lower energy saving potential (Sierra-Perez et al., 2018). Correspondingly, there are researches that investigated applied interventions to reduce energy demand of buildings. Principi and Fioretti have compared light emitting diode (LED) and compact fluorescent light (CFL) via LCA methodology, and the results showed that LED is a more environmental equipment than CFL when their lifetime were considered. Nevertheless, manufacturing stage of LED causes more negative effects on environment than manufacturing stage of CFL (Principi and Fioretti, 2014). Pargana et al. made a survey based on insulation materials via LCA methodology. The results showed that XPS causes significant impacts on environment due to its raw material and production (Pargana et al., 2014). Nicolae and George-Vlad examined refurbishment processes on insulation in an existing building in Romania by using LCA methodology. The results showed that the best insulation material is EPS; besides, energy saving rate was 55% between existing condition and refurbished condition (Nicolae and George-Vlad, 2015). Monteiro and Freire, and Sierra-Perez et al assessed impact of façade type based on thermal energy consumption by using LCA (Monteiro and Freire, 2012),( Sierra-Perez et al., 2018). Mangan and Oral analyzed 3 buildings that all of them were built in different climatic regions in Turkey; besides, they analyzed some energy efficient retrofitting activities such as PV and insulation application via LCA methodology (Mangan and Oral, 2016). Rodriges and Freire investigated a roof retrofitting activity for a single-family house in Portugal. Their results showed that the most environmental friendly frame type is wood frame for global warming and cumulative energy demand. In addition to that, polyurethane foam (PUR) material for insulation caused the least greenhouse gases to environment, extruded polystyrene (XPS) consumed the least primary energy (Rodrigues and Freire, 2014). Hee et al. investigated

changing glazing impact on energy consumption; besides, the results showed that double glazing is more efficient than single glazing based on energy consumption in buildings (Hee et al., 2015). They applied solar collectors to reduce energy consumption and investigated them within the building’s lifespan. Ardente et al. examined energy payback time of solar collectors. Thus, energy payback time of solar collectors is less than 2 year in Italy condition. Investigated buildings in this study used standard heating with radiators before retrofitting; nevertheless, radiant heating system was applied to heat the buildings according to retrofitting strategies (Ardente et al., 2005). Imanari et al. also evaluated the radiant heating system and found that it decreases energy consumption approximately 10% during the building lifespan (Imanari, 1999). On the other hand, various researchers integrated the LCA with other evaluation methods to achieve better accuracy on evaluation results. Peuportier et al. developed an approach to complements LCA with a sensitivity study in order to account influence of occupants on the performance. The results show the essential influence of occupants on the performance. Also robustness of LCA results increases the application of this method for designers (Peuportier et al., 2013). Cavalliere et al. utilized the Building Information Modelling (BIM) in order to conduct the LCA. An information flows matrix is developed through the investigation of the parameters responsible for the environmental impacts of buildings. The results show that proposed BIM environment could potentially improve the data reliability and consistency in the process (Cavalliere et al., 2018). Xining Yang et al. also presented a BIM-enabled LCA method to illustrate to facilitate the low carbon design. The paper represents that a detailed life cycle environmental performance of the buildings can be assessed by utilizing the model. This provides better accessibility and credibility to be used between the Architecture, Engineering and Construction (AEC) professionals (Xining Yang et al., 2018). Likewise, some researchers also combined Geographic Information System (GIS) and LCA methodology in literature. Energy performance of buildings were evaluated based on city scale by using GIS methodology; thus, information such as construction time, energy performance of buildings was defined in rez GIS system to examined situation of city as whole (García-Pe et al., 2018; Mastrucci et al., 2014). Furthermore, Hossain and Ng were review the several research that applied LCA with environmental concerns recently. In addition, the research demonstrated a comprehensive framework to adopt a circular economy (CE) concept by providing comprehensive assessment of buildings (Hossain and Ng, 2018). Various methodologies have defined for LCA; nevertheless, the most widely used one is developed by the International Organization for Standardization (ISO) 14040 & 14044 standards (ISO 14040, 2006; ISO 14044, 2006) which represent 4 steps for LCA as: Goal and scope, inventory analysis, life cycle impact assessment and interpretation. These steps are related with each other, and they have to be managed together during LCA. In addition, European Norm was prescribe for the assessment of the environmental profile of the buildings’ construction works called EN 15978 (EN 15978, 2011). EN 15978 divides the LCA methodology into 5 main stages as: Product, construction, use, end of life and supplementary information beyond the building life cycle stages. In this research, the retrofitting activities of buildings were analyzed to find their effects on energy consumption and environment for an entire district. LCA methodology was used from cradle-to-grave approach. The evaluation also included the waste management process of the interventions that applied during the retrofitting. This research shows its differences from the literature by analyzing the retrofitting strategies with cradle-to-grave approach in a district scale while others have investigated only a selected

€zer, H. So €zen / Journal of Cleaner Production 238 (2019) 117915 H. So

stage in a building lifespan. Effect of applied interventions were evaluated to get CED and GWP for 82 building blocks. Hence, the energy recover potential of materials’ wastes also included in the analyses. The outcomes could be used as a reference for similar applications. Correspondingly, the study emphasis the importance of data collection and preparation to get accurate results. Applied evaluation methodology for the study suggests to use multiple program for preparing the data for LCA.

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2018) and were included in BIM. Further, energy performance program called e-QUEST applied by utilizing the data of BIM to find the building's energy consumption during the building in use period (e-QUEST, 2018). Hence, all data needed for LCA are provided from the BIM and the buildings' energy models. The methodology is realized through a case study and explained in detailed in sections below. 2.1. Background information of the selected site

2. Material and method ISO 14040, ISO 14044 and EN 15978 calculation method were selected and modified for the paper's methodology. Accordingly, the taken steps to realize the building LCA were divided in 4 phases: goal and scope definition, inventory analyses, impact assessment and interpretation as represented in Fig. 1. The main purpose of the study is to evaluate environmental impact of the retrofitting activities that been realized to improve the energy performance of buildings in a district level. Therefore, the LCA of the buildings was considered from cradle to grave which includes stages of the production and construction (raw materials extraction to processing and products installation), use (operational energy flow, maintenance, replacement), and end of life (demolition or disassembly, transportation to the treatment site and end of life scenario). In this context, to be able to obtain accurate results, it is critical to identify and collect related variables before taking the step of evaluating them. Accordingly, four major steps were considered to prepare data for LCA. These are.
identifying and collecting the materials and their specifications.
defining the waste management profiles of the selected materials
defining the geographical information for locations
analyzing the energy performance of applied interventions The Autodesk Revit is used to model the physical conditions of buildings architecture to compose and manage the data of building materials in BIM (BIM-Autodesk, 2018). Indeed, all the specific information about each building element's characterization such as area or volume are included in the model. Likewise, specifications such as amounts and catalogue information of the building's materials were collected and stored in the BIM. Additionally, all information about the locations and distances between those are provided from Geographical Information Systems (Googleearth,

Fig. 1. Developed methodology.

A site, located in Soma District of Manisa was selected as a case study. The buildings are belong to EUAS¸ (Electricity Generation Company) which has its own power plant. Buildings in the demo site were occupied by the company's workers since1980s. 82 building blocks were retrofitted based on energy efficiency in term of a European Union project that is called as CityFIED in the site (Cityfied, 2019). The buildings divided in three different group as: Residential buildings (1, 2 and 3 storey and duplex blocks), guest house and single lodging and convention center as represented on Fig. 2. Applied interventions and buildings operational energy consumption were different from each other in terms of building types. Because of that, defined building types were examined via LCA methodology separately. 2.2. Goal and scope definition The goal and scope of the study were defined in detail. The goal of the study as a building retrofitting project was set to analyze impacts of energy efficient retrofitting activities on energy consumption and environment in the selected district. While applied interventions decrease the operational energy consumption of the buildings, they also consume energy and create environmental pollution during their production, transportation and end of life stages. That means, their overall effects have to be analyzed during their lifespan. Scope of the study was developed by selecting the cradle-tograve approach, then the system boundary conditions were built accordingly. Defining system boundaries is very critical and important step for LCA studies. In this study, they were established as;
Selecting the applied standard: System boundaries were defined based on EN 15978 methodology as defined on Table 1.
Calculation period of the project: The buildings were built in 1980s; besides, it was estimated that their service life will continue 50 years further after the retrofitting. Hence, functional unit (FU) was defined as m2.50years as the results were represented and compared.
Scaling the project: The buildings in the site were categorized into three different groups as: residential, guest house and conventions center. All 82 building blocks were included in the project. Applied interventions were modified accordingly.
Evaluation of substances: Impacts of interventions during the retrofitting activities were evaluated based on their cumulative energy consumption and CO2 emission. Therefore, each intervention's material and its process was included in the LCA model. The existing building materials such as concrete, tile, glass and their environmental impacts were not examined in this paper, since the aim of the study only related with interventions’ effect based on the defined boundaries. Two scenarios were developed to make comparisons; existing conditions of buildings were defined as baseline and renovated

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€zer, H. So €zen / Journal of Cleaner Production 238 (2019) 117915 H. So

Fig. 2. District area and building type.

conditions were retrofitted scenario. The existing situation of the buildings were analyzed during 50 years; besides, maintenances and replacements such as painting, glazing replacement were considered in the baseline of LCA model. All stages and steps that were included to the framework of this study were given in Fig. 3. Thus, production stage of applied materials was also included to the models. In construction stage, interventions and their transportation to the site as well as generated wastes during construction were also included. Energy that was used for construction and insulation was not added due to lack of data in construction stage. Maintenances and replacements related with retrofitting activities and operational energy use were taken into account. Finally, end of life scenario of the retrofitting activities was defined and included in the models. 2.3. Inventory analyses Life cycle inventory (LCI) step was defined in ISO 14040 and ISO 14044 in detail; as it is the most important step for establishing the base for LCA. 2.3.1. Preparing/collecting data for inventory analyses Environmental performance of buildings further described in EN 15978, and LCA approach were categorized in A-production, Aconstruction, B-use and C-end of life stages. SimaPro, version 8.5 and Ecoinvent database version 3.4 were utilized for LCA (SimaPro, 2018; Ecoinvent, 2018). Considered stages within their steps were listed as: 2.3.1.1. stage with its considered steps. Product Stage (A1, A2, A3): Production stage includes raw material extraction, transport and manufacturing steps. Thus, all materials that are used in applied interventions were investigated beyond their raw material extraction, transportation of raw materials, manufacturing based on energy consumption and environmental effects. Transport step (A4): Transportations of materials for applied interventions to construction site that are used in buildings were considered. Construction and Installation step (A5): This step includes

energy consumption and generated wastes during construction processes. Nonetheless, energy consumption for construction and installation not considered in the system boundaries based on availability of data. The waste management scheme was defined to analyze the waste's potential. 2.3.1.2. stage with its considered steps. Maintenance and Replacement steps (B2, B4): Service life of retrofitting materials have defined and maintenance or replacement were forecasted to estimate how many times they have to be maintained or replaced in LCA studies. Most of those data were obtained from their catalog information and literature. Operational energy step (B6): Operational energy of buildings in the district were categorized in two groups as heating and electricity which were obtained from the energy model of each type of buildings. Impact of operational energy on environment and energy consumption is much higher than other steps due to consumption during building lifetime; therefore, operational energy data have entered to the LCA model perceptively. 2.3.1.3. stage with its considered steps. Demolition step (C1): Applied materials on buildings will become wastes after their services life; hence, these wastes have added to the LCA models based on cradle-to-grave system boundaries. In the demolition step, the amount of waste from the applied interventions is calculated and added to the LCA models. Also, energy demand that is consumed by vehicles during demolition was investigated and also included. Transport step (C2): Impacts of waste transportation on energy consumption and environment were examined by defining the transportation of wastes from the site to the closest and the most suitable waste treatment facilities. Waste Processing and Disposal step (C3, C4): All waste types have categorized to handle in different processes based on their types. Accordingly, recyclable, landfill and demolition wastes were defined. The wastes that was not recyclable or reusable were send to the closest landfill area by vehicles. Based on defined scope, data were prepared and collected; besides, applied analyses were decided. Two different modelling were done for each building block types, one is Building Information

€zer, H. So €zen / Journal of Cleaner Production 238 (2019) 117915 H. So

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Table 1 Building type and conditioned area in Soma demo-site. Building Type

Results of BIM

Results of Energy Model

Conditioned area [m2] Number of building Façade Area [m2] BIM of the buildings

The image of the building

Energy Consumption (kWh/50year)

One-story

206

6

241

679.450

Two-story

412

32

436

1.428.150

There-story

617,2

33

632

1.985.550

Duplex

185

8

237

612.950

Single Lodging

1.093

1

645

6.269.700

Guest House

1.377

1

942

6.943.950

Convention Center 2.430,5

1

736

22.811.150

Total

82

41.168

Modelling (BIM) and another is Energy Performance Model. All the building physical conditions and characterization were modeled within the BIM to provide specific information such as façade, roof's area or materials' volume. Likewise, specifications such as amounts and catalogue information of the building's materials were collected and stored in the BIM (BIM-Autodesk, 2018). Further, energy performance program called e-QUEST applied to evaluate building energy performance by utilizing the data of BIM to find the building's energy consumption during the building in use period (e-QUEST, 2018). Furthermore, the main purpose of the retrofitting activities was to reduce energy consumption of the

buildings which related to conditioned area that were defined in Table 1 based on each building type.

2.3.1.4. Defined scenarios. LCA was performed for 2 different scenarios as: baseline scenario and retrofitted scenario. The differences based on energy consumption and environmental pollution were displayed by comparing these models. Baseline Scenario: In the baseline scenario, it is estimated that buildings will continue their life without any energy efficient interventions except standard maintenance and replacement activities which were added in the model. Similar strategies were also

€zer, H. So €zen / Journal of Cleaner Production 238 (2019) 117915 H. So

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-

Fig. 3. System boundaries for both scenarios.

applied for retrofitting scenario. Thus, the applied maintenances and replacements were listed as: -

District heating boiler replacement Lighting replacement Glazing replacement Windows frame replacement Exterior paint maintenance

Energy performance of the buildings were simulated via eQuest software (e-QUEST, 2018); besides, these results were used as operational energy consumption in the baseline model. The buildings used the local electricity grid system for electricity and coal (lignite) for heating. The system boundary of the baseline scenario was represented be seen in Fig. 4 in detail. Retrofitted Scenario: Selected retrofitting activities were applied in the district to improve energy performance of buildings. Impacts of interventions were evaluated in the retrofitted scenario. Energy reduction rates, related to energy performance of buildings were analyzed by simulating the building energy model. Since energy performance of the buildings was improved, greenhouse gas emission from the building also decreased. Thus, the applied interventions also influenced the global warming potential positively. Mentioned interventions were listed as: - Glass and frame changing

Insulation (EPS and mineral wool) application Solar collectors and tanks application Radiant heating application Light emitting diode (LED) application Photovoltaic (PV) panel application District heating system

Glazing and frame changes, façade and roof insulations were applied to improve the thermal performance of the buildings envelopes. The u-values after refurbishment became even better than related Turkish standards that is called as “Thermal insulation requirements for buildings” (TSE825, 2014). Also, solar collectors and photovoltaic panel application were applied to use renewable energy sources. Inefficient lightings were replaced with LED lighting. Before retrofitting, the buildings were used a district heating that used coal (lignite) as source; also, the pipeline system was old and inefficient based on energy consumption. Hence, new district heating system was built to benefit from waste heat that is generated in nearby thermal power plant. The new pipeline is longer than the old one, but also it is more efficient because of using waste heat as source. After waste heat reaches the buildings via new district heating pipeline, radiant heating application was used to distribute the heated water inside of the buildings. In addition, impacts of new district heating system were divided to the buildings based on their conditioned area. The length of new district heating system is approximately 12 km as seen in Fig. 2 (GIS, 2018); besides, the total conditioned area of the district is 41168 m2. Based on the calculations, 0.3 m pipe had to be tubed for one-square meter conditioned area approximately. The district heating pipeline system was distributed to the buildings according to this calculation. All applied interventions and their application schedule during the building lifespan were shown in Fig. 5. According to the timeline, LED will be replaced every 5 years, windows, photovoltaic and solar collector systems will be replaced once at 25th year, and exterior paint will be maintained every 20 years. With the all intervention applications, energy performance of the buildings were analyzed and their results were entered to LCA's model.

2.3.2. Results of inventory analyses All input and output data based on system boundaries are defined in this step, and their quantifications are calculated. LCI of baseline scenario and retrofitted scenario were defined in this section. As mentioned before, there are three types of building in the district; residential, guesthouse and convention center. Buildings were examined based on building's type as represented in Table 1.

Fig. 4. Baseline scenario based on cradle to grave system boundaries.

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Fig. 5. After interventions scenario based on cradle to grave system boundaries.

Results LCI for baseline scenario: The most significant and effected materials that were defined and the calculation of their quantifications were made based on BIM of the buildings. Thus, the most significant materials that were used in baseline scenario and their weights for all buildings are represented in Fig. 6. District Heating (DH) is related with the site area. The share of DH boiler impact on the buildings was divided likewise calculation of DH pipeline. Thus, the weight of boiler was shared based on conditioned area of the buildings. Results LCI for the retrofitted scenario: LCI of the retrofitted scenario was defined likewise baseline's. According to retrofitting

Exterior Paint; 1713 kg; 10%

activities, the most significant materials were defined, and their quantifications were calculated. BIM of the buildings, catalog data of applied materials and construction agreement information were used for calculation. The amount of materials that were used in the retrofitting was calculated for 3 references buildings (one-story residential, guest house and convention center); besides, their mass and their percentage based on mass are given in Table 2 and Fig. 7 in detail. Firstly, their weight were calculated for one application, and their service life was defined according to material type and its information. The building lifetime was defined 50 years after retrofitting. Based on this assumption, the number of replacement and

DH Boiler; 244 kg; 1% Light; 1431 kg; 8%

Single Glazing; 6397 kg; 37% Wood Frame; 7669 kg; 44%

Fig. 6. Most significant materials that were used in the all buildings based on their weight (percentage) for baseline scenario.

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Table 2 The most significant materials that were used in the reference buildings. Materials

Weight (kg)

Service Life (years)

The number of Replacements

Total during 50 years(kg)

Spillage (kg)

Totalþ Spillage (kg)

Glass Paint Plastic (PVC) EPS Stucco Solar Collector Tanks Solar Thermal Collectors Radiant system panel LED Mineral Wool Pipeline Autoclaved aerated concrete Photovoltaic TOTAL

6446 816 14,007 3120 186,213 6750 1500 31,098 300 58,951 15,594 5884 12,000

25 20 25 50 50 25 25 50 5 50 1 50 25

2 3 2 1 1 2 2 1 11 1 1 1 2

12,794 2447 28,014 3120 186,213 13,500 3000 31,098 3299 58,951 15,594 5884 24,000

0 123 0 157 18,621 0 0 0 0 2947 0 0 0

12,794 2570 28,014 3277 204,834 13,500 3000 31,098 3299 61,898 15,594 5885 24,000 409,763

Photovoltaic; 6%

Glass; 3%

Autoclaved aerated concrete; 1%

Paint; 1% Plas c (PVC); 7% EPS; 1%

Pipeline; 4%

Mineral Wool; 15%

LED; 1%

Radiant system panel; 7%

Stucco; 50%

Solar Thermal Collectors; 1% Solar Collector Tanks; 3% Fig. 7. Most significant materials that were used in the reference buildings based on their percentage.

maintenance during 50 years were calculated for all material types. According to that, their total quantities were obtained during 50 years. During construction stage, some wastes were generated from the applied materials; besides, these wastes were added to the model based on assumptions. Thus, the amounts of surplus materials were calculated from paint, EPS, stucco and mineral wool. At

the final column, the total quantities of the materials were seen during 50 years. Operational energy consumptions of the buildings were obtained from simulated model; besides, they are given in Table 3. Also, after buildings complete their lifetime the buildings will be demolished. Kuikka calculated energy demand during the

Table 3 Buildings’ energy consumptions after interventions in Soma district. Building Type

Residential Buildings

Guest House Single Lodging Convention Centre

Energy consumption (kWh)/ m2.50years

One-storey Two-storey Three-storey Duplex

Energy consumption (kWh)/50year

Electricity

Heating

Electricity

Heating

1326 1215 1180 1411 1179 1816 1174

1972 2251 2038 1903 3863 3920 8212

273,250 500,750 728,000 260,950 1,624,000 1,985,000 2,853,000

406,200 927,400 1,257,550 352,000 5,319,950 4,284,700 19,958,150

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Table 4 CED of buildings for baseline scenario. Building Type

Residential Buildings Guest House Convention Centre All Buildings

Unit (MJ/m2.50 years) Total

Materials

Lignite coal

Electricity

Transport

End of life

77,092 71,997 72,099 73,729

4202 1336 770 2103

49,482 53,461 55,489 52,811

23,074 17,159 15,818 18,684

3 1 1 2

330 40 21 130

demolition process for a school building in Sweden (Kuikka, 2012). The result of the research was utilized as energy consumption during demolishing and entered to the model. Accordingly, diesel demand of the reference residential building was calculated as 1139,6 kg diesel ¼ 54700,8 MJ. The buildings will be demolished in both scenario; hence, the main differences between two scenarios is only related with applied materials during the retrofitting process. Because of that, onlyend of life of applied interventions were evaluated in the retrofitted scenario. The closest landfill area is 65 km away from the case study site; also, the closest recycling facility is 66 km away from the buildings. The landfill for demolished wastes is 5.5 km away (GIS, 2018). These distances also were taken into account in the model.

2.4. Impact assessment Retrofitting activities were done to decrease energy consumption of the buildings and increase percentage of renewable energy sources instead of traditional sources on total consumption. Thus, main aim of this study is to analyze energy consumption during defined lifetime. Due to that, cumulative energy demand (CED) was selected as indicator. The second aim of the retrofitting is that decreasing carbon dioxide emission from the buildings; hence, global warming potential (GWP) was also selected as indicator. As it mentioned in Section 1.2, functional unit (FU) of this study is defined as m2.50year; therefore, defined indicator are listed as:

2.4.1. Results of impact assessment for baseline scenario LCA methodology was applied on the reference residential building, guest house and convention center based on defined system boundaries for the study period aiming to obtained the results of the baseline scenario. CED of baseline scenario can be seen in Table 4 based on building type and processes, in Table 5 based on EN 15978 stages. As it seen, energy consumption per m2 for 50 years is higher in residential buildings compared to other building types. When the building area increases, its energy consumption based on unit decreases. Also Table 5 results show that, the most effective stage is operational energy consumption stage in CED. In building sector, share of operational energy consumption are mostly around 70e85%; thus the results of the study show similarity with published papers (Al-Ghamdi and Bilec, 2016) The second effective stage is related materials (A1-A5 and B2 and B4), and the lowest effected stage is end of life-based on CED results. GWP results also were obtained for baseline scenario. They can be seen in Tables 6 and 7. According to the results, unit emission from residential buildings is higher than others as in CED results. GWP of operational energy consumption is the most effective as in cumulative energy demand. Ranking of the other stages is also same with CED results.

The results were represented in format of these two indicators. The models were made by using SimaPro Software version 8.5 and using Ecoinvent database version 3.4 (SimaPro, 2018; Ecoinvent, 2018).

2.4.2. Results of impact assessment for retrofitted scenario Retrofitted scenario results were obtained for selected indicators. CED results of each building types was represented in Table 8, while CED of each stage was represented in Table 9. CED results show that energy consumptions of the buildings decrease dramatically by help of retrofitting, but operational energy has still major impacts as expected. In addition to the operational energy consumption, also percentage of impact of material in both indicators are higher than baseline scenario. The reasons of that is related with more technological materials such as LED, PV, solar collectors. While these kind of products are more energy efficient, they also consume more energy during their production phase.

Table 5 CED of all stages on the baseline scenario.

Table 7 GWP of all stages on the baseline scenario.

- Global warming potential (GWP) (kg CO2eq./m2.50years) - Cumulative energy demand (CED) (MJ/m2.50years)

Stage

Unit MJ/m2.50years

Stage

Unit kg CO2 eq/m2.50years

A1-A5 (Product) B2 and B4 (Maintenance and Replacement) B6 (Operational Energy) C1eC4 (End Of life)

999 1102 71,495 130

A1-A5 (Product) B2 and B4 (Maintenance and Replacement) B6 (Operational Energy) C1eC4 (End Of life)

45 21 5980 9

Table 6 GWP for baseline. Building Type

Unit (kg CO2 eq/m2.50years) Total

Materials

Lignite, coal

Electricity

Transport

End of life

Residential Buildings Guest House Convention Centre All Buildings

6145 5975 6041 6054

130 42 25 66

4375 4727 4907 4670

1618 1203 1109 1310

0,2 0,1 0,04 0,1

22 3 2 9

€zer, H. So €zen / Journal of Cleaner Production 238 (2019) 117915 H. So

10 Table 8 CED for all buildings retrofitted scenario. Building Type

Residential Buildings Guest House Convention Centre All Buildings

Unit (MJ/m2.50years) Total

Materials

Surplus Heat

Electricity

Transport

End of life

22,362 26,564 44,647 31,191

6294 3018 8738 6017

5768 11,302 24,022 13,698

14,080 12,519 12,460 13,019

25 14 24 21

316 290 598 401

Table 9 CED of all stage on the retrofitted scenario.

Table 11 GWP of all stage on the retrofitted scenario.

Stage

Value (MJ/m2.50years)

Stage

Value kgCO2eq./m2.50years

A1-A3 (Production) A4-A5 (Construction) B2eB4 (Maintenance and Replacement) B6 (Operational Energy) C1eC4 (End Of life)

2274 21 4373 26,717 401

A1-A3 (Production) A4-A5 (Construction) B2eB4 (Maintenance and Replacement) B6 (Operational Energy) C1eC4 (End Of life)

116.4 1 295.2 1493 15

Nevertheless, their overall impact are more efficient than baseline scenario products. Correspondingly, GWP of retrofitted scenario for each building type were represented in Table 10 while stages were in Table 11. Emission of greenhouse gases decreased with retrofitting activities visibly. Nonetheless, impact of operational energy is still the highest one.

2.5. Interpretation After the results were obtained for both scenarios, the comparison was made to analyze effect of retrofitting activities. Operational energy consumption of the buildings were obtained from energy performance models based on final-energy use. LCA methodology is involved at this point to analyze background of the products and processes. Results were compared in Fig. 8 for GWP and Fig. 9 for CED. Retrofitting activities were done to decrease the energy consumption of the buildings; besides, the energy performance models of the buildings show that reduction rate is 65% for residential buildings, 59% for guest houses and 24% for convention center. On the other hand, the reduction rates in LCA model differ than the final-energy consumption results. Reduction rate of residential buildings is 71%, 63% for guest house and 38% for convention center in LCA models. LCA models also involved production phase of applied interventions, transportation and end of life stage. While these consumptions are taken in account, the expectation can be like that reduction rate based on LCA results has to be lower than reduction rate based on final-energy consumption. On the other hand, reduction rate of LCA results is higher than the other. The reason for that is using waste heat instead of coal after retrofitting. Based on Ecoinvent database, necessary energy to produce 1 MJ energy from coal is 2.05 MJ, but necessary energy to produce 1 MJ energy from waste heat is 0.813 MJ (Ecoinvent, 2018). In addition to

the CED; GWP reduction rate also significantly high. Reduction rate is 76% for residential, 74% for guest houses and 59% for convention center. The reason for these high reduction rate is using waste heat. The building used lignite before retrofitting; besides, lignite causes high CO2 emission than the waste heat.

2.5.1. The effect of applied interventions The main aim of retrofitting is reducing energy performance of the buildings. For this purpose, some interventions were applied to the buildings. Consumed energy on the buildings decreases via these interventions; nonetheless, these interventions also consume energy during production, transportation and end of life stages. In this study, materials that have applied based on retrofitting strategies also analyzed from cradle to grave. Thus, the amount of consumed energy and emitted greenhouse gases related with applied interventions were also obtained. Based on EN 15978, production stage (A1-A3), construction stage (A4, A5), maintenance step (B2), replacement step (B4) and end of life stage (C1eC4) of the applied material were evaluated. Impact of the applied interventions also compared with operational energy to show what their percentage in total. CED results of the applied interventions with their percentages and operational energy can be seen in Table 12. The result shows that applied interventions percentage differ each other based on building type. The building type that has the highest percentage is residential building; besides, the percentage are decreasing while conditioned area are increasing. Although conditioned area of convention center are higher than guest house, its applied interventions effects are higher than guest house. The reason for that is applied photovoltaic panel in convention center. PV panels were applied on convention center as it mentioned before; moreover, PV panel consumes more energy during production phase due to hightech processes. In addition to the comparison between overall applied

Table 10 GWP for retrofitted scenario. Building Type

Unit (kg CO2 eq/m2.50years) Total

Materials

Surplus Heat

Electricity

Transport

End of life

Residential Buildings Guest House Convention Centre All Buildings

1501 1549 2465 1838

386 186 564 379

244 479 1018 580

987 878 874 913

1 1 1 1

30 6 8 15

€zer, H. So €zen / Journal of Cleaner Production 238 (2019) 117915 H. So

11

7000 6145

kgCO2eq./m2.50years

6041

5975

6000

6054

5000 4000 3000

2465

2000

1838

1549

1501

1000 0 One-storey Building

Conven on Centre

Guest House

Baseline Scenario

All Buildings

Retrofi ed Scenario

Fig. 8. Comparison of GWP for all building types.

90000 80000

77092

72099

71997

73729

MJ/m2.50years

70000 60000 44647

50000 40000 30000

31191

26564

22362

20000 10000 0 One-storey Building

Guest House

Baseline Scenario

Conven on Centre

All Buildings

Retrofi ed Scenario

Fig. 9. Comparison of CED for both scenarios.

Table 12 Interventions CED effects on retrofitted scenario and their percentages. Building Type

Residential Buildings Guest House Convention Centre All Buildings

TOTAL

The Applied Interventions

Unit (MJ/m2.50years)

Unit (MJ/m2.50years)

Percentage %

Unit (MJ/m2.50years)

Percentage %

26,582 27,252 45,623 33,152

6734 3431 9141 6435

25.3 12.6 20 19.4

19,848 23,821 36,482 26,717

74.7 87.4 80 80.6

interventions effects and operational energy consumption, a comparison was made to investigate annual energy recovery potential from end of life processes. For this purpose, the year that retrofitting processes were applied to the building was selected. During implementation, the old materials such as single glazing, wooden frame in the buildings became wastes; besides, they were processed based on end of life scenario. They had an energy recovery

Operational Energy

potential as 20 MJ/m2.year due to recycling processes. When it was compared with annual operational energy consumption, end of life processes were compensated 4% of operational energy consumption for the selected year as it seen Table 13. Waste recovery potential was evaluated for the materials that were replaced during construction stage as district heating boiler, lighting, glazing, window frame and exterior paint. Furthermore,

€zer, H. So €zen / Journal of Cleaner Production 238 (2019) 117915 H. So

12

Table 13 Annual energy recovery potential from construction wastes. Potential Wastes during Construction Stage

Operational Energy CED for Retrofitting's Year (MJ/ m2.year)

Waste Recovery Potential from Retrofitting Process CED (MJ/ m2.year)

DH Boiler, Lighting, Glazing Window Frame, Exterior Paint

534

20

waste recovery potential of all the interventions as glazing, window frame, EPS, solar collector system, PV, district heating pipeline, LED and exterior paint were considered in end of life stage as it has seen in Table 14. While wastes that were generated during construction stage had an energy recovery potential, wastes from retrofitting materials had more energy recovery rate. GWP results can be seen in Table 15 as in exact result and in percent. Percentage of GWP results show similarity with the CED. Percentage of applied interventions in residential buildings is the highest one. Also, convention center's is higher than guest house because of high-tech materials that were used in convention center.

2.5.2. Evaluation of results There are 82 buildings in the case study site; also, they were categorized into three types based on purpose of use as residential buildings, guest houses and the convention center. Operational energy consumption and applied interventions are differ than each other based on defined building types. Because of that, types of the buildings were analyzed separately. Baseline situation results showed that average CED of all building is 73,729 MJ/m2.50years and average GWP is 6054 kgCO2eq./m2.50years. On the other hand, CED results of retrofitted scenario is 31,191 MJ/m2.50years, and GWP results is 1838 kgCO2eq./m2.50years. The results of the models show that cumulative energy demand of the buildings decreased by 57%; also, global warming potential decreased by 70% by help of applied interventions. Results of simulation model for the

operational energy showed that 49% reduction rate for energy demand; nonetheless, actual reduction rate is 55% for the all case study site. As it seen, LCA results are given more reduction rate than final-energy consumption performance. The reason for that is using waste heat for heating. Normally, 1 MJ coal energy is equal to 1 MJ waste heat energy based on final-energy. Nevertheless, while 1 MJ energy produced from coal consumes 2.05 MJ, 1 MJ energy produced from waste heat consumes 0.8 MJ. When the defined building types were compared separately, the reduction rate comparison can be seen in Table 16. Also, end of life of the applied interventions were investigated based on the defined system boundaries. Their waste management scenario was also included in analysis. All wastes were taken in account according to their material type; correspondingly a waste management plan was developed. The closest facilities that handle wastes were select to avoid environmental impacts and energy consumption of transportation. End of life processes impact on CED is - 401 MJ/m2.50years. Although there is a recovery potential from end of life stage by helps of recycling processes, this potential is only 1.3% of the total energy consumption of the building during 50 years. CED of operational energy consumption is 79% of the total energy consumption, and CED of product and construction stage (A) is %20 approximately. Results of retrofitted scenario by considering the stages of EN 15978 were given in Fig. 10. As it shown, there is considerable amount of reduction on energy consumption during the retrofitted

Table 14 Waste recovery potential from wastes based on square meter. Building Type

Residential Buildings Guest House Convention Center All Buildings

Waste recovery potential per square meter

Total waste recovery potential

Construction Stage (MJ/m2)

End of Life Stage (MJ/m2)

Construction Stage (MJ)

End of Life Stage (MJ)

38 13 8 20

658 334 622 538

7828 17,901 19,444 15,058

135,548 459,918 1,511,771 702,412

Table 15 GWP effects of interventions on retrofitted scenario and their percentages. Building Type

TOTAL

The Applied Interventions 2

Residential Buildings Guest House Convention Centre All Buildings

2

Operational Energy

kgCO2 eq./m .50years

kgCO2 eq./m .50years

Percentage %

kgCO2 eq./m2.50years

Percentage %

1691.7 1,592,5 2524.3 1936.2

460.1 235,8 632.6 442.8

27.2 14.8 25.1 22.9

1231.7 1356.7 1891.7 1493.4

72.8 85.2 74.9 77.1

Table 16 Reduction rate comparison between energy simulation models and LCA models. Building Type

Based on Energy Simulation Result (%)

Based on LCA Results (%)

Residential Buildings Guest House Convention Centre All Buildings

65 59 23 49

71 63 38 57

€zer, H. So €zen / Journal of Cleaner Production 238 (2019) 117915 H. So

13

Fig. 10. CED results of stages after retrofitting.

scenario. The most effected stage is operational energy consumption for both indicators as expected. After that material production stages (A1-A5, B2 and B4) have higher percentage. Finally, the most ineffective stage is end of life (C) stage. End of life stage led to an energy recovery potential as 401 MJ/m2.50years. This potential that came from recycling processes compensated 1.2% of overall consumption. Also, when recovery potentials were taken in account annually, the potential that came from end of life scenario can compensate 4% of annual operational energy consumption for the year that retrofitting activities were applied. 3. Conclusions Energy efficient retrofitting activities and their impacts on environment and energy consumption were analyzed via LCA methodology in the paper. System boundaries were limited with only applied interventions effects. Thus, applied interventions and operational energy consumption were analyzed in the retrofitted scenario. Therefore, during the lifespan of the buildings, operational energy and only maintenance and replacement activities of applied interventions were investigated. The aim of the study was that examining retrofitting strategies based on energy consumption and global warming potential during the buildings life time in a district. Consequently, product stage, use stage and end of life stage of the buildings were analyzed. According to obtained results, there is an energy recovery potential from the end of life processes of the materials that were used in retrofitting. Nonetheless, this potential is low when a comparison was made with use stage impacts. Based on GWP results, end of life stage of retrofitted scenario has still a decreasing rate due to recycling; however, landfill processes released more greenhouse gases than recycling processes. Because of that, total impact influenced the environment negatively. Retrofitting strategies were analyzed in this study with cradleto-grave approach; also, the results were compared with existing situation of the buildings. The results represent the environmental effect of strategies that applied to improve building energy performance on a district scale. Further, results represent the energy recover potential of the wastes. Hence, LCA results could be used as a reference for similar applications. Correspondingly, the study emphasis the importance of data collection and preparation to get accurate results. Applied evaluation methodology for the study suggests to use multiple program

for preparing the data for LCA. The study could be also useful for planning retrofitting activities to reach zero-energy and zero-waste building, district and cities in the future. Acknowledgements All interventions were applied according to a European Union project that was called as “Replicable and innovative future efficient districts and cities” (CITyFIED) in the case study area [17]. The most of buildings information were provided from CITyFIED project. The work is the one of the out comes of a project called Cityfied which is supported by European Commission. Grand ID: 609129 which is mentioned in the artical References Adalberth, K., 1997. Energy use during the lifetime of single-unit dwellings: examples. Build. Environ. 32 (4), 321e329. Al-Ghamdi, S., Bilec, M., 2016. Green building rating systems and whole-building life cycle assessment: comparative study of the existing assessment tools. J. Archit. Eng. 23 (1), 1e9. https://doi.org/10.1061/(ASCE) AE.19435568.0000222.©2016AmericanSocietyofCivilEngineers. Ardente, F., Beccali, G., Cellura, M., Lo Brano, V., 2005. Life cycle assessment of a solar thermal collector. Energy Build. 30, 1031e1054. https://doi.org/10.1016/j. renene.2004.09.009. ~ Muneer, T., Kelley, R., 2007. Life cycle assessment: a case study of a Asif, M.A., dwelling home in Scotland. Architect. Eng. Des. Manag. 42, 1391e1394. https:// doi.org/10.1016/j.buildenv.2005.11.023. Bastos, J., Batterman, S.A., Freire, F., 2014. Life-cycle energy and greenhouse gas analysis of three building types in a residential area in Lisbon. Energy Build. 69, 344e353. https://doi.org/10.1016/j.enbuild.2013.11.010. Beccali, M., Cellura, M., Fontana, M., Longo, S., Mistretta, M., 2013. Energy retrofit of a single-family house: life cycle net energy saving and environmental benefits. Renew. Sustain. Energy Rev. 27, 283e293. https://doi.org/10.1016/j.rser.2013.05. 040. BIM - Autodesk Inc, 2018. Revit | BIM software | Autodesk [Online]. Available. https://www.autodesk.com/products/revit/overview. Accessed: Sept. 2018. €rjesson, P., Gustavsson, L., 2000. Greenhouse gas balances in building construcBo tion: wood versus concrete from life-cycle and forest land-use perspectives Pa. Energy Policy 28, 575e588. Cavalliere, C., Dell' Osso, G.R., Pierucci, A., Iannone, F., 2018. Life cycle assessment data structure for building information modelling. J. Clean. Prod. v199, 193e204. https://doi.org/10.1016/j.jclepro.2018.07.149. Chen, T.Y., Burnett, J., Chau, C.K., 2001. Analysis of embodied energy use in the residential building of Hong Kong. Energy 26, 323e340. https://doi.org/10.1016/ S0360-5442(01)00006-8. Cityfied, 2019. Replicable and innovative future efficient districts and cities. In: 7th Framework EU Project, pp. 2014e2019. Project no: 609129. version 3.4 Ecoinvent, 2018. Institutes of the ETH Domain and the Swiss Federal Offices. https://www.ecoinvent.org/database/database.html. accessed: December 2018. EN 15978, 2011. Sustainability of Construction Works e Assessment of

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